Content from Introduction to R and RStudio
Last updated on 2024-12-04 | Edit this page
Estimated time: 55 minutes
Overview
Questions
- How to find your way around RStudio?
- How to interact with R?
- How to manage your environment?
- How to install packages?
Objectives
- Describe the purpose and use of each pane in RStudio
- Locate buttons and options in RStudio
- Define a variable
- Assign data to a variable
- Manage a workspace in an interactive R session
- Use mathematical and comparison operators
- Call functions
- Manage packages
Before Starting The Workshop
Please ensure you have the latest version of R and RStudio installed on your machine. This is important, as some packages used in the workshop may not install correctly (or at all) if R is not up to date.
Why use R and R studio?
Welcome to the R portion of the Software Carpentry workshop!
Science is a multi-step process: once you’ve designed an experiment and collected data, the real fun begins with analysis! Throughout this lesson, we’re going to teach you some of the fundamentals of the R language as well as some best practices for organizing code for scientific projects that will make your life easier.
Although we could use a spreadsheet in Microsoft Excel or Google sheets to analyze our data, these tools are limited in their flexibility and accessibility. Critically, they also are difficult to share steps which explore and change the raw data, which is key to “reproducible” research.
Therefore, this lesson will teach you how to begin exploring your data using R and RStudio. The R program is available for Windows, Mac, and Linux operating systems, and is a freely-available where you downloaded it above. To run R, all you need is the R program.
However, to make using R easier, we will use the program RStudio, which we also downloaded above. RStudio is a free, open-source, Integrated Development Environment (IDE). It provides a built-in editor, works on all platforms (including on servers) and provides many advantages such as integration with version control and project management.
Overview
We will begin with raw data, perform exploratory analyses, and learn how to plot results graphically. This example starts with a dataset from gapminder.org containing population information for many countries through time. Can you read the data into R? Can you plot the population for Senegal? Can you calculate the average income for countries on the continent of Asia? By the end of these lessons you will be able to do things like plot the populations for all of these countries in under a minute!
Basic layout
When you first open RStudio, you will be greeted by three panels:
- The interactive R console/Terminal (entire left)
- Environment/History/Connections (tabbed in upper right)
- Files/Plots/Packages/Help/Viewer (tabbed in lower right)
Once you open files, such as R scripts, an editor panel will also open in the top left.
R scripts
Any commands that you write in the R console can be saved to a file
to be re-run again. Files containing R code to be ran in this way are
called R scripts. R scripts have .R at the end of their
names to let you know what they are.
Workflow within RStudio
There are two main ways one can work within RStudio:
- Test and play within the interactive R console then copy code into a .R file to run later.
- This works well when doing small tests and initially starting off.
- It quickly becomes laborious
- Start writing in a .R file and use RStudio’s short cut keys for the Run command to push the current line, selected lines or modified lines to the interactive R console.
- This is a great way to start; all your code is saved for later
- You will be able to run the file you create from within RStudio or
using R’s
source()function.
Tip: Running segments of your code
RStudio offers you great flexibility in running code from within the editor window. There are buttons, menu choices, and keyboard shortcuts. To run the current line, you can
- click on the
Runbutton above the editor panel, or - select “Run Lines” from the “Code” menu, or
- hit Ctrl+Return in Windows or Linux or
⌘+Return on OS X. (This shortcut can also be seen
by hovering the mouse over the button). To run a block of code, select
it and then
Run. If you have modified a line of code within a block of code you have just run, there is no need to reselect the section andRun, you can use the next button along,Re-run the previous region. This will run the previous code block including the modifications you have made.
Introduction to R
Much of your time in R will be spent in the R interactive console.
This is where you will run all of your code, and can be a useful
environment to try out ideas before adding them to an R script file.
This console in RStudio is the same as the one you would get if you
typed in R in your command-line environment.
The first thing you will see in the R interactive session is a bunch of information, followed by a “>” and a blinking cursor. In many ways this is similar to the shell environment you learned about during the shell lessons: it operates on the same idea of a “Read, evaluate, print loop”: you type in commands, R tries to execute them, and then returns a result.
Using R as a calculator
The simplest thing you could do with R is to do arithmetic:
R
1 + 100
OUTPUT
[1] 101And R will print out the answer, with a preceding “[1]”. [1] is the index of the first element of the line being printed in the console. For more information on indexing vectors, see Episode 6: Subsetting Data.
If you type in an incomplete command, R will wait for you to complete it. If you are familiar with Unix Shell’s bash, you may recognize this behavior from bash.
OUTPUT
+Any time you hit return and the R session shows a “+” instead of a “>”, it means it’s waiting for you to complete the command. If you want to cancel a command you can hit Esc and RStudio will give you back the “>” prompt.
Tip: Canceling commands
If you’re using R from the command line instead of from within RStudio, you need to use Ctrl+C instead of Esc to cancel the command. This applies to Mac users as well!
Canceling a command isn’t only useful for killing incomplete commands: you can also use it to tell R to stop running code (for example if it’s taking much longer than you expect), or to get rid of the code you’re currently writing.
When using R as a calculator, the order of operations is the same as you would have learned back in school.
From highest to lowest precedence:
- Parentheses:
(,) - Exponents:
^or** - Multiply:
* - Divide:
/ - Add:
+ - Subtract:
-
R
3 + 5 * 2
OUTPUT
[1] 13Use parentheses to group operations in order to force the order of evaluation if it differs from the default, or to make clear what you intend.
R
(3 + 5) * 2
OUTPUT
[1] 16This can get unwieldy when not needed, but clarifies your intentions. Remember that others may later read your code.
R
(3 + (5 * (2 ^ 2))) # hard to read
3 + 5 * 2 ^ 2 # clear, if you remember the rules
3 + 5 * (2 ^ 2) # if you forget some rules, this might help
The text after each line of code is called a “comment”. Anything that
follows after the hash (or octothorpe) symbol # is ignored
by R when it executes code.
Really small or large numbers get a scientific notation:
R
2/10000
OUTPUT
[1] 2e-04Which is shorthand for “multiplied by 10^XX”. So
2e-4 is shorthand for 2 * 10^(-4).
You can write numbers in scientific notation too:
R
5e3 # Note the lack of minus here
OUTPUT
[1] 5000Mathematical functions
R has many built in mathematical functions. To call a function, we can type its name, followed by open and closing parentheses. Functions take arguments as inputs, anything we type inside the parentheses of a function is considered an argument. Depending on the function, the number of arguments can vary from none to multiple. For example:
R
getwd() #returns an absolute filepath
doesn’t require an argument, whereas for the next set of mathematical functions we will need to supply the function a value in order to compute the result.
R
sin(1) # trigonometry functions
OUTPUT
[1] 0.841471R
log(1) # natural logarithm
OUTPUT
[1] 0R
log10(10) # base-10 logarithm
OUTPUT
[1] 1R
exp(0.5) # e^(1/2)
OUTPUT
[1] 1.648721Don’t worry about trying to remember every function in R. You can look them up on Google, or if you can remember the start of the function’s name, use the tab completion in RStudio.
This is one advantage that RStudio has over R on its own, it has auto-completion abilities that allow you to more easily look up functions, their arguments, and the values that they take.
Typing a ? before the name of a command will open the
help page for that command. When using RStudio, this will open the
‘Help’ pane; if using R in the terminal, the help page will open in your
browser. The help page will include a detailed description of the
command and how it works. Scrolling to the bottom of the help page will
usually show a collection of code examples which illustrate command
usage. We’ll go through an example later.
Comparing things
We can also do comparisons in R:
R
1 == 1 # equality (note two equals signs, read as "is equal to")
OUTPUT
[1] TRUER
1 != 2 # inequality (read as "is not equal to")
OUTPUT
[1] TRUER
1 < 2 # less than
OUTPUT
[1] TRUER
1 <= 1 # less than or equal to
OUTPUT
[1] TRUER
1 > 0 # greater than
OUTPUT
[1] TRUER
1 >= -9 # greater than or equal to
OUTPUT
[1] TRUETip: Comparing Numbers
A word of warning about comparing numbers: you should never use
== to compare two numbers unless they are integers (a data
type which can specifically represent only whole numbers).
Computers may only represent decimal numbers with a certain degree of precision, so two numbers which look the same when printed out by R, may actually have different underlying representations and therefore be different by a small margin of error (called Machine numeric tolerance).
Instead you should use the all.equal function.
Further reading: http://floating-point-gui.de/
Variables and assignment
We can store values in variables using the assignment operator
<-, like this:
R
x <- 1/40
Notice that assignment does not print a value. Instead, we stored it
for later in something called a variable.
x now contains the value
0.025:
R
x
OUTPUT
[1] 0.025More precisely, the stored value is a decimal approximation of this fraction called a floating point number.
Look for the Environment tab in the top right panel of
RStudio, and you will see that x and its value have
appeared. Our variable x can be used in place of a number
in any calculation that expects a number:
R
log(x)
OUTPUT
[1] -3.688879Notice also that variables can be reassigned:
R
x <- 100
x used to contain the value 0.025 and now it has the
value 100.
Assignment values can contain the variable being assigned to:
R
x <- x + 1 #notice how RStudio updates its description of x on the top right tab
y <- x * 2
The right hand side of the assignment can be any valid R expression. The right hand side is fully evaluated before the assignment occurs.
Variable names can contain letters, numbers, underscores and periods but no spaces. They must start with a letter or a period followed by a letter (they cannot start with a number nor an underscore). Variables beginning with a period are hidden variables. Different people use different conventions for long variable names, these include
- periods.between.words
- underscores_between_words
- camelCaseToSeparateWords
What you use is up to you, but be consistent.
It is also possible to use the = operator for
assignment:
R
x = 1/40
But this is much less common among R users. The most important thing
is to be consistent with the operator you use. There
are occasionally places where it is less confusing to use
<- than =, and it is the most common symbol
used in the community. So the recommendation is to use
<-.
Vectorization
One final thing to be aware of is that R is vectorized, meaning that variables and functions can have vectors as values. In contrast to physics and mathematics, a vector in R describes a set of values in a certain order of the same data type. For example:
R
1:5
OUTPUT
[1] 1 2 3 4 5R
2^(1:5)
OUTPUT
[1] 2 4 8 16 32R
x <- 1:5
2^x
OUTPUT
[1] 2 4 8 16 32This is incredibly powerful; we will discuss this further in an upcoming lesson.
Managing your environment
There are a few useful commands you can use to interact with the R session.
ls will list all of the variables and functions stored
in the global environment (your working R session):
R
ls()
OUTPUT
[1] "x" "y"Note here that we didn’t give any arguments to ls, but
we still needed to give the parentheses to tell R to call the
function.
If we type ls by itself, R prints a bunch of code
instead of a listing of objects.
R
ls
OUTPUT
function (name, pos = -1L, envir = as.environment(pos), all.names = FALSE,
pattern, sorted = TRUE)
{
if (!missing(name)) {
pos <- tryCatch(name, error = function(e) e)
if (inherits(pos, "error")) {
name <- substitute(name)
if (!is.character(name))
name <- deparse(name)
warning(gettextf("%s converted to character string",
sQuote(name)), domain = NA)
pos <- name
}
}
all.names <- .Internal(ls(envir, all.names, sorted))
if (!missing(pattern)) {
if ((ll <- length(grep("[", pattern, fixed = TRUE))) &&
ll != length(grep("]", pattern, fixed = TRUE))) {
if (pattern == "[") {
pattern <- "\\["
warning("replaced regular expression pattern '[' by '\\\\['")
}
else if (length(grep("[^\\\\]\\[<-", pattern))) {
pattern <- sub("\\[<-", "\\\\\\[<-", pattern)
warning("replaced '[<-' by '\\\\[<-' in regular expression pattern")
}
}
grep(pattern, all.names, value = TRUE)
}
else all.names
}
<bytecode: 0x55b4e0d85d80>
<environment: namespace:base>What’s going on here?
Like everything in R, ls is the name of an object, and
entering the name of an object by itself prints the contents of the
object. The object x that we created earlier contains 1, 2,
3, 4, 5:
R
x
OUTPUT
[1] 1 2 3 4 5The object ls contains the R code that makes the
ls function work! We’ll talk more about how functions work
and start writing our own later.
You can use rm to delete objects you no longer need:
R
rm(x)
If you have lots of things in your environment and want to delete all
of them, you can pass the results of ls to the
rm function:
R
rm(list = ls())
In this case we’ve combined the two. Like the order of operations, anything inside the innermost parentheses is evaluated first, and so on.
In this case we’ve specified that the results of ls
should be used for the list argument in rm.
When assigning values to arguments by name, you must use the
= operator!!
If instead we use <-, there will be unintended side
effects, or you may get an error message:
R
rm(list <- ls())
ERROR
Error in rm(list <- ls()): ... must contain names or character stringsTip: Warnings vs. Errors
Pay attention when R does something unexpected! Errors, like above, are thrown when R cannot proceed with a calculation. Warnings on the other hand usually mean that the function has run, but it probably hasn’t worked as expected.
In both cases, the message that R prints out usually give you clues how to fix a problem.
R Packages
It is possible to add functions to R by writing a package, or by obtaining a package written by someone else. As of this writing, there are over 10,000 packages available on CRAN (the comprehensive R archive network). R and RStudio have functionality for managing packages:
- You can see what packages are installed by typing
installed.packages() - You can install packages by typing
install.packages("packagename"), wherepackagenameis the package name, in quotes. - You can update installed packages by typing
update.packages() - You can remove a package with
remove.packages("packagename") - You can make a package available for use with
library(packagename)
Packages can also be viewed, loaded, and detached in the Packages tab of the lower right panel in RStudio. Clicking on this tab will display all of the installed packages with a checkbox next to them. If the box next to a package name is checked, the package is loaded and if it is empty, the package is not loaded. Click an empty box to load that package and click a checked box to detach that package.
Packages can be installed and updated from the Package tab with the Install and Update buttons at the top of the tab.
Challenge 2
What will be the value of each variable after each statement in the following program?
R
mass <- 47.5
age <- 122
mass <- mass * 2.3
age <- age - 20
R
mass <- 47.5
This will give a value of 47.5 for the variable mass
R
age <- 122
This will give a value of 122 for the variable age
R
mass <- mass * 2.3
This will multiply the existing value of 47.5 by 2.3 to give a new value of 109.25 to the variable mass.
R
age <- age - 20
This will subtract 20 from the existing value of 122 to give a new value of 102 to the variable age.
Challenge 3
Run the code from the previous challenge, and write a command to compare mass to age. Is mass larger than age?
One way of answering this question in R is to use the
> to set up the following:
R
mass > age
OUTPUT
[1] TRUEThis should yield a boolean value of TRUE since 109.25 is greater than 102.
Challenge 4
Clean up your working environment by deleting the mass and age variables.
We can use the rm command to accomplish this task
R
rm(age, mass)
Challenge 5
Install the following packages: ggplot2,
plyr, gapminder
We can use the install.packages() command to install the
required packages.
R
install.packages("ggplot2")
install.packages("plyr")
install.packages("gapminder")
An alternate solution, to install multiple packages with a single
install.packages() command is:
R
install.packages(c("ggplot2", "plyr", "gapminder"))
When installing ggplot2, it may be required for some users to use the dependencies flag as a result of lazy loading affecting the install. This suggestion is not tied to any known bug discussion, and is advised based off instructor feedback/experience in resolving stochastic occurences of errors identified through delivery of this workshop:
R
install.packages("ggplot2", dependencies = TRUE)
Key Points
- Use RStudio to write and run R programs.
- R has the usual arithmetic operators and mathematical functions.
- Use
<-to assign values to variables. - Use
ls()to list the variables in a program. - Use
rm()to delete objects in a program. - Use
install.packages()to install packages (libraries).
Content from Project Management With RStudio
Last updated on 2024-12-04 | Edit this page
Estimated time: 30 minutes
Overview
Questions
- How can I manage my projects in R?
Objectives
- Create self-contained projects in RStudio
Introduction
The scientific process is naturally incremental, and many projects start life as random notes, some code, then a manuscript, and eventually everything is a bit mixed together.
Managing your projects in a reproducible fashion doesn’t just make your science reproducible, it makes your life easier.
— Vince Buffalo (@vsbuffalo) April 15, 2013
Most people tend to organize their projects like this:
There are many reasons why we should ALWAYS avoid this:
- It is really hard to tell which version of your data is the original and which is the modified;
- It gets really messy because it mixes files with various extensions together;
- It probably takes you a lot of time to actually find things, and relate the correct figures to the exact code that has been used to generate it;
A good project layout will ultimately make your life easier:
- It will help ensure the integrity of your data;
- It makes it simpler to share your code with someone else (a lab-mate, collaborator, or supervisor);
- It allows you to easily upload your code with your manuscript submission;
- It makes it easier to pick the project back up after a break.
A possible solution
Fortunately, there are tools and packages which can help you manage your work effectively.
One of the most powerful and useful aspects of RStudio is its project management functionality. We’ll be using this today to create a self-contained, reproducible project.
Challenge 1: Creating a self-contained project
We’re going to create a new project in RStudio:
- Click the “File” menu button, then “New Project”.
- Click “New Directory”.
- Click “New Project”.
- Type in the name of the directory to store your project, e.g. “my_project”.
- If available, select the checkbox for “Create a git repository.”
- Click the “Create Project” button.
The simplest way to open an RStudio project once it has been created
is to click through your file system to get to the directory where it
was saved and double click on the .Rproj file. This will
open RStudio and start your R session in the same directory as the
.Rproj file. All your data, plots and scripts will now be
relative to the project directory. RStudio projects have the added
benefit of allowing you to open multiple projects at the same time each
open to its own project directory. This allows you to keep multiple
projects open without them interfering with each other.
Challenge 2: Opening an RStudio project through the file system
- Exit RStudio.
- Navigate to the directory where you created a project in Challenge 1.
- Double click on the
.Rprojfile in that directory.
Best practices for project organization
Although there is no “best” way to lay out a project, there are some general principles to adhere to that will make project management easier:
Treat data as read only
This is probably the most important goal of setting up a project. Data is typically time consuming and/or expensive to collect. Working with them interactively (e.g., in Excel) where they can be modified means you are never sure of where the data came from, or how it has been modified since collection. It is therefore a good idea to treat your data as “read-only”.
Data Cleaning
In many cases your data will be “dirty”: it will need significant preprocessing to get into a format R (or any other programming language) will find useful. This task is sometimes called “data munging”. Storing these scripts in a separate folder, and creating a second “read-only” data folder to hold the “cleaned” data sets can prevent confusion between the two sets.
Treat generated output as disposable
Anything generated by your scripts should be treated as disposable: it should all be able to be regenerated from your scripts.
There are lots of different ways to manage this output. Having an output folder with different sub-directories for each separate analysis makes it easier later. Since many analyses are exploratory and don’t end up being used in the final project, and some of the analyses get shared between projects.
Tip: Good Enough Practices for Scientific Computing
Good Enough Practices for Scientific Computing gives the following recommendations for project organization:
- Put each project in its own directory, which is named after the project.
- Put text documents associated with the project in the
docdirectory. - Put raw data and metadata in the
datadirectory, and files generated during cleanup and analysis in aresultsdirectory. - Put source for the project’s scripts and programs in the
srcdirectory, and programs brought in from elsewhere or compiled locally in thebindirectory. - Name all files to reflect their content or function.
Separate function definition and application
One of the more effective ways to work with R is to start by writing the code you want to run directly in a .R script, and then running the selected lines (either using the keyboard shortcuts in RStudio or clicking the “Run” button) in the interactive R console.
When your project is in its early stages, the initial .R script file usually contains many lines of directly executed code. As it matures, reusable chunks get pulled into their own functions. It’s a good idea to separate these functions into two separate folders; one to store useful functions that you’ll reuse across analyses and projects, and one to store the analysis scripts.
Save the data in the data directory
Now we have a good directory structure we will now place/save the
data file in the data/ directory.
Challenge 3
Download the gapminder data from this link to a csv file.
- Download the file (right mouse click on the link above -> “Save link as” / “Save file as”, or click on the link and after the page loads, press Ctrl+S or choose File -> “Save page as”)
- Make sure it’s saved under the name
gapminder_data.csv - Save the file in the
data/folder within your project.
We will load and inspect these data later.
Challenge 4
It is useful to get some general idea about the dataset, directly from the command line, before loading it into R. Understanding the dataset better will come in handy when making decisions on how to load it in R. Use the command-line shell to answer the following questions:
- What is the size of the file?
- How many rows of data does it contain?
- What kinds of values are stored in this file?
By running these commands in the shell:
OUTPUT
-rw-r--r-- 1 runner docker 80K Dec 4 15:35 data/gapminder_data.csvThe file size is 80K.
OUTPUT
1705 data/gapminder_data.csvThere are 1705 lines. The data looks like:
OUTPUT
country,year,pop,continent,lifeExp,gdpPercap
Afghanistan,1952,8425333,Asia,28.801,779.4453145
Afghanistan,1957,9240934,Asia,30.332,820.8530296
Afghanistan,1962,10267083,Asia,31.997,853.10071
Afghanistan,1967,11537966,Asia,34.02,836.1971382
Afghanistan,1972,13079460,Asia,36.088,739.9811058
Afghanistan,1977,14880372,Asia,38.438,786.11336
Afghanistan,1982,12881816,Asia,39.854,978.0114388
Afghanistan,1987,13867957,Asia,40.822,852.3959448
Afghanistan,1992,16317921,Asia,41.674,649.3413952Tip: command line in RStudio
The Terminal tab in the console pane provides a convenient place directly within RStudio to interact directly with the command line.
Working directory
Knowing R’s current working directory is important because when you need to access other files (for example, to import a data file), R will look for them relative to the current working directory.
Each time you create a new RStudio Project, it will create a new
directory for that project. When you open an existing
.Rproj file, it will open that project and set R’s working
directory to the folder that file is in.
Challenge 5
You can check the current working directory with the
getwd() command, or by using the menus in RStudio.
- In the console, type
getwd()(“wd” is short for “working directory”) and hit Enter. - In the Files pane, double click on the
datafolder to open it (or navigate to any other folder you wish). To get the Files pane back to the current working directory, click “More” and then select “Go To Working Directory”.
You can change the working directory with setwd(), or by
using RStudio menus.
- In the console, type
setwd("data")and hit Enter. Typegetwd()and hit Enter to see the new working directory. - In the menus at the top of the RStudio window, click the “Session”
menu button, and then select “Set Working Directory” and then “Choose
Directory”. Next, in the windows navigator that opens, navigate back to
the project directory, and click “Open”. Note that a
setwdcommand will automatically appear in the console.
Tip: File does not exist errors
When you’re attempting to reference a file in your R code and you’re getting errors saying the file doesn’t exist, it’s a good idea to check your working directory. You need to either provide an absolute path to the file, or you need to make sure the file is saved in the working directory (or a subfolder of the working directory) and provide a relative path.
Version Control
It is important to use version control with projects. Go here for a good lesson which describes using Git with RStudio.
Key Points
- Use RStudio to create and manage projects with consistent layout.
- Treat raw data as read-only.
- Treat generated output as disposable.
- Separate function definition and application.
Content from Seeking Help
Last updated on 2024-12-04 | Edit this page
Estimated time: 20 minutes
Overview
Questions
- How can I get help in R?
Objectives
- To be able to read R help files for functions and special operators.
- To be able to use CRAN task views to identify packages to solve a problem.
- To be able to seek help from your peers.
Reading Help Files
R, and every package, provide help files for functions. The general syntax to search for help on any function, “function_name”, from a specific function that is in a package loaded into your namespace (your interactive R session) is:
R
?function_name
help(function_name)
For example take a look at the help file for
write.table(), we will be using a similar function in an
upcoming episode.
R
?write.table()
This will load up a help page in RStudio (or as plain text in R itself).
Each help page is broken down into sections:
- Description: An extended description of what the function does.
- Usage: The arguments of the function and their default values (which can be changed).
- Arguments: An explanation of the data each argument is expecting.
- Details: Any important details to be aware of.
- Value: The data the function returns.
- See Also: Any related functions you might find useful.
- Examples: Some examples for how to use the function.
Different functions might have different sections, but these are the main ones you should be aware of.
Notice how related functions might call for the same help file:
R
?write.table()
?write.csv()
This is because these functions have very similar applicability and often share the same arguments as inputs to the function, so package authors often choose to document them together in a single help file.
Tip: Running Examples
From within the function help page, you can highlight code in the Examples and hit Ctrl+Return to run it in RStudio console. This gives you a quick way to get a feel for how a function works.
Tip: Reading Help Files
One of the most daunting aspects of R is the large number of functions available. It would be prohibitive, if not impossible to remember the correct usage for every function you use. Luckily, using the help files means you don’t have to remember that!
Special Operators
To seek help on special operators, use quotes or backticks:
R
?"<-"
?`<-`
Getting Help with Packages
Many packages come with “vignettes”: tutorials and extended example
documentation. Without any arguments, vignette() will list
all vignettes for all installed packages;
vignette(package="package-name") will list all available
vignettes for package-name, and
vignette("vignette-name") will open the specified
vignette.
If a package doesn’t have any vignettes, you can usually find help by
typing help("package-name").
RStudio also has a set of excellent cheatsheets for many packages.
When You Remember Part of the Function Name
If you’re not sure what package a function is in or how it’s specifically spelled, you can do a fuzzy search:
R
??function_name
A fuzzy search is when you search for an approximate string match. For example, you may remember that the function to set your working directory includes “set” in its name. You can do a fuzzy search to help you identify the function:
R
??set
When You Have No Idea Where to Begin
If you don’t know what function or package you need to use CRAN Task Views is a specially maintained list of packages grouped into fields. This can be a good starting point.
When Your Code Doesn’t Work: Seeking Help from Your Peers
If you’re having trouble using a function, 9 times out of 10, the
answers you seek have already been answered on Stack Overflow. You can search
using the [r] tag. Please make sure to see their page on how to ask a good
question.
If you can’t find the answer, there are a few useful functions to help you ask your peers:
R
?dput
Will dump the data you’re working with into a format that can be copied and pasted by others into their own R session.
R
sessionInfo()
OUTPUT
R version 4.4.2 (2024-10-31)
Platform: x86_64-pc-linux-gnu
Running under: Ubuntu 22.04.5 LTS
Matrix products: default
BLAS: /usr/lib/x86_64-linux-gnu/blas/libblas.so.3.10.0
LAPACK: /usr/lib/x86_64-linux-gnu/lapack/liblapack.so.3.10.0
locale:
[1] LC_CTYPE=C.UTF-8 LC_NUMERIC=C LC_TIME=C.UTF-8
[4] LC_COLLATE=C.UTF-8 LC_MONETARY=C.UTF-8 LC_MESSAGES=C.UTF-8
[7] LC_PAPER=C.UTF-8 LC_NAME=C LC_ADDRESS=C
[10] LC_TELEPHONE=C LC_MEASUREMENT=C.UTF-8 LC_IDENTIFICATION=C
time zone: UTC
tzcode source: system (glibc)
attached base packages:
[1] stats graphics grDevices utils datasets methods base
loaded via a namespace (and not attached):
[1] compiler_4.4.2 tools_4.4.2 yaml_2.3.10 knitr_1.49 xfun_0.49
[6] renv_1.0.11 evaluate_1.0.1Will print out your current version of R, as well as any packages you have loaded. This can be useful for others to help reproduce and debug your issue.
Challenge 1
Look at the help page for the c function. What kind of
vector do you expect will be created if you evaluate the following:
R
c(1, 2, 3)
c('d', 'e', 'f')
c(1, 2, 'f')
The c() function creates a vector, in which all elements
are of the same type. In the first case, the elements are numeric, in
the second, they are characters, and in the third they are also
characters: the numeric values are “coerced” to be characters.
Challenge 2
Look at the help for the paste function. You will need
to use it later. What’s the difference between the sep and
collapse arguments?
To look at the help for the paste() function, use:
R
help("paste")
?paste
The difference between sep and collapse is
a little tricky. The paste function accepts any number of
arguments, each of which can be a vector of any length. The
sep argument specifies the string used between concatenated
terms — by default, a space. The result is a vector as long as the
longest argument supplied to paste. In contrast,
collapse specifies that after concatenation the elements
are collapsed together using the given separator, the result
being a single string.
It is important to call the arguments explicitly by typing out the
argument name e.g sep = "," so the function understands to
use the “,” as a separator and not a term to concatenate. e.g.
R
paste(c("a","b"), "c")
OUTPUT
[1] "a c" "b c"R
paste(c("a","b"), "c", ",")
OUTPUT
[1] "a c ," "b c ,"R
paste(c("a","b"), "c", sep = ",")
OUTPUT
[1] "a,c" "b,c"R
paste(c("a","b"), "c", collapse = "|")
OUTPUT
[1] "a c|b c"R
paste(c("a","b"), "c", sep = ",", collapse = "|")
OUTPUT
[1] "a,c|b,c"(For more information, scroll to the bottom of the
?paste help page and look at the examples, or try
example('paste').)
Challenge 3
Use help to find a function (and its associated parameters) that you
could use to load data from a tabular file in which columns are
delimited with “\t” (tab) and the decimal point is a “.” (period). This
check for decimal separator is important, especially if you are working
with international colleagues, because different countries have
different conventions for the decimal point (i.e. comma vs period).
Hint: use ??"read table" to look up functions related to
reading in tabular data.
The standard R function for reading tab-delimited files with a period
decimal separator is read.delim(). You can also do this with
read.table(file, sep="\t") (the period is the
default decimal separator for read.table()),
although you may have to change the comment.char argument
as well if your data file contains hash (#) characters.
Other Resources
Key Points
- Use
help()to get online help in R.
Content from Data Structures
Last updated on 2024-12-04 | Edit this page
Estimated time: 55 minutes
Overview
Questions
- How can I read data in R?
- What are the basic data types in R?
- How do I represent categorical information in R?
Objectives
- To be able to identify the 5 main data types.
- To begin exploring data frames, and understand how they are related to vectors and lists.
- To be able to ask questions from R about the type, class, and structure of an object.
- To understand the information of the attributes “names”, “class”, and “dim”.
One of R’s most powerful features is its ability to deal with tabular
data - such as you may already have in a spreadsheet or a CSV file.
Let’s start by making a toy dataset in your data/
directory, called feline-data.csv:
R
cats <- data.frame(coat = c("calico", "black", "tabby"),
weight = c(2.1, 5.0, 3.2),
likes_string = c(1, 0, 1))
We can now save cats as a CSV file. It is good practice
to call the argument names explicitly so the function knows what default
values you are changing. Here we are setting
row.names = FALSE. Recall you can use
?write.csv to pull up the help file to check out the
argument names and their default values.
R
write.csv(x = cats, file = "data/feline-data.csv", row.names = FALSE)
The contents of the new file, feline-data.csv:
Tip: Editing Text files in R
Alternatively, you can create data/feline-data.csv using
a text editor (Nano), or within RStudio with the File -> New
File -> Text File menu item.
We can load this into R via the following:
R
cats <- read.csv(file = "data/feline-data.csv")
cats
OUTPUT
coat weight likes_string
1 calico 2.1 1
2 black 5.0 0
3 tabby 3.2 1The read.table function is used for reading in tabular
data stored in a text file where the columns of data are separated by
punctuation characters such as CSV files (csv = comma-separated values).
Tabs and commas are the most common punctuation characters used to
separate or delimit data points in csv files. For convenience R provides
2 other versions of read.table. These are:
read.csv for files where the data are separated with commas
and read.delim for files where the data are separated with
tabs. Of these three functions read.csv is the most
commonly used. If needed it is possible to override the default
delimiting punctuation marks for both read.csv and
read.delim.
Check your data for factors
In recent times, the default way how R handles textual data has changed. Text data was interpreted by R automatically into a format called “factors”. But there is an easier format that is called “character”. We will hear about factors later, and what to use them for. For now, remember that in most cases, they are not needed and only complicate your life, which is why newer R versions read in text as “character”. Check now if your version of R has automatically created factors and convert them to “character” format:
- Check the data types of your input by typing
str(cats) - In the output, look at the three-letter codes after the colons: If you see only “num” and “chr”, you can continue with the lesson and skip this box. If you find “fct”, continue to step 3.
- Prevent R from automatically creating “factor” data. That can be
done by the following code:
options(stringsAsFactors = FALSE). Then, re-read the cats table for the change to take effect. - You must set this option every time you restart R. To not forget this, include it in your analysis script before you read in any data, for example in one of the first lines.
- For R versions greater than 4.0.0, text data is no longer converted to factors anymore. So you can install this or a newer version to avoid this problem. If you are working on an institute or company computer, ask your administrator to do it.
We can begin exploring our dataset right away, pulling out columns by
specifying them using the $ operator:
R
cats$weight
OUTPUT
[1] 2.1 5.0 3.2R
cats$coat
OUTPUT
[1] "calico" "black" "tabby" We can do other operations on the columns:
R
## Say we discovered that the scale weighs two Kg light:
cats$weight + 2
OUTPUT
[1] 4.1 7.0 5.2R
paste("My cat is", cats$coat)
OUTPUT
[1] "My cat is calico" "My cat is black" "My cat is tabby" But what about
R
cats$weight + cats$coat
ERROR
Error in cats$weight + cats$coat: non-numeric argument to binary operatorUnderstanding what happened here is key to successfully analyzing data in R.
Data Types
If you guessed that the last command will return an error because
2.1 plus "black" is nonsense, you’re right -
and you already have some intuition for an important concept in
programming called data types. We can ask what type of data
something is:
R
typeof(cats$weight)
OUTPUT
[1] "double"There are 5 main types: double, integer,
complex, logical and character.
For historic reasons, double is also called
numeric.
R
typeof(3.14)
OUTPUT
[1] "double"R
typeof(1L) # The L suffix forces the number to be an integer, since by default R uses float numbers
OUTPUT
[1] "integer"R
typeof(1+1i)
OUTPUT
[1] "complex"R
typeof(TRUE)
OUTPUT
[1] "logical"R
typeof('banana')
OUTPUT
[1] "character"No matter how complicated our analyses become, all data in R is interpreted as one of these basic data types. This strictness has some really important consequences.
A user has added details of another cat. This information is in the
file data/feline-data_v2.csv.
R
file.show("data/feline-data_v2.csv")
Load the new cats data like before, and check what type of data we
find in the weight column:
R
cats <- read.csv(file="data/feline-data_v2.csv")
typeof(cats$weight)
OUTPUT
[1] "character"Oh no, our weights aren’t the double type anymore! If we try to do the same math we did on them before, we run into trouble:
R
cats$weight + 2
ERROR
Error in cats$weight + 2: non-numeric argument to binary operatorWhat happened? The cats data we are working with is
something called a data frame. Data frames are one of the most
common and versatile types of data structures we will work with
in R. A given column in a data frame cannot be composed of different
data types. In this case, R does not read everything in the data frame
column weight as a double, therefore the entire
column data type changes to something that is suitable for everything in
the column.
When R reads a csv file, it reads it in as a data frame.
Thus, when we loaded the cats csv file, it is stored as a
data frame. We can recognize data frames by the first row that is
written by the str() function:
R
str(cats)
OUTPUT
'data.frame': 4 obs. of 3 variables:
$ coat : chr "calico" "black" "tabby" "tabby"
$ weight : chr "2.1" "5" "3.2" "2.3 or 2.4"
$ likes_string: int 1 0 1 1Data frames are composed of rows and columns, where each column has the same number of rows. Different columns in a data frame can be made up of different data types (this is what makes them so versatile), but everything in a given column needs to be the same type (e.g., vector, factor, or list).
Let’s explore more about different data structures and how they behave. For now, let’s remove that extra line from our cats data and reload it, while we investigate this behavior further:
feline-data.csv:
coat,weight,likes_string
calico,2.1,1
black,5.0,0
tabby,3.2,1And back in RStudio:
R
cats <- read.csv(file="data/feline-data.csv")
Vectors and Type Coercion
To better understand this behavior, let’s meet another of the data structures: the vector.
R
my_vector <- vector(length = 3)
my_vector
OUTPUT
[1] FALSE FALSE FALSEA vector in R is essentially an ordered list of things, with the
special condition that everything in the vector must be the same
basic data type. If you don’t choose the datatype, it’ll default to
logical; or, you can declare an empty vector of whatever
type you like.
R
another_vector <- vector(mode='character', length=3)
another_vector
OUTPUT
[1] "" "" ""You can check if something is a vector:
R
str(another_vector)
OUTPUT
chr [1:3] "" "" ""The somewhat cryptic output from this command indicates the basic
data type found in this vector - in this case chr,
character; an indication of the number of things in the vector -
actually, the indexes of the vector, in this case [1:3];
and a few examples of what’s actually in the vector - in this case empty
character strings. If we similarly do
R
str(cats$weight)
OUTPUT
num [1:3] 2.1 5 3.2we see that cats$weight is a vector, too - the
columns of data we load into R data.frames are all vectors, and
that’s the root of why R forces everything in a column to be the same
basic data type.
Discussion 1
Why is R so opinionated about what we put in our columns of data? How does this help us?
By keeping everything in a column the same, we allow ourselves to make simple assumptions about our data; if you can interpret one entry in the column as a number, then you can interpret all of them as numbers, so we don’t have to check every time. This consistency is what people mean when they talk about clean data; in the long run, strict consistency goes a long way to making our lives easier in R.
Coercion by combining vectors
You can also make vectors with explicit contents with the combine function:
R
combine_vector <- c(2,6,3)
combine_vector
OUTPUT
[1] 2 6 3Given what we’ve learned so far, what do you think the following will produce?
R
quiz_vector <- c(2,6,'3')
This is something called type coercion, and it is the source of many surprises and the reason why we need to be aware of the basic data types and how R will interpret them. When R encounters a mix of types (here double and character) to be combined into a single vector, it will force them all to be the same type. Consider:
R
coercion_vector <- c('a', TRUE)
coercion_vector
OUTPUT
[1] "a" "TRUE"R
another_coercion_vector <- c(0, TRUE)
another_coercion_vector
OUTPUT
[1] 0 1The type hierarchy
The coercion rules go: logical ->
integer -> double (“numeric”)
-> complex -> character, where -> can
be read as are transformed into. For example, combining
logical and character transforms the result to
character:
R
c('a', TRUE)
OUTPUT
[1] "a" "TRUE"A quick way to recognize character vectors is by the
quotes that enclose them when they are printed.
You can try to force coercion against this flow using the
as. functions:
R
character_vector_example <- c('0','2','4')
character_vector_example
OUTPUT
[1] "0" "2" "4"R
character_coerced_to_double <- as.double(character_vector_example)
character_coerced_to_double
OUTPUT
[1] 0 2 4R
double_coerced_to_logical <- as.logical(character_coerced_to_double)
double_coerced_to_logical
OUTPUT
[1] FALSE TRUE TRUEAs you can see, some surprising things can happen when R forces one basic data type into another! Nitty-gritty of type coercion aside, the point is: if your data doesn’t look like what you thought it was going to look like, type coercion may well be to blame; make sure everything is the same type in your vectors and your columns of data.frames, or you will get nasty surprises!
But coercion can also be very useful! For example, in our
cats data likes_string is numeric, but we know
that the 1s and 0s actually represent TRUE and
FALSE (a common way of representing them). We should use
the logical datatype here, which has two states:
TRUE or FALSE, which is exactly what our data
represents. We can ‘coerce’ this column to be logical by
using the as.logical function:
R
cats$likes_string
OUTPUT
[1] 1 0 1R
cats$likes_string <- as.logical(cats$likes_string)
cats$likes_string
OUTPUT
[1] TRUE FALSE TRUEChallenge 1
An important part of every data analysis is cleaning the input data. If you know that the input data is all of the same format, (e.g. numbers), your analysis is much easier! Clean the cat data set from the chapter about type coercion.
Copy the code template
Create a new script in RStudio and copy and paste the following code. Then move on to the tasks below, which help you to fill in the gaps (______).
# Read data
cats <- read.csv("data/feline-data_v2.csv")
# 1. Print the data
_____
# 2. Show an overview of the table with all data types
_____(cats)
# 3. The "weight" column has the incorrect data type __________.
# The correct data type is: ____________.
# 4. Correct the 4th weight data point with the mean of the two given values
cats$weight[4] <- 2.35
# print the data again to see the effect
cats
# 5. Convert the weight to the right data type
cats$weight <- ______________(cats$weight)
# Calculate the mean to test yourself
mean(cats$weight)
# If you see the correct mean value (and not NA), you did the exercise
# correctly!2. Overview of the data types
The data type of your data is as important as the data itself. Use a
function we saw earlier to print out the data types of all columns of
the cats table.
In the chapter “Data types” we saw two functions that can show data types. One printed just a single word, the data type name. The other printed a short form of the data type, and the first few values. We need the second here.
Challenge 1 (continued)
Solution to Challenge 1.2
str(cats)
Scroll up to the section about the type hierarchy to review the available data types
- Weight is expressed on a continuous scale (real numbers). The R data type for this is “double” (also known as “numeric”).
- The fourth row has the value “2.3 or 2.4”. That is not a number but two, and an english word. Therefore, the “character” data type is chosen. The whole column is now text, because all values in the same columns have to be the same data type.
4. Correct the problematic value
The code to assign a new weight value to the problematic fourth row is given. Think first and then execute it: What will be the data type after assigning a number like in this example? You can check the data type after executing to see if you were right.
Revisit the hierarchy of data types when two different data types are combined.
Challenge 1 (continued)
Solution to challenge 1.4
The data type of the column “weight” is “character”. The assigned data type is “double”. Combining two data types yields the data type that is higher in the following hierarchy:
logical < integer < double < complex < characterTherefore, the column is still of type character! We need to manually convert it to “double”. {: .solution}
The functions to convert data types start with as.. You
can look for the function further up in the manuscript or use the
RStudio auto-complete function: Type “as.” and then press
the TAB key.
Challenge 1 (continued)
Solution to Challenge 1.5
There are two functions that are synonymous for historic reasons:
cats$weight <- as.double(cats$weight) cats$weight <- as.numeric(cats$weight)
Some basic vector functions
The combine function, c(), will also append things to an
existing vector:
R
ab_vector <- c('a', 'b')
ab_vector
OUTPUT
[1] "a" "b"R
combine_example <- c(ab_vector, 'SWC')
combine_example
OUTPUT
[1] "a" "b" "SWC"You can also make series of numbers:
R
mySeries <- 1:10
mySeries
OUTPUT
[1] 1 2 3 4 5 6 7 8 9 10R
seq(10)
OUTPUT
[1] 1 2 3 4 5 6 7 8 9 10R
seq(1,10, by=0.1)
OUTPUT
[1] 1.0 1.1 1.2 1.3 1.4 1.5 1.6 1.7 1.8 1.9 2.0 2.1 2.2 2.3 2.4
[16] 2.5 2.6 2.7 2.8 2.9 3.0 3.1 3.2 3.3 3.4 3.5 3.6 3.7 3.8 3.9
[31] 4.0 4.1 4.2 4.3 4.4 4.5 4.6 4.7 4.8 4.9 5.0 5.1 5.2 5.3 5.4
[46] 5.5 5.6 5.7 5.8 5.9 6.0 6.1 6.2 6.3 6.4 6.5 6.6 6.7 6.8 6.9
[61] 7.0 7.1 7.2 7.3 7.4 7.5 7.6 7.7 7.8 7.9 8.0 8.1 8.2 8.3 8.4
[76] 8.5 8.6 8.7 8.8 8.9 9.0 9.1 9.2 9.3 9.4 9.5 9.6 9.7 9.8 9.9
[91] 10.0We can ask a few questions about vectors:
R
sequence_example <- 20:25
head(sequence_example, n=2)
OUTPUT
[1] 20 21R
tail(sequence_example, n=4)
OUTPUT
[1] 22 23 24 25R
length(sequence_example)
OUTPUT
[1] 6R
typeof(sequence_example)
OUTPUT
[1] "integer"We can get individual elements of a vector by using the bracket notation:
R
first_element <- sequence_example[1]
first_element
OUTPUT
[1] 20To change a single element, use the bracket on the other side of the arrow:
R
sequence_example[1] <- 30
sequence_example
OUTPUT
[1] 30 21 22 23 24 25Challenge 2
Start by making a vector with the numbers 1 through 26. Then, multiply the vector by 2.
R
x <- 1:26
x <- x * 2
Lists
Another data structure you’ll want in your bag of tricks is the
list. A list is simpler in some ways than the other types,
because you can put anything you want in it. Remember everything in
the vector must be of the same basic data type, but a list can have
different data types:
R
list_example <- list(1, "a", TRUE, 1+4i)
list_example
OUTPUT
[[1]]
[1] 1
[[2]]
[1] "a"
[[3]]
[1] TRUE
[[4]]
[1] 1+4iWhen printing the object structure with str(), we see
the data types of all elements:
R
str(list_example)
OUTPUT
List of 4
$ : num 1
$ : chr "a"
$ : logi TRUE
$ : cplx 1+4iWhat is the use of lists? They can organize data of different types. For example, you can organize different tables that belong together, similar to spreadsheets in Excel. But there are many other uses, too.
We will see another example that will maybe surprise you in the next chapter.
To retrieve one of the elements of a list, use the double bracket:
R
list_example[[2]]
OUTPUT
[1] "a"The elements of lists also can have names, they can be given by prepending them to the values, separated by an equals sign:
R
another_list <- list(title = "Numbers", numbers = 1:10, data = TRUE )
another_list
OUTPUT
$title
[1] "Numbers"
$numbers
[1] 1 2 3 4 5 6 7 8 9 10
$data
[1] TRUEThis results in a named list. Now we have a new function of our object! We can access single elements by an additional way!
R
another_list$title
OUTPUT
[1] "Numbers"Names
With names, we can give meaning to elements. It is the first time that we do not only have the data, but also explaining information. It is metadata that can be stuck to the object like a label. In R, this is called an attribute. Some attributes enable us to do more with our object, for example, like here, accessing an element by a self-defined name.
Accessing vectors and lists by name
We have already seen how to generate a named list. The way to generate a named vector is very similar. You have seen this function before:
R
pizza_price <- c( pizzasubito = 5.64, pizzafresh = 6.60, callapizza = 4.50 )
The way to retrieve elements is different, though:
R
pizza_price["pizzasubito"]
OUTPUT
pizzasubito
5.64 The approach used for the list does not work:
R
pizza_price$pizzafresh
ERROR
Error in pizza_price$pizzafresh: $ operator is invalid for atomic vectorsIt will pay off if you remember this error message, you will meet it in your own analyses. It means that you have just tried accessing an element like it was in a list, but it is actually in a vector.
Accessing and changing names
If you are only interested in the names, use the names()
function:
R
names(pizza_price)
OUTPUT
[1] "pizzasubito" "pizzafresh" "callapizza" We have seen how to access and change single elements of a vector. The same is possible for names:
R
names(pizza_price)[3]
OUTPUT
[1] "callapizza"R
names(pizza_price)[3] <- "call-a-pizza"
pizza_price
OUTPUT
pizzasubito pizzafresh call-a-pizza
5.64 6.60 4.50 Challenge 3
- What is the data type of the names of
pizza_price? You can find out using thestr()ortypeof()functions.
You get the names of an object by wrapping the object name inside
names(...). Similarly, you get the data type of the names
by again wrapping the whole code in typeof(...):
typeof(names(pizza))alternatively, use a new variable if this is easier for you to read:
n <- names(pizza)
typeof(n)Challenge 4
Instead of just changing some of the names a vector/list already has, you can also set all names of an object by writing code like (replace ALL CAPS text):
names( OBJECT ) <- CHARACTER_VECTORCreate a vector that gives the number for each letter in the alphabet!
- Generate a vector called
letter_nowith the sequence of numbers from 1 to 26! - R has a built-in object called
LETTERS. It is a 26-character vector, from A to Z. Set the names of the number sequence to this 26 letters - Test yourself by calling
letter_no["B"], which should give you the number 2!
letter_no <- 1:26 # or seq(1,26)
names(letter_no) <- LETTERS
letter_no["B"]Data frames
We have data frames at the very beginning of this lesson, they represent a table of data. We didn’t go much further into detail with our example cat data frame:
R
cats
OUTPUT
coat weight likes_string
1 calico 2.1 TRUE
2 black 5.0 FALSE
3 tabby 3.2 TRUEWe can now understand something a bit surprising in our data.frame; what happens if we run:
R
typeof(cats)
OUTPUT
[1] "list"We see that data.frames look like lists ‘under the hood’. Think again what we heard about what lists can be used for:
Lists organize data of different types
Columns of a data frame are vectors of different types, that are organized by belonging to the same table.
A data.frame is really a list of vectors. It is a special list in which all the vectors must have the same length.
How is this “special”-ness written into the object, so that R does not treat it like any other list, but as a table?
R
class(cats)
OUTPUT
[1] "data.frame"A class, just like names, is an attribute attached to the object. It tells us what this object means for humans.
You might wonder: Why do we need another
what-type-of-object-is-this-function? We already have
typeof()? That function tells us how the object is
constructed in the computer. The class is
the meaning of the object for humans. Consequently,
what typeof() returns is fixed in R (mainly the
five data types), whereas the output of class() is
diverse and extendable by R packages.
In our cats example, we have an integer, a double and a
logical variable. As we have seen already, each column of data.frame is
a vector.
R
cats$coat
OUTPUT
[1] "calico" "black" "tabby" R
cats[,1]
OUTPUT
[1] "calico" "black" "tabby" R
typeof(cats[,1])
OUTPUT
[1] "character"R
str(cats[,1])
OUTPUT
chr [1:3] "calico" "black" "tabby"Each row is an observation of different variables, itself a data.frame, and thus can be composed of elements of different types.
R
cats[1,]
OUTPUT
coat weight likes_string
1 calico 2.1 TRUER
typeof(cats[1,])
OUTPUT
[1] "list"R
str(cats[1,])
OUTPUT
'data.frame': 1 obs. of 3 variables:
$ coat : chr "calico"
$ weight : num 2.1
$ likes_string: logi TRUEChallenge 5
There are several subtly different ways to call variables, observations and elements from data.frames:
cats[1]cats[[1]]cats$coatcats["coat"]cats[1, 1]cats[, 1]cats[1, ]
Try out these examples and explain what is returned by each one.
Hint: Use the function typeof() to examine what
is returned in each case.
R
cats[1]
OUTPUT
coat
1 calico
2 black
3 tabbyWe can think of a data frame as a list of vectors. The single brace
[1] returns the first slice of the list, as another list.
In this case it is the first column of the data frame.
R
cats[[1]]
OUTPUT
[1] "calico" "black" "tabby" The double brace [[1]] returns the contents of the list
item. In this case it is the contents of the first column, a
vector of type character.
R
cats$coat
OUTPUT
[1] "calico" "black" "tabby" This example uses the $ character to address items by
name. coat is the first column of the data frame, again a
vector of type character.
R
cats["coat"]
OUTPUT
coat
1 calico
2 black
3 tabbyHere we are using a single brace ["coat"] replacing the
index number with the column name. Like example 1, the returned object
is a list.
R
cats[1, 1]
OUTPUT
[1] "calico"This example uses a single brace, but this time we provide row and column coordinates. The returned object is the value in row 1, column 1. The object is a vector of type character.
R
cats[, 1]
OUTPUT
[1] "calico" "black" "tabby" Like the previous example we use single braces and provide row and column coordinates. The row coordinate is not specified, R interprets this missing value as all the elements in this column and returns them as a vector.
R
cats[1, ]
OUTPUT
coat weight likes_string
1 calico 2.1 TRUEAgain we use the single brace with row and column coordinates. The column coordinate is not specified. The return value is a list containing all the values in the first row.
Tip: Renaming data frame columns
Data frames have column names, which can be accessed with the
names() function.
R
names(cats)
OUTPUT
[1] "coat" "weight" "likes_string"If you want to rename the second column of cats, you can
assign a new name to the second element of names(cats).
R
names(cats)[2] <- "weight_kg"
cats
OUTPUT
coat weight_kg likes_string
1 calico 2.1 TRUE
2 black 5.0 FALSE
3 tabby 3.2 TRUEMatrices
Last but not least is the matrix. We can declare a matrix full of zeros:
R
matrix_example <- matrix(0, ncol=6, nrow=3)
matrix_example
OUTPUT
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] 0 0 0 0 0 0
[2,] 0 0 0 0 0 0
[3,] 0 0 0 0 0 0What makes it special is the dim() attribute:
R
dim(matrix_example)
OUTPUT
[1] 3 6And similar to other data structures, we can ask things about our matrix:
R
typeof(matrix_example)
OUTPUT
[1] "double"R
class(matrix_example)
OUTPUT
[1] "matrix" "array" R
str(matrix_example)
OUTPUT
num [1:3, 1:6] 0 0 0 0 0 0 0 0 0 0 ...R
nrow(matrix_example)
OUTPUT
[1] 3R
ncol(matrix_example)
OUTPUT
[1] 6Challenge 6
What do you think will be the result of
length(matrix_example)? Try it. Were you right? Why / why
not?
What do you think will be the result of
length(matrix_example)?
R
matrix_example <- matrix(0, ncol=6, nrow=3)
length(matrix_example)
OUTPUT
[1] 18Because a matrix is a vector with added dimension attributes,
length gives you the total number of elements in the
matrix.
Challenge 7
Make another matrix, this time containing the numbers 1:50, with 5
columns and 10 rows. Did the matrix function fill your
matrix by column, or by row, as its default behaviour? See if you can
figure out how to change this. (hint: read the documentation for
matrix!)
Make another matrix, this time containing the numbers 1:50, with 5
columns and 10 rows. Did the matrix function fill your
matrix by column, or by row, as its default behaviour? See if you can
figure out how to change this. (hint: read the documentation for
matrix!)
R
x <- matrix(1:50, ncol=5, nrow=10)
x <- matrix(1:50, ncol=5, nrow=10, byrow = TRUE) # to fill by row
Challenge 8
Create a list of length two containing a character vector for each of the sections in this part of the workshop:
- Data types
- Data structures
Populate each character vector with the names of the data types and data structures we’ve seen so far.
R
dataTypes <- c('double', 'complex', 'integer', 'character', 'logical')
dataStructures <- c('data.frame', 'vector', 'list', 'matrix')
answer <- list(dataTypes, dataStructures)
Note: it’s nice to make a list in big writing on the board or taped to the wall listing all of these types and structures - leave it up for the rest of the workshop to remind people of the importance of these basics.
Challenge 9
Consider the R output of the matrix below:
OUTPUT
[,1] [,2]
[1,] 4 1
[2,] 9 5
[3,] 10 7What was the correct command used to write this matrix? Examine each command and try to figure out the correct one before typing them. Think about what matrices the other commands will produce.
matrix(c(4, 1, 9, 5, 10, 7), nrow = 3)matrix(c(4, 9, 10, 1, 5, 7), ncol = 2, byrow = TRUE)matrix(c(4, 9, 10, 1, 5, 7), nrow = 2)matrix(c(4, 1, 9, 5, 10, 7), ncol = 2, byrow = TRUE)
Consider the R output of the matrix below:
OUTPUT
[,1] [,2]
[1,] 4 1
[2,] 9 5
[3,] 10 7What was the correct command used to write this matrix? Examine each command and try to figure out the correct one before typing them. Think about what matrices the other commands will produce.
R
matrix(c(4, 1, 9, 5, 10, 7), ncol = 2, byrow = TRUE)
Key Points
- Use
read.csvto read tabular data in R. - The basic data types in R are double, integer, complex, logical, and character.
- Data structures such as data frames or matrices are built on top of lists and vectors, with some added attributes.
Content from Exploring Data Frames
Last updated on 2024-12-04 | Edit this page
Estimated time: 30 minutes
Overview
Questions
- How can I manipulate a data frame?
Objectives
- Add and remove rows or columns.
- Append two data frames.
- Display basic properties of data frames including size and class of the columns, names, and first few rows.
At this point, you’ve seen it all: in the last lesson, we toured all the basic data types and data structures in R. Everything you do will be a manipulation of those tools. But most of the time, the star of the show is the data frame—the table that we created by loading information from a csv file. In this lesson, we’ll learn a few more things about working with data frames.
Adding columns and rows in data frames
We already learned that the columns of a data frame are vectors, so that our data are consistent in type throughout the columns. As such, if we want to add a new column, we can start by making a new vector:
R
age <- c(2, 3, 5)
cats
OUTPUT
coat weight likes_string
1 calico 2.1 1
2 black 5.0 0
3 tabby 3.2 1We can then add this as a column via:
R
cbind(cats, age)
OUTPUT
coat weight likes_string age
1 calico 2.1 1 2
2 black 5.0 0 3
3 tabby 3.2 1 5Note that if we tried to add a vector of ages with a different number of entries than the number of rows in the data frame, it would fail:
R
age <- c(2, 3, 5, 12)
cbind(cats, age)
ERROR
Error in data.frame(..., check.names = FALSE): arguments imply differing number of rows: 3, 4R
age <- c(2, 3)
cbind(cats, age)
ERROR
Error in data.frame(..., check.names = FALSE): arguments imply differing number of rows: 3, 2Why didn’t this work? Of course, R wants to see one element in our new column for every row in the table:
R
nrow(cats)
OUTPUT
[1] 3R
length(age)
OUTPUT
[1] 2So for it to work we need to have nrow(cats) =
length(age). Let’s overwrite the content of cats with our
new data frame.
R
age <- c(2, 3, 5)
cats <- cbind(cats, age)
Now how about adding rows? We already know that the rows of a data frame are lists:
R
newRow <- list("tortoiseshell", 3.3, TRUE, 9)
cats <- rbind(cats, newRow)
Let’s confirm that our new row was added correctly.
R
cats
OUTPUT
coat weight likes_string age
1 calico 2.1 1 2
2 black 5.0 0 3
3 tabby 3.2 1 5
4 tortoiseshell 3.3 1 9Removing rows
We now know how to add rows and columns to our data frame in R. Now let’s learn to remove rows.
R
cats
OUTPUT
coat weight likes_string age
1 calico 2.1 1 2
2 black 5.0 0 3
3 tabby 3.2 1 5
4 tortoiseshell 3.3 1 9We can ask for a data frame minus the last row:
R
cats[-4, ]
OUTPUT
coat weight likes_string age
1 calico 2.1 1 2
2 black 5.0 0 3
3 tabby 3.2 1 5Notice the comma with nothing after it to indicate that we want to drop the entire fourth row.
Note: we could also remove several rows at once by putting the row
numbers inside of a vector, for example:
cats[c(-3,-4), ]
Removing columns
We can also remove columns in our data frame. What if we want to remove the column “age”. We can remove it in two ways, by variable number or by index.
R
cats[,-4]
OUTPUT
coat weight likes_string
1 calico 2.1 1
2 black 5.0 0
3 tabby 3.2 1
4 tortoiseshell 3.3 1Notice the comma with nothing before it, indicating we want to keep all of the rows.
Alternatively, we can drop the column by using the index name and the
%in% operator. The %in% operator goes through
each element of its left argument, in this case the names of
cats, and asks, “Does this element occur in the second
argument?”
R
drop <- names(cats) %in% c("age")
cats[,!drop]
OUTPUT
coat weight likes_string
1 calico 2.1 1
2 black 5.0 0
3 tabby 3.2 1
4 tortoiseshell 3.3 1We will cover subsetting with logical operators like
%in% in more detail in the next episode. See the section Subsetting through other logical
operations
Appending to a data frame
The key to remember when adding data to a data frame is that
columns are vectors and rows are lists. We can also glue two
data frames together with rbind:
R
cats <- rbind(cats, cats)
cats
OUTPUT
coat weight likes_string age
1 calico 2.1 1 2
2 black 5.0 0 3
3 tabby 3.2 1 5
4 tortoiseshell 3.3 1 9
5 calico 2.1 1 2
6 black 5.0 0 3
7 tabby 3.2 1 5
8 tortoiseshell 3.3 1 9Challenge 1
You can create a new data frame right from within R with the following syntax:
R
df <- data.frame(id = c("a", "b", "c"),
x = 1:3,
y = c(TRUE, TRUE, FALSE))
Make a data frame that holds the following information for yourself:
- first name
- last name
- lucky number
Then use rbind to add an entry for the people sitting
beside you. Finally, use cbind to add a column with each
person’s answer to the question, “Is it time for coffee break?”
R
df <- data.frame(first = c("Grace"),
last = c("Hopper"),
lucky_number = c(0))
df <- rbind(df, list("Marie", "Curie", 238) )
df <- cbind(df, coffeetime = c(TRUE,TRUE))
Realistic example
So far, you have seen the basics of manipulating data frames with our
cat data; now let’s use those skills to digest a more realistic dataset.
Let’s read in the gapminder dataset that we downloaded
previously:
R
gapminder <- read.csv("data/gapminder_data.csv")
Miscellaneous Tips
Another type of file you might encounter are tab-separated value files (.tsv). To specify a tab as a separator, use
"\\t"orread.delim().Files can also be downloaded directly from the Internet into a local folder of your choice onto your computer using the
download.filefunction. Theread.csvfunction can then be executed to read the downloaded file from the download location, for example,
R
download.file("https://raw.githubusercontent.com/swcarpentry/r-novice-gapminder/main/episodes/data/gapminder_data.csv", destfile = "data/gapminder_data.csv")
gapminder <- read.csv("data/gapminder_data.csv")
- Alternatively, you can also read in files directly into R from the
Internet by replacing the file paths with a web address in
read.csv. One should note that in doing this no local copy of the csv file is first saved onto your computer. For example,
R
gapminder <- read.csv("https://raw.githubusercontent.com/swcarpentry/r-novice-gapminder/main/episodes/data/gapminder_data.csv")
You can read directly from excel spreadsheets without converting them to plain text first by using the readxl package.
The argument “stringsAsFactors” can be useful to tell R how to read strings either as factors or as character strings. In R versions after 4.0, all strings are read-in as characters by default, but in earlier versions of R, strings are read-in as factors by default. For more information, see the call-out in the previous episode.
Let’s investigate gapminder a bit; the first thing we should always
do is check out what the data looks like with str:
R
str(gapminder)
OUTPUT
'data.frame': 1704 obs. of 6 variables:
$ country : chr "Afghanistan" "Afghanistan" "Afghanistan" "Afghanistan" ...
$ year : int 1952 1957 1962 1967 1972 1977 1982 1987 1992 1997 ...
$ pop : num 8425333 9240934 10267083 11537966 13079460 ...
$ continent: chr "Asia" "Asia" "Asia" "Asia" ...
$ lifeExp : num 28.8 30.3 32 34 36.1 ...
$ gdpPercap: num 779 821 853 836 740 ...An additional method for examining the structure of gapminder is to
use the summary function. This function can be used on
various objects in R. For data frames, summary yields a
numeric, tabular, or descriptive summary of each column. Numeric or
integer columns are described by the descriptive statistics (quartiles
and mean), and character columns by its length, class, and mode.
R
summary(gapminder)
OUTPUT
country year pop continent
Length:1704 Min. :1952 Min. :6.001e+04 Length:1704
Class :character 1st Qu.:1966 1st Qu.:2.794e+06 Class :character
Mode :character Median :1980 Median :7.024e+06 Mode :character
Mean :1980 Mean :2.960e+07
3rd Qu.:1993 3rd Qu.:1.959e+07
Max. :2007 Max. :1.319e+09
lifeExp gdpPercap
Min. :23.60 Min. : 241.2
1st Qu.:48.20 1st Qu.: 1202.1
Median :60.71 Median : 3531.8
Mean :59.47 Mean : 7215.3
3rd Qu.:70.85 3rd Qu.: 9325.5
Max. :82.60 Max. :113523.1 Along with the str and summary functions,
we can examine individual columns of the data frame with our
typeof function:
R
typeof(gapminder$year)
OUTPUT
[1] "integer"R
typeof(gapminder$country)
OUTPUT
[1] "character"R
str(gapminder$country)
OUTPUT
chr [1:1704] "Afghanistan" "Afghanistan" "Afghanistan" "Afghanistan" ...We can also interrogate the data frame for information about its
dimensions; remembering that str(gapminder) said there were
1704 observations of 6 variables in gapminder, what do you think the
following will produce, and why?
R
length(gapminder)
OUTPUT
[1] 6A fair guess would have been to say that the length of a data frame would be the number of rows it has (1704), but this is not the case; remember, a data frame is a list of vectors and factors:
R
typeof(gapminder)
OUTPUT
[1] "list"When length gave us 6, it’s because gapminder is built
out of a list of 6 columns. To get the number of rows and columns in our
dataset, try:
R
nrow(gapminder)
OUTPUT
[1] 1704R
ncol(gapminder)
OUTPUT
[1] 6Or, both at once:
R
dim(gapminder)
OUTPUT
[1] 1704 6We’ll also likely want to know what the titles of all the columns are, so we can ask for them later:
R
colnames(gapminder)
OUTPUT
[1] "country" "year" "pop" "continent" "lifeExp" "gdpPercap"At this stage, it’s important to ask ourselves if the structure R is reporting matches our intuition or expectations; do the basic data types reported for each column make sense? If not, we need to sort any problems out now before they turn into bad surprises down the road, using what we’ve learned about how R interprets data, and the importance of strict consistency in how we record our data.
Once we’re happy that the data types and structures seem reasonable, it’s time to start digging into our data proper. Check out the first few lines:
R
head(gapminder)
OUTPUT
country year pop continent lifeExp gdpPercap
1 Afghanistan 1952 8425333 Asia 28.801 779.4453
2 Afghanistan 1957 9240934 Asia 30.332 820.8530
3 Afghanistan 1962 10267083 Asia 31.997 853.1007
4 Afghanistan 1967 11537966 Asia 34.020 836.1971
5 Afghanistan 1972 13079460 Asia 36.088 739.9811
6 Afghanistan 1977 14880372 Asia 38.438 786.1134Challenge 2
It’s good practice to also check the last few lines of your data and some in the middle. How would you do this?
Searching for ones specifically in the middle isn’t too hard, but we could ask for a few lines at random. How would you code this?
To check the last few lines it’s relatively simple as R already has a function for this:
R
tail(gapminder)
tail(gapminder, n = 15)
What about a few arbitrary rows just in case something is odd in the middle?
Tip: There are several ways to achieve this.
The solution here presents one form of using nested functions, i.e. a function passed as an argument to another function. This might sound like a new concept, but you are already using it! Remember my_dataframe[rows, cols] will print to screen your data frame with the number of rows and columns you asked for (although you might have asked for a range or named columns for example). How would you get the last row if you don’t know how many rows your data frame has? R has a function for this. What about getting a (pseudorandom) sample? R also has a function for this.
R
gapminder[sample(nrow(gapminder), 5), ]
To make sure our analysis is reproducible, we should put the code into a script file so we can come back to it later.
Challenge 3
Go to file -> new file -> R script, and write an R script to
load in the gapminder dataset. Put it in the scripts/
directory and add it to version control.
Run the script using the source function, using the file
path as its argument (or by pressing the “source” button in
RStudio).
The source function can be used to use a script within a
script. Assume you would like to load the same type of file over and
over again and therefore you need to specify the arguments to fit the
needs of your file. Instead of writing the necessary argument again and
again you could just write it once and save it as a script. Then, you
can use source("Your_Script_containing_the_load_function")
in a new script to use the function of that script without writing
everything again. Check out ?source to find out more.
R
download.file("https://raw.githubusercontent.com/swcarpentry/r-novice-gapminder/main/episodes/data/gapminder_data.csv", destfile = "data/gapminder_data.csv")
gapminder <- read.csv(file = "data/gapminder_data.csv")
To run the script and load the data into the gapminder
variable:
R
source(file = "scripts/load-gapminder.R")
Challenge 4
Read the output of str(gapminder) again; this time, use
what you’ve learned about lists and vectors, as well as the output of
functions like colnames and dim to explain
what everything that str prints out for gapminder means. If
there are any parts you can’t interpret, discuss with your
neighbors!
The object gapminder is a data frame with columns
-
countryandcontinentare character strings. -
yearis an integer vector. -
pop,lifeExp, andgdpPercapare numeric vectors.
Key Points
- Use
cbind()to add a new column to a data frame. - Use
rbind()to add a new row to a data frame. - Remove rows from a data frame.
- Use
str(),summary(),nrow(),ncol(),dim(),colnames(),head(), andtypeof()to understand the structure of a data frame. - Read in a csv file using
read.csv(). - Understand what
length()of a data frame represents.
Content from Navigating Files and Directories
Last updated on 2024-12-04 | Edit this page
Estimated time: 40 minutes
Overview
Questions
- How can I move around on my computer?
- How can I see what files and directories I have?
- How can I specify the location of a file or directory on my computer?
Objectives
- Explain the similarities and differences between a file and a directory.
- Translate an absolute path into a relative path and vice versa.
- Construct absolute and relative paths that identify specific files and directories.
- Use options and arguments to change the behaviour of a shell command.
- Demonstrate the use of tab completion and explain its advantages.
Introducing and navigating the filesystem in the shell (covered in Navigating Files and Directories section) can be confusing. You may have both terminal and GUI file explorer open side by side so learners can see the content and file structure while they’re using terminal to navigate the system.
The part of the operating system responsible for managing files and directories is called the file system. It organizes our data into files, which hold information, and directories (also called ‘folders’), which hold files or other directories.
Several commands are frequently used to create, inspect, rename, and delete files and directories. To start exploring them, we’ll go to our open shell window.
First, let’s find out where we are by running a command called
pwd (which stands for ‘print working directory’).
Directories are like places — at any time while we are using
the shell, we are in exactly one place called our current
working directory. Commands mostly read and write files in the
current working directory, i.e. ‘here’, so knowing where you are before
running a command is important. pwd shows you where you
are:
OUTPUT
/Users/nelleHere, the computer’s response is /Users/nelle, which is
Nelle’s home directory:
Home Directory Variation
The home directory path will look different on different operating
systems. On Linux, it may look like /home/nelle, and on
Windows, it will be similar to
C:\Documents and Settings\nelle or
C:\Users\nelle. (Note that it may look slightly different
for different versions of Windows.) In future examples, we’ve used Mac
output as the default - Linux and Windows output may differ slightly but
should be generally similar.
We will also assume that your pwd command returns your
user’s home directory. If pwd returns something different,
you may need to navigate there using cd or some commands in
this lesson will not work as written. See Exploring Other Directories for
more details on the cd command.
To understand what a ‘home directory’ is, let’s have a look at how the file system as a whole is organized. For the sake of this example, we’ll be illustrating the filesystem on our scientist Nelle’s computer. After this illustration, you’ll be learning commands to explore your own filesystem, which will be constructed in a similar way, but not be exactly identical.
On Nelle’s computer, the filesystem looks like this:
The filesystem looks like an upside down tree. The topmost directory
is the root directory that holds everything else. We
refer to it using a slash character, /, on its own; this
character is the leading slash in /Users/nelle.
Inside that directory are several other directories: bin
(which is where some built-in programs are stored), data
(for miscellaneous data files), Users (where users’
personal directories are located), tmp (for temporary files
that don’t need to be stored long-term), and so on.
We know that our current working directory /Users/nelle
is stored inside /Users because /Users is the
first part of its name. Similarly, we know that /Users is
stored inside the root directory / because its name begins
with /.
Slashes
Notice that there are two meanings for the / character.
When it appears at the front of a file or directory name, it refers to
the root directory. When it appears inside a path, it’s just a
separator.
Underneath /Users, we find one directory for each user
with an account on Nelle’s machine, her colleagues imhotep and
larry.
The user imhotep’s files are stored in
/Users/imhotep, user larry’s in
/Users/larry, and Nelle’s in /Users/nelle.
Nelle is the user in our examples here; therefore, we get
/Users/nelle as our home directory. Typically, when you
open a new command prompt, you will be in your home directory to
start.
Now let’s learn the command that will let us see the contents of our
own filesystem. We can see what’s in our home directory by running
ls:
OUTPUT
Applications Documents Library Music Public
Desktop Downloads Movies Pictures(Again, your results may be slightly different depending on your operating system and how you have customized your filesystem.)
ls prints the names of the files and directories in the
current directory. We can make its output more comprehensible by using
the -F option which tells ls
to classify the output by adding a marker to file and directory names to
indicate what they are:
- a trailing
/indicates that this is a directory -
@indicates a link -
*indicates an executable
Depending on your shell’s default settings, the shell might also use colors to indicate whether each entry is a file or directory.
OUTPUT
Applications/ Documents/ Library/ Music/ Public/
Desktop/ Downloads/ Movies/ Pictures/Here, we can see that the home directory contains only sub-directories. Any names in the output that don’t have a classification symbol are files in the current working directory.
Clearing your terminal
If your screen gets too cluttered, you can clear your terminal using
the clear command. You can still access previous commands
using ↑ and ↓ to move line-by-line, or by
scrolling in your terminal.
Getting help
ls has lots of other options. There are
two common ways to find out how to use a command and what options it
accepts — depending on your environment, you might find that
only one of these ways works:
- We can pass a
--helpoption to any command (available on Linux and Git Bash), for example:
- We can read its manual with
man(available on Linux and macOS):
We’ll describe both ways next.
Help for built-in commands
Some commands are built in to the Bash shell, rather than existing as
separate programs on the filesystem. One example is the cd
(change directory) command. If you get a message like
No manual entry for cd, try help cd instead.
The help command is how you get usage information for Bash
built-ins.
The --help option
Most bash commands and programs that people have written to be run
from within bash, support a --help option that displays
more information on how to use the command or program.
OUTPUT
Usage: ls [OPTION]... [FILE]...
List information about the FILEs (the current directory by default).
Sort entries alphabetically if neither -cftuvSUX nor --sort is specified.
Mandatory arguments to long options are mandatory for short options, too.
-a, --all do not ignore entries starting with .
-A, --almost-all do not list implied . and ..
--author with -l, print the author of each file
-b, --escape print C-style escapes for nongraphic characters
--block-size=SIZE scale sizes by SIZE before printing them; e.g.,
'--block-size=M' prints sizes in units of
1,048,576 bytes; see SIZE format below
-B, --ignore-backups do not list implied entries ending with ~
-c with -lt: sort by, and show, ctime (time of last
modification of file status information);
with -l: show ctime and sort by name;
otherwise: sort by ctime, newest first
-C list entries by columns
--color[=WHEN] colorize the output; WHEN can be 'always' (default
if omitted), 'auto', or 'never'; more info below
-d, --directory list directories themselves, not their contents
-D, --dired generate output designed for Emacs' dired mode
-f do not sort, enable -aU, disable -ls --color
-F, --classify append indicator (one of */=>@|) to entries
... ... ...When to use short or long options
When options exist as both short and long options:
- Use the short option when typing commands directly into the shell to minimize keystrokes and get your task done faster.
- Use the long option in scripts to provide clarity. It will be read many times and typed once.
The man command
The other way to learn about ls is to type
This command will turn your terminal into a page with a description
of the ls command and its options.
To navigate through the man pages, you may use
↑ and ↓ to move line-by-line, or try b
and Spacebar to skip up and down by a full page. To search
for a character or word in the man pages, use /
followed by the character or word you are searching for. Sometimes a
search will result in multiple hits. If so, you can move between hits
using N (for moving forward) and
Shift+N (for moving backward).
To quit the man pages, press
q.
Manual pages on the web
Of course, there is a third way to access help for commands:
searching the internet via your web browser. When using internet search,
including the phrase unix man page in your search query
will help to find relevant results.
GNU provides links to its manuals including the core GNU utilities, which covers many commands introduced within this lesson.
Exploring More ls Options
You can also use two options at the same time. What does the command
ls do when used with the -l option? What about
if you use both the -l and the -h option?
Some of its output is about properties that we do not cover in this lesson (such as file permissions and ownership), but the rest should be useful nevertheless.
The -l option makes ls use a
long listing format, showing not only the
file/directory names but also additional information, such as the file
size and the time of its last modification. If you use both the
-h option and the -l option, this makes the
file size ‘human readable’, i.e. displaying something
like 5.3K instead of 5369.
Listing in Reverse Chronological Order
By default, ls lists the contents of a directory in
alphabetical order by name. The command ls -t lists items
by time of last change instead of alphabetically. The command
ls -r lists the contents of a directory in reverse order.
Which file is displayed last when you combine the -t and
-r options? Hint: You may need to use the -l
option to see the last changed dates.
The most recently changed file is listed last when using
-rt. This can be very useful for finding your most recent
edits or checking to see if a new output file was written.
Exploring Other Directories
Not only can we use ls on the current working directory,
but we can use it to list the contents of a different directory. Let’s
take a look at our Desktop directory by running
ls -F Desktop, i.e., the command ls with the
-F option and the argument
Desktop. The argument Desktop tells
ls that we want a listing of something other than our
current working directory:
OUTPUT
shell-lesson-data/Note that if a directory named Desktop does not exist in
your current working directory, this command will return an error.
Typically, a Desktop directory exists in your home
directory, which we assume is the current working directory of your bash
shell.
Your output should be a list of all the files and sub-directories in
your Desktop directory, including the shell-lesson-data
directory you downloaded at the setup for this
lesson. (On most systems, the contents of the Desktop
directory in the shell will show up as icons in a graphical user
interface behind all the open windows. See if this is the case for
you.)
Organizing things hierarchically helps us keep track of our work. While it’s possible to put hundreds of files in our home directory just as it’s possible to pile hundreds of printed papers on our desk, it’s much easier to find things when they’ve been organized into sensibly-named subdirectories.
Now that we know the shell-lesson-data directory is
located in our Desktop directory, we can do two things.
First, using the same strategy as before, we can look at its contents
by passing a directory name to ls:
OUTPUT
exercise-data/ north-pacific-gyre/Second, we can actually change our location to a different directory, so we are no longer located in our home directory.
The command to change locations is cd followed by a
directory name to change our working directory. cd stands
for ‘change directory’, which is a bit misleading. The command doesn’t
change the directory; it changes the shell’s current working directory.
In other words it changes the shell’s settings for what directory we are
in. The cd command is akin to double-clicking a folder in a
graphical interface to get into that folder.
Let’s say we want to move into the exercise-data
directory we saw above. We can use the following series of commands to
get there:
These commands will move us from our home directory into our Desktop
directory, then into the shell-lesson-data directory, then
into the exercise-data directory. You will notice that
cd doesn’t print anything. This is normal. Many shell
commands will not output anything to the screen when successfully
executed. But if we run pwd after it, we can see that we
are now in
/Users/nelle/Desktop/shell-lesson-data/exercise-data.
If we run ls -F without arguments now, it lists the
contents of
/Users/nelle/Desktop/shell-lesson-data/exercise-data,
because that’s where we now are:
OUTPUT
/Users/nelle/Desktop/shell-lesson-data/exercise-dataOUTPUT
alkanes/ animal-counts/ creatures/ numbers.txt writing/We now know how to go down the directory tree (i.e. how to go into a subdirectory), but how do we go up (i.e. how do we leave a directory and go into its parent directory)? We might try the following:
ERROR
-bash: cd: shell-lesson-data: No such file or directoryBut we get an error! Why is this?
With our methods so far, cd can only see sub-directories
inside your current directory. There are different ways to see
directories above your current location; we’ll start with the
simplest.
There is a shortcut in the shell to move up one directory level. It works as follows:
.. is a special directory name meaning “the directory
containing this one”, or more succinctly, the parent of
the current directory. Sure enough, if we run pwd after
running cd .., we’re back in
/Users/nelle/Desktop/shell-lesson-data:
OUTPUT
/Users/nelle/Desktop/shell-lesson-dataThe special directory .. doesn’t usually show up when we
run ls. If we want to display it, we can add the
-a option to ls -F:
OUTPUT
./ ../ exercise-data/ north-pacific-gyre/-a stands for ‘show all’ (including hidden files); it
forces ls to show us file and directory names that begin
with ., such as .. (which, if we’re in
/Users/nelle, refers to the /Users directory).
As you can see, it also displays another special directory that’s just
called ., which means ‘the current working directory’. It
may seem redundant to have a name for it, but we’ll see some uses for it
soon.
Note that in most command line tools, multiple options can be
combined with a single - and no spaces between the options;
ls -F -a is equivalent to ls -Fa.
These three commands are the basic commands for navigating the
filesystem on your computer: pwd, ls, and
cd. Let’s explore some variations on those commands. What
happens if you type cd on its own, without giving a
directory?
How can you check what happened? pwd gives us the
answer!
OUTPUT
/Users/nelleIt turns out that cd without an argument will return you
to your home directory, which is great if you’ve got lost in your own
filesystem.
Let’s try returning to the exercise-data directory from
before. Last time, we used three commands, but we can actually string
together the list of directories to move to exercise-data
in one step:
Check that we’ve moved to the right place by running pwd
and ls -F.
If we want to move up one level from the data directory, we could use
cd ... But there is another way to move to any directory,
regardless of your current location.
So far, when specifying directory names, or even a directory path (as
above), we have been using relative paths. When you use
a relative path with a command like ls or cd,
it tries to find that location from where we are, rather than from the
root of the file system.
However, it is possible to specify the absolute path
to a directory by including its entire path from the root directory,
which is indicated by a leading slash. The leading / tells
the computer to follow the path from the root of the file system, so it
always refers to exactly one directory, no matter where we are when we
run the command.
This allows us to move to our shell-lesson-data
directory from anywhere on the filesystem (including from inside
exercise-data). To find the absolute path we’re looking
for, we can use pwd and then extract the piece we need to
move to shell-lesson-data.
OUTPUT
/Users/nelle/Desktop/shell-lesson-data/exercise-dataRun pwd and ls -F to ensure that we’re in
the directory we expect.
Two More Shortcuts
The shell interprets a tilde (~) character at the start
of a path to mean “the current user’s home directory”. For example, if
Nelle’s home directory is /Users/nelle, then
~/data is equivalent to /Users/nelle/data.
This only works if it is the first character in the path;
here/there/~/elsewhere is not
here/there/Users/nelle/elsewhere.
Another shortcut is the - (dash) character.
cd will translate - into the previous
directory I was in, which is faster than having to remember, then
type, the full path. This is a very efficient way of moving
back and forth between two directories – i.e. if you execute
cd - twice, you end up back in the starting directory.
The difference between cd .. and cd - is
that the former brings you up, while the latter brings you
back.
Try it! First navigate to ~/Desktop/shell-lesson-data
(you should already be there).
Then cd into the exercise-data/creatures
directory
Now if you run
you’ll see you’re back in ~/Desktop/shell-lesson-data.
Run cd - again and you’re back in
~/Desktop/shell-lesson-data/exercise-data/creatures
Absolute vs Relative Paths
Starting from /Users/nelle/data, which of the following
commands could Nelle use to navigate to her home directory, which is
/Users/nelle?
cd .cd /cd /home/nellecd ../..cd ~cd homecd ~/data/..cdcd ..
- No:
.stands for the current directory. - No:
/stands for the root directory. - No: Nelle’s home directory is
/Users/nelle. - No: this command goes up two levels, i.e. ends in
/Users. - Yes:
~stands for the user’s home directory, in this case/Users/nelle. - No: this command would navigate into a directory
homein the current directory if it exists. - Yes: unnecessarily complicated, but correct.
- Yes: shortcut to go back to the user’s home directory.
- Yes: goes up one level.
Relative Path Resolution
Using the filesystem diagram below, if pwd displays
/Users/thing, what will ls -F ../backup
display?
../backup: No such file or directory2012-12-01 2013-01-08 2013-01-272012-12-01/ 2013-01-08/ 2013-01-27/original/ pnas_final/ pnas_sub/
- No: there is a directory
backupin/Users. - No: this is the content of
Users/thing/backup, but with.., we asked for one level further up. - No: see previous explanation.
- Yes:
../backup/refers to/Users/backup/.
ls Reading Comprehension
Using the filesystem diagram below, if pwd displays
/Users/backup, and -r tells ls to
display things in reverse order, what command(s) will result in the
following output:
OUTPUT
pnas_sub/ pnas_final/ original/ls pwdls -r -Fls -r -F /Users/backup
- No:
pwdis not the name of a directory. - Yes:
lswithout directory argument lists files and directories in the current directory. - Yes: uses the absolute path explicitly.
General Syntax of a Shell Command
We have now encountered commands, options, and arguments, but it is perhaps useful to formalise some terminology.
Consider the command below as a general example of a command, which we will dissect into its component parts:
ls is the command, with an
option -F and an argument
/. We’ve already encountered options which either start
with a single dash (-), known as short
options, or two dashes (--), known as long
options. [Options] change the behavior of a command and Arguments
tell the command what to operate on (e.g. files and directories).
Sometimes options and arguments are referred to as
parameters. A command can be called with more than one
option and more than one argument, but a command doesn’t always require
an argument or an option.
You might sometimes see options being referred to as switches or flags, especially for options that take no argument. In this lesson we will stick with using the term option.
Each part is separated by spaces. If you omit the space between
ls and -F the shell will look for a command
called ls-F, which doesn’t exist. Also, capitalization can
be important. For example, ls -s will display the size of
files and directories alongside the names, while ls -S will
sort the files and directories by size, as shown below:
OUTPUT
total 28
4 animal-counts 4 creatures 12 numbers.txt 4 alkanes 4 writingNote that the sizes returned by ls -s are in
blocks. As these are defined differently for different
operating systems, you may not obtain the same figures as in the
example.
OUTPUT
animal-counts creatures alkanes writing numbers.txtPutting all that together, our command ls -F / above
gives us a listing of files and directories in the root directory
/. An example of the output you might get from the above
command is given below:
OUTPUT
Applications/ System/
Library/ Users/
Network/ Volumes/Nelle’s Pipeline: Organizing Files
Knowing this much about files and directories, Nelle is ready to organize the files that the protein assay machine will create.
She creates a directory called north-pacific-gyre (to
remind herself where the data came from), which will contain the data
files from the assay machine and her data processing scripts.
Each of her physical samples is labelled according to her lab’s
convention with a unique ten-character ID, such as ‘NENE01729A’. This ID
is what she used in her collection log to record the location, time,
depth, and other characteristics of the sample, so she decides to use it
within the filename of each data file. Since the output of the assay
machine is plain text, she will call her files
NENE01729A.txt, NENE01812A.txt, and so on. All
1520 files will go into the same directory.
Now in her current directory shell-lesson-data, Nelle
can see what files she has using the command:
This command is a lot to type, but she can let the shell do most of the work through what is called tab completion. If she types:
and then presses Tab (the tab key on her keyboard), the shell automatically completes the directory name for her:
Pressing Tab again does nothing, since there are multiple possibilities; pressing Tab twice brings up a list of all the files.
If Nelle then presses G and then presses Tab again, the shell will append ‘goo’ since all files that start with ‘g’ share the first three characters ‘goo’.
To see all of those files, she can press Tab twice more.
This is called tab completion, and we will see it in many other tools as we go on.
Key Points
- The file system is responsible for managing information on the disk.
- Information is stored in files, which are stored in directories (folders).
- Directories can also store other directories, which then form a directory tree.
-
pwdprints the user’s current working directory. -
ls [path]prints a listing of a specific file or directory;lson its own lists the current working directory. -
cd [path]changes the current working directory. - Most commands take options that begin with a single
-. - Directory names in a path are separated with
/on Unix, but\on Windows. -
/on its own is the root directory of the whole file system. - An absolute path specifies a location from the root of the file system.
- A relative path specifies a location starting from the current location.
-
.on its own means ‘the current directory’;..means ‘the directory above the current one’.
Content from Automated Version Control
Last updated on 2024-12-04 | Edit this page
Estimated time: 5 minutes
Overview
Questions
- What is version control and why should I use it?
Objectives
- Understand the benefits of an automated version control system.
- Understand the basics of how automated version control systems work.
We’ll start by exploring how version control can be used to keep track of what one person did and when. Even if you aren’t collaborating with other people, automated version control is much better than this situation:
“notFinal.doc” by Jorge Cham, https://www.phdcomics.com
We’ve all been in this situation before: it seems unnecessary to have multiple nearly-identical versions of the same document. Some word processors let us deal with this a little better, such as Microsoft Word’s Track Changes, Google Docs’ version history, or LibreOffice’s Recording and Displaying Changes.
Version control systems start with a base version of the document and then record changes you make each step of the way. You can think of it as a recording of your progress: you can rewind to start at the base document and play back each change you made, eventually arriving at your more recent version.
Once you think of changes as separate from the document itself, you can then think about “playing back” different sets of changes on the base document, ultimately resulting in different versions of that document. For example, two users can make independent sets of changes on the same document.
Unless multiple users make changes to the same section of the document - a conflict - you can incorporate two sets of changes into the same base document.
A version control system is a tool that keeps track of these changes for us, effectively creating different versions of our files. It allows us to decide which changes will be made to the next version (each record of these changes is called a commit), and keeps useful metadata about them. The complete history of commits for a particular project and their metadata make up a repository. Repositories can be kept in sync across different computers, facilitating collaboration among different people.
The Long History of Version Control Systems
Automated version control systems are nothing new. Tools like RCS, CVS, or Subversion have been around since the early 1980s and are used by many large companies. However, many of these are now considered legacy systems (i.e., outdated) due to various limitations in their capabilities. More modern systems, such as Git and Mercurial, are distributed, meaning that they do not need a centralized server to host the repository. These modern systems also include powerful merging tools that make it possible for multiple authors to work on the same files concurrently.
Paper Writing
Imagine you drafted an excellent paragraph for a paper you are writing, but later ruin it. How would you retrieve the excellent version of your conclusion? Is it even possible?
Imagine you have 5 co-authors. How would you manage the changes and comments they make to your paper? If you use LibreOffice Writer or Microsoft Word, what happens if you accept changes made using the
Track Changesoption? Do you have a history of those changes?
Recovering the excellent version is only possible if you created a copy of the old version of the paper. The danger of losing good versions often leads to the problematic workflow illustrated in the PhD Comics cartoon at the top of this page.
Collaborative writing with traditional word processors is cumbersome. Either every collaborator has to work on a document sequentially (slowing down the process of writing), or you have to send out a version to all collaborators and manually merge their comments into your document. The ‘track changes’ or ‘record changes’ option can highlight changes for you and simplifies merging, but as soon as you accept changes you will lose their history. You will then no longer know who suggested that change, why it was suggested, or when it was merged into the rest of the document. Even online word processors like Google Docs or Microsoft Office Online do not fully resolve these problems.
Key Points
- Version control is like an unlimited ‘undo’.
- Version control also allows many people to work in parallel.
Content from Setting Up Git
Last updated on 2024-12-04 | Edit this page
Estimated time: 5 minutes
Overview
Questions
- How do I get set up to use Git?
Objectives
- Configure
gitthe first time it is used on a computer. - Understand the meaning of the
--globalconfiguration flag.
When we use Git on a new computer for the first time, we need to configure a few things. Below are a few examples of configurations we will set as we get started with Git:
- our name and email address,
- what our preferred text editor is,
- and that we want to use these settings globally (i.e. for every project).
On a command line, Git commands are written as
git verb options, where verb is what we
actually want to do and options is additional optional
information which may be needed for the verb. So here is
how you can configure git on your own machine:
BASH
$ git config --global user.name "<Your Full Name>"
$ git config --global user.email "<your email address>"This user name and email will be associated with your subsequent Git activity, which means that any changes pushed to GitHub, BitBucket, GitLab or another Git host server after this lesson will include this information.
For this lesson, we will be interacting with GitHub and so the email address used should be the same as the one used when setting up your GitHub account. If you are concerned about privacy, please review GitHub’s instructions for keeping your email address private.
Keeping your email private
If you elect to use a private email address with GitHub, then use
GitHub’s no-reply email address for the user.email value.
It looks like ID+username@users.noreply.github.com. You can
look up your own address in your GitHub email settings.
Line Endings
As with other keys, when you hit Enter or ↵ or on Macs, Return on your keyboard, your computer encodes this input as a character. Different operating systems use different character(s) to represent the end of a line. (You may also hear these referred to as newlines or line breaks.) Because Git uses these characters to compare files, it may cause unexpected issues when editing a file on different machines. Though it is beyond the scope of this lesson, you can read more about this issue in the Pro Git book.
You can change the way Git recognizes and encodes line endings using
the core.autocrlf command to git config. The
following settings are recommended:
On macOS and Linux:
And on Windows:
You can also set your favorite text editor, following this table:
| Editor | Configuration command |
|---|---|
| Atom | $ git config --global core.editor "atom --wait" |
| nano | $ git config --global core.editor "nano -w" |
| BBEdit (Mac, with command line tools) | $ git config --global core.editor "bbedit -w" |
| Sublime Text (Mac) | $ git config --global core.editor "/Applications/Sublime\ Text.app/Contents/SharedSupport/bin/subl -n -w" |
| Sublime Text (Win, 32-bit install) | $ git config --global core.editor "'c:/program files (x86)/sublime text 3/sublime_text.exe' -w" |
| Sublime Text (Win, 64-bit install) | $ git config --global core.editor "'c:/program files/sublime text 3/sublime_text.exe' -w" |
| Notepad (Win) | $ git config --global core.editor "c:/Windows/System32/notepad.exe" |
| Notepad++ (Win, 32-bit install) | $ git config --global core.editor "'c:/program files (x86)/Notepad++/notepad++.exe' -multiInst -notabbar -nosession -noPlugin" |
| Notepad++ (Win, 64-bit install) | $ git config --global core.editor "'c:/program files/Notepad++/notepad++.exe' -multiInst -notabbar -nosession -noPlugin" |
| Kate (Linux) | $ git config --global core.editor "kate" |
| Gedit (Linux) | $ git config --global core.editor "gedit --wait --new-window" |
| Scratch (Linux) | $ git config --global core.editor "scratch-text-editor" |
| Emacs | $ git config --global core.editor "emacs" |
| Vim | $ git config --global core.editor "vim" |
| VS Code | $ git config --global core.editor "code --wait" |
It is possible to reconfigure the text editor for Git whenever you want to change it.
Exiting Vim
Note that Vim is the default editor for many programs. If you haven’t
used Vim before and wish to exit a session without saving your changes,
press Esc then type :q! and hit Enter
or ↵ or on Macs, Return. If you want to save your
changes and quit, press Esc then type :wq and
hit Enter or ↵ or on Macs, Return.
Git (2.28+) allows configuration of the name of the branch created
when you initialize any new repository You should set this to
main so it matches the cloud service you will eventually
use.
Default Git branch naming
Source file changes are associated with a “branch.” For new learners
in this lesson, it’s enough to know that branches exist, and this lesson
uses one branch.
By default, Git will create a branch called master when you
create a new repository with git init (as explained in the
next Episode). This term evokes the racist practice of human slavery and
the software development
community has moved to adopt more inclusive language.
In 2020, most Git code hosting services transitioned to using
main as the default branch. As an example, any new
repository that is opened in GitHub and GitLab default to
main. However, Git has not yet made the same change. As a
result, local repositories must be manually configured have the same
main branch name as most cloud services.
For versions of Git prior to 2.28, the change can be made on an
individual repository level. The command for this is in the next
episode. Note that if this value is unset in your local Git
configuration, the init.defaultBranch value defaults to
master.
The five commands we just ran above only need to be run once: the
flag --global tells Git to use the settings for every
project, in your user account, on this computer.
Let’s review those settings and test our core.editor
right away:
Let’s close the file without making any additional changes. Remember, since typos in the config file will cause issues, it’s safer to view the configuration with:
And if necessary, change your configuration using the same commands to choose another editor or update your email address. This can be done as many times as you want.
Proxy
In some networks you need to use a proxy. If this is the case, you may also need to tell Git about the proxy:
To disable the proxy, use
Git Help and Manual
Always remember that if you forget the subcommands or options of a
git command, you can access the relevant list of options
typing git <command> -h or access the corresponding
Git manual by typing git <command> --help, e.g.:
While viewing the manual, remember the : is a prompt
waiting for commands and you can press Q to exit the
manual.
More generally, you can get the list of available git
commands and further resources of the Git manual typing:
Key Points
- Use
git configwith the--globaloption to configure a user name, email address, editor, and other preferences once per machine.
Content from Creating a Repository
Last updated on 2024-12-04 | Edit this page
Estimated time: 10 minutes
Overview
Questions
- Where does Git store information?
Objectives
- Create a local Git repository.
- Describe the purpose of the
.gitdirectory.
Once Git is configured, we can start using it.
To demonstrate the use of git, we will build a data
dictionary for the data we obtained from UKHSA.
First, let’s create a new directory in the Desktop
folder for our work and then change the current working directory to the
newly created one:
Then we tell Git to make data-dictionary a repository – a place where Git can
store versions of our files:
It is important to note that git init will create a
repository that can include subdirectories and their files – there is no
need to create separate repositories nested within the
data-dictionary repository, whether subdirectories are
present from the beginning or added later. Also, note that the creation
of the data-dictionary directory and its initialization as
a repository are completely separate processes.
If we use ls to show the directory’s contents, it
appears that nothing has changed:
But if we add the -a flag to show everything, we can see
that Git has created a hidden directory within
data-dictionary called .git:
OUTPUT
. .. .gitGit uses this special subdirectory to store all the information about
the project, including the tracked files and sub-directories located
within the project’s directory. If we ever delete the .git
subdirectory, we will lose the project’s history.
Next, we will change the default branch to be called
main. This might be the default branch depending on your
settings and version of git. See the setup episode for
more information on this change.
OUTPUT
Switched to a new branch 'main'We can now start using one of the most important git commands, which
is particularly helpful to beginners. git status tells us
the status of our project, and better, a list of changes in the project
and options on what to do with those changes. We can use it as often as
we want, whenever we want to understand what is going on.
OUTPUT
On branch main
No commits yet
nothing to commit (create/copy files and use "git add" to track)If you are using a different version of git, the exact
wording of the output might be slightly different.
Places to Create Git Repositories
Along with tracking information about the data dictionary (the
project we have already created), we would also like to track
information about related datasets. Despite any concerns, we create a
related-data project inside the
data-dictionary project with the following sequence of
commands:
BASH
$ cd ~/Desktop # return to Desktop directory
$ cd data-dictionary # go into data-dictionary directory, which is already a Git repository
$ ls -a # ensure the .git subdirectory is still present in the data-dictionary directory
$ mkdir related-data # make a subdirectory data-dictionary/related-data
$ cd related-data # go into related-data subdirectory
$ git init # make the related-data subdirectory a Git repository
$ ls -a # ensure the .git subdirectory is present indicating we have created a new Git repositoryIs the git init command, run inside the
related-data subdirectory, required for tracking files
stored in the related-data subdirectory?
No. We do not need to make the related-data subdirectory
a Git repository because the data-dictionary repository can
track any files, sub-directories, and subdirectory files under the
data-dictionary directory. Thus, in order to track all
information about related data, we only needed to add the
related-data subdirectory to the
data-dictionary directory.
Additionally, Git repositories can interfere with each other if they
are “nested”: the outer repository will try to version-control the inner
repository. Therefore, it’s best to create each new Git repository in a
separate directory. To be sure that there is no conflicting repository
in the directory, check the output of git status. If it
looks like the following, you are good to go to create a new repository
as shown above:
OUTPUT
fatal: Not a git repository (or any of the parent directories): .gitCorrecting git init Mistakes
Now that we know that a nested repository is redundant and may cause
confusion down the road, we would like to go back to a single git
repository. How can we undo our last git init in the
related-data subdirectory?
Background
Removing files from a Git repository needs to be done with caution. But we have not learned yet how to tell Git to track a particular file; we will learn this in the next episode. Files that are not tracked by Git can easily be removed like any other “ordinary” files with
Similarly a directory can be removed using
rm -r dirname. If the files or folder being removed in this
fashion are tracked by Git, then their removal becomes another change
that we will need to track, as we will see in the next episode.
Solution
Git keeps all of its files in the .git directory. To
recover from this little mistake, we can remove the .git
folder in the related-data subdirectory by running the
following command from inside the data-dictionary
directory:
But be careful! Running this command in the wrong directory will
remove the entire Git history of a project you might want to keep. In
general, deleting files and directories using rm from the
command line cannot be reversed. Therefore, always check your current
directory using the command pwd.
Key Points
-
git initinitializes a repository. - Git stores all of its repository data in the
.gitdirectory.
Content from Tracking Changes
Last updated on 2024-12-04 | Edit this page
Estimated time: 20 minutes
Overview
Questions
- How do I record changes in Git?
- How do I check the status of my version control repository?
- How do I record notes about what changes I made and why?
Objectives
- Go through the modify-add-commit cycle for one or more files.
- Explain where information is stored at each stage of that cycle.
- Distinguish between descriptive and non-descriptive commit messages.
First let’s make sure we’re still in the right directory. You should
be in the data-dictionary directory.
Let’s create a file called amr-data-dictionary.txt that
will contain the description of the variables in our AMR data. We’ll use
RStudio to edit the file; but you can use whatever editor you like. In
particular, this does not have to be the core.editor you
set globally earlier.
First create the file from the command line:
Now open the file in RStudio (or your preferred editor).
Type the text below into the amr-data-dictionary.txt
file:
OUTPUT
AMR data
100,000 rows of 12 variables
These data represent the sort of data that might be obtained from the Second Generation Surveillance System (SGSS)and save the file.
Let’s first verify that the file was properly created by running the
list command (ls):
OUTPUT
amr-data-dictionary.txtamr-data-dictionary.txt should contain 4 lines, which we
can see by running:
OUTPUT
AMR data
100,000 rows of 12 variables
These data represent the sort of data that might be obtained from the Second Generation Surveillance System (SGSS)If we check the status of our project again, Git tells us that it’s noticed the new file:
OUTPUT
On branch main
No commits yet
Untracked files:
(use "git add <file>..." to include in what will be committed)
amr-data-dictionary.txt
nothing added to commit but untracked files present (use "git add" to track)The “untracked files” message means that there’s a file in the
directory that Git isn’t keeping track of. We can tell Git to track a
file using git add:
and then check that the right thing happened:
OUTPUT
On branch main
No commits yet
Changes to be committed:
(use "git rm --cached <file>..." to unstage)
new file: amr-data-dictionary.txt
Git now knows that it’s supposed to keep track of
amr-data-dictionary.txt, but it hasn’t recorded these
changes as a commit yet. To get it to do that, we need to run one more
command:
OUTPUT
[main (root-commit) f22b25e] Start notes on Mars as a base
1 file changed, 1 insertion(+)
create mode 100644 amr-data-dictionary.txtWhen we run git commit, Git takes everything we have
told it to save by using git add and stores a copy
permanently inside the special .git directory. This
permanent copy is called a commit
(or revision) and its short
identifier is f22b25e. Your commit may have another
identifier.
We use the -m flag (for “message”) to record a short,
descriptive, and specific comment that will help us remember later on
what we did and why. If we just run git commit without the
-m option, Git will launch nano (or whatever
other editor we configured as core.editor) so that we can
write a longer message.
Good commit
messages start with a brief (<50 characters) statement about the
changes made in the commit. Generally, the message should complete the
sentence “If applied, this commit will”
If we run git status now:
OUTPUT
On branch main
nothing to commit, working tree cleanit tells us everything is up to date. If we want to know what we’ve
done recently, we can ask Git to show us the project’s history using
git log:
OUTPUT
commit f22b25e3233b4645dabd0d81e651fe074bd8e73b
Author: <John Doe> <john.doe@unkown.com>
Date: Thu Aug 22 09:51:46 2013 -0400
Start data dictionary for AMR datagit log lists all commits made to a repository in
reverse chronological order. The listing for each commit includes the
commit’s full identifier (which starts with the same characters as the
short identifier printed by the git commit command
earlier), the commit’s author, when it was created, and the log message
Git was given when the commit was created.
Where Are My Changes?
If we run ls at this point, we will still see just one
file called amr-data-dictionary.txt. That’s because Git
saves information about files’ history in the special .git
directory mentioned earlier so that our filesystem doesn’t become
cluttered (and so that we can’t accidentally edit or delete an old
version).
Now suppose we add more information to the file. (Again, we’ll edit
with RStudio and then cat the file to show its contents;
you may use a different editor, and don’t need to cat.)
OUTPUT
AMR data
100,000 rows of 12 variables
These data represent the sort of data that might be obtained from the Second Generation Surveillance System (SGSS)
* id Integer - A unique identifier for each personWhen we run git status now, it tells us that a file it
already knows about has been modified:
OUTPUT
On branch main
Changes not staged for commit:
(use "git add <file>..." to update what will be committed)
(use "git checkout -- <file>..." to discard changes in working directory)
modified: amr-data-dictionary.txt
no changes added to commit (use "git add" and/or "git commit -a")The last line is the key phrase: “no changes added to commit”. We
have changed this file, but we haven’t told Git we will want to save
those changes (which we do with git add) nor have we saved
them (which we do with git commit). So let’s do that now.
It is good practice to always review our changes before saving them. We
do this using git diff. This shows us the differences
between the current state of the file and the most recently saved
version:
OUTPUT
diff --git a/amr-data-dictionary.txt b/amr-data-dictionary.txt
index df0654a..315bf3a 100644
--- a/amr-data-dictionary.txt
+++ b/amr-data-dictionary.txt
@@ -2,3 +2,5 @@ AMR data
100,000 rows of 12 variables
These data represent the sort of data that might be obtained from the Second Generation Surveillance System (SGSS)
+
+* id Integer - A unique identifier for each personThe output is cryptic because it is actually a series of commands for
tools like editors and patch telling them how to
reconstruct one file given the other. If we break it down into
pieces:
- The first line tells us that Git is producing output similar to the
Unix
diffcommand comparing the old and new versions of the file. - The second line tells exactly which versions of the file Git is
comparing;
df0654aand315bf3aare unique computer-generated labels for those versions. - The third and fourth lines once again show the name of the file being changed.
- The remaining lines are the most interesting, they show us the
actual differences and the lines on which they occur. In particular, the
+marker in the first column shows where we added a line.
After reviewing our change, it’s time to commit it:
OUTPUT
On branch main
Changes not staged for commit:
(use "git add <file>..." to update what will be committed)
(use "git checkout -- <file>..." to discard changes in working directory)
modified: amr-data-dictionary.txt
no changes added to commit (use "git add" and/or "git commit -a")Whoops: Git won’t commit because we didn’t use git add
first. Let’s fix that:
OUTPUT
[main 7464434] Add entry for the id column
1 file changed, 2 insertions(+)Git insists that we add files to the set we want to commit before actually committing anything. This allows us to commit our changes in stages and capture changes in logical portions rather than only large batches. For example, suppose we’re adding a few citations to relevant research to our thesis. We might want to commit those additions, and the corresponding bibliography entries, but not commit some of our work drafting the conclusion (which we haven’t finished yet).
To allow for this, Git has a special staging area where it keeps track of things that have been added to the current changeset but not yet committed.
Staging Area
If you think of Git as taking snapshots of changes over the life of a
project, git add specifies what will go in a
snapshot (putting things in the staging area), and
git commit then actually takes the snapshot, and
makes a permanent record of it (as a commit). If you don’t have anything
staged when you type git commit, Git will prompt you to use
git commit -a or git commit --all, which is
kind of like gathering everyone to take a group photo! However,
it’s almost always better to explicitly add things to the staging area,
because you might commit changes you forgot you made. (Going back to the
group photo simile, you might get an extra with incomplete makeup
walking on the stage for the picture because you used -a!)
Try to stage things manually, or you might find yourself searching for
“git undo commit” more than you would like!
Let’s watch as our changes to a file move from our editor to the staging area and into long-term storage. First, we’ll add a few more lines to the file and complete our dictionary:
OUTPUT
AMR data
100,000 rows of 12 variables
These data represent the sort of data that might be obtained from the Second Generation Surveillance System (SGSS)
* id Integer - A unique identifier for each person
* dob Character - a string giving the date of birth
* spec_date Character - a string giving the date a specimen was taken
* sex_male Binary - indicates whether the person from whom the specimen was taken was male or not. 1 (male) 0 (not male)
* region Character - a string indicating the England region of laboratory testing the specimen
* had_surgery_past_yr Binary - indicates whether person from whom sample was taken had undergone surgery in hospital in the past year before specimen taken. 1 (surgery within last year) 0 (No surgery within last year)
* ethnicity Character - indicates self-reported ethnicity group according to Office for National Statistics groupings
* imd Integer - indicates the Index of Multiple Deprivation for residence for person from whom specimen was taken. Range: 1 (least deprived) - 5 (most deprived)
* organism Character - indicates the species name for the organism detected
* coamox Binary - indicates specimen was resistant to Coamoxiclav
* gentam Binary - indicates specimen was resistant to Gentamicin
* ciprof Binary - indicates specimen was resistant to CiprofloxacinOUTPUT
diff --git a/amr-data-dictionary.txt b/amr-data-dictionary.txt
index f2c537e..c9a8214 100644
--- a/amr-data-dictionary.txt
+++ b/amr-data-dictionary.txt
@@ -4,3 +4,14 @@ AMR data
These data represent the sort of data that might be obtained from the Second Generation Surveillance System (SGSS)
* id Integer - A unique identifier for each person
+* dob Character - a string giving the date of birth
+* spec_date Character - a string giving the date a specimen was taken
+* sex_male Binary - indicates whether the person from whom the specimen was taken was male or not. 1 (male) 0 (not male)
+* region Character - a string indicating the England region of laboratory testing the specimen
+* had_surgery_past_yr Binary - indicates whether person from whom sample was taken had undergone surgery in hospital in the past year before specimen taken. 1 (surgery within last year) 0 (No surgery within last year)
+* ethnicity Character - indicates self-reported ethnicity group according to Office for National Statistics groupings
+* imd Integer - indicates the Index of Multiple Deprivation for residence for person from whom specimen was taken. Range: 1 (least deprived) - 5 (most deprived)
+* organism Character - indicates the species name for the organism detected
+* coamox Binary - indicates specimen was resistant to Coamoxiclav
+* gentam Binary - indicates specimen was resistant to Gentamicin
+* ciprof Binary - indicates specimen was resistant to CiprofloxacinSo far, so good: we’ve added the necessary lines to the end of the
file (shown with a + in the first column). Now let’s put
that change in the staging area and see what git diff
reports:
There is no output: as far as Git can tell, there’s no difference between what it’s been asked to save permanently and what’s currently in the directory. However, if we do this:
OUTPUT
diff --git a/amr-data-dictionary.txt b/amr-data-dictionary.txt
index f2c537e..c9a8214 100644
--- a/amr-data-dictionary.txt
+++ b/amr-data-dictionary.txt
@@ -4,3 +4,14 @@ AMR data
These data represent the sort of data that might be obtained from the Second Generation Surveillance System (SGSS)
* id Integer - A unique identifier for each person
+* dob Character - a string giving the date of birth
+* spec_date Character - a string giving the date a specimen was taken
+* sex_male Binary - indicates whether the person from whom the specimen was taken was male or not. 1 (male) 0 (not male)
+* region Character - a string indicating the England region of laboratory testing the specimen
+* had_surgery_past_yr Binary - indicates whether person from whom sample was taken had undergone surgery in hospital in the past year before specimen taken. 1 (surgery within last year) 0 (No surgery within last year)
+* ethnicity Character - indicates self-reported ethnicity group according to Office for National Statistics groupings
+* imd Integer - indicates the Index of Multiple Deprivation for residence for person from whom specimen was taken. Range: 1 (least deprived) - 5 (most deprived)
+* organism Character - indicates the species name for the organism detected
+* coamox Binary - indicates specimen was resistant to Coamoxiclav
+* gentam Binary - indicates specimen was resistant to Gentamicin
+* ciprof Binary - indicates specimen was resistant to Ciprofloxacinit shows us the difference between the last committed change and what’s in the staging area. Let’s save our changes:
OUTPUT
[main 1c642ba] Complete the data dictionary
1 file changed, 11 insertions(+)check our status:
OUTPUT
On branch main
nothing to commit, working tree cleanand look at the history of what we’ve done so far:
OUTPUT
commit 1c642ba5c32a722081ea9e3c80ef0634b4e071f3 (HEAD -> main)
Author: John Doe <john.doe@unkown.com>
Date: Wed Aug 14 15:01:56 2024 +0100
Complete the data dictionary
commit 746443401e4f3e41a4bb67844dfb03e0241a1721
Author: John Doe <john.doe@unkown.com>
Date: Wed Aug 14 14:57:35 2024 +0100
Add entry for the id column
commit 0f988204ddcf33c060ecb849d640b3bd7aec71cc
Author: John Doe <john.doe@unkown.com>
Date: Wed Aug 14 14:54:11 2024 +0100
Start data dictionaryWord-based diffing
Sometimes, e.g. in the case of the text documents a line-wise diff is
too coarse. That is where the --color-words option of
git diff comes in very useful as it highlights the changed
words using colors.
Paging the Log
When the output of git log is too long to fit in your
screen, git uses a program to split it into pages of the
size of your screen. When this “pager” is called, you will notice that
the last line in your screen is a :, instead of your usual
prompt.
- To get out of the pager, press Q.
- To move to the next page, press Spacebar.
- To search for
some_wordin all pages, press / and typesome_word. Navigate through matches pressing N.
Limit Log Size
To avoid having git log cover your entire terminal
screen, you can limit the number of commits that Git lists by using
-N, where N is the number of commits that you
want to view. For example, if you only want information from the last
commit you can use:
OUTPUT
commit 1c642ba5c32a722081ea9e3c80ef0634b4e071f3 (HEAD -> main)
Author: John Doe <john.doe@unkown.com>
Date: Wed Aug 14 15:01:56 2024 +0100
Complete the data dictionaryYou can also reduce the quantity of information using the
--oneline option:
OUTPUT
1c642ba (HEAD -> main) Complete the data dictionary
7464434 Add entry for the id column
0f98820 Start data dictionaryYou can also combine the --oneline option with others.
One useful combination adds --graph to display the commit
history as a text-based graph and to indicate which commits are
associated with the current HEAD, the current branch
main, or other
Git references:
OUTPUT
* 1c642ba (HEAD -> main) Complete the data dictionary
* 7464434 Add entry for the id column
* 0f98820 Start data dictionaryDirectories
Two important facts you should know about directories in Git.
- Git does not track directories on their own, only files within them. Try it for yourself:
Note, our newly created empty directory notes does not
appear in the list of untracked files even if we explicitly add it
(via git add) to our repository. This is the
reason why you will sometimes see .gitkeep files in
otherwise empty directories. Unlike .gitignore, these files
are not special and their sole purpose is to populate a directory so
that Git adds it to the repository. In fact, you can name such files
anything you like.
- If you create a directory in your Git repository and populate it with files, you can add all files in the directory at once by:
Try it for yourself:
BASH
$ touch notes/2024-08-14.txt spaceships/2024-08-13.txt
$ git status
$ git add notes
$ git statusBefore moving on, we will commit these changes.
To recap, when we want to add changes to our repository, we first
need to add the changed files to the staging area (git add)
and then commit the staged changes to the repository
(git commit):
Choosing a Commit Message
Which of the following commit messages would be most appropriate for
the last commit made to amr-data-dictionary.txt?
- “Changes”
- “Added lines 7-17 to amr-data-dictionary.txt”
- “Add description for each data variable”
Answer 1 is not descriptive enough, and the purpose of the commit is unclear; and answer 2 is redundant to using “git diff” to see what changed in this commit; but answer 3 is good: short, descriptive, and imperative.
Committing Changes to Git
Which command(s) below would save the changes of
myfile.txt to my local Git repository?
- Would only create a commit if files have already been staged.
- Would try to create a new repository.
- Is correct: first add the file to the staging area, then commit.
- Would try to commit a file “my recent changes” with the message myfile.txt.
Committing Multiple Files
The staging area can hold changes from any number of files that you want to commit as a single snapshot.
- Add some text to
amr-data-dictionary.txtto mention that more detailed information on each variable can be found in a separate file with the same name as the variable. - Create a new file
ciprof.txtwith a short description of what Ciproflaxacin is (feel free to make something up). - Add changes from both files to the staging area, and commit those changes.
The output below from cat amr-data-dictionary.txt
reflects only content added during this exercise. Your output may
vary.
First we make our changes to the amr-data-dictionary.txt
and ciprof.txt files:
OUTPUT
More information on each variable can be found in the corresponding file.OUTPUT
Ciprofloxacin is a fluoroquinolone antibiotic used to treat a number of bacterial infections.Now you can add both files to the staging area. We can do that in one line:
Or with multiple commands:
Now the files are ready to commit. You can check that using
git status. If you are ready to commit use:
```output
[main cc127c2]
Add more detailed information about ciprofloxacin
2 files changed, 2 insertions(+)
create mode 100644 ciprof.txt
bio Repository
- Create a new Git repository on your computer called
bio. - Write a three-line biography for yourself in a file called
me.txt, commit your changes - Modify one line, add a fourth line
- Display the differences between its updated state and its original state.
If needed, move out of the data-dictionary folder:
Create a new folder called bio and ‘move’ into it:
Initialise git:
Create your biography file me.txt using
nano or another text editor. Once in place, add and commit
it to the repository:
Modify the file as described (modify one line, add a fourth line). To
display the differences between its updated state and its original
state, use git diff:
Key Points
-
git statusshows the status of a repository. - Files can be stored in a project’s working directory (which users see), the staging area (where the next commit is being built up) and the local repository (where commits are permanently recorded).
-
git addputs files in the staging area. -
git commitsaves the staged content as a new commit in the local repository. - Write a commit message that accurately describes your changes.
Content from Exploring History
Last updated on 2024-12-04 | Edit this page
Estimated time: 25 minutes
Overview
Questions
- How can I identify old versions of files?
- How do I review my changes?
- How can I recover old versions of files?
Objectives
- Explain what the HEAD of a repository is and how to use it.
- Identify and use Git commit numbers.
- Compare various versions of tracked files.
- Restore old versions of files.
As we saw in the previous episode, we can refer to commits by their
identifiers. You can refer to the most recent commit of the
working directory by using the identifier HEAD.
We’ve been adding one line at a time to
amr-data-dictionary.txt, so it’s easy to track our progress
by looking, so let’s do that using our HEADs. Before we
start, let’s make a change to amr-data-dictionary.txt,
adding yet another line.
Showing only the last few lines:
OUTPUT
* sex_male Binary - indicates whether the person from whom the specimen was taken was male or not. 1 (male) 0 (not male)
* region Character - a string indicating the England region of laboratory testing the specimen
* had_surgery_past_yr Binary - indicates whether person from whom sample was taken had undergone surgery in hospital in the past year before specimen taken. 1 (surgery within last year) 0 (No surgery within last year)
* ethnicity Character - indicates self-reported ethnicity group according to Office for National Statistics groupings
* imd Integer - indicates the Index of Multiple Deprivation for residence for person from whom specimen was taken. Range: 1 (least deprived) - 5 (most deprived)
* organism Character - indicates the species name for the organism detected
* coamox Binary - indicates specimen was resistant to Coamoxiclav
* gentam Binary - indicates specimen was resistant to Gentamicin
* ciprof Binary - indicates specimen was resistant to Ciprofloxacin
* name Character - a string giving the name of the person from whom the specimen was takenNow, let’s see what we get.
OUTPUT
diff --git a/amr-data-dictionary.txt b/amr-data-dictionary.txt
index c9a8214..d7d742c 100644
--- a/amr-data-dictionary.txt
+++ b/amr-data-dictionary.txt
@@ -15,3 +15,4 @@ These data represent the sort of data that might be obtained from the Second Gen
* coamox Binary - indicates specimen was resistant to Coamoxiclav
* gentam Binary - indicates specimen was resistant to Gentamicin
* ciprof Binary - indicates specimen was resistant to Ciprofloxacin
+* name Character - a string giving the name of the person from whom the specimen was takenwhich is the same as what you would get if you leave out
HEAD (try it). The real goodness in all this is when you
can refer to previous commits. We do that by adding ~1
(where “~” is “tilde”, pronounced [til-duh])
to refer to the commit one before HEAD.
If we want to see the differences between older commits we can use
git diff again, but with the notation HEAD~1,
HEAD~2, and so on, to refer to them:
OUTPUT
diff --git a/amr-data-dictionary.txt b/amr-data-dictionary.txt
index 55895cc..d7d742c 100644
--- a/amr-data-dictionary.txt
+++ b/amr-data-dictionary.txt
@@ -2,3 +2,17 @@ AMR data
100,000 rows of 12 variables
These data represent the sort of data that might be obtained from the Second Generation Surveillance System (SGSS)
+
+* id Integer - A unique identifier for each person
+* dob Character - a string giving the date of birth
+* spec_date Character - a string giving the date a specimen was taken
+* sex_male Binary - indicates whether the person from whom the specimen was taken was male or not. 1 (male) 0 (not male)
+* region Character - a string indicating the England region of laboratory testing the specimen
+* had_surgery_past_yr Binary - indicates whether person from whom sample was taken had undergone surgery in hospital in the past year before specimen taken. 1 (surgery within last year) 0 (No surgery within last year)
+* ethnicity Character - indicates self-reported ethnicity group according to Office for National Statistics groupings
+* imd Integer - indicates the Index of Multiple Deprivation for residence for person from whom specimen was taken. Range: 1 (least deprived) - 5 (most deprived)
+* organism Character - indicates the species name for the organism detected
+* coamox Binary - indicates specimen was resistant to Coamoxiclav
+* gentam Binary - indicates specimen was resistant to Gentamicin
+* ciprof Binary - indicates specimen was resistant to Ciprofloxacin
+* name Character - a string giving the name of the person from whom the specimen was takenWe could also use git show which shows us what changes
we made at an older commit as well as the commit message, rather than
the differences between a commit and our working directory that
we see by using git diff.
OUTPUT
commit 0f988204ddcf33c060ecb849d640b3bd7aec71cc
Author: John Doe <john.doe@unknown.com>
Date: Wed Aug 14 14:54:11 2024 +0100
Start data dictionary
diff --git a/amr-data-dictionary.txt b/amr-data-dictionary.txt
new file mode 100644
index 0000000..55895cc
--- /dev/null
+++ b/amr-data-dictionary.txt
@@ -0,0 +1,4 @@
+AMR data
+100,000 rows of 12 variables
+
+These data represent the sort of data that might be obtained from the Second Generation Surveillance System (SGSS)In this way, we can build up a chain of commits. The most recent end
of the chain is referred to as HEAD; we can refer to
previous commits using the ~ notation, so
HEAD~1 means “the previous commit”, while
HEAD~123 goes back 123 commits from where we are now.
We can also refer to commits using those long strings of digits and
letters that both git log and git show
display. These are unique IDs for the changes, and “unique” really does
mean unique: every change to any set of files on any computer has a
unique 40-character identifier. Our first commit was given the ID
0f988204ddcf33c060ecb849d640b3bd7aec71cc, so let’s try
this:
OUTPUT
diff --git a/amr-data-dictionary.txt b/amr-data-dictionary.txt
index 55895cc..d7d742c 100644
--- a/amr-data-dictionary.txt
+++ b/amr-data-dictionary.txt
@@ -2,3 +2,17 @@ AMR data
100,000 rows of 12 variables
These data represent the sort of data that might be obtained from the Second Generation Surveillance System (SGSS)
+
+* id Integer - A unique identifier for each person
+* dob Character - a string giving the date of birth
+* spec_date Character - a string giving the date a specimen was taken
+* sex_male Binary - indicates whether the person from whom the specimen was taken was male or not. 1 (male) 0 (not male)
+* region Character - a string indicating the England region of laboratory testing the specimen
+* had_surgery_past_yr Binary - indicates whether person from whom sample was taken had undergone surgery in hospital in the past year before specimen taken. 1 (surgery within last year) 0 (No surgery within last year)
+* ethnicity Character - indicates self-reported ethnicity group according to Office for National Statistics groupings
+* imd Integer - indicates the Index of Multiple Deprivation for residence for person from whom specimen was taken. Range: 1 (least deprived) - 5 (most deprived)
+* organism Character - indicates the species name for the organism detected
+* coamox Binary - indicates specimen was resistant to Coamoxiclav
+* gentam Binary - indicates specimen was resistant to Gentamicin
+* ciprof Binary - indicates specimen was resistant to Ciprofloxacin
+* name Character - a string giving the name of the person from whom the specimen was takenThat’s the right answer, but typing out random 40-character strings is annoying, so Git lets us use just the first few characters (typically seven for normal size projects):
All right! So we can save changes to files and see what we’ve
changed. Now, how can we restore older versions of things? Let’s suppose
we change our mind about the last update to
amr-data-dictionary.txt (we realise the name
variable is not actually part of the data).
git status now tells us that the file has been changed,
but those changes haven’t been staged:
OUTPUT
On branch main
Changes not staged for commit:
(use "git add <file>..." to update what will be committed)
(use "git restore <file>..." to discard changes in working directory)
modified: amr-data-dictionary.txt
no changes added to commit (use "git add" and/or "git commit -a")We can put things back the way they were by using
git restore:
OUTPUT
* spec_date Character - a string giving the date a specimen was taken
* sex_male Binary - indicates whether the person from whom the specimen was taken was male or not. 1 (male) 0 (not male)
* region Character - a string indicating the England region of laboratory testing the specimen
* had_surgery_past_yr Binary - indicates whether person from whom sample was taken had undergone surgery in hospital in the past year before specimen taken. 1 (surgery within last year) 0 (No surgery within last year)
* ethnicity Character - indicates self-reported ethnicity group according to Office for National Statistics groupings
* imd Integer - indicates the Index of Multiple Deprivation for residence for person from whom specimen was taken. Range: 1 (least deprived) - 5 (most deprived)
* organism Character - indicates the species name for the organism detected
* coamox Binary - indicates specimen was resistant to Coamoxiclav
* gentam Binary - indicates specimen was resistant to Gentamicin
* ciprof Binary - indicates specimen was resistant to CiprofloxacinAs you might guess from its name, git restore restores
an old version of a file. By default, it recovers the version of the
file recorded in HEAD, which is the last saved commit. If
we want to go back even further, we can use a commit identifier instead,
using -s option:
OUTPUT
AMR data
100,000 rows of 12 variables
These data represent the sort of data that might be obtained from the Second Generation Surveillance System (SGSS)OUTPUT
On branch main
Changes not staged for commit:
(use "git add <file>..." to update what will be committed)
(use "git restore <file>..." to discard changes in working directory)
modified: amr-data-dictionary.txt
no changes added to commit (use "git add" and/or "git commit -a")
Notice that the changes are currently in the staging area. Again, we
can put things back the way they were by using
git restore:
OUTPUT
AMR data
100,000 rows of 12 variables
These data represent the sort of data that might be obtained from the Second Generation Surveillance System (SGSS)
* id Integer - A unique identifier for each person
* dob Character - a string giving the date of birth
* spec_date Character - a string giving the date a specimen was taken
* sex_male Binary - indicates whether the person from whom the specimen was taken was male or not. 1 (male) 0 (not male)
* region Character - a string indicating the England region of laboratory testing the specimen
* had_surgery_past_yr Binary - indicates whether person from whom sample was taken had undergone surgery in hospital in the past year before specimen taken. 1 (surgery within last year) 0 (No surgery within last year)
* ethnicity Character - indicates self-reported ethnicity group according to Office for National Statistics groupings
* imd Integer - indicates the Index of Multiple Deprivation for residence for person from whom specimen was taken. Range: 1 (least deprived) - 5 (most deprived)
* organism Character - indicates the species name for the organism detected
* coamox Binary - indicates specimen was resistant to Coamoxiclav
* gentam Binary - indicates specimen was resistant to Gentamicin
* ciprof Binary - indicates specimen was resistant to CiprofloxacinIt’s important to remember that we must use the commit number that
identifies the state of the repository before the change we’re
trying to undo. A common mistake is to use the number of the commit in
which we made the change we’re trying to discard. In the example below,
we want to retrieve the state from before the most recent commit
(HEAD~1), which is commit f22b25e. We use the
. to mean all files:
So, to put it all together, here’s how Git works in cartoon form:
The fact that files can be reverted one by one tends to change the way people organize their work. If everything is in one large document, it’s hard (but not impossible) to undo changes to the introduction without also undoing changes made later to the conclusion. If the introduction and conclusion are stored in separate files, on the other hand, moving backward and forward in time becomes much easier.
Recovering Older Versions of a File
Jennifer has made changes to the Python script that she has been working on for weeks, and the modifications she made this morning “broke” the script and it no longer runs. She has spent ~ 1hr trying to fix it, with no luck…
Luckily, she has been keeping track of her project’s versions using
Git! Which commands below will let her recover the last committed
version of her Python script called data_cruncher.py?
$ git restore$ git restore data_cruncher.py$ git restore -s HEAD~1 data_cruncher.py$ git restore -s <unique ID of last commit> data_cruncher.pyBoth 2 and 4
The answer is (5)-Both 2 and 4.
The restore command restores files from the repository,
overwriting the files in your working directory. Answers 2 and 4 both
restore the latest version in the repository of the
file data_cruncher.py. Answer 2 uses HEAD to
indicate the latest, whereas answer 4 uses the unique ID of the
last commit, which is what HEAD means.
Answer 3 gets the version of data_cruncher.py from the
commit before HEAD, which is NOT what we
wanted.
Answer 1 results in an error. You need to specify a file to restore.
If you want to restore all files you should use
git restore .
Reverting a Commit
Jennifer is collaborating with colleagues on her Python script. She
realizes her last commit to the project’s repository contained an error,
and wants to undo it. Jennifer wants to undo correctly so everyone in
the project’s repository gets the correct change. The command
git revert [erroneous commit ID] will create a new commit
that reverses the erroneous commit.
The command git revert is different from
git restore -s [commit ID] . because
git restore returns the files not yet committed within the
local repository to a previous state, whereas git revert
reverses changes committed to the local and project repositories.
Below are the right steps and explanations for Jennifer to use
git revert, what is the missing command?
________ # Look at the git history of the project to find the commit IDCopy the ID (the first few characters of the ID, e.g. 0b1d055).
git revert [commit ID]Type in the new commit message.
Save and close
The command git log lists project history with commit
IDs.
The command git show HEAD shows changes made at the
latest commit, and lists the commit ID; however, Jennifer should
double-check it is the correct commit, and no one else has committed
changes to the repository.
Understanding Workflow and History
What is the output of the last command in
BASH
$ cd planets
$ echo "Venus is beautiful and full of love" > venus.txt
$ git add venus.txt
$ echo "Venus is too hot to be suitable as a base" >> venus.txt
$ git commit -m "Comment on Venus as an unsuitable base"
$ git restore venus.txt
$ cat venus.txt #this will print the contents of venus.txt to the screenOUTPUT
Venus is too hot to be suitable as a baseOUTPUT
Venus is beautiful and full of loveOUTPUT
Venus is beautiful and full of love Venus is too hot to be suitable as a baseOUTPUT
Error because you have changed venus.txt without committing the changes
The answer is 2.
The command git add venus.txt places the current version
of venus.txt into the staging area. The changes to the file
from the second echo command are only applied to the
working copy, not the version in the staging area.
So, when
git commit -m "Comment on Venus as an unsuitable base" is
executed, the version of venus.txt committed to the
repository is the one from the staging area and has only one line.
At this time, the working copy still has the second line (and
git status will show that the file is modified). However,
git restore venus.txt replaces the working copy with the
most recently committed version of venus.txt.
So, cat venus.txt will output
OUTPUT
Venus is beautiful and full of love.Checking Understanding of
git diff
Consider this command:
git diff HEAD~9 amr-data-dictionary.txt. What do you
predict this command will do if you execute it? What happens when you do
execute it? Why?
Try another command,
git diff [ID] amr-data-dictionary.txt, where [ID] is
replaced with the unique identifier for your most recent commit. What do
you think will happen, and what does happen?
Getting Rid of Staged Changes
git restore can be used to restore a previous commit
when unstaged changes have been made, but will it also work for changes
that have been staged but not committed? Make a change to
amr-data-dictionary.txt, add that change using
git add, then use git restore to see if you
can remove your change.
After adding a change, git restore can not be used
directly. Let’s look at the output of git status:
OUTPUT
On branch main
Changes to be committed:
(use "git restore --staged <file>..." to unstage)
modified: amr-data-dictionary.txt
Note that if you don’t have the same output you may either have forgotten to change the file, or you have added it and committed it.
Using the command git restore amr-data-dictionary.txt
now does not give an error, but it does not restore the file either. Git
helpfully tells us that we need to use git restore --staged
first to unstage the file:
Now, git status gives us:
OUTPUT
On branch main
Changes not staged for commit:
(use "git add <file>..." to update what will be committed)
(use "git git restore <file>..." to discard changes in working directory)
modified: amr-data-dictionary.txt
no changes added to commit (use "git add" and/or "git commit -a")This means we can now use git restore to restore the
file to the previous commit:
OUTPUT
On branch main
nothing to commit, working tree cleanExplore and Summarize Histories
Exploring history is an important part of Git, and often it is a challenge to find the right commit ID, especially if the commit is from several months ago.
Imagine the data-dictionary project has more than 50
files. You would like to find a commit that modifies some specific text
in amr-data-dictionary.txt. When you type
git log, a very long list appeared. How can you narrow down
the search?
Recall that the git diff command allows us to explore
one specific file, e.g., git diff amr-data-dictionary.txt.
We can apply a similar idea here.
Unfortunately some of these commit messages are very ambiguous, e.g.,
update files. How can you search through these files?
Both git diff and git log are very useful
and they summarize a different part of the history for you. Is it
possible to combine both? Let’s try the following:
You should get a long list of output, and you should be able to see both commit messages and the difference between each commit.
Question: What does the following command do?
Key Points
-
git diffdisplays differences between commits. -
git restorerecovers old versions of files.
Content from Ignoring Things
Last updated on 2024-12-04 | Edit this page
Estimated time: 5 minutes
Overview
Questions
- How can I tell Git to ignore files I don’t want to track?
Objectives
- Configure Git to ignore specific files.
- Explain why ignoring files can be useful.
What if we have files that we do not want Git to track for us, like backup files created by our editor or intermediate files created during data analysis? Let’s create a few dummy files:
and see what Git says:
OUTPUT
On branch main
Untracked files:
(use "git add <file>..." to include in what will be committed)
a.csv
b.csv
c.csv
results/
nothing added to commit but untracked files present (use "git add" to track)Putting these files under version control would be a waste of disk space. What’s worse, having them all listed could distract us from changes that actually matter, so let’s tell Git to ignore them.
We do this by creating a file in the root directory of our project
called .gitignore:
OUTPUT
*.csv
results/These patterns tell Git to ignore any file whose name ends in
.csv and everything in the results directory.
(If any of these files were already being tracked, Git would continue to
track them.)
Once we have created this file, the output of git status
is much cleaner:
OUTPUT
On branch main
Untracked files:
(use "git add <file>..." to include in what will be committed)
.gitignore
nothing added to commit but untracked files present (use "git add" to track)The only thing Git notices now is the newly-created
.gitignore file. You might think we wouldn’t want to track
it, but everyone we’re sharing our repository with will probably want to
ignore the same things that we’re ignoring. Let’s add and commit
.gitignore:
OUTPUT
On branch main
nothing to commit, working tree cleanAs a bonus, using .gitignore helps us avoid accidentally
adding files to the repository that we don’t want to track:
OUTPUT
The following paths are ignored by one of your .gitignore files:
a.csv
Use -f if you really want to add them.If we really want to override our ignore settings, we can use
git add -f to force Git to add something. For example,
git add -f a.csv. We can also always see the status of
ignored files if we want:
OUTPUT
On branch main
Ignored files:
(use "git add -f <file>..." to include in what will be committed)
a.csv
b.csv
c.csv
results/
nothing to commit, working tree cleanIf you only want to ignore the contents of
results/plots, you can change your .gitignore
to ignore only the /plots/ subfolder by adding the
following line to your .gitignore:
OUTPUT
results/plots/This line will ensure only the contents of results/plots
is ignored, and not the contents of results/data.
As with most programming issues, there are a few alternative ways that one may ensure this ignore rule is followed. The “Ignoring Nested Files: Variation” exercise has a slightly different directory structure that presents an alternative solution. Further, the discussion page has more detail on ignore rules.
Including Specific Files
How would you ignore all .csv files in your root
directory except for final.csv? Hint: Find out what
! (the exclamation point operator) does
You would add the following two lines to your .gitignore:
OUTPUT
*.csv # ignore all data files
!final.csv # except final.csvThe exclamation point operator will include a previously excluded entry.
Note also that because you’ve previously committed .csv
files in this lesson they will not be ignored with this new rule. Only
future additions of .csv files added to the root directory
will be ignored.
Ignoring Nested Files: Variation
Given a directory structure that looks similar to the earlier Nested Files exercise, but with a slightly different directory structure:
How would you ignore all of the contents in the results folder, but
not results/data?
Hint: think a bit about how you created an exception with the
! operator before.
If you want to ignore the contents of results/ but not
those of results/data/, you can change your
.gitignore to ignore the contents of results folder, but
create an exception for the contents of the results/data
subfolder. Your .gitignore would look like this:
OUTPUT
results/* # ignore everything in results folder
!results/data/ # do not ignore results/data/ contentsIgnoring all data Files in a Directory
Assuming you have an empty .gitignore file, and given a directory structure that looks like:
BASH
results/data/position/gps/a.csv
results/data/position/gps/b.csv
results/data/position/gps/c.csv
results/data/position/gps/info.txt
results/plotsWhat’s the shortest .gitignore rule you could write to
ignore all .csv files in
result/data/position/gps? Do not ignore the
info.txt.
Appending results/data/position/gps/*.csv will match
every file in results/data/position/gps that ends with
.csv. The file
results/data/position/gps/info.txt will not be ignored.
Ignoring all data Files in the repository
Let us assume you have many .csv files in different
subdirectories of your repository. For example, you might have:
BASH
results/a.csv
data/experiment_1/b.csv
data/experiment_2/c.csv
data/experiment_2/variation_1/d.csvHow do you ignore all the .csv files, without explicitly
listing the names of the corresponding folders?
In the .gitignore file, write:
OUTPUT
**/*.csvThis will ignore all the .csv files, regardless of their
position in the directory tree. You can still include some specific
exception with the exclamation point operator.
The ! modifier will negate an entry from a previously
defined ignore pattern. Because the !*.csv entry negates
all of the previous .csv files in the
.gitignore, none of them will be ignored, and all
.csv files will be tracked.
Log Files
You wrote a script that creates many intermediate log-files of the
form log_01, log_02, log_03, etc.
You want to keep them but you do not want to track them through
git.
Write one
.gitignoreentry that excludes files of the formlog_01,log_02, etc.Test your “ignore pattern” by creating some dummy files of the form
log_01, etc.You find that the file
log_01is very important after all, add it to the tracked files without changing the.gitignoreagain.Discuss with your neighbor what other types of files could reside in your directory that you do not want to track and thus would exclude via
.gitignore.
- append either
log_*orlog*as a new entry in your .gitignore - track
log_01usinggit add -f log_01
Key Points
- The
.gitignorefile tells Git what files to ignore.
Content from Supplemental: Using Git from RStudio
Last updated on 2024-12-04 | Edit this page
Estimated time: 10 minutes
Overview
Questions
- How can I use Git with RStudio?
Objectives
- Understand how to use Git from RStudio.
Version control can be very useful when developing data analysis scripts. For that reason, the popular development environment RStudio for the R programming language has built-in integration with Git. While some advanced Git features still require the command-line, RStudio has a nice interface for many common Git operations.
RStudio allows us to create a project associated with a given directory to keep track of various related files. To be able to track the development of the project over time, to be able to revert to previous versions, and to collaborate with others, we version control the Rstudio project with Git. To get started using Git in RStudio, we create a new project:
This opens a dialog asking us how we want to create the project. We have some options here. Let’s say that we want to use RStudio with the planets repository that we already made. Since that repository lives in a directory on our computer, we choose the option “Existing Directory”:
Do You See a “Version Control” Option?
Although we’re not going to use it here, there should be a “version control” option on this menu. That is what you would click on if you wanted to create a project on your computer by cloning a repository from GitHub. If that option is not present, it probably means that RStudio doesn’t know where your Git executable is, and you won’t be able to progress further in this lesson until you tell RStudio where it is.
Find your Git Executable
First let’s make sure that Git is installed on your computer. Open your shell on Mac or Linux, or on Windows open the command prompt and then type:
-
which git(macOS, Linux) -
where git(Windows)
If there is no version of Git on your computer, please follow the Git
installation instructions in the setup of this lesson to install Git
now. Next open your shell or command prompt and type
which git (macOS, Linux), or where git
(Windows). Copy the path to the git executable.
On one Windows computer which had GitHub Desktop installed on it, the
path was:
C:/Users/UserName/AppData/Local/GitHubDesktop/app-1.1.1/resources/app/git/cmd/git.exe
NOTE: The path on your computer will be somewhat different.
Next, RStudio will ask which existing directory we want to use. Click “Browse…” and navigate to the correct directory, then click “Create Project”:
Ta-da! We have created a new project in RStudio within the existing planets repository. Notice the vertical “Git” menu in the menu bar. RStudio has recognized that the current directory is a Git repository, and gives us a number of tools to use Git:
To edit the existing files in the repository, we can click on them in the “Files” panel on the lower right. Now let’s add some additional information about Pluto:
Once we have saved our edited files, we can use RStudio to commit the changes by clicking on “Commit…” in the Git menu:
This will open a dialogue where we can select which files to commit
(by checking the appropriate boxes in the “Staged” column), and enter a
commit message (in the upper right panel). The icons in the “Status”
column indicate the current status of each file. Clicking on a file
shows information about changes in the lower panel (using output of
git diff). Once everything is the way we want it, we click
“Commit”:
The changes can be pushed by selecting “Push Branch” from the Git menu. There are also options to pull from the remote repository, and to view the commit history:
Are the Push/Pull Commands Grayed Out?
Grayed out Push/Pull commands generally mean that RStudio doesn’t
know the location of your remote repository (e.g. on GitHub). To fix
this, open a terminal to the repository and enter the command:
git push -u origin main. Then restart RStudio.
If we click on “History”, we can see a graphical version of what
git log would tell us:
RStudio creates a number of files that it uses to keep track of a
project. We often don’t want to track these, in which case we add them
to our .gitignore file:
Tip: versioning disposable output
Generally you do not want to version control disposable output (or
read-only data). You should modify the .gitignore file to
tell Git to ignore these files and directories.
Challenge
- Create a new directory within your project called
graphs. - Modify the
.gitignoreso that thegraphsdirectory is not version controlled.
This can be done in Rstudio:
R
dir.create("./graphs")
Then open up the .gitignore file from the right-hand
panel of Rstudio and add graphs/ to the list of files to
ignore.
There are many more features in the RStudio Git menu, but these should be enough to get you started!
Key Points
- Using RStudio’s Git integration allows you to version control a project over time.
Content from Subsetting Data
Last updated on 2024-12-04 | Edit this page
Estimated time: 50 minutes
Overview
Questions
- How can I work with subsets of data in R?
Objectives
- To be able to subset vectors, factors, matrices, lists, and data frames
- To be able to extract individual and multiple elements: by index, by name, using comparison operations
- To be able to skip and remove elements from various data structures.
R has many powerful subset operators. Mastering them will allow you to easily perform complex operations on any kind of dataset.
There are six different ways we can subset any kind of object, and three different subsetting operators for the different data structures.
Let’s start with the workhorse of R: a simple numeric vector.
R
x <- c(5.4, 6.2, 7.1, 4.8, 7.5)
names(x) <- c('a', 'b', 'c', 'd', 'e')
x
OUTPUT
a b c d e
5.4 6.2 7.1 4.8 7.5 Atomic vectors
In R, simple vectors containing character strings, numbers, or logical values are called atomic vectors because they can’t be further simplified.
So now that we’ve created a dummy vector to play with, how do we get at its contents?
Accessing elements using their indices
To extract elements of a vector we can give their corresponding index, starting from one:
R
x[1]
OUTPUT
a
5.4 R
x[4]
OUTPUT
d
4.8 It may look different, but the square brackets operator is a function. For vectors (and matrices), it means “get me the nth element”.
We can ask for multiple elements at once:
R
x[c(1, 3)]
OUTPUT
a c
5.4 7.1 Or slices of the vector:
R
x[1:4]
OUTPUT
a b c d
5.4 6.2 7.1 4.8 the : operator creates a sequence of numbers from the
left element to the right.
R
1:4
OUTPUT
[1] 1 2 3 4R
c(1, 2, 3, 4)
OUTPUT
[1] 1 2 3 4We can ask for the same element multiple times:
R
x[c(1,1,3)]
OUTPUT
a a c
5.4 5.4 7.1 If we ask for an index beyond the length of the vector, R will return a missing value:
R
x[6]
OUTPUT
<NA>
NA This is a vector of length one containing an NA, whose
name is also NA.
If we ask for the 0th element, we get an empty vector:
R
x[0]
OUTPUT
named numeric(0)Vector numbering in R starts at 1
In many programming languages (C and Python, for example), the first element of a vector has an index of 0. In R, the first element is 1.
Skipping and removing elements
If we use a negative number as the index of a vector, R will return every element except for the one specified:
R
x[-2]
OUTPUT
a c d e
5.4 7.1 4.8 7.5 We can skip multiple elements:
R
x[c(-1, -5)] # or x[-c(1,5)]
OUTPUT
b c d
6.2 7.1 4.8 Tip: Order of operations
A common trip up for novices occurs when trying to skip slices of a vector. It’s natural to try to negate a sequence like so:
R
x[-1:3]
This gives a somewhat cryptic error:
ERROR
Error in x[-1:3]: only 0's may be mixed with negative subscriptsBut remember the order of operations. : is really a
function. It takes its first argument as -1, and its second as 3, so
generates the sequence of numbers: c(-1, 0, 1, 2, 3).
The correct solution is to wrap that function call in brackets, so
that the - operator applies to the result:
R
x[-(1:3)]
OUTPUT
d e
4.8 7.5 To remove elements from a vector, we need to assign the result back into the variable:
R
x <- x[-4]
x
OUTPUT
a b c e
5.4 6.2 7.1 7.5 Challenge 1
Given the following code:
R
x <- c(5.4, 6.2, 7.1, 4.8, 7.5)
names(x) <- c('a', 'b', 'c', 'd', 'e')
print(x)
OUTPUT
a b c d e
5.4 6.2 7.1 4.8 7.5 Come up with at least 2 different commands that will produce the following output:
OUTPUT
b c d
6.2 7.1 4.8 After you find 2 different commands, compare notes with your neighbour. Did you have different strategies?
R
x[2:4]
OUTPUT
b c d
6.2 7.1 4.8 R
x[-c(1,5)]
OUTPUT
b c d
6.2 7.1 4.8 R
x[c(2,3,4)]
OUTPUT
b c d
6.2 7.1 4.8 Subsetting by name
We can extract elements by using their name, instead of extracting by index:
R
x <- c(a=5.4, b=6.2, c=7.1, d=4.8, e=7.5) # we can name a vector 'on the fly'
x[c("a", "c")]
OUTPUT
a c
5.4 7.1 This is usually a much more reliable way to subset objects: the position of various elements can often change when chaining together subsetting operations, but the names will always remain the same!
Subsetting through other logical operations
We can also use any logical vector to subset:
R
x[c(FALSE, FALSE, TRUE, FALSE, TRUE)]
OUTPUT
c e
7.1 7.5 Since comparison operators (e.g. >,
<, ==) evaluate to logical vectors, we can
also use them to succinctly subset vectors: the following statement
gives the same result as the previous one.
R
x[x > 7]
OUTPUT
c e
7.1 7.5 Breaking it down, this statement first evaluates x>7,
generating a logical vector
c(FALSE, FALSE, TRUE, FALSE, TRUE), and then selects the
elements of x corresponding to the TRUE
values.
We can use == to mimic the previous method of indexing
by name (remember you have to use == rather than
= for comparisons):
R
x[names(x) == "a"]
OUTPUT
a
5.4 Tip: Combining logical conditions
We often want to combine multiple logical criteria. For example, we might want to find all the countries that are located in Asia or Europe and have life expectancies within a certain range. Several operations for combining logical vectors exist in R:
-
&, the “logical AND” operator: returnsTRUEif both the left and right areTRUE. -
|, the “logical OR” operator: returnsTRUE, if either the left or right (or both) areTRUE.
You may sometimes see && and ||
instead of & and |. These two-character
operators only look at the first element of each vector and ignore the
remaining elements. In general you should not use the two-character
operators in data analysis; save them for programming, i.e. deciding
whether to execute a statement.
-
!, the “logical NOT” operator: convertsTRUEtoFALSEandFALSEtoTRUE. It can negate a single logical condition (eg!TRUEbecomesFALSE), or a whole vector of conditions(eg!c(TRUE, FALSE)becomesc(FALSE, TRUE)).
Additionally, you can compare the elements within a single vector
using the all function (which returns TRUE if
every element of the vector is TRUE) and the
any function (which returns TRUE if one or
more elements of the vector are TRUE).
Challenge 2
Given the following code:
R
x <- c(5.4, 6.2, 7.1, 4.8, 7.5)
names(x) <- c('a', 'b', 'c', 'd', 'e')
print(x)
OUTPUT
a b c d e
5.4 6.2 7.1 4.8 7.5 Write a subsetting command to return the values in x that are greater than 4 and less than 7.
R
x_subset <- x[x<7 & x>4]
print(x_subset)
OUTPUT
a b d
5.4 6.2 4.8 Tip: Non-unique names
You should be aware that it is possible for multiple elements in a vector to have the same name. (For a data frame, columns can have the same name — although R tries to avoid this — but row names must be unique.) Consider these examples:
R
x <- 1:3
x
OUTPUT
[1] 1 2 3R
names(x) <- c('a', 'a', 'a')
x
OUTPUT
a a a
1 2 3 R
x['a'] # only returns first value
OUTPUT
a
1 R
x[names(x) == 'a'] # returns all three values
OUTPUT
a a a
1 2 3 Tip: Getting help for operators
Remember you can search for help on operators by wrapping them in
quotes: help("%in%") or ?"%in%".
Skipping named elements
Skipping or removing named elements is a little harder. If we try to skip one named element by negating the string, R complains (slightly obscurely) that it doesn’t know how to take the negative of a string:
R
x <- c(a=5.4, b=6.2, c=7.1, d=4.8, e=7.5) # we start again by naming a vector 'on the fly'
x[-"a"]
ERROR
Error in -"a": invalid argument to unary operatorHowever, we can use the != (not-equals) operator to
construct a logical vector that will do what we want:
R
x[names(x) != "a"]
OUTPUT
b c d e
6.2 7.1 4.8 7.5 Skipping multiple named indices is a little bit harder still. Suppose
we want to drop the "a" and "c" elements, so
we try this:
R
x[names(x)!=c("a","c")]
WARNING
Warning in names(x) != c("a", "c"): longer object length is not a multiple of
shorter object lengthOUTPUT
b c d e
6.2 7.1 4.8 7.5 R did something, but it gave us a warning that we ought to
pay attention to - and it apparently gave us the wrong answer
(the "c" element is still included in the vector)!
So what does != actually do in this case? That’s an
excellent question.
Recycling
Let’s take a look at the comparison component of this code:
R
names(x) != c("a", "c")
WARNING
Warning in names(x) != c("a", "c"): longer object length is not a multiple of
shorter object lengthOUTPUT
[1] FALSE TRUE TRUE TRUE TRUEWhy does R give TRUE as the third element of this
vector, when names(x)[3] != "c" is obviously false? When
you use !=, R tries to compare each element of the left
argument with the corresponding element of its right argument. What
happens when you compare vectors of different lengths?
When one vector is shorter than the other, it gets recycled:
In this case R repeats c("a", "c") as
many times as necessary to match names(x), i.e. we get
c("a","c","a","c","a"). Since the recycled "a"
doesn’t match the third element of names(x), the value of
!= is TRUE. Because in this case the longer
vector length (5) isn’t a multiple of the shorter vector length (2), R
printed a warning message. If we had been unlucky and
names(x) had contained six elements, R would
silently have done the wrong thing (i.e., not what we intended
it to do). This recycling rule can can introduce hard-to-find and subtle
bugs!
The way to get R to do what we really want (match each
element of the left argument with all of the elements of the
right argument) it to use the %in% operator. The
%in% operator goes through each element of its left
argument, in this case the names of x, and asks, “Does this
element occur in the second argument?”. Here, since we want to
exclude values, we also need a ! operator to
change “in” to “not in”:
R
x[! names(x) %in% c("a","c") ]
OUTPUT
b d e
6.2 4.8 7.5 Challenge 3
Selecting elements of a vector that match any of a list of components
is a very common data analysis task. For example, the gapminder data set
contains country and continent variables, but
no information between these two scales. Suppose we want to pull out
information from southeast Asia: how do we set up an operation to
produce a logical vector that is TRUE for all of the
countries in southeast Asia and FALSE otherwise?
Suppose you have these data:
R
seAsia <- c("Myanmar","Thailand","Cambodia","Vietnam","Laos")
## read in the gapminder data that we downloaded in episode 2
gapminder <- read.csv("data/gapminder_data.csv", header=TRUE)
## extract the `country` column from a data frame (we'll see this later);
## convert from a factor to a character;
## and get just the non-repeated elements
countries <- unique(as.character(gapminder$country))
There’s a wrong way (using only ==), which will give you
a warning; a clunky way (using the logical operators == and
|); and an elegant way (using %in%). See
whether you can come up with all three and explain how they (don’t)
work.
- The wrong way to do this problem is
countries==seAsia. This gives a warning ("In countries == seAsia : longer object length is not a multiple of shorter object length") and the wrong answer (a vector of allFALSEvalues), because none of the recycled values ofseAsiahappen to line up correctly with matching values incountry. - The clunky (but technically correct) way to do this problem is
R
(countries=="Myanmar" | countries=="Thailand" |
countries=="Cambodia" | countries == "Vietnam" | countries=="Laos")
(or countries==seAsia[1] | countries==seAsia[2] | ...).
This gives the correct values, but hopefully you can see how awkward it
is (what if we wanted to select countries from a much longer list?).
- The best way to do this problem is
countries %in% seAsia, which is both correct and easy to type (and read).
Handling special values
At some point you will encounter functions in R that cannot handle missing, infinite, or undefined data.
There are a number of special functions you can use to filter out this data:
-
is.nawill return all positions in a vector, matrix, or data.frame containingNA(orNaN) - likewise,
is.nan, andis.infinitewill do the same forNaNandInf. -
is.finitewill return all positions in a vector, matrix, or data.frame that do not containNA,NaNorInf. -
na.omitwill filter out all missing values from a vector
Factor subsetting
Now that we’ve explored the different ways to subset vectors, how do we subset the other data structures?
Factor subsetting works the same way as vector subsetting.
R
f <- factor(c("a", "a", "b", "c", "c", "d"))
f[f == "a"]
OUTPUT
[1] a a
Levels: a b c dR
f[f %in% c("b", "c")]
OUTPUT
[1] b c c
Levels: a b c dR
f[1:3]
OUTPUT
[1] a a b
Levels: a b c dSkipping elements will not remove the level even if no more of that category exists in the factor:
R
f[-3]
OUTPUT
[1] a a c c d
Levels: a b c dMatrix subsetting
Matrices are also subsetted using the [ function. In
this case it takes two arguments: the first applying to the rows, the
second to its columns:
R
set.seed(1)
m <- matrix(rnorm(6*4), ncol=4, nrow=6)
m[3:4, c(3,1)]
OUTPUT
[,1] [,2]
[1,] 1.12493092 -0.8356286
[2,] -0.04493361 1.5952808You can leave the first or second arguments blank to retrieve all the rows or columns respectively:
R
m[, c(3,4)]
OUTPUT
[,1] [,2]
[1,] -0.62124058 0.82122120
[2,] -2.21469989 0.59390132
[3,] 1.12493092 0.91897737
[4,] -0.04493361 0.78213630
[5,] -0.01619026 0.07456498
[6,] 0.94383621 -1.98935170If we only access one row or column, R will automatically convert the result to a vector:
R
m[3,]
OUTPUT
[1] -0.8356286 0.5757814 1.1249309 0.9189774If you want to keep the output as a matrix, you need to specify a
third argument; drop = FALSE:
R
m[3, , drop=FALSE]
OUTPUT
[,1] [,2] [,3] [,4]
[1,] -0.8356286 0.5757814 1.124931 0.9189774Unlike vectors, if we try to access a row or column outside of the matrix, R will throw an error:
R
m[, c(3,6)]
ERROR
Error in m[, c(3, 6)]: subscript out of boundsTip: Higher dimensional arrays
when dealing with multi-dimensional arrays, each argument to
[ corresponds to a dimension. For example, a 3D array, the
first three arguments correspond to the rows, columns, and depth
dimension.
Because matrices are vectors, we can also subset using only one argument:
R
m[5]
OUTPUT
[1] 0.3295078This usually isn’t useful, and often confusing to read. However it is useful to note that matrices are laid out in column-major format by default. That is the elements of the vector are arranged column-wise:
R
matrix(1:6, nrow=2, ncol=3)
OUTPUT
[,1] [,2] [,3]
[1,] 1 3 5
[2,] 2 4 6If you wish to populate the matrix by row, use
byrow=TRUE:
R
matrix(1:6, nrow=2, ncol=3, byrow=TRUE)
OUTPUT
[,1] [,2] [,3]
[1,] 1 2 3
[2,] 4 5 6Matrices can also be subsetted using their rownames and column names instead of their row and column indices.
Challenge 4
Given the following code:
R
m <- matrix(1:18, nrow=3, ncol=6)
print(m)
OUTPUT
[,1] [,2] [,3] [,4] [,5] [,6]
[1,] 1 4 7 10 13 16
[2,] 2 5 8 11 14 17
[3,] 3 6 9 12 15 18- Which of the following commands will extract the values 11 and 14?
A. m[2,4,2,5]
B. m[2:5]
C. m[4:5,2]
D. m[2,c(4,5)]
D
List subsetting
Now we’ll introduce some new subsetting operators. There are three
functions used to subset lists. We’ve already seen these when learning
about atomic vectors and matrices: [, [[, and
$.
Using [ will always return a list. If you want to
subset a list, but not extract an element, then you
will likely use [.
R
xlist <- list(a = "Software Carpentry", b = 1:10, data = head(mtcars))
xlist[1]
OUTPUT
$a
[1] "Software Carpentry"This returns a list with one element.
We can subset elements of a list exactly the same way as atomic
vectors using [. Comparison operations however won’t work
as they’re not recursive, they will try to condition on the data
structures in each element of the list, not the individual elements
within those data structures.
R
xlist[1:2]
OUTPUT
$a
[1] "Software Carpentry"
$b
[1] 1 2 3 4 5 6 7 8 9 10To extract individual elements of a list, you need to use the
double-square bracket function: [[.
R
xlist[[1]]
OUTPUT
[1] "Software Carpentry"Notice that now the result is a vector, not a list.
You can’t extract more than one element at once:
R
xlist[[1:2]]
ERROR
Error in xlist[[1:2]]: subscript out of boundsNor use it to skip elements:
R
xlist[[-1]]
ERROR
Error in xlist[[-1]]: invalid negative subscript in get1index <real>But you can use names to both subset and extract elements:
R
xlist[["a"]]
OUTPUT
[1] "Software Carpentry"The $ function is a shorthand way for extracting
elements by name:
R
xlist$data
OUTPUT
mpg cyl disp hp drat wt qsec vs am gear carb
Mazda RX4 21.0 6 160 110 3.90 2.620 16.46 0 1 4 4
Mazda RX4 Wag 21.0 6 160 110 3.90 2.875 17.02 0 1 4 4
Datsun 710 22.8 4 108 93 3.85 2.320 18.61 1 1 4 1
Hornet 4 Drive 21.4 6 258 110 3.08 3.215 19.44 1 0 3 1
Hornet Sportabout 18.7 8 360 175 3.15 3.440 17.02 0 0 3 2
Valiant 18.1 6 225 105 2.76 3.460 20.22 1 0 3 1Challenge 5
Given the following list:
R
xlist <- list(a = "Software Carpentry", b = 1:10, data = head(mtcars))
Using your knowledge of both list and vector subsetting, extract the number 2 from xlist. Hint: the number 2 is contained within the “b” item in the list.
R
xlist$b[2]
OUTPUT
[1] 2R
xlist[[2]][2]
OUTPUT
[1] 2R
xlist[["b"]][2]
OUTPUT
[1] 2Challenge 6
Given a linear model:
R
mod <- aov(pop ~ lifeExp, data=gapminder)
Extract the residual degrees of freedom (hint:
attributes() will help you)
R
attributes(mod) ## `df.residual` is one of the names of `mod`
R
mod$df.residual
Data frames
Remember the data frames are lists underneath the hood, so similar rules apply. However they are also two dimensional objects:
[ with one argument will act the same way as for lists,
where each list element corresponds to a column. The resulting object
will be a data frame:
R
head(gapminder[3])
OUTPUT
pop
1 8425333
2 9240934
3 10267083
4 11537966
5 13079460
6 14880372Similarly, [[ will act to extract a single
column:
R
head(gapminder[["lifeExp"]])
OUTPUT
[1] 28.801 30.332 31.997 34.020 36.088 38.438And $ provides a convenient shorthand to extract columns
by name:
R
head(gapminder$year)
OUTPUT
[1] 1952 1957 1962 1967 1972 1977With two arguments, [ behaves the same way as for
matrices:
R
gapminder[1:3,]
OUTPUT
country year pop continent lifeExp gdpPercap
1 Afghanistan 1952 8425333 Asia 28.801 779.4453
2 Afghanistan 1957 9240934 Asia 30.332 820.8530
3 Afghanistan 1962 10267083 Asia 31.997 853.1007If we subset a single row, the result will be a data frame (because the elements are mixed types):
R
gapminder[3,]
OUTPUT
country year pop continent lifeExp gdpPercap
3 Afghanistan 1962 10267083 Asia 31.997 853.1007But for a single column the result will be a vector (this can be
changed with the third argument, drop = FALSE).
Challenge 7
Fix each of the following common data frame subsetting errors:
- Extract observations collected for the year 1957
- Extract all columns except 1 through to 4
R
gapminder[,-1:4]
- Extract the rows where the life expectancy is longer the 80 years
R
gapminder[gapminder$lifeExp > 80]
- Extract the first row, and the fourth and fifth columns
(
continentandlifeExp).
R
gapminder[1, 4, 5]
- Advanced: extract rows that contain information for the years 2002 and 2007
R
gapminder[gapminder$year == 2002 | 2007,]
Fix each of the following common data frame subsetting errors:
- Extract observations collected for the year 1957
R
# gapminder[gapminder$year = 1957,]
gapminder[gapminder$year == 1957,]
- Extract all columns except 1 through to 4
R
# gapminder[,-1:4]
gapminder[,-c(1:4)]
- Extract the rows where the life expectancy is longer than 80 years
R
# gapminder[gapminder$lifeExp > 80]
gapminder[gapminder$lifeExp > 80,]
- Extract the first row, and the fourth and fifth columns
(
continentandlifeExp).
R
# gapminder[1, 4, 5]
gapminder[1, c(4, 5)]
- Advanced: extract rows that contain information for the years 2002 and 2007
R
# gapminder[gapminder$year == 2002 | 2007,]
gapminder[gapminder$year == 2002 | gapminder$year == 2007,]
gapminder[gapminder$year %in% c(2002, 2007),]
Challenge 8
Why does
gapminder[1:20]return an error? How does it differ fromgapminder[1:20, ]?Create a new
data.framecalledgapminder_smallthat only contains rows 1 through 9 and 19 through 23. You can do this in one or two steps.
gapminderis a data.frame so needs to be subsetted on two dimensions.gapminder[1:20, ]subsets the data to give the first 20 rows and all columns.
R
gapminder_small <- gapminder[c(1:9, 19:23),]
Key Points
- Indexing in R starts at 1, not 0.
- Access individual values by location using
[]. - Access slices of data using
[low:high]. - Access arbitrary sets of data using
[c(...)]. - Use logical operations and logical vectors to access subsets of data.
Content from Creating Publication-Quality Graphics with ggplot2
Last updated on 2024-12-04 | Edit this page
Estimated time: 80 minutes
Overview
Questions
- How can I create publication-quality graphics in R?
Objectives
- To be able to use ggplot2 to generate publication-quality graphics.
- To apply geometry, aesthetic, and statistics layers to a ggplot plot.
- To manipulate the aesthetics of a plot using different colors, shapes, and lines.
- To improve data visualization through transforming scales and paneling by group.
- To save a plot created with ggplot to disk.
Plotting our data is one of the best ways to quickly explore it and the various relationships between variables.
There are three main plotting systems in R, the base plotting system, the lattice package, and the ggplot2 package.
Today we’ll be learning about the ggplot2 package, because it is the most effective for creating publication-quality graphics.
ggplot2 is built on the grammar of graphics, the idea that any plot can be built from the same set of components: a data set, mapping aesthetics, and graphical layers:
Data sets are the data that you, the user, provide.
Mapping aesthetics are what connect the data to the graphics. They tell ggplot2 how to use your data to affect how the graph looks, such as changing what is plotted on the X or Y axis, or the size or color of different data points.
Layers are the actual graphical output from ggplot2. Layers determine what kinds of plot are shown (scatterplot, histogram, etc.), the coordinate system used (rectangular, polar, others), and other important aspects of the plot. The idea of layers of graphics may be familiar to you if you have used image editing programs like Photoshop, Illustrator, or Inkscape.
Let’s start off building an example using the gapminder data from
earlier. The most basic function is ggplot, which lets R
know that we’re creating a new plot. Any of the arguments we give the
ggplot function are the global options for the
plot: they apply to all layers on the plot.
R
library("ggplot2")
ggplot(data = gapminder)
Here we called ggplot and told it what data we want to
show on our figure. This is not enough information for
ggplot to actually draw anything. It only creates a blank
slate for other elements to be added to.
Now we’re going to add in the mapping aesthetics
using the aes function. aes tells
ggplot how variables in the data map to
aesthetic properties of the figure, such as which columns of
the data should be used for the x and
y locations.
R
ggplot(data = gapminder, mapping = aes(x = gdpPercap, y = lifeExp))
Here we told ggplot we want to plot the “gdpPercap”
column of the gapminder data frame on the x-axis, and the “lifeExp”
column on the y-axis. Notice that we didn’t need to explicitly pass
aes these columns
(e.g. x = gapminder[, "gdpPercap"]), this is because
ggplot is smart enough to know to look in the
data for that column!
The final part of making our plot is to tell ggplot how
we want to visually represent the data. We do this by adding a new
layer to the plot using one of the
geom functions.
R
ggplot(data = gapminder, mapping = aes(x = gdpPercap, y = lifeExp)) +
geom_point()
Here we used geom_point, which tells ggplot
we want to visually represent the relationship between
x and y as a scatterplot of
points.
Challenge 1
Modify the example so that the figure shows how life expectancy has changed over time:
R
ggplot(data = gapminder, mapping = aes(x = gdpPercap, y = lifeExp)) + geom_point()
Hint: the gapminder dataset has a column called “year”, which should appear on the x-axis.
Here is one possible solution:
R
ggplot(data = gapminder, mapping = aes(x = year, y = lifeExp)) + geom_point()
Challenge 2
In the previous examples and challenge we’ve used the
aes function to tell the scatterplot geom
about the x and y locations of each
point. Another aesthetic property we can modify is the point
color. Modify the code from the previous challenge to
color the points by the “continent” column. What trends
do you see in the data? Are they what you expected?
The solution presented below adds color=continent to the
call of the aes function. The general trend seems to
indicate an increased life expectancy over the years. On continents with
stronger economies we find a longer life expectancy.
R
ggplot(data = gapminder, mapping = aes(x = year, y = lifeExp, color=continent)) +
geom_point()
Layers
Using a scatterplot probably isn’t the best for visualizing change
over time. Instead, let’s tell ggplot to visualize the data
as a line plot:
R
ggplot(data = gapminder, mapping = aes(x=year, y=lifeExp, color=continent)) +
geom_line()
Instead of adding a geom_point layer, we’ve added a
geom_line layer.
However, the result doesn’t look quite as we might have expected: it seems to be jumping around a lot in each continent. Let’s try to separate the data by country, plotting one line for each country:
R
ggplot(data = gapminder, mapping = aes(x=year, y=lifeExp, group=country, color=continent)) +
geom_line()
We’ve added the group aesthetic, which
tells ggplot to draw a line for each country.
But what if we want to visualize both lines and points on the plot? We can add another layer to the plot:
R
ggplot(data = gapminder, mapping = aes(x=year, y=lifeExp, group=country, color=continent)) +
geom_line() + geom_point()
It’s important to note that each layer is drawn on top of the previous layer. In this example, the points have been drawn on top of the lines. Here’s a demonstration:
R
ggplot(data = gapminder, mapping = aes(x=year, y=lifeExp, group=country)) +
geom_line(mapping = aes(color=continent)) + geom_point()
In this example, the aesthetic mapping of
color has been moved from the global plot options in
ggplot to the geom_line layer so it no longer
applies to the points. Now we can clearly see that the points are drawn
on top of the lines.
Tip: Setting an aesthetic to a value instead of a mapping
So far, we’ve seen how to use an aesthetic (such as
color) as a mapping to a variable in the data.
For example, when we use
geom_line(mapping = aes(color=continent)), ggplot will give
a different color to each continent. But what if we want to change the
color of all lines to blue? You may think that
geom_line(mapping = aes(color="blue")) should work, but it
doesn’t. Since we don’t want to create a mapping to a specific variable,
we can move the color specification outside of the aes()
function, like this: geom_line(color="blue").
Challenge 3
Switch the order of the point and line layers from the previous example. What happened?
The lines now get drawn over the points!
R
ggplot(data = gapminder, mapping = aes(x=year, y=lifeExp, group=country)) +
geom_point() + geom_line(mapping = aes(color=continent))
Transformations and statistics
ggplot2 also makes it easy to overlay statistical models over the data. To demonstrate we’ll go back to our first example:
R
ggplot(data = gapminder, mapping = aes(x = gdpPercap, y = lifeExp)) +
geom_point()
Currently it’s hard to see the relationship between the points due to some strong outliers in GDP per capita. We can change the scale of units on the x axis using the scale functions. These control the mapping between the data values and visual values of an aesthetic. We can also modify the transparency of the points, using the alpha function, which is especially helpful when you have a large amount of data which is very clustered.
R
ggplot(data = gapminder, mapping = aes(x = gdpPercap, y = lifeExp)) +
geom_point(alpha = 0.5) + scale_x_log10()
The scale_x_log10 function applied a transformation to
the coordinate system of the plot, so that each multiple of 10 is evenly
spaced from left to right. For example, a GDP per capita of 1,000 is the
same horizontal distance away from a value of 10,000 as the 10,000 value
is from 100,000. This helps to visualize the spread of the data along
the x-axis.
Tip Reminder: Setting an aesthetic to a value instead of a mapping
Notice that we used geom_point(alpha = 0.5). As the
previous tip mentioned, using a setting outside of the
aes() function will cause this value to be used for all
points, which is what we want in this case. But just like any other
aesthetic setting, alpha can also be mapped to a variable in
the data. For example, we can give a different transparency to each
continent with
geom_point(mapping = aes(alpha = continent)).
We can fit a simple relationship to the data by adding another layer,
geom_smooth:
R
ggplot(data = gapminder, mapping = aes(x = gdpPercap, y = lifeExp)) +
geom_point(alpha = 0.5) + scale_x_log10() + geom_smooth(method="lm")
OUTPUT
`geom_smooth()` using formula = 'y ~ x'
We can make the line thicker by setting the
linewidth aesthetic in the geom_smooth
layer:
R
ggplot(data = gapminder, mapping = aes(x = gdpPercap, y = lifeExp)) +
geom_point(alpha = 0.5) + scale_x_log10() + geom_smooth(method="lm", linewidth=1.5)
OUTPUT
`geom_smooth()` using formula = 'y ~ x'
There are two ways an aesthetic can be specified. Here we
set the linewidth aesthetic by passing it as
an argument to geom_smooth and it is applied the same to
the whole geom. Previously in the lesson we’ve used the
aes function to define a mapping between data
variables and their visual representation.
Challenge 4a
Modify the color and size of the points on the point layer in the previous example.
Hint: do not use the aes function.
Hint: the equivalent of linewidth for points is
size.
Here a possible solution: Notice that the color argument
is supplied outside of the aes() function. This means that
it applies to all data points on the graph and is not related to a
specific variable.
R
ggplot(data = gapminder, mapping = aes(x = gdpPercap, y = lifeExp)) +
geom_point(size=3, color="orange") + scale_x_log10() +
geom_smooth(method="lm", linewidth=1.5)
OUTPUT
`geom_smooth()` using formula = 'y ~ x'
Challenge 4b
Modify your solution to Challenge 4a so that the points are now a different shape and are colored by continent with new trendlines. Hint: The color argument can be used inside the aesthetic.
Here is a possible solution: Notice that supplying the
color argument inside the aes() functions
enables you to connect it to a certain variable. The shape
argument, as you can see, modifies all data points the same way (it is
outside the aes() call) while the color
argument which is placed inside the aes() call modifies a
point’s color based on its continent value.
R
ggplot(data = gapminder, mapping = aes(x = gdpPercap, y = lifeExp, color = continent)) +
geom_point(size=3, shape=17) + scale_x_log10() +
geom_smooth(method="lm", linewidth=1.5)
OUTPUT
`geom_smooth()` using formula = 'y ~ x'
Multi-panel figures
Earlier we visualized the change in life expectancy over time across all countries in one plot. Alternatively, we can split this out over multiple panels by adding a layer of facet panels.
Tip
We start by making a subset of data including only countries located in the Americas. This includes 25 countries, which will begin to clutter the figure. Note that we apply a “theme” definition to rotate the x-axis labels to maintain readability. Nearly everything in ggplot2 is customizable.
R
americas <- gapminder[gapminder$continent == "Americas",]
ggplot(data = americas, mapping = aes(x = year, y = lifeExp)) +
geom_line() +
facet_wrap( ~ country) +
theme(axis.text.x = element_text(angle = 45))
The facet_wrap layer took a “formula” as its argument,
denoted by the tilde (~). This tells R to draw a panel for each unique
value in the country column of the gapminder dataset.
Modifying text
To clean this figure up for a publication we need to change some of the text elements. The x-axis is too cluttered, and the y axis should read “Life expectancy”, rather than the column name in the data frame.
We can do this by adding a couple of different layers. The
theme layer controls the axis text, and overall text
size. Labels for the axes, plot title and any legend can be set using
the labs function. Legend titles are set using the same
names we used in the aes specification. Thus below the
color legend title is set using color = "Continent", while
the title of a fill legend would be set using
fill = "MyTitle".
R
ggplot(data = americas, mapping = aes(x = year, y = lifeExp, color=continent)) +
geom_line() + facet_wrap( ~ country) +
labs(
x = "Year", # x axis title
y = "Life expectancy", # y axis title
title = "Figure 1", # main title of figure
color = "Continent" # title of legend
) +
theme(axis.text.x = element_text(angle = 90, hjust = 1))
Exporting the plot
The ggsave() function allows you to export a plot
created with ggplot. You can specify the dimension and resolution of
your plot by adjusting the appropriate arguments (width,
height and dpi) to create high quality
graphics for publication. In order to save the plot from above, we first
assign it to a variable lifeExp_plot, then tell
ggsave to save that plot in png format to a
directory called results. (Make sure you have a
results/ folder in your working directory.)
R
lifeExp_plot <- ggplot(data = americas, mapping = aes(x = year, y = lifeExp, color=continent)) +
geom_line() + facet_wrap( ~ country) +
labs(
x = "Year", # x axis title
y = "Life expectancy", # y axis title
title = "Figure 1", # main title of figure
color = "Continent" # title of legend
) +
theme(axis.text.x = element_text(angle = 90, hjust = 1))
ggsave(filename = "results/lifeExp.png", plot = lifeExp_plot, width = 12, height = 10, dpi = 300, units = "cm")
There are two nice things about ggsave. First, it
defaults to the last plot, so if you omit the plot argument
it will automatically save the last plot you created with
ggplot. Secondly, it tries to determine the format you want
to save your plot in from the file extension you provide for the
filename (for example .png or .pdf). If you
need to, you can specify the format explicitly in the
device argument.
This is a taste of what you can do with ggplot2. RStudio provides a really useful cheat sheet of the different layers available, and more extensive documentation is available on the ggplot2 website. All RStudio cheat sheets are available from the RStudio website. Finally, if you have no idea how to change something, a quick Google search will usually send you to a relevant question and answer on Stack Overflow with reusable code to modify!
Challenge 5
Generate boxplots to compare life expectancy between the different continents during the available years.
Advanced:
- Rename y axis as Life Expectancy.
- Remove x axis labels.
Here a possible solution: xlab() and ylab()
set labels for the x and y axes, respectively The axis title, text and
ticks are attributes of the theme and must be modified within a
theme() call.
R
ggplot(data = gapminder, mapping = aes(x = continent, y = lifeExp, fill = continent)) +
geom_boxplot() + facet_wrap(~year) +
ylab("Life Expectancy") +
theme(axis.title.x=element_blank(),
axis.text.x = element_blank(),
axis.ticks.x = element_blank())
Key Points
- Use
ggplot2to create plots. - Think about graphics in layers: aesthetics, geometry, statistics, scale transformation, and grouping.
Content from Writing Data
Last updated on 2024-12-04 | Edit this page
Estimated time: 20 minutes
Overview
Questions
- How can I save plots and data created in R?
Objectives
- To be able to write out plots and data from R.
Saving plots
You have already seen how to save the most recent plot you create in
ggplot2, using the command ggsave. As a
refresher:
R
ggsave("My_most_recent_plot.pdf")
You can save a plot from within RStudio using the ‘Export’ button in the ‘Plot’ window. This will give you the option of saving as a .pdf or as .png, .jpg or other image formats.
Sometimes you will want to save plots without creating them in the ‘Plot’ window first. Perhaps you want to make a pdf document with multiple pages: each one a different plot, for example. Or perhaps you’re looping through multiple subsets of a file, plotting data from each subset, and you want to save each plot, but obviously can’t stop the loop to click ‘Export’ for each one.
In this case you can use a more flexible approach. The function
pdf creates a new pdf device. You can control the size and
resolution using the arguments to this function.
R
pdf("Life_Exp_vs_time.pdf", width=12, height=4)
ggplot(data=gapminder, aes(x=year, y=lifeExp, colour=country)) +
geom_line() +
theme(legend.position = "none")
# You then have to make sure to turn off the pdf device!
dev.off()
Open up this document and have a look.
Challenge 1
Rewrite your ‘pdf’ command to print a second page in the pdf, showing
a facet plot (hint: use facet_grid) of the same data with
one panel per continent.
R
pdf("Life_Exp_vs_time.pdf", width = 12, height = 4)
p <- ggplot(data = gapminder, aes(x = year, y = lifeExp, colour = country)) +
geom_line() +
theme(legend.position = "none")
p
p + facet_grid(~continent)
dev.off()
The commands jpeg, png etc. are used
similarly to produce documents in different formats.
Writing data
At some point, you’ll also want to write out data from R.
We can use the write.table function for this, which is
very similar to read.table from before.
Let’s create a data-cleaning script, for this analysis, we only want to focus on the gapminder data for Australia:
R
aust_subset <- gapminder[gapminder$country == "Australia",]
write.table(aust_subset,
file="cleaned-data/gapminder-aus.csv",
sep=","
)
Let’s switch back to the shell to take a look at the data to make sure it looks OK:
OUTPUT
"country","year","pop","continent","lifeExp","gdpPercap"
"61","Australia",1952,8691212,"Oceania",69.12,10039.59564
"62","Australia",1957,9712569,"Oceania",70.33,10949.64959
"63","Australia",1962,10794968,"Oceania",70.93,12217.22686
"64","Australia",1967,11872264,"Oceania",71.1,14526.12465
"65","Australia",1972,13177000,"Oceania",71.93,16788.62948
"66","Australia",1977,14074100,"Oceania",73.49,18334.19751
"67","Australia",1982,15184200,"Oceania",74.74,19477.00928
"68","Australia",1987,16257249,"Oceania",76.32,21888.88903
"69","Australia",1992,17481977,"Oceania",77.56,23424.76683Hmm, that’s not quite what we wanted. Where did all these quotation marks come from? Also the row numbers are meaningless.
Let’s look at the help file to work out how to change this behaviour.
R
?write.table
By default R will wrap character vectors with quotation marks when writing out to file. It will also write out the row and column names.
Let’s fix this:
R
write.table(
gapminder[gapminder$country == "Australia",],
file="cleaned-data/gapminder-aus.csv",
sep=",", quote=FALSE, row.names=FALSE
)
Now lets look at the data again using our shell skills:
OUTPUT
country,year,pop,continent,lifeExp,gdpPercap
Australia,1952,8691212,Oceania,69.12,10039.59564
Australia,1957,9712569,Oceania,70.33,10949.64959
Australia,1962,10794968,Oceania,70.93,12217.22686
Australia,1967,11872264,Oceania,71.1,14526.12465
Australia,1972,13177000,Oceania,71.93,16788.62948
Australia,1977,14074100,Oceania,73.49,18334.19751
Australia,1982,15184200,Oceania,74.74,19477.00928
Australia,1987,16257249,Oceania,76.32,21888.88903
Australia,1992,17481977,Oceania,77.56,23424.76683That looks better!
Challenge 2
Write a data-cleaning script file that subsets the gapminder data to include only data points collected since 1990.
Use this script to write out the new subset to a file in the
cleaned-data/ directory.
R
write.table(
gapminder[gapminder$year > 1990, ],
file = "cleaned-data/gapminder-after1990.csv",
sep = ",", quote = FALSE, row.names = FALSE
)
Key Points
- Save plots from RStudio using the ‘Export’ button.
- Use
write.tableto save tabular data.
Content from Remotes in GitHub
Last updated on 2024-12-04 | Edit this page
Estimated time: 45 minutes
Overview
Questions
- How do I share my changes with others on the web?
Objectives
- Explain what remote repositories are and why they are useful.
- Push to or pull from a remote repository.
Version control really comes into its own when we begin to collaborate with other people. We already have most of the machinery we need to do this; the only thing missing is to copy changes from one repository to another.
Systems like Git allow us to move work between any two repositories. In practice, though, it’s easiest to use one copy as a central hub, and to keep it on the web rather than on someone’s laptop. Most programmers use hosting services like GitHub, Bitbucket or GitLab to hold those main copies; we’ll explore the pros and cons of this in a later episode.
Let’s start by sharing the changes we’ve made to our current project with the world. To this end we are going to create a remote repository that will be linked to our local repository.
1. Create a remote repository
Log in to GitHub, then click on the
icon in the top right corner to create a new repository called
planets:
Name your repository “planets” and then click “Create Repository”.
Note: Since this repository will be connected to a local repository, it needs to be empty. Leave “Initialize this repository with a README” unchecked, and keep “None” as options for both “Add .gitignore” and “Add a license.” See the “GitHub License and README files” exercise below for a full explanation of why the repository needs to be empty.
As soon as the repository is created, GitHub displays a page with a URL and some information on how to configure your local repository:
This effectively does the following on GitHub’s servers:
If you remember back to the earlier episode where we added and committed our
earlier work on mars.txt, we had a diagram of the local
repository which looked like this:
Now that we have two repositories, we need a diagram like this:
Note that our local repository still contains our earlier work on
mars.txt, but the remote repository on GitHub appears empty
as it doesn’t contain any files yet.
2. Connect local to remote repository
Now we connect the two repositories. We do this by making the GitHub repository a remote for the local repository. The home page of the repository on GitHub includes the URL string we need to identify it:
Click on the ‘SSH’ link to change the protocol from HTTPS to SSH.
HTTPS vs. SSH
We use SSH here because, while it requires some additional configuration, it is a security protocol widely used by many applications. The steps below describe SSH at a minimum level for GitHub.
Copy that URL from the browser, go into the local
planets repository, and run this command:
Make sure to use the URL for your repository rather than Vlad’s: the
only difference should be your username instead of
vlad.
origin is a local name used to refer to the remote
repository. It could be called anything, but origin is a
convention that is often used by default in git and GitHub, so it’s
helpful to stick with this unless there’s a reason not to.
We can check that the command has worked by running
git remote -v:
OUTPUT
origin git@github.com:vlad/planets.git (fetch)
origin git@github.com:vlad/planets.git (push)We’ll discuss remotes in more detail in the next episode, while talking about how they might be used for collaboration.
3. SSH Background and Setup
Before Dracula can connect to a remote repository, he needs to set up a way for his computer to authenticate with GitHub so it knows it’s him trying to connect to his remote repository.
We are going to set up the method that is commonly used by many different services to authenticate access on the command line. This method is called Secure Shell Protocol (SSH). SSH is a cryptographic network protocol that allows secure communication between computers using an otherwise insecure network.
SSH uses what is called a key pair. This is two keys that work together to validate access. One key is publicly known and called the public key, and the other key called the private key is kept private. Very descriptive names.
You can think of the public key as a padlock, and only you have the key (the private key) to open it. You use the public key where you want a secure method of communication, such as your GitHub account. You give this padlock, or public key, to GitHub and say “lock the communications to my account with this so that only computers that have my private key can unlock communications and send git commands as my GitHub account.”
What we will do now is the minimum required to set up the SSH keys and add the public key to a GitHub account.
Advanced SSH
A supplemental episode in this lesson discusses SSH and key pairs in more depth and detail.
The first thing we are going to do is check if this has already been done on the computer you’re on. Because generally speaking, this setup only needs to happen once and then you can forget about it.
Keeping your keys secure
You shouldn’t really forget about your SSH keys, since they keep your account secure. It’s good practice to audit your secure shell keys every so often. Especially if you are using multiple computers to access your account.
We will run the list command to check what key pairs already exist on your computer.
Your output is going to look a little different depending on whether or not SSH has ever been set up on the computer you are using.
Dracula has not set up SSH on his computer, so his output is
OUTPUT
ls: cannot access '/c/Users/Vlad Dracula/.ssh': No such file or directoryIf SSH has been set up on the computer you’re using, the public and
private key pairs will be listed. The file names are either
id_ed25519/id_ed25519.pub or
id_rsa/id_rsa.pub depending on how the key
pairs were set up.
Since they don’t exist on Dracula’s computer, he uses this command to
create them.
3.1 Create an SSH key pair
To create an SSH key pair Vlad uses this command, where the
-t option specifies which type of algorithm to use and
-C attaches a comment to the key (here, Vlad’s email):
If you are using a legacy system that doesn’t support the Ed25519
algorithm, use:
$ ssh-keygen -t rsa -b 4096 -C "your_email@example.com"
OUTPUT
Generating public/private ed25519 key pair.
Enter file in which to save the key (/c/Users/Vlad Dracula/.ssh/id_ed25519):We want to use the default file, so just press Enter.
OUTPUT
Created directory '/c/Users/Vlad Dracula/.ssh'.
Enter passphrase (empty for no passphrase):Now, it is prompting Dracula for a passphrase. Since he is using his lab’s laptop that other people sometimes have access to, he wants to create a passphrase. Be sure to use something memorable or save your passphrase somewhere, as there is no “reset my password” option. Note that, when typing a passphrase on a terminal, there won’t be any visual feedback of your typing. This is normal: your passphrase will be recorded even if you see nothing changing on your screen.
OUTPUT
Enter same passphrase again:After entering the same passphrase a second time, we receive the confirmation
OUTPUT
Your identification has been saved in /c/Users/Vlad Dracula/.ssh/id_ed25519
Your public key has been saved in /c/Users/Vlad Dracula/.ssh/id_ed25519.pub
The key fingerprint is:
SHA256:SMSPIStNyA00KPxuYu94KpZgRAYjgt9g4BA4kFy3g1o vlad@tran.sylvan.ia
The key's randomart image is:
+--[ED25519 256]--+
|^B== o. |
|%*=.*.+ |
|+=.E =.+ |
| .=.+.o.. |
|.... . S |
|.+ o |
|+ = |
|.o.o |
|oo+. |
+----[SHA256]-----+The “identification” is actually the private key. You should never share it. The public key is appropriately named. The “key fingerprint” is a shorter version of a public key.
Now that we have generated the SSH keys, we will find the SSH files when we check.
OUTPUT
drwxr-xr-x 1 Vlad Dracula 197121 0 Jul 16 14:48 ./
drwxr-xr-x 1 Vlad Dracula 197121 0 Jul 16 14:48 ../
-rw-r--r-- 1 Vlad Dracula 197121 419 Jul 16 14:48 id_ed25519
-rw-r--r-- 1 Vlad Dracula 197121 106 Jul 16 14:48 id_ed25519.pub3.2 Copy the public key to GitHub
Now we have a SSH key pair and we can run this command to check if GitHub can read our authentication.
OUTPUT
The authenticity of host 'github.com (192.30.255.112)' can't be established.
RSA key fingerprint is SHA256:nThbg6kXUpJWGl7E1IGOCspRomTxdCARLviKw6E5SY8.
This key is not known by any other names
Are you sure you want to continue connecting (yes/no/[fingerprint])? y
Please type 'yes', 'no' or the fingerprint: yes
Warning: Permanently added 'github.com' (RSA) to the list of known hosts.
git@github.com: Permission denied (publickey).Right, we forgot that we need to give GitHub our public key!
First, we need to copy the public key. Be sure to include the
.pub at the end, otherwise you’re looking at the private
key.
OUTPUT
ssh-ed25519 AAAAC3NzaC1lZDI1NTE5AAAAIDmRA3d51X0uu9wXek559gfn6UFNF69yZjChyBIU2qKI vlad@tran.sylvan.iaNow, going to GitHub.com, click on your profile icon in the top right corner to get the drop-down menu. Click “Settings,” then on the settings page, click “SSH and GPG keys,” on the left side “Account settings” menu. Click the “New SSH key” button on the right side. Now, you can add the title (Dracula uses the title “Vlad’s Lab Laptop” so he can remember where the original key pair files are located), paste your SSH key into the field, and click the “Add SSH key” to complete the setup.
Now that we’ve set that up, let’s check our authentication again from the command line.
OUTPUT
Hi Vlad! You've successfully authenticated, but GitHub does not provide shell access.Good! This output confirms that the SSH key works as intended. We are now ready to push our work to the remote repository.
4. Push local changes to a remote
Now that authentication is setup, we can return to the remote. This command will push the changes from our local repository to the repository on GitHub:
Since Dracula set up a passphrase, it will prompt him for it. If you completed advanced settings for your authentication, it will not prompt for a passphrase.
OUTPUT
Enumerating objects: 16, done.
Counting objects: 100% (16/16), done.
Delta compression using up to 8 threads.
Compressing objects: 100% (11/11), done.
Writing objects: 100% (16/16), 1.45 KiB | 372.00 KiB/s, done.
Total 16 (delta 2), reused 0 (delta 0)
remote: Resolving deltas: 100% (2/2), done.
To https://github.com/vlad/planets.git
* [new branch] main -> mainProxy
If the network you are connected to uses a proxy, there is a chance that your last command failed with “Could not resolve hostname” as the error message. To solve this issue, you need to tell Git about the proxy:
BASH
$ git config --global http.proxy http://user:password@proxy.url
$ git config --global https.proxy https://user:password@proxy.urlWhen you connect to another network that doesn’t use a proxy, you will need to tell Git to disable the proxy using:
Password Managers
If your operating system has a password manager configured,
git push will try to use it when it needs your username and
password. For example, this is the default behavior for Git Bash on
Windows. If you want to type your username and password at the terminal
instead of using a password manager, type:
in the terminal, before you run git push. Despite the
name, Git
uses SSH_ASKPASS for all credential entry, so you may
want to unset SSH_ASKPASS whether you are using Git via SSH
or https.
You may also want to add unset SSH_ASKPASS at the end of
your ~/.bashrc to make Git default to using the terminal
for usernames and passwords.
Our local and remote repositories are now in this state:
The ‘-u’ Flag
You may see a -u option used with git push
in some documentation. This option is synonymous with the
--set-upstream-to option for the git branch
command, and is used to associate the current branch with a remote
branch so that the git pull command can be used without any
arguments. To do this, simply use git push -u origin main
once the remote has been set up.
We can pull changes from the remote repository to the local one as well:
OUTPUT
From https://github.com/vlad/planets
* branch main -> FETCH_HEAD
Already up-to-date.Pulling has no effect in this case because the two repositories are already synchronized. If someone else had pushed some changes to the repository on GitHub, though, this command would download them to our local repository.
GitHub GUI
Browse to your planets repository on GitHub. Underneath
the Code button, find and click on the text that says “XX commits”
(where “XX” is some number). Hover over, and click on, the three buttons
to the right of each commit. What information can you gather/explore
from these buttons? How would you get that same information in the
shell?
The left-most button (with the picture of a clipboard) copies the
full identifier of the commit to the clipboard. In the shell,
git log will show you the full commit identifier for each
commit.
When you click on the middle button, you’ll see all of the changes
that were made in that particular commit. Green shaded lines indicate
additions and red ones removals. In the shell we can do the same thing
with git diff. In particular,
git diff ID1..ID2 where ID1 and ID2 are commit identifiers
(e.g. git diff a3bf1e5..041e637) will show the differences
between those two commits.
The right-most button lets you view all of the files in the
repository at the time of that commit. To do this in the shell, we’d
need to checkout the repository at that particular time. We can do this
with git checkout ID where ID is the identifier of the
commit we want to look at. If we do this, we need to remember to put the
repository back to the right state afterwards!
Uploading files directly in GitHub browser
Github also allows you to skip the command line and upload files directly to your repository without having to leave the browser. There are two options. First you can click the “Upload files” button in the toolbar at the top of the file tree. Or, you can drag and drop files from your desktop onto the file tree. You can read more about this on this GitHub page.
GitHub Timestamp
Create a remote repository on GitHub. Push the contents of your local repository to the remote. Make changes to your local repository and push these changes. Go to the repo you just created on GitHub and check the timestamps of the files. How does GitHub record times, and why?
GitHub displays timestamps in a human readable relative format (i.e. “22 hours ago” or “three weeks ago”). However, if you hover over the timestamp, you can see the exact time at which the last change to the file occurred.
Push vs. Commit
In this episode, we introduced the “git push” command. How is “git push” different from “git commit”?
When we push changes, we’re interacting with a remote repository to update it with the changes we’ve made locally (often this corresponds to sharing the changes we’ve made with others). Commit only updates your local repository.
GitHub License and README files
In this episode we learned about creating a remote repository on GitHub, but when you initialized your GitHub repo, you didn’t add a README.md or a license file. If you had, what do you think would have happened when you tried to link your local and remote repositories?
In this case, we’d see a merge conflict due to unrelated histories. When GitHub creates a README.md file, it performs a commit in the remote repository. When you try to pull the remote repository to your local repository, Git detects that they have histories that do not share a common origin and refuses to merge.
OUTPUT
warning: no common commits
remote: Enumerating objects: 3, done.
remote: Counting objects: 100% (3/3), done.
remote: Total 3 (delta 0), reused 0 (delta 0), pack-reused 0
Unpacking objects: 100% (3/3), done.
From https://github.com/vlad/planets
* branch main -> FETCH_HEAD
* [new branch] main -> origin/main
fatal: refusing to merge unrelated historiesYou can force git to merge the two repositories with the option
--allow-unrelated-histories. Be careful when you use this
option and carefully examine the contents of local and remote
repositories before merging.
OUTPUT
From https://github.com/vlad/planets
* branch main -> FETCH_HEAD
Merge made by the 'recursive' strategy.
README.md | 1 +
1 file changed, 1 insertion(+)
create mode 100644 README.mdKey Points
- A local Git repository can be connected to one or more remote repositories.
- Use the SSH protocol to connect to remote repositories.
-
git pushcopies changes from a local repository to a remote repository. -
git pullcopies changes from a remote repository to a local repository.
Content from Collaborating
Last updated on 2024-12-04 | Edit this page
Estimated time: 25 minutes
Overview
Questions
- How can I use version control to collaborate with other people?
Objectives
- Clone a remote repository.
- Collaborate by pushing to a common repository.
- Describe the basic collaborative workflow.
For the next step, get into pairs. One person will be the “Owner” and the other will be the “Collaborator”. The goal is that the Collaborator add changes into the Owner’s repository. We will switch roles at the end, so both persons will play Owner and Collaborator.
Practicing By Yourself
If you’re working through this lesson on your own, you can carry on by opening a second terminal window. This window will represent your partner, working on another computer. You won’t need to give anyone access on GitHub, because both ‘partners’ are you.
The Owner needs to give the Collaborator access. In your repository page on GitHub, click the “Settings” button on the right, select “Collaborators”, click “Add people”, and then enter your partner’s username.
To accept access to the Owner’s repo, the Collaborator needs to go to https://github.com/notifications or check for email notification. Once there she can accept access to the Owner’s repo.
Next, the Collaborator needs to download a copy of the Owner’s repository to her machine. This is called “cloning a repo”.
The Collaborator doesn’t want to overwrite her own version of
planets.git, so needs to clone the Owner’s repository to a
different location than her own repository with the same name.
To clone the Owner’s repo into her Desktop folder, the
Collaborator enters:
Replace ‘vlad’ with the Owner’s username.
If you choose to clone without the clone path
(~/Desktop/vlad-planets) specified at the end, you will
clone inside your own planets folder! Make sure to navigate to the
Desktop folder first.
The Collaborator can now make a change in her clone of the Owner’s repository, exactly the same way as we’ve been doing before:
OUTPUT
It is so a planet!OUTPUT
1 file changed, 1 insertion(+)
create mode 100644 pluto.txtThen push the change to the Owner’s repository on GitHub:
OUTPUT
Enumerating objects: 4, done.
Counting objects: 4, done.
Delta compression using up to 4 threads.
Compressing objects: 100% (2/2), done.
Writing objects: 100% (3/3), 306 bytes, done.
Total 3 (delta 0), reused 0 (delta 0)
To https://github.com/vlad/planets.git
9272da5..29aba7c main -> mainNote that we didn’t have to create a remote called
origin: Git uses this name by default when we clone a
repository. (This is why origin was a sensible choice
earlier when we were setting up remotes by hand.)
Take a look at the Owner’s repository on GitHub again, and you should be able to see the new commit made by the Collaborator. You may need to refresh your browser to see the new commit.
Some more about remotes
In this episode and the previous one, our local repository has had a
single “remote”, called origin. A remote is a copy of the
repository that is hosted somewhere else, that we can push to and pull
from, and there’s no reason that you have to work with only one. For
example, on some large projects you might have your own copy in your own
GitHub account (you’d probably call this origin) and also
the main “upstream” project repository (let’s call this
upstream for the sake of examples). You would pull from
upstream from time to time to get the latest updates that
other people have committed.
Remember that the name you give to a remote only exists locally. It’s
an alias that you choose - whether origin, or
upstream, or fred - and not something
intrinstic to the remote repository.
The git remote family of commands is used to set up and
alter the remotes associated with a repository. Here are some of the
most useful ones:
-
git remote -vlists all the remotes that are configured (we already used this in the last episode) -
git remote add [name] [url]is used to add a new remote -
git remote remove [name]removes a remote. Note that it doesn’t affect the remote repository at all - it just removes the link to it from the local repo. -
git remote set-url [name] [newurl]changes the URL that is associated with the remote. This is useful if it has moved, e.g. to a different GitHub account, or from GitHub to a different hosting service. Or, if we made a typo when adding it! -
git remote rename [oldname] [newname]changes the local alias by which a remote is known - its name. For example, one could use this to changeupstreamtofred.
To download the Collaborator’s changes from GitHub, the Owner now enters:
OUTPUT
remote: Enumerating objects: 4, done.
remote: Counting objects: 100% (4/4), done.
remote: Compressing objects: 100% (2/2), done.
remote: Total 3 (delta 0), reused 3 (delta 0), pack-reused 0
Unpacking objects: 100% (3/3), done.
From https://github.com/vlad/planets
* branch main -> FETCH_HEAD
9272da5..29aba7c main -> origin/main
Updating 9272da5..29aba7c
Fast-forward
pluto.txt | 1 +
1 file changed, 1 insertion(+)
create mode 100644 pluto.txtNow the three repositories (Owner’s local, Collaborator’s local, and Owner’s on GitHub) are back in sync.
A Basic Collaborative Workflow
In practice, it is good to be sure that you have an updated version
of the repository you are collaborating on, so you should
git pull before making our changes. The basic collaborative
workflow would be:
- update your local repo with
git pull origin main, - make your changes and stage them with
git add, - commit your changes with
git commit -m, and - upload the changes to GitHub with
git push origin main
It is better to make many commits with smaller changes rather than of one commit with massive changes: small commits are easier to read and review.
Switch Roles and Repeat
Switch roles and repeat the whole process.
Review Changes
The Owner pushed commits to the repository without giving any information to the Collaborator. How can the Collaborator find out what has changed with command line? And on GitHub?
On the command line, the Collaborator can use
git fetch origin main to get the remote changes into the
local repository, but without merging them. Then by running
git diff main origin/main the Collaborator will see the
changes output in the terminal.
On GitHub, the Collaborator can go to the repository and click on “commits” to view the most recent commits pushed to the repository.
Version History, Backup, and Version Control
Some backup software can keep a history of the versions of your files. They also allows you to recover specific versions. How is this functionality different from version control? What are some of the benefits of using version control, Git and GitHub?
Key Points
-
git clonecopies a remote repository to create a local repository with a remote calledoriginautomatically set up.
Content from Conflicts
Last updated on 2024-12-04 | Edit this page
Estimated time: 15 minutes
Overview
Questions
- What do I do when my changes conflict with someone else’s?
Objectives
- Explain what conflicts are and when they can occur.
- Resolve conflicts resulting from a merge.
As soon as people can work in parallel, they’ll likely step on each other’s toes. This will even happen with a single person: if we are working on a piece of software on both our laptop and a server in the lab, we could make different changes to each copy. Version control helps us manage these conflicts by giving us tools to resolve overlapping changes.
To see how we can resolve conflicts, we must first create one. The
file mars.txt currently looks like this in both partners’
copies of our planets repository:
OUTPUT
Cold and dry, but everything is my favorite color
The two moons may be a problem for Wolfman
But the Mummy will appreciate the lack of humidityLet’s add a line to the collaborator’s copy only:
OUTPUT
Cold and dry, but everything is my favorite color
The two moons may be a problem for Wolfman
But the Mummy will appreciate the lack of humidity
This line added to Wolfman's copyand then push the change to GitHub:
OUTPUT
[main 5ae9631] Add a line in our home copy
1 file changed, 1 insertion(+)OUTPUT
Enumerating objects: 5, done.
Counting objects: 100% (5/5), done.
Delta compression using up to 8 threads
Compressing objects: 100% (3/3), done.
Writing objects: 100% (3/3), 331 bytes | 331.00 KiB/s, done.
Total 3 (delta 2), reused 0 (delta 0)
remote: Resolving deltas: 100% (2/2), completed with 2 local objects.
To https://github.com/vlad/planets.git
29aba7c..dabb4c8 main -> mainNow let’s have the owner make a different change to their copy without updating from GitHub:
OUTPUT
Cold and dry, but everything is my favorite color
The two moons may be a problem for Wolfman
But the Mummy will appreciate the lack of humidity
We added a different line in the other copyWe can commit the change locally:
OUTPUT
[main 07ebc69] Add a line in my copy
1 file changed, 1 insertion(+)but Git won’t let us push it to GitHub:
OUTPUT
To https://github.com/vlad/planets.git
! [rejected] main -> main (fetch first)
error: failed to push some refs to 'https://github.com/vlad/planets.git'
hint: Updates were rejected because the remote contains work that you do
hint: not have locally. This is usually caused by another repository pushing
hint: to the same ref. You may want to first integrate the remote changes
hint: (e.g., 'git pull ...') before pushing again.
hint: See the 'Note about fast-forwards' in 'git push --help' for details.
Git rejects the push because it detects that the remote repository has new updates that have not been incorporated into the local branch. What we have to do is pull the changes from GitHub, merge them into the copy we’re currently working in, and then push that. Let’s start by pulling:
OUTPUT
remote: Enumerating objects: 5, done.
remote: Counting objects: 100% (5/5), done.
remote: Compressing objects: 100% (1/1), done.
remote: Total 3 (delta 2), reused 3 (delta 2), pack-reused 0
Unpacking objects: 100% (3/3), done.
From https://github.com/vlad/planets
* branch main -> FETCH_HEAD
29aba7c..dabb4c8 main -> origin/main
Auto-merging mars.txt
CONFLICT (content): Merge conflict in mars.txt
Automatic merge failed; fix conflicts and then commit the result.The git pull command updates the local repository to
include those changes already included in the remote repository. After
the changes from remote branch have been fetched, Git detects that
changes made to the local copy overlap with those made to the remote
repository, and therefore refuses to merge the two versions to stop us
from trampling on our previous work. The conflict is marked in in the
affected file:
OUTPUT
Cold and dry, but everything is my favorite color
The two moons may be a problem for Wolfman
But the Mummy will appreciate the lack of humidity
<<<<<<< HEAD
We added a different line in the other copy
=======
This line added to Wolfman's copy
>>>>>>> dabb4c8c450e8475aee9b14b4383acc99f42af1dOur change is preceded by
<<<<<<< HEAD. Git has then inserted
======= as a separator between the conflicting changes and
marked the end of the content downloaded from GitHub with
>>>>>>>. (The string of letters and
digits after that marker identifies the commit we’ve just
downloaded.)
It is now up to us to edit this file to remove these markers and reconcile the changes. We can do anything we want: keep the change made in the local repository, keep the change made in the remote repository, write something new to replace both, or get rid of the change entirely. Let’s replace both so that the file looks like this:
OUTPUT
Cold and dry, but everything is my favorite color
The two moons may be a problem for Wolfman
But the Mummy will appreciate the lack of humidity
We removed the conflict on this lineTo finish merging, we add mars.txt to the changes being
made by the merge and then commit:
OUTPUT
On branch main
All conflicts fixed but you are still merging.
(use "git commit" to conclude merge)
Changes to be committed:
modified: mars.txt
OUTPUT
[main 2abf2b1] Merge changes from GitHubNow we can push our changes to GitHub:
OUTPUT
Enumerating objects: 10, done.
Counting objects: 100% (10/10), done.
Delta compression using up to 8 threads
Compressing objects: 100% (6/6), done.
Writing objects: 100% (6/6), 645 bytes | 645.00 KiB/s, done.
Total 6 (delta 4), reused 0 (delta 0)
remote: Resolving deltas: 100% (4/4), completed with 2 local objects.
To https://github.com/vlad/planets.git
dabb4c8..2abf2b1 main -> mainGit keeps track of what we’ve merged with what, so we don’t have to fix things by hand again when the collaborator who made the first change pulls again:
OUTPUT
remote: Enumerating objects: 10, done.
remote: Counting objects: 100% (10/10), done.
remote: Compressing objects: 100% (2/2), done.
remote: Total 6 (delta 4), reused 6 (delta 4), pack-reused 0
Unpacking objects: 100% (6/6), done.
From https://github.com/vlad/planets
* branch main -> FETCH_HEAD
dabb4c8..2abf2b1 main -> origin/main
Updating dabb4c8..2abf2b1
Fast-forward
mars.txt | 2 +-
1 file changed, 1 insertion(+), 1 deletion(-)We get the merged file:
OUTPUT
Cold and dry, but everything is my favorite color
The two moons may be a problem for Wolfman
But the Mummy will appreciate the lack of humidity
We removed the conflict on this lineWe don’t need to merge again because Git knows someone has already done that.
Git’s ability to resolve conflicts is very useful, but conflict resolution costs time and effort, and can introduce errors if conflicts are not resolved correctly. If you find yourself resolving a lot of conflicts in a project, consider these technical approaches to reducing them:
- Pull from upstream more frequently, especially before starting new work
- Use topic branches to segregate work, merging to main when complete
- Make smaller more atomic commits
- Push your work when it is done and encourage your team to do the same to reduce work in progress and, by extension, the chance of having conflicts
- Where logically appropriate, break large files into smaller ones so that it is less likely that two authors will alter the same file simultaneously
Conflicts can also be minimized with project management strategies:
- Clarify who is responsible for what areas with your collaborators
- Discuss what order tasks should be carried out in with your collaborators so that tasks expected to change the same lines won’t be worked on simultaneously
- If the conflicts are stylistic churn (e.g. tabs vs. spaces),
establish a project convention that is governing and use code style
tools (e.g.
htmltidy,perltidy,rubocop, etc.) to enforce, if necessary
Solving Conflicts that You Create
Clone the repository created by your instructor. Add a new file to it, and modify an existing file (your instructor will tell you which one). When asked by your instructor, pull her changes from the repository to create a conflict, then resolve it.
Conflicts on Non-textual files
What does Git do when there is a conflict in an image or some other non-textual file that is stored in version control?
Let’s try it. Suppose Dracula takes a picture of Martian surface and
calls it mars.jpg.
If you do not have an image file of Mars available, you can create a dummy binary file like this:
OUTPUT
-rw-r--r-- 1 vlad 57095 1.0K Mar 8 20:24 mars.jpgls shows us that this created a 1-kilobyte file. It is
full of random bytes read from the special file,
/dev/urandom.
Now, suppose Dracula adds mars.jpg to his
repository:
OUTPUT
[main 8e4115c] Add picture of Martian surface
1 file changed, 0 insertions(+), 0 deletions(-)
create mode 100644 mars.jpgSuppose that Wolfman has added a similar picture in the meantime. His
is a picture of the Martian sky, but it is also called
mars.jpg. When Dracula tries to push, he gets a familiar
message:
OUTPUT
To https://github.com/vlad/planets.git
! [rejected] main -> main (fetch first)
error: failed to push some refs to 'https://github.com/vlad/planets.git'
hint: Updates were rejected because the remote contains work that you do
hint: not have locally. This is usually caused by another repository pushing
hint: to the same ref. You may want to first integrate the remote changes
hint: (e.g., 'git pull ...') before pushing again.
hint: See the 'Note about fast-forwards' in 'git push --help' for details.We’ve learned that we must pull first and resolve any conflicts:
When there is a conflict on an image or other binary file, git prints a message like this:
OUTPUT
$ git pull origin main
remote: Counting objects: 3, done.
remote: Compressing objects: 100% (3/3), done.
remote: Total 3 (delta 0), reused 0 (delta 0)
Unpacking objects: 100% (3/3), done.
From https://github.com/vlad/planets.git
* branch main -> FETCH_HEAD
6a67967..439dc8c main -> origin/main
warning: Cannot merge binary files: mars.jpg (HEAD vs. 439dc8c08869c342438f6dc4a2b615b05b93c76e)
Auto-merging mars.jpg
CONFLICT (add/add): Merge conflict in mars.jpg
Automatic merge failed; fix conflicts and then commit the result.The conflict message here is mostly the same as it was for
mars.txt, but there is one key additional line:
OUTPUT
warning: Cannot merge binary files: mars.jpg (HEAD vs. 439dc8c08869c342438f6dc4a2b615b05b93c76e)Git cannot automatically insert conflict markers into an image as it does for text files. So, instead of editing the image file, we must check out the version we want to keep. Then we can add and commit this version.
On the key line above, Git has conveniently given us commit
identifiers for the two versions of mars.jpg. Our version
is HEAD, and Wolfman’s version is 439dc8c0....
If we want to use our version, we can use git checkout:
BASH
$ git checkout HEAD mars.jpg
$ git add mars.jpg
$ git commit -m "Use image of surface instead of sky"OUTPUT
[main 21032c3] Use image of surface instead of skyIf instead we want to use Wolfman’s version, we can use
git checkout with Wolfman’s commit identifier,
439dc8c0:
BASH
$ git checkout 439dc8c0 mars.jpg
$ git add mars.jpg
$ git commit -m "Use image of sky instead of surface"OUTPUT
[main da21b34] Use image of sky instead of surfaceWe can also keep both images. The catch is that we cannot keep them under the same name. But, we can check out each version in succession and rename it, then add the renamed versions. First, check out each image and rename it:
BASH
$ git checkout HEAD mars.jpg
$ git mv mars.jpg mars-surface.jpg
$ git checkout 439dc8c0 mars.jpg
$ mv mars.jpg mars-sky.jpgThen, remove the old mars.jpg and add the two new
files:
BASH
$ git rm mars.jpg
$ git add mars-surface.jpg
$ git add mars-sky.jpg
$ git commit -m "Use two images: surface and sky"OUTPUT
[main 94ae08c] Use two images: surface and sky
2 files changed, 0 insertions(+), 0 deletions(-)
create mode 100644 mars-sky.jpg
rename mars.jpg => mars-surface.jpg (100%)Now both images of Mars are checked into the repository, and
mars.jpg no longer exists.
A Typical Work Session
You sit down at your computer to work on a shared project that is tracked in a remote Git repository. During your work session, you take the following actions, but not in this order:
-
Make changes by appending the number
100to a text filenumbers.txt - Update remote repository to match the local repository
- Celebrate your success with some fancy beverage(s)
- Update local repository to match the remote repository
- Stage changes to be committed
- Commit changes to the local repository
In what order should you perform these actions to minimize the chances of conflicts? Put the commands above in order in the action column of the table below. When you have the order right, see if you can write the corresponding commands in the command column. A few steps are populated to get you started.
| order | action . . . . . . . . . . | command . . . . . . . . . . |
|---|---|---|
| 1 | ||
| 2 | echo 100 >> numbers.txt |
|
| 3 | ||
| 4 | ||
| 5 | ||
| 6 | Celebrate! |
| order | action . . . . . . | command . . . . . . . . . . . . . . . . . . . |
|---|---|---|
| 1 | Update local | git pull origin main |
| 2 | Make changes | echo 100 >> numbers.txt |
| 3 | Stage changes | git add numbers.txt |
| 4 | Commit changes | git commit -m "Add 100 to numbers.txt" |
| 5 | Update remote | git push origin main |
| 6 | Celebrate! |
Key Points
- Conflicts occur when two or more people change the same lines of the same file.
- The version control system does not allow people to overwrite each other’s changes blindly, but highlights conflicts so that they can be resolved.
Content from Data Frame Manipulation with dplyr
Last updated on 2024-12-04 | Edit this page
Estimated time: 55 minutes
Overview
Questions
- How can I manipulate data frames without repeating myself?
Objectives
- To be able to use the six main data frame manipulation ‘verbs’ with
pipes in
dplyr. - To understand how
group_by()andsummarize()can be combined to summarize datasets. - Be able to analyze a subset of data using logical filtering.
Manipulation of data frames means many things to many researchers: we often select certain observations (rows) or variables (columns), we often group the data by a certain variable(s), or we even calculate summary statistics. We can do these operations using the normal base R operations:
R
mean(gapminder$gdpPercap[gapminder$continent == "Africa"])
OUTPUT
[1] 2193.755R
mean(gapminder$gdpPercap[gapminder$continent == "Americas"])
OUTPUT
[1] 7136.11R
mean(gapminder$gdpPercap[gapminder$continent == "Asia"])
OUTPUT
[1] 7902.15But this isn’t very nice because there is a fair bit of repetition. Repeating yourself will cost you time, both now and later, and potentially introduce some nasty bugs.
The dplyr package
Luckily, the dplyr
package provides a number of very useful functions for manipulating data
frames in a way that will reduce the above repetition, reduce the
probability of making errors, and probably even save you some typing. As
an added bonus, you might even find the dplyr grammar
easier to read.
Tip: Tidyverse
dplyr package belongs to a broader family of opinionated
R packages designed for data science called the “Tidyverse”. These
packages are specifically designed to work harmoniously together. Some
of these packages will be covered along this course, but you can find
more complete information here: https://www.tidyverse.org/.
Here we’re going to cover 5 of the most commonly used functions as
well as using pipes (%>%) to combine them.
select()filter()group_by()summarize()mutate()
If you have have not installed this package earlier, please do so:
R
install.packages('dplyr')
Now let’s load the package:
R
library("dplyr")
Using select()
If, for example, we wanted to move forward with only a few of the
variables in our data frame we could use the select()
function. This will keep only the variables you select.
R
year_country_gdp <- select(gapminder, year, country, gdpPercap)
If we want to remove one column only from the gapminder
data, for example, removing the continent column.
R
smaller_gapminder_data <- select(gapminder, -continent)
If we open up year_country_gdp we’ll see that it only
contains the year, country and gdpPercap. Above we used ‘normal’
grammar, but the strengths of dplyr lie in combining
several functions using pipes. Since the pipes grammar is unlike
anything we’ve seen in R before, let’s repeat what we’ve done above
using pipes.
R
year_country_gdp <- gapminder %>% select(year, country, gdpPercap)
To help you understand why we wrote that in that way, let’s walk
through it step by step. First we summon the gapminder data frame and
pass it on, using the pipe symbol %>%, to the next step,
which is the select() function. In this case we don’t
specify which data object we use in the select() function
since in gets that from the previous pipe. Fun Fact:
There is a good chance you have encountered pipes before in the shell.
In R, a pipe symbol is %>% while in the shell it is
| but the concept is the same!
Tip: Renaming data frame columns in dplyr
In Chapter 4 we covered how you can rename columns with base R by
assigning a value to the output of the names() function.
Just like select, this is a bit cumbersome, but thankfully dplyr has a
rename() function.
Within a pipeline, the syntax is
rename(new_name = old_name). For example, we may want to
rename the gdpPercap column name from our select()
statement above.
R
tidy_gdp <- year_country_gdp %>% rename(gdp_per_capita = gdpPercap)
head(tidy_gdp)
OUTPUT
year country gdp_per_capita
1 1952 Afghanistan 779.4453
2 1957 Afghanistan 820.8530
3 1962 Afghanistan 853.1007
4 1967 Afghanistan 836.1971
5 1972 Afghanistan 739.9811
6 1977 Afghanistan 786.1134Using filter()
If we now want to move forward with the above, but only with European
countries, we can combine select and
filter
R
year_country_gdp_euro <- gapminder %>%
filter(continent == "Europe") %>%
select(year, country, gdpPercap)
If we now want to show life expectancy of European countries but only for a specific year (e.g., 2007), we can do as below.
R
europe_lifeExp_2007 <- gapminder %>%
filter(continent == "Europe", year == 2007) %>%
select(country, lifeExp)
Challenge 1
Write a single command (which can span multiple lines and includes
pipes) that will produce a data frame that has the African values for
lifeExp, country and year, but
not for other Continents. How many rows does your data frame have and
why?
R
year_country_lifeExp_Africa <- gapminder %>%
filter(continent == "Africa") %>%
select(year, country, lifeExp)
As with last time, first we pass the gapminder data frame to the
filter() function, then we pass the filtered version of the
gapminder data frame to the select() function.
Note: The order of operations is very important in this
case. If we used ‘select’ first, filter would not be able to find the
variable continent since we would have removed it in the previous
step.
Using group_by()
Now, we were supposed to be reducing the error prone repetitiveness
of what can be done with base R, but up to now we haven’t done that
since we would have to repeat the above for each continent. Instead of
filter(), which will only pass observations that meet your
criteria (in the above: continent=="Europe"), we can use
group_by(), which will essentially use every unique
criteria that you could have used in filter.
R
str(gapminder)
OUTPUT
'data.frame': 1704 obs. of 6 variables:
$ country : chr "Afghanistan" "Afghanistan" "Afghanistan" "Afghanistan" ...
$ year : int 1952 1957 1962 1967 1972 1977 1982 1987 1992 1997 ...
$ pop : num 8425333 9240934 10267083 11537966 13079460 ...
$ continent: chr "Asia" "Asia" "Asia" "Asia" ...
$ lifeExp : num 28.8 30.3 32 34 36.1 ...
$ gdpPercap: num 779 821 853 836 740 ...R
str(gapminder %>% group_by(continent))
OUTPUT
gropd_df [1,704 × 6] (S3: grouped_df/tbl_df/tbl/data.frame)
$ country : chr [1:1704] "Afghanistan" "Afghanistan" "Afghanistan" "Afghanistan" ...
$ year : int [1:1704] 1952 1957 1962 1967 1972 1977 1982 1987 1992 1997 ...
$ pop : num [1:1704] 8425333 9240934 10267083 11537966 13079460 ...
$ continent: chr [1:1704] "Asia" "Asia" "Asia" "Asia" ...
$ lifeExp : num [1:1704] 28.8 30.3 32 34 36.1 ...
$ gdpPercap: num [1:1704] 779 821 853 836 740 ...
- attr(*, "groups")= tibble [5 × 2] (S3: tbl_df/tbl/data.frame)
..$ continent: chr [1:5] "Africa" "Americas" "Asia" "Europe" ...
..$ .rows : list<int> [1:5]
.. ..$ : int [1:624] 25 26 27 28 29 30 31 32 33 34 ...
.. ..$ : int [1:300] 49 50 51 52 53 54 55 56 57 58 ...
.. ..$ : int [1:396] 1 2 3 4 5 6 7 8 9 10 ...
.. ..$ : int [1:360] 13 14 15 16 17 18 19 20 21 22 ...
.. ..$ : int [1:24] 61 62 63 64 65 66 67 68 69 70 ...
.. ..@ ptype: int(0)
..- attr(*, ".drop")= logi TRUEYou will notice that the structure of the data frame where we used
group_by() (grouped_df) is not the same as the
original gapminder (data.frame). A
grouped_df can be thought of as a list where
each item in the listis a data.frame which
contains only the rows that correspond to the a particular value
continent (at least in the example above).
Using summarize()
The above was a bit on the uneventful side but
group_by() is much more exciting in conjunction with
summarize(). This will allow us to create new variable(s)
by using functions that repeat for each of the continent-specific data
frames. That is to say, using the group_by() function, we
split our original data frame into multiple pieces, then we can run
functions (e.g. mean() or sd()) within
summarize().
R
gdp_bycontinents <- gapminder %>%
group_by(continent) %>%
summarize(mean_gdpPercap = mean(gdpPercap))
R
continent mean_gdpPercap
<fctr> <dbl>
1 Africa 2193.755
2 Americas 7136.110
3 Asia 7902.150
4 Europe 14469.476
5 Oceania 18621.609That allowed us to calculate the mean gdpPercap for each continent, but it gets even better.
Challenge 2
Calculate the average life expectancy per country. Which has the longest average life expectancy and which has the shortest average life expectancy?
R
lifeExp_bycountry <- gapminder %>%
group_by(country) %>%
summarize(mean_lifeExp = mean(lifeExp))
lifeExp_bycountry %>%
filter(mean_lifeExp == min(mean_lifeExp) | mean_lifeExp == max(mean_lifeExp))
OUTPUT
# A tibble: 2 × 2
country mean_lifeExp
<chr> <dbl>
1 Iceland 76.5
2 Sierra Leone 36.8Another way to do this is to use the dplyr function
arrange(), which arranges the rows in a data frame
according to the order of one or more variables from the data frame. It
has similar syntax to other functions from the dplyr
package. You can use desc() inside arrange()
to sort in descending order.
R
lifeExp_bycountry %>%
arrange(mean_lifeExp) %>%
head(1)
OUTPUT
# A tibble: 1 × 2
country mean_lifeExp
<chr> <dbl>
1 Sierra Leone 36.8R
lifeExp_bycountry %>%
arrange(desc(mean_lifeExp)) %>%
head(1)
OUTPUT
# A tibble: 1 × 2
country mean_lifeExp
<chr> <dbl>
1 Iceland 76.5Alphabetical order works too
R
lifeExp_bycountry %>%
arrange(desc(country)) %>%
head(1)
OUTPUT
# A tibble: 1 × 2
country mean_lifeExp
<chr> <dbl>
1 Zimbabwe 52.7The function group_by() allows us to group by multiple
variables. Let’s group by year and
continent.
R
gdp_bycontinents_byyear <- gapminder %>%
group_by(continent, year) %>%
summarize(mean_gdpPercap = mean(gdpPercap))
OUTPUT
`summarise()` has grouped output by 'continent'. You can override using the
`.groups` argument.That is already quite powerful, but it gets even better! You’re not
limited to defining 1 new variable in summarize().
R
gdp_pop_bycontinents_byyear <- gapminder %>%
group_by(continent, year) %>%
summarize(mean_gdpPercap = mean(gdpPercap),
sd_gdpPercap = sd(gdpPercap),
mean_pop = mean(pop),
sd_pop = sd(pop))
OUTPUT
`summarise()` has grouped output by 'continent'. You can override using the
`.groups` argument.count() and n()
A very common operation is to count the number of observations for
each group. The dplyr package comes with two related
functions that help with this.
For instance, if we wanted to check the number of countries included
in the dataset for the year 2002, we can use the count()
function. It takes the name of one or more columns that contain the
groups we are interested in, and we can optionally sort the results in
descending order by adding sort=TRUE:
R
gapminder %>%
filter(year == 2002) %>%
count(continent, sort = TRUE)
OUTPUT
continent n
1 Africa 52
2 Asia 33
3 Europe 30
4 Americas 25
5 Oceania 2If we need to use the number of observations in calculations, the
n() function is useful. It will return the total number of
observations in the current group rather than counting the number of
observations in each group within a specific column. For instance, if we
wanted to get the standard error of the life expectency per
continent:
R
gapminder %>%
group_by(continent) %>%
summarize(se_le = sd(lifeExp)/sqrt(n()))
OUTPUT
# A tibble: 5 × 2
continent se_le
<chr> <dbl>
1 Africa 0.366
2 Americas 0.540
3 Asia 0.596
4 Europe 0.286
5 Oceania 0.775You can also chain together several summary operations; in this case
calculating the minimum, maximum,
mean and se of each continent’s per-country
life-expectancy:
R
gapminder %>%
group_by(continent) %>%
summarize(
mean_le = mean(lifeExp),
min_le = min(lifeExp),
max_le = max(lifeExp),
se_le = sd(lifeExp)/sqrt(n()))
OUTPUT
# A tibble: 5 × 5
continent mean_le min_le max_le se_le
<chr> <dbl> <dbl> <dbl> <dbl>
1 Africa 48.9 23.6 76.4 0.366
2 Americas 64.7 37.6 80.7 0.540
3 Asia 60.1 28.8 82.6 0.596
4 Europe 71.9 43.6 81.8 0.286
5 Oceania 74.3 69.1 81.2 0.775Using mutate()
We can also create new variables prior to (or even after) summarizing
information using mutate().
R
gdp_pop_bycontinents_byyear <- gapminder %>%
mutate(gdp_billion = gdpPercap*pop/10^9) %>%
group_by(continent,year) %>%
summarize(mean_gdpPercap = mean(gdpPercap),
sd_gdpPercap = sd(gdpPercap),
mean_pop = mean(pop),
sd_pop = sd(pop),
mean_gdp_billion = mean(gdp_billion),
sd_gdp_billion = sd(gdp_billion))
OUTPUT
`summarise()` has grouped output by 'continent'. You can override using the
`.groups` argument.Connect mutate with logical filtering: ifelse
When creating new variables, we can hook this with a logical
condition. A simple combination of mutate() and
ifelse() facilitates filtering right where it is needed: in
the moment of creating something new. This easy-to-read statement is a
fast and powerful way of discarding certain data (even though the
overall dimension of the data frame will not change) or for updating
values depending on this given condition.
R
## keeping all data but "filtering" after a certain condition
# calculate GDP only for people with a life expectation above 25
gdp_pop_bycontinents_byyear_above25 <- gapminder %>%
mutate(gdp_billion = ifelse(lifeExp > 25, gdpPercap * pop / 10^9, NA)) %>%
group_by(continent, year) %>%
summarize(mean_gdpPercap = mean(gdpPercap),
sd_gdpPercap = sd(gdpPercap),
mean_pop = mean(pop),
sd_pop = sd(pop),
mean_gdp_billion = mean(gdp_billion),
sd_gdp_billion = sd(gdp_billion))
OUTPUT
`summarise()` has grouped output by 'continent'. You can override using the
`.groups` argument.R
## updating only if certain condition is fullfilled
# for life expectations above 40 years, the gpd to be expected in the future is scaled
gdp_future_bycontinents_byyear_high_lifeExp <- gapminder %>%
mutate(gdp_futureExpectation = ifelse(lifeExp > 40, gdpPercap * 1.5, gdpPercap)) %>%
group_by(continent, year) %>%
summarize(mean_gdpPercap = mean(gdpPercap),
mean_gdpPercap_expected = mean(gdp_futureExpectation))
OUTPUT
`summarise()` has grouped output by 'continent'. You can override using the
`.groups` argument.Combining dplyr and ggplot2
First install and load ggplot2:
R
install.packages('ggplot2')
R
library("ggplot2")
In the plotting lesson we looked at how to make a multi-panel figure
by adding a layer of facet panels using ggplot2. Here is
the code we used (with some extra comments):
R
# Filter countries located in the Americas
americas <- gapminder[gapminder$continent == "Americas", ]
# Make the plot
ggplot(data = americas, mapping = aes(x = year, y = lifeExp)) +
geom_line() +
facet_wrap( ~ country) +
theme(axis.text.x = element_text(angle = 45))
This code makes the right plot but it also creates an intermediate
variable (americas) that we might not have any other uses
for. Just as we used %>% to pipe data along a chain of
dplyr functions we can use it to pass data to
ggplot(). Because %>% replaces the first
argument in a function we don’t need to specify the data =
argument in the ggplot() function. By combining
dplyr and ggplot2 functions we can make the
same figure without creating any new variables or modifying the
data.
R
gapminder %>%
# Filter countries located in the Americas
filter(continent == "Americas") %>%
# Make the plot
ggplot(mapping = aes(x = year, y = lifeExp)) +
geom_line() +
facet_wrap( ~ country) +
theme(axis.text.x = element_text(angle = 45))
More examples of using the function mutate() and the
ggplot2 package.
R
gapminder %>%
# extract first letter of country name into new column
mutate(startsWith = substr(country, 1, 1)) %>%
# only keep countries starting with A or Z
filter(startsWith %in% c("A", "Z")) %>%
# plot lifeExp into facets
ggplot(aes(x = year, y = lifeExp, colour = continent)) +
geom_line() +
facet_wrap(vars(country)) +
theme_minimal()
Advanced Challenge
Calculate the average life expectancy in 2002 of 2 randomly selected
countries for each continent. Then arrange the continent names in
reverse order. Hint: Use the dplyr
functions arrange() and sample_n(), they have
similar syntax to other dplyr functions.
R
lifeExp_2countries_bycontinents <- gapminder %>%
filter(year==2002) %>%
group_by(continent) %>%
sample_n(2) %>%
summarize(mean_lifeExp=mean(lifeExp)) %>%
arrange(desc(mean_lifeExp))
Other great resources
- R for Data Science (online book)
- Data Wrangling Cheat sheet (pdf file)
- Introduction to dplyr (online documentation)
- Data wrangling with R and RStudio (online video)
Key Points
- Use the
dplyrpackage to manipulate data frames. - Use
select()to choose variables from a data frame. - Use
filter()to choose data based on values. - Use
group_by()andsummarize()to work with subsets of data. - Use
mutate()to create new variables.
Content from Data Frame Manipulation with tidyr
Last updated on 2024-12-04 | Edit this page
Estimated time: 45 minutes
Overview
Questions
- How can I change the layout of a data frame?
Objectives
- To understand the concepts of ‘longer’ and ‘wider’ data frame
formats and be able to convert between them with
tidyr.
Researchers often want to reshape their data frames from ‘wide’ to ‘longer’ layouts, or vice-versa. The ‘long’ layout or format is where:
- each column is a variable
- each row is an observation
In the purely ‘long’ (or ‘longest’) format, you usually have 1 column for the observed variable and the other columns are ID variables.
For the ‘wide’ format each row is often a site/subject/patient and
you have multiple observation variables containing the same type of
data. These can be either repeated observations over time, or
observation of multiple variables (or a mix of both). You may find data
input may be simpler or some other applications may prefer the ‘wide’
format. However, many of R‘s functions have been designed
assuming you have ’longer’ formatted data. This tutorial will help you
efficiently transform your data shape regardless of original format.
Long and wide data frame layouts mainly affect readability. For humans, the wide format is often more intuitive since we can often see more of the data on the screen due to its shape. However, the long format is more machine readable and is closer to the formatting of databases. The ID variables in our data frames are similar to the fields in a database and observed variables are like the database values.
Getting started
First install the packages if you haven’t already done so (you probably installed dplyr in the previous lesson):
R
#install.packages("tidyr")
#install.packages("dplyr")
Load the packages
R
library("tidyr")
library("dplyr")
First, lets look at the structure of our original gapminder data frame:
R
str(gapminder)
OUTPUT
'data.frame': 1704 obs. of 6 variables:
$ country : chr "Afghanistan" "Afghanistan" "Afghanistan" "Afghanistan" ...
$ year : int 1952 1957 1962 1967 1972 1977 1982 1987 1992 1997 ...
$ pop : num 8425333 9240934 10267083 11537966 13079460 ...
$ continent: chr "Asia" "Asia" "Asia" "Asia" ...
$ lifeExp : num 28.8 30.3 32 34 36.1 ...
$ gdpPercap: num 779 821 853 836 740 ...Challenge 1
Is gapminder a purely long, purely wide, or some intermediate format?
The original gapminder data.frame is in an intermediate format. It is
not purely long since it had multiple observation variables
(pop,lifeExp,gdpPercap).
Sometimes, as with the gapminder dataset, we have multiple types of
observed data. It is somewhere in between the purely ‘long’ and ‘wide’
data formats. We have 3 “ID variables” (continent,
country, year) and 3 “Observation variables”
(pop,lifeExp,gdpPercap). This
intermediate format can be preferred despite not having ALL observations
in 1 column given that all 3 observation variables have different units.
There are few operations that would need us to make this data frame any
longer (i.e. 4 ID variables and 1 Observation variable).
While using many of the functions in R, which are often vector based,
you usually do not want to do mathematical operations on values with
different units. For example, using the purely long format, a single
mean for all of the values of population, life expectancy, and GDP would
not be meaningful since it would return the mean of values with 3
incompatible units. The solution is that we first manipulate the data
either by grouping (see the lesson on dplyr), or we change
the structure of the data frame. Note: Some plotting
functions in R actually work better in the wide format data.
From wide to long format with pivot_longer()
Until now, we’ve been using the nicely formatted original gapminder dataset, but ‘real’ data (i.e. our own research data) will never be so well organized. Here let’s start with the wide formatted version of the gapminder dataset.
Download the wide version of the gapminder data from this link to a csv file and save it in your data folder.
We’ll load the data file and look at it. Note: we don’t want our
continent and country columns to be factors, so we use the
stringsAsFactors argument for read.csv() to disable
that.
R
gap_wide <- read.csv("data/gapminder_wide.csv", stringsAsFactors = FALSE)
str(gap_wide)
OUTPUT
'data.frame': 142 obs. of 38 variables:
$ continent : chr "Africa" "Africa" "Africa" "Africa" ...
$ country : chr "Algeria" "Angola" "Benin" "Botswana" ...
$ gdpPercap_1952: num 2449 3521 1063 851 543 ...
$ gdpPercap_1957: num 3014 3828 960 918 617 ...
$ gdpPercap_1962: num 2551 4269 949 984 723 ...
$ gdpPercap_1967: num 3247 5523 1036 1215 795 ...
$ gdpPercap_1972: num 4183 5473 1086 2264 855 ...
$ gdpPercap_1977: num 4910 3009 1029 3215 743 ...
$ gdpPercap_1982: num 5745 2757 1278 4551 807 ...
$ gdpPercap_1987: num 5681 2430 1226 6206 912 ...
$ gdpPercap_1992: num 5023 2628 1191 7954 932 ...
$ gdpPercap_1997: num 4797 2277 1233 8647 946 ...
$ gdpPercap_2002: num 5288 2773 1373 11004 1038 ...
$ gdpPercap_2007: num 6223 4797 1441 12570 1217 ...
$ lifeExp_1952 : num 43.1 30 38.2 47.6 32 ...
$ lifeExp_1957 : num 45.7 32 40.4 49.6 34.9 ...
$ lifeExp_1962 : num 48.3 34 42.6 51.5 37.8 ...
$ lifeExp_1967 : num 51.4 36 44.9 53.3 40.7 ...
$ lifeExp_1972 : num 54.5 37.9 47 56 43.6 ...
$ lifeExp_1977 : num 58 39.5 49.2 59.3 46.1 ...
$ lifeExp_1982 : num 61.4 39.9 50.9 61.5 48.1 ...
$ lifeExp_1987 : num 65.8 39.9 52.3 63.6 49.6 ...
$ lifeExp_1992 : num 67.7 40.6 53.9 62.7 50.3 ...
$ lifeExp_1997 : num 69.2 41 54.8 52.6 50.3 ...
$ lifeExp_2002 : num 71 41 54.4 46.6 50.6 ...
$ lifeExp_2007 : num 72.3 42.7 56.7 50.7 52.3 ...
$ pop_1952 : num 9279525 4232095 1738315 442308 4469979 ...
$ pop_1957 : num 10270856 4561361 1925173 474639 4713416 ...
$ pop_1962 : num 11000948 4826015 2151895 512764 4919632 ...
$ pop_1967 : num 12760499 5247469 2427334 553541 5127935 ...
$ pop_1972 : num 14760787 5894858 2761407 619351 5433886 ...
$ pop_1977 : num 17152804 6162675 3168267 781472 5889574 ...
$ pop_1982 : num 20033753 7016384 3641603 970347 6634596 ...
$ pop_1987 : num 23254956 7874230 4243788 1151184 7586551 ...
$ pop_1992 : num 26298373 8735988 4981671 1342614 8878303 ...
$ pop_1997 : num 29072015 9875024 6066080 1536536 10352843 ...
$ pop_2002 : int 31287142 10866106 7026113 1630347 12251209 7021078 15929988 4048013 8835739 614382 ...
$ pop_2007 : int 33333216 12420476 8078314 1639131 14326203 8390505 17696293 4369038 10238807 710960 ...
To change this very wide data frame layout back to our nice,
intermediate (or longer) layout, we will use one of the two available
pivot functions from the tidyr package. To
convert from wide to a longer format, we will use the
pivot_longer() function. pivot_longer() makes
datasets longer by increasing the number of rows and decreasing the
number of columns, or ‘lengthening’ your observation variables into a
single variable.
R
gap_long <- gap_wide %>%
pivot_longer(
cols = c(starts_with('pop'), starts_with('lifeExp'), starts_with('gdpPercap')),
names_to = "obstype_year", values_to = "obs_values"
)
str(gap_long)
OUTPUT
tibble [5,112 × 4] (S3: tbl_df/tbl/data.frame)
$ continent : chr [1:5112] "Africa" "Africa" "Africa" "Africa" ...
$ country : chr [1:5112] "Algeria" "Algeria" "Algeria" "Algeria" ...
$ obstype_year: chr [1:5112] "pop_1952" "pop_1957" "pop_1962" "pop_1967" ...
$ obs_values : num [1:5112] 9279525 10270856 11000948 12760499 14760787 ...Here we have used piping syntax which is similar to what we were doing in the previous lesson with dplyr. In fact, these are compatible and you can use a mix of tidyr and dplyr functions by piping them together.
We first provide to pivot_longer() a vector of column
names that will be pivoted into longer format. We could type out all the
observation variables, but as in the select() function (see
dplyr lesson), we can use the starts_with()
argument to select all variables that start with the desired character
string. pivot_longer() also allows the alternative syntax
of using the - symbol to identify which variables are not
to be pivoted (i.e. ID variables).
The next arguments to pivot_longer() are
names_to for naming the column that will contain the new ID
variable (obstype_year) and values_to for
naming the new amalgamated observation variable
(obs_value). We supply these new column names as
strings.
R
gap_long <- gap_wide %>%
pivot_longer(
cols = c(-continent, -country),
names_to = "obstype_year", values_to = "obs_values"
)
str(gap_long)
OUTPUT
tibble [5,112 × 4] (S3: tbl_df/tbl/data.frame)
$ continent : chr [1:5112] "Africa" "Africa" "Africa" "Africa" ...
$ country : chr [1:5112] "Algeria" "Algeria" "Algeria" "Algeria" ...
$ obstype_year: chr [1:5112] "gdpPercap_1952" "gdpPercap_1957" "gdpPercap_1962" "gdpPercap_1967" ...
$ obs_values : num [1:5112] 2449 3014 2551 3247 4183 ...That may seem trivial with this particular data frame, but sometimes you have 1 ID variable and 40 observation variables with irregular variable names. The flexibility is a huge time saver!
Now obstype_year actually contains 2 pieces of
information, the observation type
(pop,lifeExp, or gdpPercap) and
the year. We can use the separate() function
to split the character strings into multiple variables
R
gap_long <- gap_long %>% separate(obstype_year, into = c('obs_type', 'year'), sep = "_")
gap_long$year <- as.integer(gap_long$year)
Challenge 2
Using gap_long, calculate the mean life expectancy,
population, and gdpPercap for each continent. Hint: use
the group_by() and summarize() functions we
learned in the dplyr lesson
R
gap_long %>% group_by(continent, obs_type) %>%
summarize(means=mean(obs_values))
OUTPUT
`summarise()` has grouped output by 'continent'. You can override using the
`.groups` argument.OUTPUT
# A tibble: 15 × 3
# Groups: continent [5]
continent obs_type means
<chr> <chr> <dbl>
1 Africa gdpPercap 2194.
2 Africa lifeExp 48.9
3 Africa pop 9916003.
4 Americas gdpPercap 7136.
5 Americas lifeExp 64.7
6 Americas pop 24504795.
7 Asia gdpPercap 7902.
8 Asia lifeExp 60.1
9 Asia pop 77038722.
10 Europe gdpPercap 14469.
11 Europe lifeExp 71.9
12 Europe pop 17169765.
13 Oceania gdpPercap 18622.
14 Oceania lifeExp 74.3
15 Oceania pop 8874672. From long to intermediate format with pivot_wider()
It is always good to check work. So, let’s use the second
pivot function, pivot_wider(), to ‘widen’ our
observation variables back out. pivot_wider() is the
opposite of pivot_longer(), making a dataset wider by
increasing the number of columns and decreasing the number of rows. We
can use pivot_wider() to pivot or reshape our
gap_long to the original intermediate format or the widest
format. Let’s start with the intermediate format.
The pivot_wider() function takes names_from
and values_from arguments.
To names_from we supply the column name whose contents
will be pivoted into new output columns in the widened data frame. The
corresponding values will be added from the column named in the
values_from argument.
R
gap_normal <- gap_long %>%
pivot_wider(names_from = obs_type, values_from = obs_values)
dim(gap_normal)
OUTPUT
[1] 1704 6R
dim(gapminder)
OUTPUT
[1] 1704 6R
names(gap_normal)
OUTPUT
[1] "continent" "country" "year" "gdpPercap" "lifeExp" "pop" R
names(gapminder)
OUTPUT
[1] "country" "year" "pop" "continent" "lifeExp" "gdpPercap"Now we’ve got an intermediate data frame gap_normal with
the same dimensions as the original gapminder, but the
order of the variables is different. Let’s fix that before checking if
they are all.equal().
R
gap_normal <- gap_normal[, names(gapminder)]
all.equal(gap_normal, gapminder)
OUTPUT
[1] "Attributes: < Component \"class\": Lengths (3, 1) differ (string compare on first 1) >"
[2] "Attributes: < Component \"class\": 1 string mismatch >"
[3] "Component \"country\": 1704 string mismatches"
[4] "Component \"pop\": Mean relative difference: 1.634504"
[5] "Component \"continent\": 1212 string mismatches"
[6] "Component \"lifeExp\": Mean relative difference: 0.203822"
[7] "Component \"gdpPercap\": Mean relative difference: 1.162302" R
head(gap_normal)
OUTPUT
# A tibble: 6 × 6
country year pop continent lifeExp gdpPercap
<chr> <int> <dbl> <chr> <dbl> <dbl>
1 Algeria 1952 9279525 Africa 43.1 2449.
2 Algeria 1957 10270856 Africa 45.7 3014.
3 Algeria 1962 11000948 Africa 48.3 2551.
4 Algeria 1967 12760499 Africa 51.4 3247.
5 Algeria 1972 14760787 Africa 54.5 4183.
6 Algeria 1977 17152804 Africa 58.0 4910.R
head(gapminder)
OUTPUT
country year pop continent lifeExp gdpPercap
1 Afghanistan 1952 8425333 Asia 28.801 779.4453
2 Afghanistan 1957 9240934 Asia 30.332 820.8530
3 Afghanistan 1962 10267083 Asia 31.997 853.1007
4 Afghanistan 1967 11537966 Asia 34.020 836.1971
5 Afghanistan 1972 13079460 Asia 36.088 739.9811
6 Afghanistan 1977 14880372 Asia 38.438 786.1134We’re almost there, the original was sorted by country,
then year.
R
gap_normal <- gap_normal %>% arrange(country, year)
all.equal(gap_normal, gapminder)
OUTPUT
[1] "Attributes: < Component \"class\": Lengths (3, 1) differ (string compare on first 1) >"
[2] "Attributes: < Component \"class\": 1 string mismatch >" That’s great! We’ve gone from the longest format back to the intermediate and we didn’t introduce any errors in our code.
Now let’s convert the long all the way back to the wide. In the wide
format, we will keep country and continent as ID variables and pivot the
observations across the 3 metrics
(pop,lifeExp,gdpPercap) and time
(year). First we need to create appropriate labels for all
our new variables (time*metric combinations) and we also need to unify
our ID variables to simplify the process of defining
gap_wide.
R
gap_temp <- gap_long %>% unite(var_ID, continent, country, sep = "_")
str(gap_temp)
OUTPUT
tibble [5,112 × 4] (S3: tbl_df/tbl/data.frame)
$ var_ID : chr [1:5112] "Africa_Algeria" "Africa_Algeria" "Africa_Algeria" "Africa_Algeria" ...
$ obs_type : chr [1:5112] "gdpPercap" "gdpPercap" "gdpPercap" "gdpPercap" ...
$ year : int [1:5112] 1952 1957 1962 1967 1972 1977 1982 1987 1992 1997 ...
$ obs_values: num [1:5112] 2449 3014 2551 3247 4183 ...R
gap_temp <- gap_long %>%
unite(ID_var, continent, country, sep = "_") %>%
unite(var_names, obs_type, year, sep = "_")
str(gap_temp)
OUTPUT
tibble [5,112 × 3] (S3: tbl_df/tbl/data.frame)
$ ID_var : chr [1:5112] "Africa_Algeria" "Africa_Algeria" "Africa_Algeria" "Africa_Algeria" ...
$ var_names : chr [1:5112] "gdpPercap_1952" "gdpPercap_1957" "gdpPercap_1962" "gdpPercap_1967" ...
$ obs_values: num [1:5112] 2449 3014 2551 3247 4183 ...Using unite() we now have a single ID variable which is
a combination of continent,country,and we have
defined variable names. We’re now ready to pipe in
pivot_wider()
R
gap_wide_new <- gap_long %>%
unite(ID_var, continent, country, sep = "_") %>%
unite(var_names, obs_type, year, sep = "_") %>%
pivot_wider(names_from = var_names, values_from = obs_values)
str(gap_wide_new)
OUTPUT
tibble [142 × 37] (S3: tbl_df/tbl/data.frame)
$ ID_var : chr [1:142] "Africa_Algeria" "Africa_Angola" "Africa_Benin" "Africa_Botswana" ...
$ gdpPercap_1952: num [1:142] 2449 3521 1063 851 543 ...
$ gdpPercap_1957: num [1:142] 3014 3828 960 918 617 ...
$ gdpPercap_1962: num [1:142] 2551 4269 949 984 723 ...
$ gdpPercap_1967: num [1:142] 3247 5523 1036 1215 795 ...
$ gdpPercap_1972: num [1:142] 4183 5473 1086 2264 855 ...
$ gdpPercap_1977: num [1:142] 4910 3009 1029 3215 743 ...
$ gdpPercap_1982: num [1:142] 5745 2757 1278 4551 807 ...
$ gdpPercap_1987: num [1:142] 5681 2430 1226 6206 912 ...
$ gdpPercap_1992: num [1:142] 5023 2628 1191 7954 932 ...
$ gdpPercap_1997: num [1:142] 4797 2277 1233 8647 946 ...
$ gdpPercap_2002: num [1:142] 5288 2773 1373 11004 1038 ...
$ gdpPercap_2007: num [1:142] 6223 4797 1441 12570 1217 ...
$ lifeExp_1952 : num [1:142] 43.1 30 38.2 47.6 32 ...
$ lifeExp_1957 : num [1:142] 45.7 32 40.4 49.6 34.9 ...
$ lifeExp_1962 : num [1:142] 48.3 34 42.6 51.5 37.8 ...
$ lifeExp_1967 : num [1:142] 51.4 36 44.9 53.3 40.7 ...
$ lifeExp_1972 : num [1:142] 54.5 37.9 47 56 43.6 ...
$ lifeExp_1977 : num [1:142] 58 39.5 49.2 59.3 46.1 ...
$ lifeExp_1982 : num [1:142] 61.4 39.9 50.9 61.5 48.1 ...
$ lifeExp_1987 : num [1:142] 65.8 39.9 52.3 63.6 49.6 ...
$ lifeExp_1992 : num [1:142] 67.7 40.6 53.9 62.7 50.3 ...
$ lifeExp_1997 : num [1:142] 69.2 41 54.8 52.6 50.3 ...
$ lifeExp_2002 : num [1:142] 71 41 54.4 46.6 50.6 ...
$ lifeExp_2007 : num [1:142] 72.3 42.7 56.7 50.7 52.3 ...
$ pop_1952 : num [1:142] 9279525 4232095 1738315 442308 4469979 ...
$ pop_1957 : num [1:142] 10270856 4561361 1925173 474639 4713416 ...
$ pop_1962 : num [1:142] 11000948 4826015 2151895 512764 4919632 ...
$ pop_1967 : num [1:142] 12760499 5247469 2427334 553541 5127935 ...
$ pop_1972 : num [1:142] 14760787 5894858 2761407 619351 5433886 ...
$ pop_1977 : num [1:142] 17152804 6162675 3168267 781472 5889574 ...
$ pop_1982 : num [1:142] 20033753 7016384 3641603 970347 6634596 ...
$ pop_1987 : num [1:142] 23254956 7874230 4243788 1151184 7586551 ...
$ pop_1992 : num [1:142] 26298373 8735988 4981671 1342614 8878303 ...
$ pop_1997 : num [1:142] 29072015 9875024 6066080 1536536 10352843 ...
$ pop_2002 : num [1:142] 31287142 10866106 7026113 1630347 12251209 ...
$ pop_2007 : num [1:142] 33333216 12420476 8078314 1639131 14326203 ...Challenge 3
Take this 1 step further and create a
gap_ludicrously_wide format data by pivoting over
countries, year and the 3 metrics? Hint this new data
frame should only have 5 rows.
R
gap_ludicrously_wide <- gap_long %>%
unite(var_names, obs_type, year, country, sep = "_") %>%
pivot_wider(names_from = var_names, values_from = obs_values)
Now we have a great ‘wide’ format data frame, but the
ID_var could be more usable, let’s separate it into 2
variables with separate()
R
gap_wide_betterID <- separate(gap_wide_new, ID_var, c("continent", "country"), sep="_")
gap_wide_betterID <- gap_long %>%
unite(ID_var, continent, country, sep = "_") %>%
unite(var_names, obs_type, year, sep = "_") %>%
pivot_wider(names_from = var_names, values_from = obs_values) %>%
separate(ID_var, c("continent","country"), sep = "_")
str(gap_wide_betterID)
OUTPUT
tibble [142 × 38] (S3: tbl_df/tbl/data.frame)
$ continent : chr [1:142] "Africa" "Africa" "Africa" "Africa" ...
$ country : chr [1:142] "Algeria" "Angola" "Benin" "Botswana" ...
$ gdpPercap_1952: num [1:142] 2449 3521 1063 851 543 ...
$ gdpPercap_1957: num [1:142] 3014 3828 960 918 617 ...
$ gdpPercap_1962: num [1:142] 2551 4269 949 984 723 ...
$ gdpPercap_1967: num [1:142] 3247 5523 1036 1215 795 ...
$ gdpPercap_1972: num [1:142] 4183 5473 1086 2264 855 ...
$ gdpPercap_1977: num [1:142] 4910 3009 1029 3215 743 ...
$ gdpPercap_1982: num [1:142] 5745 2757 1278 4551 807 ...
$ gdpPercap_1987: num [1:142] 5681 2430 1226 6206 912 ...
$ gdpPercap_1992: num [1:142] 5023 2628 1191 7954 932 ...
$ gdpPercap_1997: num [1:142] 4797 2277 1233 8647 946 ...
$ gdpPercap_2002: num [1:142] 5288 2773 1373 11004 1038 ...
$ gdpPercap_2007: num [1:142] 6223 4797 1441 12570 1217 ...
$ lifeExp_1952 : num [1:142] 43.1 30 38.2 47.6 32 ...
$ lifeExp_1957 : num [1:142] 45.7 32 40.4 49.6 34.9 ...
$ lifeExp_1962 : num [1:142] 48.3 34 42.6 51.5 37.8 ...
$ lifeExp_1967 : num [1:142] 51.4 36 44.9 53.3 40.7 ...
$ lifeExp_1972 : num [1:142] 54.5 37.9 47 56 43.6 ...
$ lifeExp_1977 : num [1:142] 58 39.5 49.2 59.3 46.1 ...
$ lifeExp_1982 : num [1:142] 61.4 39.9 50.9 61.5 48.1 ...
$ lifeExp_1987 : num [1:142] 65.8 39.9 52.3 63.6 49.6 ...
$ lifeExp_1992 : num [1:142] 67.7 40.6 53.9 62.7 50.3 ...
$ lifeExp_1997 : num [1:142] 69.2 41 54.8 52.6 50.3 ...
$ lifeExp_2002 : num [1:142] 71 41 54.4 46.6 50.6 ...
$ lifeExp_2007 : num [1:142] 72.3 42.7 56.7 50.7 52.3 ...
$ pop_1952 : num [1:142] 9279525 4232095 1738315 442308 4469979 ...
$ pop_1957 : num [1:142] 10270856 4561361 1925173 474639 4713416 ...
$ pop_1962 : num [1:142] 11000948 4826015 2151895 512764 4919632 ...
$ pop_1967 : num [1:142] 12760499 5247469 2427334 553541 5127935 ...
$ pop_1972 : num [1:142] 14760787 5894858 2761407 619351 5433886 ...
$ pop_1977 : num [1:142] 17152804 6162675 3168267 781472 5889574 ...
$ pop_1982 : num [1:142] 20033753 7016384 3641603 970347 6634596 ...
$ pop_1987 : num [1:142] 23254956 7874230 4243788 1151184 7586551 ...
$ pop_1992 : num [1:142] 26298373 8735988 4981671 1342614 8878303 ...
$ pop_1997 : num [1:142] 29072015 9875024 6066080 1536536 10352843 ...
$ pop_2002 : num [1:142] 31287142 10866106 7026113 1630347 12251209 ...
$ pop_2007 : num [1:142] 33333216 12420476 8078314 1639131 14326203 ...R
all.equal(gap_wide, gap_wide_betterID)
OUTPUT
[1] "Attributes: < Component \"class\": Lengths (1, 3) differ (string compare on first 1) >"
[2] "Attributes: < Component \"class\": 1 string mismatch >" There and back again!
Other great resources
- R for Data Science (online book)
- Data Wrangling Cheat sheet (pdf file)
- Introduction to tidyr (online documentation)
- Data wrangling with R and RStudio (online video)
Key Points
- Use the
tidyrpackage to change the layout of data frames. - Use
pivot_longer()to go from wide to longer layout. - Use
pivot_wider()to go from long to wider layout.
Content from Producing Reports With Quarto
Last updated on 2024-12-04 | Edit this page
Estimated time: 75 minutes
Overview
Questions
- How can I integrate software and reports?
Objectives
- Understand the value of writing reproducible reports
- Learn how to recognise and compile the basic components of an Quarto file
- Become familiar with R code chunks, and understand their purpose, structure and options
- Demonstrate the use of inline chunks for weaving R outputs into text blocks, for example when discussing the results of some calculations
- Be aware of alternative output formats to which a Quarto file can be exported
Data analysis reports
Data analysts tend to write a lot of reports, describing their analyses and results, for their collaborators or to document their work for future reference.
Many new users begin by first writing a single R script containing all of their work, and then share the analysis by emailing the script and various graphs as attachments. But this can be cumbersome, requiring a lengthy discussion to explain which attachment was which result.
Writing formal reports with Word or LaTeX can simplify this process by incorporating both the analysis report and output graphs into a single document. But tweaking formatting to make figures look correct and fixing obnoxious page breaks can be tedious and lead to a lengthy “whack-a-mole” game of fixing new mistakes resulting from a single formatting change.
Creating a report as a web page (which is an html file) using Quarto makes things easier. The report can be one long stream, so tall figures that wouldn’t ordinarily fit on one page can be kept at full size and easier to read, since the reader can simply keep scrolling. Additionally, the formatting of a Quarto document is simple and easy to modify, allowing you to spend more time on your analyses instead of writing reports.
Callout
You might also have heard about R Markdown as a literate
programming tool. In a lot of ways, Quarto is the next-generation
version of R Markdown with more advanced features and multi-language
support. However, at its core, Quarto still works the same as R Markdown
when it comes to R-based documents and R Markdown files
(.Rmd) are still compatible with Quarto. Much of what we
cover in this episode is thus also valid for traditional R Markdown
files.
Literate programming
Ideally, such analysis reports are reproducible documents: If an error is discovered, or if some additional subjects are added to the data, you can just re-compile the report and get the new or corrected results rather than having to reconstruct figures, paste them into a Word document, and hand-edit various detailed results.
The key R package here is knitr. It allows you
to create a document that is a mixture of text and chunks of code. When
the document is processed by knitr, chunks of code will be
executed, and graphs or other results will be inserted into the final
document.
This sort of idea has been called “literate programming”.
When rendering a document, knitr will execute the R code
in each chunk and creates a new markdown (.md) document,
which will include both the regular text and output from the executed
code chunks. This markdown file is then converted to the final output
format with pandoc. This whole process
is handled for you by the Render button in the RStudio IDE.
Creating a Quarto document
Within RStudio, click
File → New File → Quarto document... and you’ll get a
dialog box like this:
You can stick with the default (HTML output), but give it a title.
Basic components of R Markdown
The initial chunk of text (header) contains instructions for Quarto
to specify what kind of document will be created, and the options
chosen. You can use the header to give your document a title, author,
date, and tell it what type of output you want to produce. In this case,
we’re creating an html document.
You can delete any of those fields if you don’t want them included. The double-quotes aren’t strictly necessary in this case. They’re mostly needed if you want to include a colon in the title.
RStudio creates the document with some example text to get you started. Note below that there are chunks like
{verbatim} ```{r} 1 + 1 ```
These are chunks of R code that will be executed by
knitr and replaced by their results. More on this
later.
Markdown
Markdown is a system for writing web pages by marking up the text much as you would in an email rather than writing html code. The marked-up text gets converted to html, replacing the marks with the proper html code.
For now, let’s delete all of the stuff that’s there and write a bit of markdown.
You make things bold using two asterisks, like this:
**bold**, and you make things italics by using
underscores, like this: _italics_.
You can make a bulleted list by writing a list with hyphens or asterisks with a space between the list and other text, like this:
MARKDOWN
A list:
* bold with double-asterisks
* italics with underscores
* code-type font with backticksor like this:
MARKDOWN
A second list:
- bold with double-asterisks
- italics with underscores
- code-type font with backticksEach will appear as:
- bold with double-asterisks
- italics with underscores
- code-type font with backticks
You can use whatever method you prefer, but be consistent. This maintains the readability of your code.
You can make a numbered list by just using numbers. You can even use the same number over and over if you want:
This will appear as:
- bold with double-asterisks
- italics with underscores
- code-type font with backticks
You can make section headers of different sizes by initiating a line
with some number of # symbols:
You compile the R Markdown document to an html webpage by clicking the “Render” button in the upper-left. Or using the keyboard shortcut Shift+Ctrl+K on Windows and Linux, or Shift+Cmd+K on Mac.
Challenge 1
Create a new Quarto document. Delete all of the R code chunks and write a bit of Markdown (some sections, some italicized text, and an itemized list).
Convert the document to a webpage.
In RStudio, select
File > New file > Quarto Document...
Delete the placeholder text and add the following:
MARKDOWN
# Introduction
## Background on Data
This report uses the *gapminder* dataset, which has columns that include:
* country
* continent
* year
* lifeExp
* pop
* gdpPercap
## Background on MethodsThen click the ‘Render’ button on the toolbar to generate an html document (webpage).
A bit more Markdown
You can make a hyperlink like this:
[Carpentries Home Page](https://carpentries.org/).
You can include an image file like this:
You can do subscripts (e.g., F2) with F~2~
and superscripts (e.g., F2) with F^2^.
If you know how to write equations in LaTeX, you can use
$ $ and $$ $$ to insert math equations, like
$E = mc^2$ and
$$y = \mu + \sum_{i=1}^p \beta_i x_i + \epsilon$$which will show as
\[y = \mu + \sum_{i=1}^p \beta_i x_i + \epsilon\]
You can review Markdown syntax by navigating to the “Markdown Quick Reference” under the “Help” field in the toolbar at the top of RStudio.
R code chunks
The real power of Quarto comes from mixing markdown with chunks of code. When processed, the R code will be executed; if they produce figures, the figures will be inserted in the final document.
The main code chunks look like this:
{verbatim} ```{r} #| label: load_data gapminder <- read.csv("gapminder.csv") ```
That is, you place a chunk of R code between ```{r} and
```. You should give each chunk a unique name, by inserting
the line #| label: label_name as they will help you to fix
errors and, if any graphs are produced, the file names are based on the
name of the code chunk that produced them. You can create code chunks
quickly in RStudio using the shortcuts
Ctrl+Alt+I on Windows and Linux, or
Cmd+Option+I on Mac.
In R Markdown, you add chunk labels by including them within the
```{r} line like so:
{verbatim} ```{r label_data} gapminder <- read.csv("gapminder.csv") ```
Challenge 2
Add code chunks to:
- Load the ggplot2 package
- Read the gapminder data
- Create a plot
{verbatim} ```{r} #| label: libraries library(ggplot2) ```
{verbatim} ```{r} #| label: load-gapminder-data gapminder <- read.csv("gapminder.csv") ```
{verbatim} ```{r} #| label: make-plot plot(lifeExp ~ year, data = gapminder) ```
How things get compiled
When you press the “Render” button, the Quarto document is processed
by knitr and a plain
Markdown document is produced (as well as, potentially, a set of figure
files): the R code is executed and replaced by both the input and the
output; if figures are produced, links to those figures are
included.
The Markdown and figure documents are then processed by the tool pandoc, which converts the
Markdown file into an html file, with the figures embedded.
Chunk options
There are a variety of options to affect how the code chunks are treated. Here are some examples:
- Use
echo=FALSEto avoid having the code itself shown. - Use
results="hide"to avoid having any results printed. - Use
eval=FALSEto have the code shown but not evaluated. - Use
warning=FALSEandmessage=FALSEto hide any warnings or messages produced. - Use
fig.heightandfig.widthto control the size of the figures produced (in inches).
So you might write:
{verbatim} ```{r} #| label: load_libraries #| echo: false #| message: false library(dplyr) library(ggplot2) ```
Often there will be particular options that you’ll want to use repeatedly; for this, you can set global chunk options in the files YAML header like so:
YAML
---
...
knitr:
opts_chunk:
message: false
warning: false
echo: false
results: "hide"
fig.path: "Figs/
fig.width: 11
---The fig.path option defines where the figures will be
saved. The / here is really important; without it, the
figures would be saved in the standard place but just with names that
begin with Figs.
If you have multiple R Markdown files in a common directory, you
might want to use fig.path to define separate prefixes for
the figure file names, like fig.path="Figs/cleaning-" and
fig.path="Figs/analysis-".
Challenge 3
Use chunk options to control the size of a figure and to hide the code.
{verbatim} ```{r} #| label: faitful-plot #| echo: false #| fig.width: 3 plot(faitful) ```
You can review all of the R chunk options by navigating
to the “R Markdown Cheat Sheet” under the “Cheatsheets” section of the
“Help” field in the toolbar at the top of RStudio.
Inline R code
You can make every number in your report reproducible. Use
`r and ` for an in-line code chunk, like so:
``r "r round(some_value, 2)"``. The code will be executed
and replaced with the value of the result.
Don’t let these in-line chunks get split across lines.
Perhaps precede the paragraph with a larger code chunk that does
calculations and defines variables, with include=FALSE for
that larger chunk (which is the same as echo=FALSE and
results="hide").
Challenge 4
Try out a bit of in-line R code.
Here’s some inline code to determine that 2 + 2 =
r 2+2:
{verbatim} Here's some inline code to determine that 2 + 2 = `r 2+2`:
Other output options
You can also convert R Markdown to a PDF or a Word document. Change
the format: field in the YAML header to pdf or
docx. For an overview of all the available output formats,
see the Quarto
documentation
Parameterised reports
Literate programming with tools like Quarto and R Markdown is very powerful in that it allows you to generate analysis reports in a reproducible manner. This makes it very easy to update your work and alter the input parameters within the report You can take this one step further, by parametrising the reports themselves. This is very useful in a number of cases, for example:
- Running the same analysis on different datasets
- Generating multiple reports for different groups of the data (e.g. geographic location or time periods)
- Controlling the
knitroptions; e.g. you might want to show the code in some reports but not in others
Including parameters in a Quarto document
Including parameters in a Quarto document (or R Markdown, which
follows the same syntax) can be done by adding the params
field to they YAML header. This field can hold a list of multiple
parameters.
For example, imagine we want to analyse the life expectancy of
different countries, using the gapminder dataset, but we
want a separate report for each country. To achieve this, we set the
YAML header for our Quarto document as follows:
YAML
---
title: "Life Expectancy Report"
format: html
execute:
echo: false
warning: false
message: false
params:
country: "Afghanistan"
---We can then reference this parameter anywhere in the R code in our
report by accessing the params object. To calculate the
life expectancy for just the country defined by the params,
we can do:
`{verbatim}{r} library(tidyverse) library(gapminder)
```{r}
life_expectancy <-
gapminder |>
select(country, year, lifeExp) |>
filter(country == params$country)
The last line in the code chunk above uses the `params` object to filter the `gapminder` dataset.
Note that we can also `params` in inline R code snippets. So we can generate a heading that will
change based on the country parameter:
````{verbatim}
## Life Expectancy in `r params$country`
```{r}
#| label: !expr paste0("life-expectancy-plot", params$country)
ggplot(life_expectancy, aes(year, lifeExp)) +
geom_line() +
theme_minimal()
```In fact, we can even use this in the main document title in the YAML header, as it also accepts R code expressions:
Rendering Quarto documents from within R
Of course, manually editing the YAML header every time you want to
generate a report isn’t much better than manually editing the report
itself. The real power of parameterised reports is when we render them
programmatically. This can be done using the {quarto} R
package, which provides the quarto_render() function.
This function takes a Quarto file and any execution parameters as
input.
So to generate the life expectancy report for Afghanistan, we can write a script with the following code:
R
# render-report.R
library(quarto)
quarto_render("life_expectancy_report.qmd", execute_params = list(country = "Afghanistan"))
And now for the real magic, we can modify our script to render a
report for a list of countries of interest from the
gapminder dataset.
{r} # render-all-reports.R library(quarto) countries <- c("Afghanistan", "Belgium", "India", "United Kingdom") for (country in countries) { quarto_render( input = "life_expectancy_report.qmd", output_file = paste0("life_expectancy_", country, ".html"), execute_params = list(country = country) ) }
After running this script, we should have the following files in our working directory:
.
├── life_expectancy_Afghanistan.html
├── life_expectancy_Belgium.html
├── life_expectancy_India.html
├── life_expectancy_United Kingdom.html
├── life_expectancy_report.qmd
└── life_expectancy_report_filesCallout
WARNING: although this will work and generate the correct output files, you might notice that each report will show the exact same plot, which is unexpected. This is an issue with the Quarto R package.
With R Markdown we don’t have this issue, to render we would use the following code:
R
rmarkdown::render(
input = "life_expectency_report.Rmd",
output_file = paste0("life_expectancy_", country, ".html"),
params = list(country = country)
)
Tip: Creating PDF documents
Creating .pdf documents may require installation of some extra
software. The R package tinytex provides some tools to help
make this process easier for R users. With tinytex
installed, run tinytex::install_tinytex() to install the
required software (you’ll only need to do this once) and then when you
knit to pdf tinytex will automatically detect and install
any additional LaTeX packages that are needed to produce the pdf
document. Visit the tinytex
website for more information.
Tip: Visual markdown editing in RStudio
RStudio versions 1.4 and later include visual markdown editing mode.
In visual editing mode, markdown expressions (like
**bold words**) are transformed to the formatted appearance
(bold words) as you type. This mode also includes a
toolbar at the top with basic formatting buttons, similar to what you
might see in common word processing software programs. You can turn
visual editing on and off by pressing the 
button in the top right corner of your R Markdown document.
Resources
- Knitr in a knutshell tutorial
- Dynamic Documents with R and knitr (book)
- R Markdown documentation
- R Markdown cheat sheet
- Getting started with R Markdown
- R Markdown: The Definitive Guide (book by Rstudio team)
- Reproducible Reporting
- The Ecosystem of R Markdown
- Introducing Bookdown
Key Points
- Mix reporting written in R Markdown with software written in R.
- Specify chunk options to control formatting.
- Use
knitrto convert these documents into PDF and other formats.
Content from Basic Statistics: describing, modelling and reporting
Last updated on 2024-12-04 | Edit this page
Estimated time: 80 minutes
Overview
Questions
- How can I detect the type of data I have?
- How can I make meaningful summaries of my data?
Objectives
- To be able to describe the different types of data
- To be able to do basic data exploration of a real dataset
- To be able to calculate descriptive statistics
- To be able to perform statistical inference on a dataset
Content
- Types of Data
- Exploring your dataset
- Descriptive Statistics
- Inferential Statistics
Data
R
# We will need these libraries and this data later.
library(tidyverse)
library(ggplot2)
# loading data
lon_dims_imd_2019 <- read.csv("data/English_IMD_2019_Domains_rebased_London_by_CDRC.csv")
# create a binary membership variable for City of London (for later examples)
lon_dims_imd_2019 <- lon_dims_imd_2019 %>% mutate(city = la19nm == "City of London")
We are going to use the data from the Consumer Data Research Centre, specifically the London IMD 2019 (English IMD 2019 Domains rebased) data. Atribution: Data provided by the Consumer Data Research Centre, an ESRC Data Investment: ES/L011840/1, ES/L011891/1
The statistical unit areas used to provide indices of relative deprivation across the country are Lower layer Super Output Areas (LSOAs), dimensions of depravation include income, employment, education, health, crime, barriers to housing and services, and the living environment. We have added a variable city indicating if an LSOA is within the City of London, or not.
The big picture
- Research often seeks to answer a question about a larger population by collecting data on a small sample
- Data collection:
- Many variables
- For each person/unit.
- This procedure, sampling, must be controlled so as to ensure representative data.
Descriptive and inferential statistics
Callout
Just as data in general are of different types - for example numeric vs text data - statistical data are assigned to different levels of measure. The level of measure determines how we can describe and model the data.
Describing data
- Continuous variables
- Discrete variables
Callout
How do we convey information on what your data looks like, using numbers or figures?
Describing continuous data.
First establish the distribution of the data. You can visualise this with a histogram.
R
ggplot(lon_dims_imd_2019, aes(x = barriers_london_rank)) +
geom_histogram()
OUTPUT
`stat_bin()` using `bins = 30`. Pick better value with `binwidth`.
What is the distribution of this data?
What is the distribution of population?
The raw values are difficult to visualise, so we can take the log of the values and log those. Try this command
R
ggplot(lon_dims_imd_2019, aes(x = log(barriers_london_rank))) +
geom_histogram()
OUTPUT
`stat_bin()` using `bins = 30`. Pick better value with `binwidth`.
What is the distribution of this data?
Parametric vs non-parametric analysis
- Parametric analysis assumes that
- The data follows a known distribution
- It can be described using parameters
- Examples of distributions include, normal, Poisson, exponential.
- Non parametric data
- The data can’t be said to follow a known distribution
Emphasise that parametric is not equal to normal.
Describing parametric and non-parametric data
How do you use numbers to convey what your data looks like.
- Parametric data
- Use the parameters that describe the distribution.
- For a Gaussian (normal) distribution - use mean and standard deviation
- For a Poisson distribution - use average event rate
- etc.
- Non Parametric data
- Use the median (the middle number when they are ranked from lowest to highest) and the interquartile range (the number 75% of the way up the list when ranked minus the number 25% of the way)
- You can use the command
summary(data_frame_name)to get these numbers for each variable.
Mean versus standard deviation
- What does standard deviation mean?
- Both graphs have the same mean (center), but the second one has data which is more spread out.
R
# small standard deviation
dummy_1 <- rnorm(1000, mean = 10, sd = 0.5)
dummy_1 <- as.data.frame(dummy_1)
ggplot(dummy_1, aes(x = dummy_1)) +
geom_histogram()
OUTPUT
`stat_bin()` using `bins = 30`. Pick better value with `binwidth`.
R
# larger standard deviation
dummy_2 <- rnorm(1000, mean = 10, sd = 200)
dummy_2 <- as.data.frame(dummy_2)
ggplot(dummy_2, aes(x = dummy_2)) +
geom_histogram()
OUTPUT
`stat_bin()` using `bins = 30`. Pick better value with `binwidth`.
Get them to plot the graphs. Explain that we are generating random data from different distributions and plotting them.
Calculating mean and standard deviation
R
mean(lon_dims_imd_2019$barriers_london_rank, na.rm = TRUE)
OUTPUT
[1] 2418Calculate the standard deviation and confirm that it is the square root of the variance:
R
sdbarriers <- sd(lon_dims_imd_2019$barriers_london_rank, na.rm = TRUE)
print(sdbarriers)
OUTPUT
[1] 1395.889R
varbarriers <- var(lon_dims_imd_2019$barriers_london_rank, na.rm = TRUE)
print(varbarriers)
OUTPUT
[1] 1948505R
sqrt(varbarriers) == sdbarriers
OUTPUT
[1] TRUEThe na.rm argument tells R to ignore missing values in
the variable.
Describing discrete data
- Frequencies
R
table(lon_dims_imd_2019$la19nm)
OUTPUT
Barking and Dagenham Barnet Bexley
110 211 146
Brent Bromley Camden
173 197 133
City of London Croydon Ealing
6 220 196
Enfield Greenwich Hackney
183 151 144
Hammersmith and Fulham Haringey Harrow
113 145 137
Havering Hillingdon Hounslow
150 161 142
Islington Kensington and Chelsea Kingston upon Thames
123 103 98
Lambeth Lewisham Merton
178 169 124
Newham Redbridge Richmond upon Thames
164 161 115
Southwark Sutton Tower Hamlets
166 121 144
Waltham Forest Wandsworth Westminster
144 179 128 - Proportions
R
areastable <- table(lon_dims_imd_2019$la19nm)
prop.table(areastable)
OUTPUT
Barking and Dagenham Barnet Bexley
0.022750776 0.043640124 0.030196484
Brent Bromley Camden
0.035780765 0.040744571 0.027507756
City of London Croydon Ealing
0.001240951 0.045501551 0.040537746
Enfield Greenwich Hackney
0.037849018 0.031230610 0.029782834
Hammersmith and Fulham Haringey Harrow
0.023371251 0.029989659 0.028335057
Havering Hillingdon Hounslow
0.031023785 0.033298862 0.029369183
Islington Kensington and Chelsea Kingston upon Thames
0.025439504 0.021302999 0.020268873
Lambeth Lewisham Merton
0.036814891 0.034953464 0.025646329
Newham Redbridge Richmond upon Thames
0.033919338 0.033298862 0.023784902
Southwark Sutton Tower Hamlets
0.034332989 0.025025853 0.029782834
Waltham Forest Wandsworth Westminster
0.029782834 0.037021717 0.026473630 Contingency tables of frequencies can also be tabulated with table(). For example:
R
table(
lon_dims_imd_2019$la19nm,
lon_dims_imd_2019$IDAOP_london_decile
)
OUTPUT
1 2 3 4 5 6 7 8 9 10
Barking and Dagenham 6 11 23 25 22 12 7 4 0 0
Barnet 6 7 13 15 18 32 29 37 29 25
Bexley 0 3 2 5 11 11 15 24 30 45
Brent 12 19 24 28 43 18 17 11 1 0
Bromley 2 3 6 9 10 12 20 19 41 75
Camden 12 19 14 18 14 10 9 16 11 10
City of London 0 0 1 0 0 0 0 1 0 4
Croydon 8 7 16 25 23 20 29 24 29 39
Ealing 11 18 22 23 24 23 31 21 18 5
Enfield 9 19 27 22 26 17 16 22 18 7
[ reached getOption("max.print") -- omitted 23 rows ]Which leads quite naturally to the consideration of any association between the observed frequencies.
Inferential statistics
Meaningful analysis
- What is your hypothesis - what is your null hypothesis?
Callout
Always: the level of the independent variable has no effect on the level of the dependent variable.
What type of variables (data type) do you have?
What are the assumptions of the test you are using?
Interpreting the result
Testing significance
p-value
<0.05
-
0.03-0.049
- Would benefit from further testing.
0.05 is not a magic number.
Comparing means
It all starts with a hypothesis
- Null hypothesis
- “There is no difference in mean height between men and women” \[mean\_height\_men - mean\_height\_women = 0\]
- Alternate hypothesis
- “There is a difference in mean height between men and women”
More on hypothesis testing
The null hypothesis (H0) assumes that the true mean difference (μd) is equal to zero.
The two-tailed alternative hypothesis (H1) assumes that μd is not equal to zero.
The upper-tailed alternative hypothesis (H1) assumes that μd is greater than zero.
The lower-tailed alternative hypothesis (H1) assumes that μd is less than zero.
Remember: hypotheses are never about data, they are about the processes which produce the data. The value of μd is unknown. The goal of hypothesis testing is to determine the hypothesis (null or alternative) with which the data are more consistent.
Comparing means
Is there an absolute difference between the income ranks of the Lower-layer Super Output Areas?
R
lon_dims_imd_2019 %>%
group_by(la19nm) %>%
summarise(avg = mean(Income_london_rank)) %>%
arrange(la19nm, .locale = "en")
OUTPUT
# A tibble: 33 × 2
la19nm avg
<chr> <dbl>
1 Barking and Dagenham 7786.
2 Barnet 17049.
3 Bexley 18592.
4 Brent 11500.
5 Bromley 20826.
6 Camden 14359.
7 City of London 19800.
8 Croydon 14686.
9 Ealing 13718.
10 Enfield 11403.
# ℹ 23 more rowsIs the difference between the income ranks statistically significant?
t-test
Assumptions of a t-test
One independent categorical variable with 2 groups and one dependent continuous variable
The dependent variable is approximately normally distributed in each group
The observations are independent of each other
For students’ original t-statistic, that the variances in both groups are more or less equal. This constraint should probably be abandoned in favour of always using a conservative test.
Doing a t-test
R
t.test(health_london_rank ~ city, data = lon_dims_imd_2019)$statistic
OUTPUT
t
-0.5183242 R
t.test(health_london_rank ~ city, data = lon_dims_imd_2019)$parameter
OUTPUT
df
5.015827 Notice that the summary()** of the test contains more data than is output by default.
Write a paragraph in markdown format reporting this test result including the t-statistic, the degrees of freedom, the confidence interval and the p-value to 4 places. To do this include your r code inline with your text, rather than in an R code chunk.
More than two levels of IV
While the t-test is sufficient where there are two levels of the IV, for situations where there are more than two, we use the ANOVA family of procedures. To show this, we will create a variable that subsets our data by per capita GDP levels. If the ANOVA result is statistically significant, we will use a post-hoc test method to do pairwise comparisons (here Tukey’s Honest Significant Differences.)
R
anovamodel <- aov(lon_dims_imd_2019$health_london_rank ~ lon_dims_imd_2019$la19nm)
summary(anovamodel)
OUTPUT
Df Sum Sq Mean Sq F value Pr(>F)
lon_dims_imd_2019$la19nm 32 1.156e+11 3.614e+09 94.3 <2e-16 ***
Residuals 4802 1.840e+11 3.832e+07
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1R
TukeyHSD(anovamodel)
OUTPUT
Tukey multiple comparisons of means
95% family-wise confidence level
Fit: aov(formula = lon_dims_imd_2019$health_london_rank ~ lon_dims_imd_2019$la19nm)
$`lon_dims_imd_2019$la19nm`
diff lwr
Barnet-Barking and Dagenham 14629.43408 11864.704458
Bexley-Barking and Dagenham 10324.16189 7356.018133
Brent-Barking and Dagenham 8976.53678 6109.643394
Bromley-Barking and Dagenham 13160.91347 10362.721854
Camden-Barking and Dagenham 8842.99282 5813.159809
City of London-Barking and Dagenham 8728.87879 -1126.986222
Croydon-Barking and Dagenham 5472.01364 2726.731357
Ealing-Barking and Dagenham 7444.55056 4643.802426
Enfield-Barking and Dagenham 9856.81595 7020.532420
Greenwich-Barking and Dagenham 3308.37658 361.423935
Hackney-Barking and Dagenham -2303.09343 -5280.080786
Hammersmith and Fulham-Barking and Dagenham 3374.21360 225.344643
Haringey-Barking and Dagenham 4977.28683 2004.748485
Harrow-Barking and Dagenham 14760.22064 11750.476548
Havering-Barking and Dagenham 9781.09212 6830.002345
Hillingdon-Barking and Dagenham 7988.28148 5080.156381
Hounslow-Barking and Dagenham 6633.44686 3647.394114
Islington-Barking and Dagenham -824.36918 -3909.451677
Kensington and Chelsea-Barking and Dagenham 12368.11342 9144.725551
Kingston upon Thames-Barking and Dagenham 14113.29035 10847.712764
Lambeth-Barking and Dagenham 672.68029 -2178.519304
Lewisham-Barking and Dagenham 2032.14605 -847.904610
Merton-Barking and Dagenham 10555.97287 7476.768867
Newham-Barking and Dagenham 3111.49058 214.182117
Redbridge-Barking and Dagenham 12151.31254 9243.187437
upr p adj
Barnet-Barking and Dagenham 17394.16370 0.0000000
Bexley-Barking and Dagenham 13292.30565 0.0000000
Brent-Barking and Dagenham 11843.43017 0.0000000
Bromley-Barking and Dagenham 15959.10510 0.0000000
Camden-Barking and Dagenham 11872.82584 0.0000000
City of London-Barking and Dagenham 18584.74380 0.1877166
Croydon-Barking and Dagenham 8217.29592 0.0000000
Ealing-Barking and Dagenham 10245.29869 0.0000000
Enfield-Barking and Dagenham 12693.09947 0.0000000
Greenwich-Barking and Dagenham 6255.32923 0.0085802
Hackney-Barking and Dagenham 673.89392 0.4778538
Hammersmith and Fulham-Barking and Dagenham 6523.08255 0.0185918
Haringey-Barking and Dagenham 7949.82518 0.0000001
Harrow-Barking and Dagenham 17769.96473 0.0000000
Havering-Barking and Dagenham 12732.18190 0.0000000
Hillingdon-Barking and Dagenham 10896.40658 0.0000000
Hounslow-Barking and Dagenham 9619.49961 0.0000000
Islington-Barking and Dagenham 2260.71332 1.0000000
Kensington and Chelsea-Barking and Dagenham 15591.50128 0.0000000
Kingston upon Thames-Barking and Dagenham 17378.86794 0.0000000
Lambeth-Barking and Dagenham 3523.87988 1.0000000
Lewisham-Barking and Dagenham 4912.19670 0.6922986
Merton-Barking and Dagenham 13635.17688 0.0000000
Newham-Barking and Dagenham 6008.79904 0.0179605
Redbridge-Barking and Dagenham 15059.43763 0.0000000
[ reached getOption("max.print") -- omitted 503 rows ]Regression Modelling
The most common use of regression modelling is to explore the
relationship between two continuous variables, for example between
Income_london_rank and health_london_rank in
our data. We can first determine whether there is any significant
correlation between the values, and if there is, plot the
relationship.
R
cor.test(lon_dims_imd_2019$Income_london_rank, lon_dims_imd_2019$health_london_rank)
OUTPUT
Pearson's product-moment correlation
data: lon_dims_imd_2019$Income_london_rank and lon_dims_imd_2019$health_london_rank
t = 92.907, df = 4833, p-value < 2.2e-16
alternative hypothesis: true correlation is not equal to 0
95 percent confidence interval:
0.7903110 0.8105571
sample estimates:
cor
0.8006626 R
ggplot(lon_dims_imd_2019, aes(Income_london_rank, health_london_rank)) +
geom_point() +
geom_smooth()
OUTPUT
`geom_smooth()` using method = 'gam' and formula = 'y ~ s(x, bs = "cs")'
Having decided that a further investigation of this relationship is
worthwhile, we can create a linear model with the function
lm().
R
modelone <- lm(lon_dims_imd_2019$Income_london_rank ~ lon_dims_imd_2019$health_london_rank)
summary(modelone)
OUTPUT
Call:
lm(formula = lon_dims_imd_2019$Income_london_rank ~ lon_dims_imd_2019$health_london_rank)
Residuals:
Min 1Q Median 3Q Max
-15354 -3547 -102 3458 24528
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) -3.223e+03 2.039e+02 -15.80 <2e-16 ***
lon_dims_imd_2019$health_london_rank 8.634e-01 9.293e-03 92.91 <2e-16 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 5087 on 4833 degrees of freedom
Multiple R-squared: 0.6411, Adjusted R-squared: 0.641
F-statistic: 8632 on 1 and 4833 DF, p-value: < 2.2e-16Regression with a categorical IV (the t-test)
Run the following code chunk and compare the results to the t-test conducted earlier.
R
lon_dims_imd_2019 %>%
mutate(city = factor(city))
OUTPUT
ls11cd la19nm IDAOP_london_rank IDAOP_london_decile
1 E01000001 City of London 32,820 10
2 E01000002 City of London 31,938 10
3 E01000003 City of London 16,377 8
4 E01000005 City of London 3,885 3
IDACI_london_rank IDACI_london_decile Income_london_rank Income_london_decile
1 32806 10 32831 10
2 29682 10 29901 10
3 27063 9 18510 7
4 9458 4 6029 2
employment_london_rank employment_london_decile crime_london_rank
1 32742 10 32662
2 31190 10 32789
3 15103 5 29363
4 7833 2 31059
crime_london_decile barriers_london_rank barriers_london_decile
1 10 2679 6
2 10 3645 8
3 10 984 3
4 10 1003 3
livingEnv_london_rank livingEnv_london_decile health_london_rank
1 7789 4 32113
2 13070 7 29705
3 4092 2 17600
4 9397 5 17907
health_london_decile edu_london_rank edu_london_decile city
1 10 32842 10 TRUE
2 9 32832 10 TRUE
3 4 26386 8 TRUE
4 4 12370 2 TRUE
[ reached 'max' / getOption("max.print") -- omitted 4831 rows ]R
modelttest <- lm(lon_dims_imd_2019$health_london_rank ~ lon_dims_imd_2019$city)
summary(modelttest)
OUTPUT
Call:
lm(formula = lon_dims_imd_2019$health_london_rank ~ lon_dims_imd_2019$city)
Residuals:
Min 1Q Median 3Q Max
-19251.6 -6392.6 367.4 6853.4 12362.4
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 20481.6 113.3 180.75 <2e-16 ***
lon_dims_imd_2019$cityTRUE 1478.2 3216.6 0.46 0.646
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 7874 on 4833 degrees of freedom
Multiple R-squared: 4.37e-05, Adjusted R-squared: -0.0001632
F-statistic: 0.2112 on 1 and 4833 DF, p-value: 0.6458Content from Linear regression and Broom
Last updated on 2024-12-04 | Edit this page
Estimated time: 100 minutes
Overview
Questions
- How can I explore relationships between variables in my data?
- How can I present model outputs in an easier to read way?
Objectives
- To be able to explore relationships between variables
- To be able to calculate predicted variables and residuals
- To be able to construct linear regression models
- To be able to present model outcomes using Broom
Content
- Linear Regression Models
- Use of Log transform
- Use of Categorical Variables
- Use of Broom
Data
R
# We will need these libraries and this data later.
library(ggplot2)
library(tidyverse)
library(lmtest)
library(sandwich)
library(broom)
lon_dims_imd_2019 <- read.csv("data/English_IMD_2019_Domains_rebased_London_by_CDRC.csv")
We are going to use the data from the Consumer Data Research Centre, specifically the London IMD 2019 (English IMD 2019 Domains rebased).
Atribution: Data provided by the Consumer Data Research Centre, an ESRC Data Investment: ES/L011840/1, ES/L011891/1
The statistical unit areas across the country are Lower layer Super Output Areas (LSOAs). We will explore the relationships between the different dimensions of the Indices of Multiple Deprivation.
Linear regression
Linear Regression enables use to to explore the the linear relationship of the dependent variable Y and independent variable(s) X(s). We are going to explore the linear relationship between the Health Deprivation and Disability Domain and the Living Environment Deprivation Domain.
The Health Deprivation and Disability Domain measures the risk of premature death and the impairment of quality of life through poor physical or mental health. The domain measures morbidity, disability and premature mortality but not aspects of behaviour or environment that may be predictive of future health deprivation.
The Living Environment Deprivation Domain measures the quality of the local environment. The indicators fall into two sub-domains. The ‘indoors’ living environment measures the quality of housing; while the ‘outdoors’ living environment contains measures of air quality and road traffic accidents.
Reference: McLennan, David et al. The English Indices of Deprivation 2019 : Technical Report. Ministry of Housing, Communities and Local Government, 2019. Print.
Simple linear regression
In the simple linear regression example we have only one dependent variable (health_london_rank) and one independent variable (livingEnv_london_rank).
R
reg_LivEnv_health <- lm(health_london_rank ~ livingEnv_london_rank, data = lon_dims_imd_2019)
# We put the dependent variable to the left of the '~' and the independent variable(s) to the right
# and we tell R which dataset we are referring to.
summary(reg_LivEnv_health)
OUTPUT
Call:
lm(formula = health_london_rank ~ livingEnv_london_rank, data = lon_dims_imd_2019)
Residuals:
Min 1Q Median 3Q Max
-21549.6 -5948.2 609.1 6239.2 15792.2
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 1.692e+04 2.274e+02 74.40 <2e-16 ***
livingEnv_london_rank 3.430e-01 1.915e-02 17.91 <2e-16 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 7625 on 4833 degrees of freedom
Multiple R-squared: 0.06225, Adjusted R-squared: 0.06205
F-statistic: 320.8 on 1 and 4833 DF, p-value: < 2.2e-16From the result of this analysis, we can see that the Living Environment Deprivation Domain rank has a significant(small p-value, general rule of thumb <0.05) and positive relationship(positive coefficient) with the Health Deprivation and Disability Domain rank.
One way of interpreting the result is: One unit increase in the Living Environment rank is related to around 0.343 (3.430e-01) points increase of the Health Deprivation and Disability rank.
R-square shows the amount of variance of Y explained by X. In this case the Living Environment rank explains 6.225% of the variance in the Health Deprivation and Disability rank. Adj R2(6.205%) shows the same as R2 but adjusted by the # of cases and # of variables. When the # of variables is small and the # of cases is very large then Adj R2 is closer to R2.
Log transform
If your data is skewed, it can be useful to transform a variable to it’s log form when doing the regression. You can either transform the variable beforehand or do so in the equation.
R
reg_logbarriers_health <- lm(health_london_rank ~ log(barriers_london_rank), data = lon_dims_imd_2019)
summary(reg_logbarriers_health)
OUTPUT
Call:
lm(formula = health_london_rank ~ log(barriers_london_rank),
data = lon_dims_imd_2019)
Residuals:
Min 1Q Median 3Q Max
-20379.3 -5611.7 774.9 5988.6 23828.5
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) -1349.4 798.3 -1.69 0.091 .
log(barriers_london_rank) 2917.0 105.7 27.59 <2e-16 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 7319 on 4833 degrees of freedom
Multiple R-squared: 0.1361, Adjusted R-squared: 0.1359
F-statistic: 761.1 on 1 and 4833 DF, p-value: < 2.2e-16The interpretation of the log-transformed variable is a bit different. In this example only the predictor variable is log tranformed, therefore to interpret the slope coefficient we divide it by 100 (2917.0/100=29.170).
If the dependent/response variable is solely log-transformed, exponentiate the coefficient. This gives the multiplicative factor for every one-unit increase in the independent variable. Example: the coefficient is 0.198. exp(0.198) = 1.218962. For every one-unit increase in the independent variable, our dependent variable increases by a factor of about 1.22, or 22%. Recall that multiplying a number by 1.22 is the same as increasing the number by 22%. Likewise, multiplying a number by, say 0.84, is the same as decreasing the number by 1 – 0.84 = 0.16, or 16%.
If both are transformed, interpret the coefficient as the percent increase in the dependent variable for every 1% increase in the independent variable. Example: the coefficient is 0.198. For every 1% increase in the independent variable, our dependent variable increases by about 0.20%. For x percent increase, calculate 1.x to the power of the coefficient, subtract 1, and multiply by 100. Example: For every 20% increase in the independent variable, our dependent variable increases by about (1.20 0.198 - 1) * 100 = 3.7 percent.
Predicted values and residuals
We can expand our simple linear regression example to incorporate the Barriers to Housing and Services Domain rank. The Barriers to Housing and Services Domain measures the physical and financial accessibility of housing and local services. The indicators fall into two sub-domains: ‘geographical barriers’, which relate to the physical proximity of local services, and ‘wider barriers’ which includes issues relating to access to housing, such as affordability.
R
reg_LivEnv_barriers_health <- lm(
health_london_rank ~ livingEnv_london_rank + barriers_london_rank,
data = lon_dims_imd_2019
)
summary(reg_LivEnv_barriers_health)
OUTPUT
Call:
lm(formula = health_london_rank ~ livingEnv_london_rank + barriers_london_rank,
data = lon_dims_imd_2019)
Residuals:
Min 1Q Median 3Q Max
-21685.8 -4834.9 546.5 5142.4 18971.7
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 1.169e+04 2.502e+02 46.74 <2e-16 ***
livingEnv_london_rank 2.620e-01 1.721e-02 15.22 <2e-16 ***
barriers_london_rank 2.508e+00 7.059e-02 35.54 <2e-16 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 6790 on 4832 degrees of freedom
Multiple R-squared: 0.2566, Adjusted R-squared: 0.2562
F-statistic: 833.7 on 2 and 4832 DF, p-value: < 2.2e-16After running the regression model, we can access the model predicted values and the residuals compared to the real observations.
R
# first we fit the predictions
health_rank_pred <- fitted(reg_LivEnv_barriers_health)
health_rank_pred <- as.data.frame(health_rank_pred)
# now we add the residual values too
health_rank_resid <- residuals(reg_LivEnv_barriers_health)
health_rank_pred$resid <- health_rank_resid
# We can thenview the predictions and residuals
head(health_rank_pred)
OUTPUT
health_rank_pred resid
1 20454.30 11658.702
2 24260.97 5444.031
3 15233.92 2366.080
4 16671.36 1235.645
5 15719.80 5861.196
6 14981.47 1432.528R
# You can view the full data in RStudio with the View() function
View(health_rank_pred)
Robust regression
We can run the robust standard error regressions(control for heteroskedasticity, meaning unequal variances):
R
reg_LivEnv_barriers_health$robse <- vcovHC(reg_LivEnv_barriers_health, type = "HC1")
coeftest(reg_LivEnv_barriers_health, reg_LivEnv_barriers_health$robse)
OUTPUT
t test of coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 1.1694e+04 2.3776e+02 49.182 < 2.2e-16 ***
livingEnv_london_rank 2.6197e-01 1.7458e-02 15.006 < 2.2e-16 ***
barriers_london_rank 2.5085e+00 6.4394e-02 38.955 < 2.2e-16 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1In addition, we can access the cluster-robust standard errors regression results:
R
# cluster-robust standard errors
coeftest(reg_LivEnv_barriers_health, reg_LivEnv_barriers_health$clse)
OUTPUT
t test of coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 1.1694e+04 2.5018e+02 46.741 < 2.2e-16 ***
livingEnv_london_rank 2.6197e-01 1.7207e-02 15.225 < 2.2e-16 ***
barriers_london_rank 2.5085e+00 7.0588e-02 35.537 < 2.2e-16 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1Challenge 1
Use the gapminder data to create a linear model between
two continuous variables.
Discuss your question and your findings.
Regression with categorical independent variables
We will explore the use of categorical independent variables in linear regression in this episode. When the dependent variable is a categorical variable, you may consider the alternatives of linear regression like logit regression and multinomial regression.
R
# As a categorical variable we have added la19nm, these are the names of the London boroughs
reg_cat_var <- lm(health_london_rank ~ livingEnv_london_rank + barriers_london_rank + la19nm, data = lon_dims_imd_2019)
summary(reg_cat_var)
OUTPUT
Call:
lm(formula = health_london_rank ~ livingEnv_london_rank + barriers_london_rank +
la19nm, data = lon_dims_imd_2019)
Residuals:
Min 1Q Median 3Q Max
-21694.3 -3423.6 248.1 3691.8 19321.5
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 1.105e+04 5.429e+02 20.346 < 2e-16 ***
livingEnv_london_rank 3.595e-02 1.802e-02 1.996 0.046036 *
barriers_london_rank 3.149e+00 7.888e-02 39.924 < 2e-16 ***
la19nmBarnet 8.400e+03 6.508e+02 12.908 < 2e-16 ***
la19nmBexley 1.416e+03 7.186e+02 1.970 0.048856 *
la19nmBrent 7.765e+03 6.545e+02 11.863 < 2e-16 ***
la19nmBromley 5.208e+03 6.789e+02 7.670 2.06e-14 ***
la19nmCamden -1.842e+03 7.426e+02 -2.480 0.013184 *
la19nmCity of London 4.742e+03 2.251e+03 2.107 0.035185 *
la19nmCroydon 7.488e+02 6.388e+02 1.172 0.241192
la19nmEaling 3.697e+03 6.459e+02 5.724 1.11e-08 ***
la19nmEnfield 7.344e+03 6.501e+02 11.297 < 2e-16 ***
la19nmGreenwich -2.221e+03 6.873e+02 -3.232 0.001238 **
la19nmHackney -2.725e+03 6.811e+02 -4.000 6.43e-05 ***
la19nmHammersmith and Fulham -3.907e+03 7.438e+02 -5.252 1.57e-07 ***
la19nmHaringey 1.019e+03 6.877e+02 1.481 0.138580
la19nmHarrow 9.993e+03 7.053e+02 14.168 < 2e-16 ***
la19nmHavering -3.945e+02 7.317e+02 -0.539 0.589781
la19nmHillingdon 8.459e+02 6.937e+02 1.219 0.222791
la19nmHounslow 2.462e+03 6.890e+02 3.573 0.000356 ***
la19nmIslington -8.217e+03 7.305e+02 -11.248 < 2e-16 ***
la19nmKensington and Chelsea 9.191e+03 7.473e+02 12.299 < 2e-16 ***
la19nmKingston upon Thames 4.899e+03 7.804e+02 6.277 3.75e-10 ***
la19nmLambeth -6.270e+03 6.830e+02 -9.180 < 2e-16 ***
la19nmLewisham -1.991e+03 6.675e+02 -2.983 0.002869 **
la19nmMerton 3.387e+02 7.474e+02 0.453 0.650434
la19nmNewham 4.209e+03 6.617e+02 6.361 2.19e-10 ***
la19nmRedbridge 4.420e+03 6.914e+02 6.392 1.79e-10 ***
la19nmRichmond upon Thames 4.469e+03 7.740e+02 5.774 8.22e-09 ***
la19nmSouthwark -3.363e+03 6.731e+02 -4.996 6.05e-07 ***
la19nmSutton -1.729e+02 7.537e+02 -0.229 0.818563
la19nmTower Hamlets -5.862e+03 6.968e+02 -8.414 < 2e-16 ***
la19nmWaltham Forest 2.026e+03 6.854e+02 2.956 0.003137 **
la19nmWandsworth 1.087e+01 6.797e+02 0.016 0.987246
la19nmWestminster 5.683e+02 7.472e+02 0.761 0.446958
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 5362 on 4800 degrees of freedom
Multiple R-squared: 0.5395, Adjusted R-squared: 0.5363
F-statistic: 165.4 on 34 and 4800 DF, p-value: < 2.2e-16R automatically recognizes la19nm as a factor and treats it accordingly. The missing one in the coefficient summary (Barking and Dagenham) is treated as a base line, therefore the value is 0. However, we can also modify our model to show for all:
R
reg_cat_var_showall <- lm(
health_london_rank ~ 0 + livingEnv_london_rank + barriers_london_rank + la19nm,
data = lon_dims_imd_2019
)
summary(reg_cat_var_showall)
OUTPUT
Call:
lm(formula = health_london_rank ~ 0 + livingEnv_london_rank +
barriers_london_rank + la19nm, data = lon_dims_imd_2019)
Residuals:
Min 1Q Median 3Q Max
-21694.3 -3423.6 248.1 3691.8 19321.5
Coefficients:
Estimate Std. Error t value Pr(>|t|)
livingEnv_london_rank 3.595e-02 1.802e-02 1.996 0.046 *
barriers_london_rank 3.149e+00 7.888e-02 39.924 < 2e-16 ***
la19nmBarking and Dagenham 1.105e+04 5.429e+02 20.346 < 2e-16 ***
la19nmBarnet 1.945e+04 4.764e+02 40.820 < 2e-16 ***
la19nmBexley 1.246e+04 5.876e+02 21.209 < 2e-16 ***
la19nmBrent 1.881e+04 4.526e+02 41.564 < 2e-16 ***
la19nmBromley 1.625e+04 5.444e+02 29.858 < 2e-16 ***
la19nmCamden 9.205e+03 5.783e+02 15.918 < 2e-16 ***
la19nmCity of London 1.579e+04 2.198e+03 7.184 7.78e-13 ***
la19nmCroydon 1.180e+04 4.574e+02 25.789 < 2e-16 ***
la19nmEaling 1.474e+04 4.388e+02 33.601 < 2e-16 ***
la19nmEnfield 1.839e+04 4.549e+02 40.431 < 2e-16 ***
la19nmGreenwich 8.825e+03 5.233e+02 16.865 < 2e-16 ***
la19nmHackney 8.322e+03 4.675e+02 17.802 < 2e-16 ***
la19nmHammersmith and Fulham 7.140e+03 5.675e+02 12.582 < 2e-16 ***
la19nmHaringey 1.207e+04 4.848e+02 24.886 < 2e-16 ***
la19nmHarrow 2.104e+04 5.667e+02 37.127 < 2e-16 ***
la19nmHavering 1.065e+04 6.178e+02 17.243 < 2e-16 ***
la19nmHillingdon 1.189e+04 5.541e+02 21.464 < 2e-16 ***
la19nmHounslow 1.351e+04 5.050e+02 26.750 < 2e-16 ***
la19nmIslington 2.830e+03 5.500e+02 5.145 2.78e-07 ***
la19nmKensington and Chelsea 2.024e+04 5.491e+02 36.859 < 2e-16 ***
la19nmKingston upon Thames 1.595e+04 6.476e+02 24.624 < 2e-16 ***
la19nmLambeth 4.777e+03 4.657e+02 10.257 < 2e-16 ***
la19nmLewisham 9.055e+03 4.543e+02 19.931 < 2e-16 ***
la19nmMerton 1.139e+04 5.935e+02 19.182 < 2e-16 ***
la19nmNewham 1.526e+04 4.467e+02 34.149 < 2e-16 ***
la19nmRedbridge 1.547e+04 5.307e+02 29.141 < 2e-16 ***
la19nmRichmond upon Thames 1.552e+04 6.355e+02 24.414 < 2e-16 ***
la19nmSouthwark 7.684e+03 4.662e+02 16.481 < 2e-16 ***
la19nmSutton 1.087e+04 6.274e+02 17.332 < 2e-16 ***
la19nmTower Hamlets 5.184e+03 5.107e+02 10.151 < 2e-16 ***
la19nmWaltham Forest 1.307e+04 4.831e+02 27.057 < 2e-16 ***
la19nmWandsworth 1.106e+04 4.905e+02 22.543 < 2e-16 ***
la19nmWestminster 1.161e+04 5.649e+02 20.560 < 2e-16 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 5362 on 4800 degrees of freedom
Multiple R-squared: 0.9407, Adjusted R-squared: 0.9403
F-statistic: 2177 on 35 and 4800 DF, p-value: < 2.2e-16Categorical variables with interaction terms
Sometimes we are interested in how a variable interacts with another variable. We can explore any interactions between locations (la19nm) and the living environment and barrier ranks.
R
reg_cat_var_int <- lm(health_london_rank ~ la19nm * (livingEnv_london_rank + barriers_london_rank), data = lon_dims_imd_2019)
summary(reg_cat_var_int)
OUTPUT
Call:
lm(formula = health_london_rank ~ la19nm * (livingEnv_london_rank +
barriers_london_rank), data = lon_dims_imd_2019)
Residuals:
Min 1Q Median 3Q Max
-19227.9 -3254.4 297.6 3372.8 17891.5
Coefficients:
Estimate Std. Error
(Intercept) 1.300e+04 1.431e+03
la19nmBarnet 9.411e+03 1.909e+03
la19nmBexley -5.447e+03 2.464e+03
la19nmBrent 3.068e+03 1.866e+03
la19nmBromley 1.577e+03 2.107e+03
la19nmCamden -1.547e+04 3.565e+03
la19nmCity of London -8.405e+02 5.283e+03
la19nmCroydon -3.824e+03 1.679e+03
la19nmEaling 2.124e+03 1.841e+03
la19nmEnfield 2.420e+03 1.750e+03
la19nmGreenwich -3.383e+03 2.268e+03
la19nmHackney -1.803e+03 1.937e+03
la19nmHammersmith and Fulham -1.123e+04 2.389e+03
la19nmHaringey -4.527e+02 1.975e+03
la19nmHarrow 7.800e+03 2.476e+03
la19nmHavering -8.133e+03 2.519e+03
la19nmHillingdon 7.792e+02 2.030e+03
la19nmHounslow 4.939e+03 2.064e+03
la19nmIslington -4.614e+03 2.592e+03
la19nmKensington and Chelsea 1.264e+04 2.185e+03
la19nmKingston upon Thames 5.297e+03 2.972e+03
la19nmLambeth -6.973e+03 2.276e+03
la19nmLewisham -4.745e+03 1.912e+03
la19nmMerton -8.433e+03 2.793e+03
la19nmNewham 3.468e+03 1.786e+03
la19nmRedbridge 4.339e+03 2.156e+03
la19nmRichmond upon Thames 3.822e+03 4.288e+03
la19nmSouthwark -6.830e+03 1.923e+03
la19nmSutton -8.242e+03 2.600e+03
la19nmTower Hamlets -2.705e+03 2.163e+03
la19nmWaltham Forest 2.070e+03 1.814e+03
la19nmWandsworth 6.438e+02 2.060e+03
la19nmWestminster -1.063e+04 3.281e+03
livingEnv_london_rank -1.900e-01 1.321e-01
barriers_london_rank 3.620e+00 8.023e-01
la19nmBarnet:livingEnv_london_rank 1.641e-01 1.553e-01
la19nmBexley:livingEnv_london_rank 5.286e-01 1.644e-01
la19nmBrent:livingEnv_london_rank 5.219e-01 1.663e-01
la19nmBromley:livingEnv_london_rank 4.577e-01 1.492e-01
la19nmCamden:livingEnv_london_rank -4.599e-02 1.783e-01
la19nmCity of London:livingEnv_london_rank 3.448e-01 9.482e-01
la19nmCroydon:livingEnv_london_rank 4.524e-01 1.417e-01
la19nmEaling:livingEnv_london_rank 2.053e-01 1.624e-01
la19nmEnfield:livingEnv_london_rank 5.217e-01 1.556e-01
la19nmGreenwich:livingEnv_london_rank 2.230e-01 1.620e-01
la19nmHackney:livingEnv_london_rank -2.882e-01 1.817e-01
la19nmHammersmith and Fulham:livingEnv_london_rank 1.915e-01 2.025e-01
la19nmHaringey:livingEnv_london_rank -9.428e-02 2.048e-01
la19nmHarrow:livingEnv_london_rank 3.559e-01 1.774e-01
la19nmHavering:livingEnv_london_rank 5.238e-01 1.584e-01
la19nmHillingdon:livingEnv_london_rank 3.026e-01 1.572e-01
la19nmHounslow:livingEnv_london_rank -3.776e-02 1.691e-01
la19nmIslington:livingEnv_london_rank -4.471e-01 1.967e-01
la19nmKensington and Chelsea:livingEnv_london_rank -1.673e+00 2.725e-01
la19nmKingston upon Thames:livingEnv_london_rank 2.551e-01 1.748e-01
la19nmLambeth:livingEnv_london_rank -1.901e-01 2.037e-01
la19nmLewisham:livingEnv_london_rank 1.834e-01 1.687e-01
la19nmMerton:livingEnv_london_rank 5.430e-01 1.761e-01
la19nmNewham:livingEnv_london_rank -4.372e-03 1.627e-01
la19nmRedbridge:livingEnv_london_rank 2.310e-01 1.655e-01
la19nmRichmond upon Thames:livingEnv_london_rank -2.672e-03 1.876e-01
la19nmSouthwark:livingEnv_london_rank 2.786e-01 1.656e-01
la19nmSutton:livingEnv_london_rank 5.311e-01 1.576e-01
la19nmTower Hamlets:livingEnv_london_rank 1.954e-01 1.629e-01
la19nmWaltham Forest:livingEnv_london_rank -2.538e-02 1.729e-01
la19nmWandsworth:livingEnv_london_rank -1.552e-01 1.637e-01
la19nmWestminster:livingEnv_london_rank -9.646e-01 2.107e-01
la19nmBarnet:barriers_london_rank -1.334e+00 8.565e-01
la19nmBexley:barriers_london_rank -4.421e-01 8.661e-01
la19nmBrent:barriers_london_rank -7.477e-01 9.505e-01
la19nmBromley:barriers_london_rank -1.240e+00 8.666e-01
la19nmCamden:barriers_london_rank 2.994e+00 1.172e+00
la19nmCity of London:barriers_london_rank 1.001e+00 3.050e+00
la19nmCroydon:barriers_london_rank -6.200e-01 8.595e-01
la19nmEaling:barriers_london_rank -5.816e-01 8.604e-01
la19nmEnfield:barriers_london_rank -6.740e-01 8.776e-01
la19nmGreenwich:barriers_london_rank -8.003e-01 8.842e-01
la19nmHackney:barriers_london_rank 4.611e-01 1.427e+00
la19nmHammersmith and Fulham:barriers_london_rank 1.442e+00 9.425e-01
la19nmHaringey:barriers_london_rank 4.613e-01 9.154e-01
la19nmHarrow:barriers_london_rank -1.413e+00 9.202e-01
la19nmHavering:barriers_london_rank -3.766e-01 9.029e-01
la19nmHillingdon:barriers_london_rank -1.592e+00 8.683e-01
la19nmHounslow:barriers_london_rank -1.445e+00 9.061e-01
la19nmIslington:barriers_london_rank -7.852e-01 1.031e+00
la19nmKensington and Chelsea:barriers_london_rank 1.076e+00 1.007e+00
la19nmKingston upon Thames:barriers_london_rank -1.257e+00 9.816e-01
la19nmLambeth:barriers_london_rank -3.110e-01 9.491e-01
la19nmLewisham:barriers_london_rank 1.004e-01 9.045e-01
la19nmMerton:barriers_london_rank 4.934e-01 9.399e-01
la19nmNewham:barriers_london_rank 2.625e+00 2.260e+00
la19nmRedbridge:barriers_london_rank -1.116e+00 8.944e-01
la19nmRichmond upon Thames:barriers_london_rank -1.884e-01 1.104e+00
la19nmSouthwark:barriers_london_rank 5.627e-02 9.074e-01
la19nmSutton:barriers_london_rank -5.571e-02 9.399e-01
la19nmTower Hamlets:barriers_london_rank -2.394e+00 9.808e-01
la19nmWaltham Forest:barriers_london_rank -5.478e-01 9.237e-01
la19nmWandsworth:barriers_london_rank -2.874e-01 8.705e-01
la19nmWestminster:barriers_london_rank 3.494e+00 1.111e+00
t value Pr(>|t|)
(Intercept) 9.089 < 2e-16 ***
la19nmBarnet 4.929 8.57e-07 ***
la19nmBexley -2.210 0.027119 *
la19nmBrent 1.645 0.100112
la19nmBromley 0.749 0.454155
la19nmCamden -4.338 1.47e-05 ***
la19nmCity of London -0.159 0.873612
la19nmCroydon -2.277 0.022851 *
la19nmEaling 1.154 0.248528
la19nmEnfield 1.382 0.166890
la19nmGreenwich -1.491 0.135952
la19nmHackney -0.931 0.352136
la19nmHammersmith and Fulham -4.700 2.68e-06 ***
la19nmHaringey -0.229 0.818706
la19nmHarrow 3.150 0.001640 **
la19nmHavering -3.228 0.001254 **
la19nmHillingdon 0.384 0.701039
la19nmHounslow 2.393 0.016735 *
la19nmIslington -1.780 0.075114 .
la19nmKensington and Chelsea 5.787 7.61e-09 ***
la19nmKingston upon Thames 1.782 0.074808 .
la19nmLambeth -3.064 0.002197 **
la19nmLewisham -2.482 0.013106 *
la19nmMerton -3.019 0.002549 **
la19nmNewham 1.942 0.052165 .
la19nmRedbridge 2.013 0.044191 *
la19nmRichmond upon Thames 0.891 0.372776
la19nmSouthwark -3.552 0.000387 ***
la19nmSutton -3.169 0.001538 **
la19nmTower Hamlets -1.251 0.211119
la19nmWaltham Forest 1.141 0.253966
la19nmWandsworth 0.313 0.754638
la19nmWestminster -3.240 0.001203 **
livingEnv_london_rank -1.438 0.150471
barriers_london_rank 4.511 6.60e-06 ***
la19nmBarnet:livingEnv_london_rank 1.057 0.290593
la19nmBexley:livingEnv_london_rank 3.215 0.001312 **
la19nmBrent:livingEnv_london_rank 3.139 0.001705 **
la19nmBromley:livingEnv_london_rank 3.068 0.002169 **
la19nmCamden:livingEnv_london_rank -0.258 0.796425
la19nmCity of London:livingEnv_london_rank 0.364 0.716133
la19nmCroydon:livingEnv_london_rank 3.191 0.001425 **
la19nmEaling:livingEnv_london_rank 1.264 0.206349
la19nmEnfield:livingEnv_london_rank 3.354 0.000803 ***
la19nmGreenwich:livingEnv_london_rank 1.376 0.168758
la19nmHackney:livingEnv_london_rank -1.586 0.112711
la19nmHammersmith and Fulham:livingEnv_london_rank 0.946 0.344403
la19nmHaringey:livingEnv_london_rank -0.460 0.645286
la19nmHarrow:livingEnv_london_rank 2.005 0.044971 *
la19nmHavering:livingEnv_london_rank 3.307 0.000951 ***
la19nmHillingdon:livingEnv_london_rank 1.925 0.054317 .
la19nmHounslow:livingEnv_london_rank -0.223 0.823335
la19nmIslington:livingEnv_london_rank -2.273 0.023082 *
la19nmKensington and Chelsea:livingEnv_london_rank -6.137 9.08e-10 ***
la19nmKingston upon Thames:livingEnv_london_rank 1.459 0.144509
la19nmLambeth:livingEnv_london_rank -0.934 0.350602
la19nmLewisham:livingEnv_london_rank 1.087 0.277108
la19nmMerton:livingEnv_london_rank 3.082 0.002065 **
la19nmNewham:livingEnv_london_rank -0.027 0.978565
la19nmRedbridge:livingEnv_london_rank 1.396 0.162864
la19nmRichmond upon Thames:livingEnv_london_rank -0.014 0.988639
la19nmSouthwark:livingEnv_london_rank 1.683 0.092533 .
la19nmSutton:livingEnv_london_rank 3.370 0.000759 ***
la19nmTower Hamlets:livingEnv_london_rank 1.200 0.230337
la19nmWaltham Forest:livingEnv_london_rank -0.147 0.883300
la19nmWandsworth:livingEnv_london_rank -0.948 0.343019
la19nmWestminster:livingEnv_london_rank -4.578 4.80e-06 ***
la19nmBarnet:barriers_london_rank -1.558 0.119396
la19nmBexley:barriers_london_rank -0.510 0.609807
la19nmBrent:barriers_london_rank -0.787 0.431493
la19nmBromley:barriers_london_rank -1.431 0.152500
la19nmCamden:barriers_london_rank 2.555 0.010647 *
la19nmCity of London:barriers_london_rank 0.328 0.742734
la19nmCroydon:barriers_london_rank -0.721 0.470718
la19nmEaling:barriers_london_rank -0.676 0.499110
la19nmEnfield:barriers_london_rank -0.768 0.442499
la19nmGreenwich:barriers_london_rank -0.905 0.365429
la19nmHackney:barriers_london_rank 0.323 0.746543
la19nmHammersmith and Fulham:barriers_london_rank 1.530 0.126056
la19nmHaringey:barriers_london_rank 0.504 0.614335
la19nmHarrow:barriers_london_rank -1.535 0.124794
la19nmHavering:barriers_london_rank -0.417 0.676607
la19nmHillingdon:barriers_london_rank -1.834 0.066734 .
la19nmHounslow:barriers_london_rank -1.595 0.110827
la19nmIslington:barriers_london_rank -0.762 0.446220
la19nmKensington and Chelsea:barriers_london_rank 1.068 0.285397
la19nmKingston upon Thames:barriers_london_rank -1.280 0.200487
la19nmLambeth:barriers_london_rank -0.328 0.743140
la19nmLewisham:barriers_london_rank 0.111 0.911614
la19nmMerton:barriers_london_rank 0.525 0.599625
la19nmNewham:barriers_london_rank 1.161 0.245561
la19nmRedbridge:barriers_london_rank -1.247 0.212307
la19nmRichmond upon Thames:barriers_london_rank -0.171 0.864559
la19nmSouthwark:barriers_london_rank 0.062 0.950560
la19nmSutton:barriers_london_rank -0.059 0.952740
la19nmTower Hamlets:barriers_london_rank -2.440 0.014708 *
la19nmWaltham Forest:barriers_london_rank -0.593 0.553200
la19nmWandsworth:barriers_london_rank -0.330 0.741265
la19nmWestminster:barriers_london_rank 3.146 0.001667 **
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 5162 on 4736 degrees of freedom
Multiple R-squared: 0.5789, Adjusted R-squared: 0.5702
F-statistic: 66.45 on 98 and 4736 DF, p-value: < 2.2e-16Challenge 2
Using the gapminder data to create a linear model
between a categorical and a continuous variable .
Discuss your question and your findings.
Broom
The ‘broom’ package offers an alternative way of presenting the output of statistical analysis. It centers around three S3 methods, each of which take common objects produced by R statistical functions (lm, t.test, nls, etc) and convert them into a tibble.
These are:
- tidy: constructs a tibble that summarizes the model’s statistical findings. This includes coefficients and p-values for each term in a regression, per-cluster information in clustering applications, or per-test information for multtest functions.
- augment: add columns to the original data that was modeled. This includes predictions, residuals, and cluster assignments.
- glance: construct a concise one-row summary of the model. This typically contains values such as R^2, adjusted R^2, and residual standard error that are computed once for the entire model.
Let’s revisit our initial linear model:
R
reg_LivEnv_health <- lm(health_london_rank ~ livingEnv_london_rank, data = lon_dims_imd_2019)
summary(reg_LivEnv_health)
OUTPUT
Call:
lm(formula = health_london_rank ~ livingEnv_london_rank, data = lon_dims_imd_2019)
Residuals:
Min 1Q Median 3Q Max
-21549.6 -5948.2 609.1 6239.2 15792.2
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 1.692e+04 2.274e+02 74.40 <2e-16 ***
livingEnv_london_rank 3.430e-01 1.915e-02 17.91 <2e-16 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 7625 on 4833 degrees of freedom
Multiple R-squared: 0.06225, Adjusted R-squared: 0.06205
F-statistic: 320.8 on 1 and 4833 DF, p-value: < 2.2e-16There is a lot of useful information, but it not available in a way so that you can combine it with other models or do further analysis. We can convert this to tabular data using the ‘tidy’ function.
R
tidy(reg_LivEnv_health)
OUTPUT
# A tibble: 2 × 5
term estimate std.error statistic p.value
<chr> <dbl> <dbl> <dbl> <dbl>
1 (Intercept) 16916. 227. 74.4 0
2 livingEnv_london_rank 0.343 0.0192 17.9 1.63e-69The row names have been moved into a column called term, and the column names are simple and consistent (and can be accessed using $).
Information about the model can be explored with ‘augment’. The function augments the original data with information from the model, such as the fitted values and residuals for each of the original points in the regression.
R
augment(reg_LivEnv_health)
OUTPUT
# A tibble: 4,835 × 8
health_london_rank livingEnv_london_rank .fitted .resid .hat .sigma
<int> <int> <dbl> <dbl> <dbl> <dbl>
1 32113 7789 19588. 12525. 0.000250 7624.
2 29705 13070 21400. 8305. 0.000252 7625.
3 17600 4092 18320. -720. 0.000458 7626.
4 17907 9397 20140. -2233. 0.000213 7626.
5 21581 10629 20562. 1019. 0.000207 7626.
6 16414 11162 20745. -4331. 0.000210 7626.
7 12334 8672 19891. -7557. 0.000226 7625.
8 9661 9611 20213. -10552. 0.000211 7625.
9 16050 2269 17694. -1644. 0.000624 7626.
10 18178 4309 18394. -216. 0.000441 7626.
# ℹ 4,825 more rows
# ℹ 2 more variables: .cooksd <dbl>, .std.resid <dbl>Some of the data presented by ‘augment’ will be discussed in the episode Linear Regression Diagnostics.
Summary statistics are computed for the entire regression, such as R^2 and the F-statistic can be accessed with the ‘glance’ function:
R
glance(reg_LivEnv_health)
OUTPUT
# A tibble: 1 × 12
r.squared adj.r.squared sigma statistic p.value df logLik AIC BIC
<dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
1 0.0622 0.0621 7625. 321. 1.63e-69 1 -50081. 100167. 100187.
# ℹ 3 more variables: deviance <dbl>, df.residual <int>, nobs <int>Generalised linear models
We can also use the ‘broom’ functions to present data from Generalised linear and non-linear models. For example, if we wanted to explore the Income Rank in relation to whether or not an area was within the City of London.
R
# add a variable to indicate whether or not an area is within the City of London
lon_dims_imd_2019 <- lon_dims_imd_2019 %>% mutate(city = la19nm == "City of London")
# create a Generalised Linear Model
glmlondims <- glm(city ~ Income_london_rank, lon_dims_imd_2019, family = "binomial")
summary(glmlondims)
OUTPUT
Call:
glm(formula = city ~ Income_london_rank, family = "binomial",
data = lon_dims_imd_2019)
Coefficients:
Estimate Std. Error z value Pr(>|z|)
(Intercept) -7.868e+00 1.004e+00 -7.835 4.68e-15 ***
Income_london_rank 6.888e-05 4.635e-05 1.486 0.137
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
(Dispersion parameter for binomial family taken to be 1)
Null deviance: 92.295 on 4834 degrees of freedom
Residual deviance: 90.062 on 4833 degrees of freedom
AIC: 94.062
Number of Fisher Scoring iterations: 10Use of ‘tidy’:
R
tidy(glmlondims)
OUTPUT
# A tibble: 2 × 5
term estimate std.error statistic p.value
<chr> <dbl> <dbl> <dbl> <dbl>
1 (Intercept) -7.87 1.00 -7.84 4.68e-15
2 Income_london_rank 0.0000689 0.0000463 1.49 1.37e- 1Use of ‘augment’:
R
augment(glmlondims)
OUTPUT
# A tibble: 4,835 × 8
city Income_london_rank .fitted .resid .hat .sigma .cooksd .std.resid
<lgl> <int> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
1 TRUE 32831 -5.61 3.35 0.00194 0.128 2.65e-1 3.35
2 TRUE 29901 -5.81 3.41 0.00115 0.127 1.93e-1 3.41
3 TRUE 18510 -6.59 3.63 0.000233 0.126 8.51e-2 3.63
4 TRUE 6029 -7.45 3.86 0.000332 0.125 2.87e-1 3.86
5 FALSE 14023 -6.90 -0.0448 0.000239 0.137 1.20e-7 -0.0448
6 FALSE 6261 -7.44 -0.0343 0.000330 0.137 9.72e-8 -0.0343
7 FALSE 3382 -7.64 -0.0311 0.000360 0.137 8.70e-8 -0.0311
8 FALSE 7506 -7.35 -0.0358 0.000315 0.137 1.01e-7 -0.0358
9 FALSE 8902 -7.25 -0.0376 0.000298 0.137 1.05e-7 -0.0376
10 FALSE 9033 -7.25 -0.0378 0.000296 0.137 1.06e-7 -0.0378
# ℹ 4,825 more rowsUse of ‘glance’:
R
glance(glmlondims)
OUTPUT
# A tibble: 1 × 8
null.deviance df.null logLik AIC BIC deviance df.residual nobs
<dbl> <int> <dbl> <dbl> <dbl> <dbl> <int> <int>
1 92.3 4834 -45.0 94.1 107. 90.1 4833 4835You will notice that the statistics computed by ‘glance’ are different for glm objects than for lm (e.g. deviance rather than R^2).
Hypothesis testing
The tidy function can also be applied a range of hypotheses tests, such as built-in functions like t.test, cor.test, and wilcox.test.
t-test
R
tt <- t.test(Income_london_rank ~ city, lon_dims_imd_2019)
tidy(tt)
OUTPUT
# A tibble: 1 × 10
estimate estimate1 estimate2 statistic p.value parameter conf.low conf.high
<dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
1 -5344. 14456. 19800. -1.24 0.270 5.01 -16407. 5719.
# ℹ 2 more variables: method <chr>, alternative <chr>Some cases might have fewer columns (for example, no confidence interval).
Wilcox test:
R
wt <- wilcox.test(Income_london_rank ~ city, lon_dims_imd_2019)
tidy(wt)
OUTPUT
# A tibble: 1 × 4
statistic p.value method alternative
<dbl> <dbl> <chr> <chr>
1 9836. 0.174 Wilcoxon rank sum test with continuity correcti… two.sided Since the ‘tidy’ output is already only one row, glance returns the same output:
R
# t-test
glance(tt)
OUTPUT
# A tibble: 1 × 10
estimate estimate1 estimate2 statistic p.value parameter conf.low conf.high
<dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
1 -5344. 14456. 19800. -1.24 0.270 5.01 -16407. 5719.
# ℹ 2 more variables: method <chr>, alternative <chr>R
# Wilcox test
glance(wt)
OUTPUT
# A tibble: 1 × 4
statistic p.value method alternative
<dbl> <dbl> <chr> <chr>
1 9836. 0.174 Wilcoxon rank sum test with continuity correcti… two.sided The chisq.test enables use to investigate whether changes in one categorical variable are related to changes in another categorical variable.
The ‘augment’ method is defined only for chi-squared tests, since there is no meaningful sense, for other tests, in which a hypothesis test produces output about each initial data point.
R
# convert IDAOP_london_decile to a factor so it is not interprested as continuous data
lon_dims_imd_2019$IDAOP_london_decile <- factor(lon_dims_imd_2019$IDAOP_london_decile)
# xtabs creates a frequency table of IMD deciles within London borooughs
chit <- chisq.test(xtabs(~ la19nm + IDAOP_london_decile, data = lon_dims_imd_2019))
WARNING
Warning in chisq.test(xtabs(~la19nm + IDAOP_london_decile, data =
lon_dims_imd_2019)): Chi-squared approximation may be incorrectR
tidy(chit)
OUTPUT
# A tibble: 1 × 4
statistic p.value parameter method
<dbl> <dbl> <int> <chr>
1 2841. 0 288 Pearson's Chi-squared testR
augment(chit)
OUTPUT
# A tibble: 330 × 9
la19nm IDAOP_london_decile .observed .prop .row.prop .col.prop .expected
<fct> <fct> <int> <dbl> <dbl> <dbl> <dbl>
1 Barking … 1 6 1.24e-3 0.0545 0.0124 11.0
2 Barnet 1 6 1.24e-3 0.0284 0.0124 21.1
3 Bexley 1 0 0 0 0 14.6
4 Brent 1 12 2.48e-3 0.0694 0.0248 17.3
5 Bromley 1 2 4.14e-4 0.0102 0.00414 19.7
6 Camden 1 12 2.48e-3 0.0902 0.0248 13.3
7 City of … 1 0 0 0 0 0.599
8 Croydon 1 8 1.65e-3 0.0364 0.0166 22.0
9 Ealing 1 11 2.28e-3 0.0561 0.0228 19.6
10 Enfield 1 9 1.86e-3 0.0492 0.0186 18.3
# ℹ 320 more rows
# ℹ 2 more variables: .resid <dbl>, .std.resid <dbl>There are a number of underlying assumptions of a Chi-Square test, these are:
Independence: The Chi-Square test assumes that the observations in the data are independent of each other. This means that the outcome of one observation should not influence the outcome of another.
Random sampling: The data should be obtained through random sampling to ensure that it is representative of the population from which it was drawn.
Expected frequency: The Chi-Square test assumes that the expected frequency count for each cell in the contingency table should be at least 5. If this assumption is not met, the test results may not be reliable.
As we have received a warning about the reliability of our test, it is likely that one of these assumptions has not been met, and that this is not a suitable test for this data.
Challenge 3
Use broom to amend the display of your model outputs.
Which function(s) did you use and why?
Conventions
There are some conventions that enable consistency across the broom functions, these are: * The output of the tidy, augment and glance functions is always a tibble.
- The output never has rownames. This ensures that you can combine it with other tidy outputs without fear of losing information (since rownames in R cannot contain duplicates).
- Some column names are kept consistent, so that they can be combined across different models and so that you know what to expect (in contrast to asking “is it pval or PValue?” every time).
Content from Assumption Diagnostics and Regression Trouble Shooting
Last updated on 2024-12-04 | Edit this page
Estimated time: 100 minutes
Overview
Questions
- How can I check that my data is suitable for use in a linear regression model?
Objectives
- To be able to check assumptions for linear regression models
Content
- Residual diagnostics
- Heteroskedasticity Check
- Multicollinearity Check
- Identification of Influential Points
Data
R
# We will need these libraries and this data later.
library(ggplot2)
library(olsrr)
library(car)
lon_dims_imd_2019 <- read.csv("data/English_IMD_2019_Domains_rebased_London_by_CDRC.csv")
For accurate model interpretation and prediction, there are a number of assumptions about linear regression models that need to be verified. These are: * Linear Relationship: The core premise of multiple linear regression is the existence of a linear relationship between the dependent (outcome) variable and the independent variables. T * Multivariate Normality: The analysis assumes that the residuals (the differences between observed and predicted values) are normally distributed. This assumption can be assessed by examining histograms or Q-Q plots of the residuals, or through statistical tests such as the Kolmogorov-Smirnov test. * No Multicollinearity: It is essential that the independent variables are not too highly correlated with each other, a condition known as multicollinearity. This can be checked using: + Correlation matrices, where correlation coefficients should ideally be below 0.80. + Variance Inflation Factor (VIF), with VIF values above 10 indicating problematic multicollinearity. * Homoscedasticity: The variance of error terms (residuals) should be consistent across all levels of the independent variables.
We can perform a number of tests to see if the assumptions are met.
Residual Diagnostics
Residual QQ Plot
Plot for detecting violation of normality assumption.
R
model1 <- lm(health_london_rank ~ livingEnv_london_rank + barriers_london_rank + la19nm, data = lon_dims_imd_2019)
ols_plot_resid_qq(model1)
Residual Normality Test
Test for detecting violation of normality assumption.
R
ols_test_normality(model1)
OUTPUT
-----------------------------------------------
Test Statistic pvalue
-----------------------------------------------
Shapiro-Wilk 0.9968 0.0000
Kolmogorov-Smirnov 0.0238 0.0084
Cramer-von Mises 404.803 0.0000
Anderson-Darling 4.1283 0.0000
-----------------------------------------------Correlation between observed residuals and expected residuals under normality.
R
ols_test_correlation(model1)
OUTPUT
[1] 0.9983931From these tests we can see that our assumptions are seemingly correct.
Residual vs Fitted Values Plot
We can create a scatter plot of residuals on the y axis and fitted values on the x axis to detect non-linearity, unequal error variances, and outliers.
Characteristics of a well behaved residual vs fitted plot: * The residuals spread randomly around the 0 line indicating that the relationship is linear. * The residuals form an approximate horizontal band around the 0 line indicating homogeneity of error variance. * No one residual is visibly away from the random pattern of the residuals indicating that there are no outliers.
R
ols_plot_resid_fit(model1)
Additional Diagnostics
In addition the residual diagnostics, we can also assess our model for Heteroskedasticity, Multicollinearity and any Influential/High leverage points.
Heteroskedasticity Check
We can use the ncvTest() function to test for equal variances.
R
ncvTest(model1)
OUTPUT
Non-constant Variance Score Test
Variance formula: ~ fitted.values
Chisquare = 52.92299, Df = 1, p = 3.4689e-13The p-value here is low, indicating that this model may have a problem of unequal variances.
Multicollinearity Check
We want to know whether we have too many variables that have high correlation with each other. If the value of GVIF is greater than 4, it suggests collinearity.
R
vif(model1)
OUTPUT
GVIF Df GVIF^(1/(2*Df))
livingEnv_london_rank 1.790038 1 1.337923
barriers_london_rank 2.038530 1 1.427771
la19nm 3.583479 32 1.020143Outlier Identification
We can identify outliers in our data by creating a QQPlot and running statistical tests on the data. The outlierTest() reports the Bonferroni p-values for testing each observation in turn to be a mean-shift outlier, based Studentized residuals in linear (t-tests), generalized linear models (normal tests), and linear mixed models.
R
# Create a qqPlot
qqPlot(model1, id.n = 2)
OUTPUT
[1] 4612 4721R
# Test for outliers
outlierTest(model1)
OUTPUT
No Studentized residuals with Bonferroni p < 0.05
Largest |rstudent|:
rstudent unadjusted p-value Bonferroni p
4612 -4.069694 4.7832e-05 0.23127The null hypothesis for the Bonferonni adjusted outlier test is the observation is an outlier. Here observation related to ‘4612’ is an outlier. In our data ‘4612’ is difficult to identify as it may refer to either a Living Environment or a Barriers rank.
Identifying Influence Points
We can identify potential influential points via an Influence Plot, these may be Ouliers and/or High Leverage points. A point can be considered influential if it’s exclusion causes substantial change in the estimated regression.
An influence plot summarises the 3 metrics for influence analysis in one single glance. The X-axis plots the leverage, which is normalised between 0 and 1. The Y-axis plots the studentized residuals, which can be positive or negative. The size of the circles for each data point reflect its Cook’s distance, degree of influence.
Vertical reference lines are drawn at twice and three times the average hat value, horizontal reference lines at -2, 0, and 2 on the Studentized-residual scale.
R
# Influence Plots
influencePlot(model1)
OUTPUT
StudRes Hat CookD
1 1.5548629 0.166808357 0.0138248622
2 0.4024213 0.167706627 0.0009324887
4612 -4.0696939 0.008281120 0.0039386753
4675 -1.1177591 0.166718323 0.0071416294
4676 -0.2645859 0.167101314 0.0004013628
4721 3.6227234 0.007981167 0.0030092149Identified influential points are returned in a data frame with the hat values, Studentized residuals and Cook’s distance of the identified points. If no points are identified, nothing is returned.
Influence points can be further explored with an Influence Index Plot which provides index plots of influence and related diagnostics for a regression model.
R
influenceIndexPlot(model1)
If an observation is influential then that observation can change the fit of the linear model.
An observation may be influential because: 1. Someone made a recording error 2. Someone made a fundamental mistake collecting the observation 3. The data point is perfectly valid, in which case the model cannot account for the behaviour.
If the case is 1 or 2, then you can remove the point (or correct it). If it’s 3, it’s not worth deleting a valid point; the data may be better suited a non-linear model.
Challenge
Choose 3 of the of the regression diagnostics, check that the
assumptions are met for the linear models you have created using the
gapminder data.
State what you tested and discuss your findings.
Content from Logistic Regression
Last updated on 2024-12-04 | Edit this page
Estimated time: 120 minutes
Overview
Questions
- How can I identify factors for antibiotic resistance?
- How can I check the validity of model?
Objectives
- To be able to construct regression models for a binary outcome
- To be able to calculate predicted variables and residuals
- To be able to present model outcomes using Broom
Content
- Exploratory Data Analysis
- Model Creation and Estimation
- Reporting the Logistic Regression Results
Data
R
# We will need these libraries and this data later.
library(aod)
library(broom)
library(ggplot2)
library(lubridate)
library(odds.n.ends)
library(tidyverse)
amrData <- read.csv("data/dig_health_hub_amr.csv")
The data used in this episode was provided by Simon Thelwall from the UKHSA. It has been created to represent the sort of data that might be obtained from the Second Generation Surveillance System (SGSS). The data has 100,000 rows of 12 variables.
Exploratory Data Analysis
We can preview our data by using ‘head’:
R
head(amrData)
OUTPUT
id dob spec_date sex_male region had_surgery_past_yr
1 1 1981-04-04 2014-05-25 1 London 0
2 2 1969-05-22 2014-05-25 0 East 0
3 3 1935-11-20 2014-05-25 0 London 1
4 4 1967-05-19 2014-05-25 1 London 0
5 5 1961-06-30 2014-05-25 0 North West 0
6 6 1987-01-11 2014-05-25 1 North East 0
ethnicity imd organism coamox
1 Other ethnic group 4 E. coli 1
2 Other ethnic group 3 E. coli 0
3 Black, Black British, Black Welsh, Caribbean or African 2 E. coli 1
4 Mixed or Multiple ethnic groups 5 E. coli 0
5 Mixed or Multiple ethnic groups 4 E. coli 0
6 Mixed or Multiple ethnic groups 4 E. coli 0
cipro gentam
1 0 0
2 0 0
3 0 0
4 0 0
5 0 0
6 0 0We can also request information about variable names and data types:
R
sapply(amrData, class)
OUTPUT
id dob spec_date sex_male
"integer" "character" "character" "integer"
region had_surgery_past_yr ethnicity imd
"character" "integer" "character" "integer"
organism coamox cipro gentam
"character" "integer" "integer" "integer" We can see that dates are currently stored as the char data type. We also do not know the age of the participant when the sample was taken.
R
# Calculate age (in years) as of their last birthday and add as an additional variable to our data.
# The %--% and %/% are synax specific to lubridate.
# In the first part we are asking it to find the difference between the two dates.
# We are then rounding down to the nearest year.
amrData <- amrData %>%
mutate(
age_years_sd = (dob %--% spec_date) %/% years(1)
)
We can also convert ‘spec_date’, the date the specimen was taken from text to a date:
R
# Convert char to date and store as additional variable
amrData <- amrData %>%
mutate(
spec_date_YMD = as.Date(amrData$spec_date)
)
We can use a histogram to explore the age distribution of the participants:
R
# histogram of age
ageHisto <- amrData %>%
ggplot(aes(x = age_years_sd)) +
geom_histogram(bins = 10, color = "white") +
theme_minimal(base_size = 14, base_family = "sans") +
labs(x = "Age when specimen taken (years)", y = "Frequency")
ageHisto
We can also look at where the specimens were processed:
R
xtabs(~region, data = amrData)
OUTPUT
region
East East Midlands London
11084 11160 11253
North East North West South East
11082 10919 11101
South West West Midlands Yorkshire and The Humber
11278 11032 11091 and for which organism:
R
xtabs(~organism, data = amrData)
OUTPUT
organism
E. coli
100000 In addition, we can use cross-tabulation to identify if the specimen indicated resistance to one or more of Coamoxiclav, Gentamicin and Ciprofloxacin for the participants:
R
xtabs(~ coamox + cipro + gentam, data = amrData)
OUTPUT
, , gentam = 0
cipro
coamox 0 1
0 61844 5814
1 24319 3109
, , gentam = 1
cipro
coamox 0 1
0 2815 362
1 1510 227We can see from our table that only 227 participants indicated reistance to Coamoxiclav, Gentamicin and Ciprofloxacin. Coamoxiclav appears to have the highest individual indication of resistance. We will explore indicators to Coamoxiclav first.
Model Creation and Estimation
As the dependent variable we want to explore is binary (0,1), we will use a binomial generalised linear model.
R
coamox_logit <- glm(coamox ~ age_years_sd + sex_male, data = amrData, family = "binomial")
summary(coamox_logit)
OUTPUT
Call:
glm(formula = coamox ~ age_years_sd + sex_male, family = "binomial",
data = amrData)
Coefficients:
Estimate Std. Error z value Pr(>|z|)
(Intercept) -3.2215791 0.0284626 -113.186 < 2e-16 ***
age_years_sd 0.0404280 0.0004449 90.867 < 2e-16 ***
sex_male 0.0540494 0.0146011 3.702 0.000214 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
(Dispersion parameter for binomial family taken to be 1)
Null deviance: 120724 on 99999 degrees of freedom
Residual deviance: 111460 on 99997 degrees of freedom
AIC: 111466
Number of Fisher Scoring iterations: 4In this initial model focusing on demographic indicators, age at time of sample being taken and whether or not the participant is male both seem to be statistically significant.
age_years_sd: For every unit increase in age_years_sd the log-odds of Coamoxiclav resistance increase by 0.0404280.
sex_male: The difference in the log-odds of Coamoxiclav resistance between males and non-males is 0.0540494.
Older participants and male participants have higher log-odds of Coamoxicalv resistance.
We can check to see that our indicators sex_male and age_years_sd are independent:
R
# check VIF for no perfect multicollinearity assumption
car::vif(coamox_logit)
OUTPUT
age_years_sd sex_male
1.000015 1.000015 We can also check the linearity of the variable age_years_sd
R
# make a variable of the logit of the predicted values
logit.use <- log(coamox_logit$fitted.values / (1 - coamox_logit$fitted.values))
# make a small data frame with the logit variable and the age predictor
linearity.data <- data.frame(logit.use, age = coamox_logit$model$age_years_sd)
# create a plot with linear and actual relationships shown
linearPlot <- linearity.data %>%
ggplot(aes(x = age, y = logit.use)) +
geom_point(aes(size = "Observation"), color = "blue", alpha = .6) +
geom_smooth(se = FALSE, aes(color = "Loess curve")) +
geom_smooth(method = lm, se = FALSE, aes(color = "linear")) +
theme_minimal(base_size = 14, base_family = "serif") +
labs(x = "Age in years on sample date", y = "Log-odds of coamox resistance predicted probability") +
scale_color_manual(name = "Type of fit line", values = c("red", "black")) +
scale_size_manual(values = 1.5, name = "")
linearPlot
OUTPUT
`geom_smooth()` using method = 'gam' and formula = 'y ~ s(x, bs = "cs")'
`geom_smooth()` using formula = 'y ~ x'
Challenge 1
Update the model coamox_logit to include had_surgery_past_yr as an independent variable. What is the log-odds reported and is it statistically significant?
You may choose to create a new glm:
R
coamox_surg_logit <- glm(coamox ~ age_years_sd + sex_male + had_surgery_past_yr, data = amrData, family = "binomial")
summary(coamox_surg_logit)
OUTPUT
Call:
glm(formula = coamox ~ age_years_sd + sex_male + had_surgery_past_yr,
family = "binomial", data = amrData)
Coefficients:
Estimate Std. Error z value Pr(>|z|)
(Intercept) -3.2407115 0.0286059 -113.288 < 2e-16 ***
age_years_sd 0.0404424 0.0004451 90.870 < 2e-16 ***
sex_male 0.0538298 0.0146056 3.686 0.000228 ***
had_surgery_past_yr 0.1802123 0.0238522 7.555 4.18e-14 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
(Dispersion parameter for binomial family taken to be 1)
Null deviance: 120724 on 99999 degrees of freedom
Residual deviance: 111404 on 99996 degrees of freedom
AIC: 111412
Number of Fisher Scoring iterations: 4had_surgery_past_yr: The difference in the log-odds of Coamoxiclav resistance between those who have had surgery in the past year and those who have not is 0.1802123. It is statistically significant.
You may also want to check for culticollinearity:
R
car::vif(coamox_surg_logit)
OUTPUT
age_years_sd sex_male had_surgery_past_yr
1.000156 1.000018 1.000144 As the value of GVIF is lower than 4, it suggests that the assumption of independnce between the variables is held.
Incorporating a multi-level factor
So far we have considered binary and continuos variable indicators in our model(s). Our data set also contains some categorical variables: region, ethinicity and imd.
We are going to incorporate region into our model:
R
# To include reporting for all regions I will include the 0 flag
coamox_region_logit <- glm(coamox ~ 0 + age_years_sd + sex_male + region, data = amrData, family = "binomial")
summary(coamox_region_logit)
OUTPUT
Call:
glm(formula = coamox ~ 0 + age_years_sd + sex_male + region,
family = "binomial", data = amrData)
Coefficients:
Estimate Std. Error z value Pr(>|z|)
age_years_sd 0.040432 0.000445 90.867 < 2e-16 ***
sex_male 0.054155 0.014602 3.709 0.000208 ***
regionEast -3.246673 0.035328 -91.900 < 2e-16 ***
regionEast Midlands -3.213569 0.035077 -91.616 < 2e-16 ***
regionLondon -3.204244 0.034972 -91.625 < 2e-16 ***
regionNorth East -3.219060 0.035140 -91.606 < 2e-16 ***
regionNorth West -3.217271 0.035244 -91.285 < 2e-16 ***
regionSouth East -3.183229 0.035058 -90.799 < 2e-16 ***
regionSouth West -3.222338 0.035057 -91.917 < 2e-16 ***
regionWest Midlands -3.236012 0.035275 -91.736 < 2e-16 ***
regionYorkshire and The Humber -3.255309 0.035302 -92.213 < 2e-16 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
(Dispersion parameter for binomial family taken to be 1)
Null deviance: 138629 on 100000 degrees of freedom
Residual deviance: 111452 on 99989 degrees of freedom
AIC: 111474
Number of Fisher Scoring iterations: 4It initially seems that all regions are significant and have a negative log-odds of Coamoxiclav resistance.
We can use the Wald test to explore the overall effect of region. We will use the wald.test function of the aod library. The order in which the coefficients are given in the table of coefficients is the same as the order of the terms in the model. This is important because the wald.test function refers to the coefficients by their order in the model. We use the wald.test function. b supplies the coefficients, while Sigma supplies the variance covariance matrix of the error terms, finally Terms tells R which terms in the model are to be tested, in this case, terms 3 to 11, are the three terms for the different regions.
R
# model with just the regions added
wald.test(b = coef(coamox_region_logit), Sigma = vcov(coamox_region_logit), Terms = 3:11)
OUTPUT
Wald test:
----------
Chi-squared test:
X2 = 12815.9, df = 9, P(> X2) = 0.0The chi-squared test statistic of 12815.9, with nine degrees of freedom is associated with a p-value of 0.00 indicating that the overall effect of region is statistically significant.
Challenge 2
Update the model you created in Challenge 1 to include either ethnicity or imd as an independent variable. What is the log-odds reported and is it statistically significant?
If you chose to incorporate imd, this would first need to be converted to a factor
R
amrData$imd <- factor(amrData$imd)
coamox_surg_imd_logit <- glm(
coamox ~ age_years_sd + sex_male + had_surgery_past_yr + imd,
data = amrData,
family = "binomial"
)
summary(coamox_surg_imd_logit)
OUTPUT
Call:
glm(formula = coamox ~ age_years_sd + sex_male + had_surgery_past_yr +
imd, family = "binomial", data = amrData)
Coefficients:
Estimate Std. Error z value Pr(>|z|)
(Intercept) -3.2405156 0.0320951 -100.966 < 2e-16 ***
age_years_sd 0.0404419 0.0004451 90.866 < 2e-16 ***
sex_male 0.0538963 0.0146067 3.690 0.000224 ***
had_surgery_past_yr 0.1801131 0.0238532 7.551 4.32e-14 ***
imd2 -0.0135384 0.0231010 -0.586 0.557840
imd3 -0.0044812 0.0230452 -0.194 0.845821
imd4 -0.0046000 0.0230556 -0.200 0.841857
imd5 0.0216405 0.0230414 0.939 0.347627
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
(Dispersion parameter for binomial family taken to be 1)
Null deviance: 120724 on 99999 degrees of freedom
Residual deviance: 111401 on 99992 degrees of freedom
AIC: 111417
Number of Fisher Scoring iterations: 4As we did not include the 0 flag IMD quintile 1 has been used a reference for the other Quintiles. Quintiles 2 to 5 are not significantly significant. We may want to test that the coefficient for imd=1 is equal to the coefficient for imd=2. The first line of code below creates a vector l that defines the test we want to perform. In this case, we want to test the difference (subtraction) of the terms for imd=1 and imd=2 (i.e., the 4th and 5th terms in the model). To contrast these two terms, we multiply one of them by 1, and the other by -1. The other terms in the model are not involved in the test, so they are multiplied by 0. The second line of code below uses L=l to tell R that we wish to base the test on the vector l (rather than using the Terms option as we did above).
R
l <- cbind(0, 0, 0, 1, -1, 0, 0, 0)
wald.test(b = coef(coamox_surg_imd_logit), Sigma = vcov(coamox_surg_imd_logit), L = l)
OUTPUT
Wald test:
----------
Chi-squared test:
X2 = 33.9, df = 1, P(> X2) = 5.7e-09The chi-squared test statistic of 33.9, with 1 degree of freedom is associated with a p-value of 5.7e-09 indicating that the overall effect of region is statistically significant.
Reporting the Logistic Regression Results
For our model coamox_region_logit there are various things that we can report, and different functions and packages that can be used.
We can report the CIs using profiled log-likelihood or using standard errors for our model.
R
# CIs using log-likelihood
confint(coamox_region_logit)
OUTPUT
Waiting for profiling to be done...OUTPUT
2.5 % 97.5 %
age_years_sd 0.03956087 0.04130508
sex_male 0.02553710 0.08277680
regionEast -3.31607182 -3.17758553
regionEast Midlands -3.28247264 -3.14497346
regionLondon -3.27293944 -3.13585237
regionNorth East -3.28808726 -3.15033821
regionNorth West -3.28650481 -3.14834796
regionSouth East -3.25209244 -3.11466610
regionSouth West -3.29120225 -3.15377971
regionWest Midlands -3.30530677 -3.16702900
regionYorkshire and The Humber -3.32465587 -3.18627353R
## CIs using standard errors
confint.default(coamox_region_logit)
OUTPUT
2.5 % 97.5 %
age_years_sd 0.03955954 0.04130374
sex_male 0.02553490 0.08277421
regionEast -3.31591576 -3.17743094
regionEast Midlands -3.28231824 -3.14482054
regionLondon -3.27278672 -3.13570109
regionNorth East -3.28793328 -3.15018570
regionNorth West -3.28634826 -3.14819290
regionSouth East -3.25194196 -3.11451707
regionSouth West -3.29104882 -3.15362773
regionWest Midlands -3.30515053 -3.16687424
regionYorkshire and The Humber -3.32449918 -3.18611831Alternatively we may be interested in the odds-ratio:
R
## odds ratios only
exp(coef(coamox_region_logit))
OUTPUT
age_years_sd sex_male
1.04126013 1.05564775
regionEast regionEast Midlands
0.03890341 0.04021282
regionLondon regionNorth East
0.04058958 0.03999265
regionNorth West regionSouth East
0.04006426 0.04145157
regionSouth West regionWest Midlands
0.03986174 0.03932038
regionYorkshire and The Humber
0.03856891 R
# including confidence intervals
exp(cbind(OR = coef(coamox_region_logit), confint(coamox_region_logit)))
OUTPUT
Waiting for profiling to be done...OUTPUT
OR 2.5 % 97.5 %
age_years_sd 1.04126013 1.04035382 1.04217000
sex_male 1.05564775 1.02586597 1.08629932
regionEast 0.03890341 0.03629513 0.04168618
regionEast Midlands 0.04021282 0.03753533 0.04306807
regionLondon 0.04058958 0.03789487 0.04346269
regionNorth East 0.03999265 0.03732517 0.04283764
regionNorth West 0.04006426 0.03738429 0.04292298
regionSouth East 0.04145157 0.03869316 0.04439333
regionSouth West 0.03986174 0.03720909 0.04269046
regionWest Midlands 0.03932038 0.03668796 0.04212858
regionYorkshire and The Humber 0.03856891 0.03598490 0.04132558These can also be presented using broom:
R
# as Log-Odds
tidy(coamox_region_logit)
OUTPUT
# A tibble: 11 × 5
term estimate std.error statistic p.value
<chr> <dbl> <dbl> <dbl> <dbl>
1 age_years_sd 0.0404 0.000445 90.9 0
2 sex_male 0.0542 0.0146 3.71 0.000208
3 regionEast -3.25 0.0353 -91.9 0
4 regionEast Midlands -3.21 0.0351 -91.6 0
5 regionLondon -3.20 0.0350 -91.6 0
6 regionNorth East -3.22 0.0351 -91.6 0
7 regionNorth West -3.22 0.0352 -91.3 0
8 regionSouth East -3.18 0.0351 -90.8 0
9 regionSouth West -3.22 0.0351 -91.9 0
10 regionWest Midlands -3.24 0.0353 -91.7 0
11 regionYorkshire and The Humber -3.26 0.0353 -92.2 0 R
# as ORs
tidy(coamox_region_logit, exp = TRUE)
OUTPUT
# A tibble: 11 × 5
term estimate std.error statistic p.value
<chr> <dbl> <dbl> <dbl> <dbl>
1 age_years_sd 1.04 0.000445 90.9 0
2 sex_male 1.06 0.0146 3.71 0.000208
3 regionEast 0.0389 0.0353 -91.9 0
4 regionEast Midlands 0.0402 0.0351 -91.6 0
5 regionLondon 0.0406 0.0350 -91.6 0
6 regionNorth East 0.0400 0.0351 -91.6 0
7 regionNorth West 0.0401 0.0352 -91.3 0
8 regionSouth East 0.0415 0.0351 -90.8 0
9 regionSouth West 0.0399 0.0351 -91.9 0
10 regionWest Midlands 0.0393 0.0353 -91.7 0
11 regionYorkshire and The Humber 0.0386 0.0353 -92.2 0 The odd.n.ends package provides a wide range of reporting tools
R
# Odds ratios and confidence intervals
coamox_region_logitOR <- odds.n.ends::odds.n.ends(coamox_region_logit)
OUTPUT
Waiting for profiling to be done...R
coamox_region_logitCI <- coamox_region_logitOR$`Predictor odds ratios and 95% CI`
coamox_region_logitCI
OUTPUT
OR 2.5 % 97.5 %
age_years_sd 1.04126013 1.04035382 1.04217000
sex_male 1.05564775 1.02586597 1.08629932
regionEast 0.03890341 0.03629513 0.04168618
regionEast Midlands 0.04021282 0.03753533 0.04306807
regionLondon 0.04058958 0.03789487 0.04346269
regionNorth East 0.03999265 0.03732517 0.04283764
regionNorth West 0.04006426 0.03738429 0.04292298
regionSouth East 0.04145157 0.03869316 0.04439333
regionSouth West 0.03986174 0.03720909 0.04269046
regionWest Midlands 0.03932038 0.03668796 0.04212858
regionYorkshire and The Humber 0.03856891 0.03598490 0.04132558R
# model fit
modfit <- coamox_region_logitOR$`Count R-squared (model fit): percent correctly predicted`
modfit
OUTPUT
[1] 70.938R
# Other model statistics
odds.n.ends::odds.n.ends(coamox_region_logit)
OUTPUT
Waiting for profiling to be done...OUTPUT
$`Logistic regression model significance`
Chi-squared d.f. p
27177.424 11 <.001
$`Contingency tables (model fit): frequency predicted`
Number observed
Number predicted 1 0 Sum
1 4613 4510 9123
0 24552 66325 90877
Sum 29165 70835 100000
$`Count R-squared (model fit): percent correctly predicted`
[1] 70.938
$`Model sensitivity`
[1] 0.158169
$`Model specificity`
[1] 0.9363309
$`Predictor odds ratios and 95% CI`
OR 2.5 % 97.5 %
age_years_sd 1.04126013 1.04035382 1.04217000
sex_male 1.05564775 1.02586597 1.08629932
regionEast 0.03890341 0.03629513 0.04168618
regionEast Midlands 0.04021282 0.03753533 0.04306807
regionLondon 0.04058958 0.03789487 0.04346269
regionNorth East 0.03999265 0.03732517 0.04283764
regionNorth West 0.04006426 0.03738429 0.04292298
regionSouth East 0.04145157 0.03869316 0.04439333
regionSouth West 0.03986174 0.03720909 0.04269046
regionWest Midlands 0.03932038 0.03668796 0.04212858
regionYorkshire and The Humber 0.03856891 0.03598490 0.04132558As you can see we have a range of probabilities, odds ratios and log-odds. We need to be aware of which we are referring to. One way is to look at the range of the estimates. Probabilities always have a range from zero to 1. Logit units generally range from about -4 to +4, with zero meaning an equal probability of no event or the event outcome occurring. Odds ratios can range from very small (but positive) numbers to very large positive numbers.
These odds ratios versions of the estimates are more easily interpretable than logit scores. Odds ratios of less than one means that an increase in that predictor makes the outcome less likely to occur, and an odds ratio of greater than one means that an increase in that predictor makes the outcome more likely to occur.
Discussion
- What other indicators could we have included in our model?
- What question(s) would they help us to answer?
Challenge 3
We have explored potential indicators of Coamoxiclav resistance.
Explore potential indicators of either Gentamicin or Ciprofloxacin resistance.
Present your analysis steps and findings in a Quarto report.
Content from SQL and R
Last updated on 2024-12-04 | Edit this page
Estimated time: 150 minutes
Overview
Questions
- What is the relationship between a relational database and SQL?
- How do you query databases using SQL?
- How can I filter data?
- Can SQL be used to make calculations?
- How do I join two tables if they share a common point of information?
Objectives
- Explain what SQL is and why to use it.
- Understand how SQL can be used to query databases
- Write queries that SELECT data based on conditions, such as AND, OR, and NOT and use of the WHERE clause.
- Use SQL functions like AVG in combination with clauses like Group By to aggregate values and make calculations on fields using SQL.
- Understand how to link tables together via joins.
Content
- Relational Databases - an overview
- Creating a SQLite database
- Selecting data
- Filtering data
- Calculated fields and Aggregation
- Joining data
Relational Databases - an overview
In this episode we will be using SQLite, a Relational Database Management Systems (RDBMS) within R. We have chosen SQLite as it is an embedded RDBMS and does not rely on a connection to a server. It uses most of the SQL standard, and it is fully ACID compliant.
What is SQL?
Structured Query Language, or SQL (sometimes pronounced “sequel”), is a powerful language used to interrogate and manipulate relational databases. It is not a general programming language that you can use to write an entire program. However, SQL queries can be called from programming languages to let any program interact with databases. There are several variants of SQL, but all support the same basic statements that we will be covering today.
Relational databases
Relational databases consist of one or more tables of data. These tables have fields (columns) and records (rows). Every field has a data type. Every value in the same field of each record has the same type. These tables can be linked to each other when a field in one table can be matched to a field in another table. SQL queries are the commands that let you look up data in a database or make calculations based on columns.
Why use SQL?
SQL is well established and has been around since the 1970s. It is still widely used in a variety of settings.
SQL lets you keep the data separate from the analysis. There is no risk of accidentally changing data when you are analysing it. If the data is updated, a saved query can be re-run to analyse the new data.
SQL is optimised for handling large amounts of data. Data types help quality control of entries - you will receive an error if you try to enter a word into a field that should contain a number.
Creating a SQLite database
For creating and querying a SQLite database in R we will be using 2 additional packages, RSQLite and DBI.
R
# As RSQLite uses functions defined in the DBI package, we load DBI first
library(DBI)
library(RSQLite)
We will be using data from the Consumer Data Research Centre (CDRC), the Access to Healthy Assets & Hazards (AHAH) from 2022 and the UK Indices of Multiple Deprivation data from 2019. The statistical unit area used in both are Lower layer Super Output Areas (LSOAs).
R
# Import data initially to dataframes
ahah_2022 <- read.csv('data/AHAH_V3_0.csv')
imd_2019 <- read.csv('data/uk_imd2019.csv')
We can now connect to SQLite and create a new empty database:
R
cdrcDB <- dbConnect(RSQLite::SQLite(), "cdrcDB.sqlite")
cdrcDB
OUTPUT
<SQLiteConnection>
Path: /home/runner/work/r-amr-epidemiology/r-amr-epidemiology/site/built/cdrcDB.sqlite
Extensions: TRUEand start adding our tables:
R
#create tables
dbWriteTable(cdrcDB, "ahah", ahah_2022)
ERROR
Error: Table ahah exists in database, and both overwrite and append are FALSER
dbWriteTable(cdrcDB, "imd", imd_2019)
ERROR
Error: Table imd exists in database, and both overwrite and append are FALSER
dbListTables(cdrcDB)
OUTPUT
[1] "ahah" "imd" We can view the Fields in our tables:
R
dbListFields(cdrcDB,"ahah")
OUTPUT
[1] "lsoa11" "ah3gp" "ah3dent" "ah3phar" "ah3hosp"
[6] "ah3blue" "ah3gpas" "ah3ffood" "ah3gamb" "ah3leis"
[11] "ah3pubs" "ah3tob" "ah3no2" "ah3so2" "ah3pm10"
[16] "ah3gp_rnk" "ah3dent_rnk" "ah3phar_rnk" "ah3hosp_rnk" "ah3leis_rnk"
[21] "ah3gpas_rnk" "ah3blue_rnk" "ah3no2_rnk" "ah3so2_rnk" "ah3pm10_rnk"
[26] "ah3gamb_rnk" "ah3pubs_rnk" "ah3tob_rnk" "ah3ffood_rnk" "ah3gp_pct"
[31] "ah3dent_pct" "ah3phar_pct" "ah3hosp_pct" "ah3leis_pct" "ah3gpas_pct"
[36] "ah3blue_pct" "ah3no2_pct" "ah3so2_pct" "ah3pm10_pct" "ah3gamb_pct"
[41] "ah3pubs_pct" "ah3tob_pct" "ah3ffood_pct" "ah3h" "ah3g"
[46] "ah3e" "ah3r" "ah3h_rnk" "ah3g_rnk" "ah3e_rnk"
[51] "ah3r_rnk" "ah3h_pct" "ah3g_pct" "ah3e_pct" "ah3r_pct"
[56] "ah3ahah" "ah3ahah_rn" "ah3ahah_pc" Selecting data
A query is a question or request for data. For example, “What are the IMD deciles for the City of London?”. When we query a database, we can ask the same question using Structured Query Language (SQL) in what is called a statement. Some of the most useful queries are used to return results from a table that match specific criteria.
The basic structure of a SQL query contains a SELECT statement indicating which columns are desired and a FROM clause explaining where to find them:
R
dbGetQuery(cdrcDB, "SELECT LANAME FROM imd LIMIT 10")
OUTPUT
LANAME
1 City of London
2 City of London
3 City of London
4 City of London
5 Barking and Dagenham
6 Barking and Dagenham
7 Barking and Dagenham
8 Barking and Dagenham
9 Barking and Dagenham
10 Barking and DagenhamThe string, “SELECT LANAME FROM imd LIMIT 10” is a SQL query.
SELECT is the statement, and it has the basic syntax of:
SELECT var1, var2 FROM tableWe add an additional clause, LIMIT 10 to reduce the amount of output. This is useful when testing queries, especially when you have a large data set.
In the query above, we have capitalized the words SELECT and FROM because they are SQL keywords. Even though capitalization makes no difference to the SQL interpreter, capitalization of these SQL terms helps for readability and is therefore considered good style.
As the data has repeating area name values (LANAME) due to them containing multiple LSOA units, we can specify unique values using DISTINCT:
R
dbGetQuery(cdrcDB, "SELECT DISTINCT LANAME FROM imd LIMIT 10")
OUTPUT
LANAME
1 City of London
2 Barking and Dagenham
3 Barnet
4 Bexley
5 Brent
6 Bromley
7 Camden
8 Croydon
9 Ealing
10 EnfieldWe can expand our initial query to return Rank in addition to LANAME:
R
dbGetQuery(cdrcDB, "SELECT LANAME, Rank FROM imd LIMIT 10")
OUTPUT
LANAME Rank
1 City of London 29199
2 City of London 30379
3 City of London 14915
4 City of London 8678
5 Barking and Dagenham 14486
6 Barking and Dagenham 7256
7 Barking and Dagenham 5010
8 Barking and Dagenham 6736
9 Barking and Dagenham 6900
10 Barking and Dagenham 7698We can also make use of the wildcard character ’*’ to select all Fields in a table:
R
dbGetQuery(cdrcDB, "SELECT * FROM imd LIMIT 10")
OUTPUT
LSOA LANAME Rank SOA_pct SOA_decile LA_Rank LA_pct
1 E01000001 City of London 29199 89 9 208 66
2 E01000002 City of London 30379 92 10 208 66
3 E01000003 City of London 14915 45 5 208 66
4 E01000005 City of London 8678 26 3 208 66
5 E01000006 Barking and Dagenham 14486 44 5 5 2
6 E01000007 Barking and Dagenham 7256 22 3 5 2
7 E01000008 Barking and Dagenham 5010 15 2 5 2
8 E01000009 Barking and Dagenham 6736 21 3 5 2
9 E01000010 Barking and Dagenham 6900 21 3 5 2
10 E01000011 Barking and Dagenham 7698 23 3 5 2
LA_decile
1 7
2 7
3 7
4 7
5 1
6 1
7 1
8 1
9 1
10 1Sorting
We can also sort the results of our queries by using the keyword ORDER BY. Let’s create a query that sorts the imd table in ascending order by Rank using the ASC keyword in conjunction with ORDER BY.
R
dbGetQuery(cdrcDB, "SELECT *
FROM imd
ORDER BY Rank ASC
LIMIT 10")
OUTPUT
LSOA LANAME Rank SOA_pct SOA_decile LA_Rank LA_pct
1 E01021988 Tendring 1 0 1 32 10
2 W01000240 Denbighshire 1 0 1 10 45
3 S01010891 Inverclyde 1 0 1 3 9
4 95ZZ06W1 Derry City and Strabane 1 0 1 1 9
5 E01012673 Blackpool 2 0 1 1 0
6 W01000239 Denbighshire 2 0 1 10 45
7 S01010245 Glasgow City 2 0 1 1 3
8 95GG47S2 Belfast 2 0 1 4 36
9 E01012681 Blackpool 3 0 1 1 0
10 W01001421 Caerphilly 3 0 1 5 23
LA_decile
1 1
2 5
3 1
4 1
5 1
6 5
7 1
8 3
9 1
10 2ASC is the default, so by omitting ASC or DESC, SQLite will sort ascending (ASC).
Challenge 1
Write a query that returns lsoa11, ah3h_rnk, ah3g_rnk and ah3e_rnk from the ahah table, ordered by the ah3h_rnk from highest to lowest value.
R
dbGetQuery(cdrcDB, "SELECT lsoa11, ah3h_rnk, ah3g_rnk, ah3e_rnk
FROM ahah
ORDER BY ah3h_rnk DESC")
OUTPUT
lsoa11 ah3h_rnk ah3g_rnk ah3e_rnk
1 S01007287 41729 765 72
2 S01011831 41728 109 17
3 S01011832 41727 64 14
4 S01010812 41726 89 2
5 S01009033 41725 7178 15
6 S01009027 41724 451 12
7 S01010814 41723 283 22
8 S01011827 41722 340 7
9 S01009032 41721 4912 13
10 S01010693 41720 20 69
11 S01009029 41719 1350 47
12 S01010691 41718 399 20
13 S01013121 41717 168 158
14 S01010678 41716 2156 61
15 S01009025 41715 259 28
16 S01010669 41714 7 45
17 S01009030 41713 1418 62
18 S01012017 41712 1942 146
19 S01010655 41711 923 31
20 S01010504 41710 8 90
21 S01012406 41709 3 100
22 S01009031 41708 5120 33
23 S01010683 41707 1226 87
24 S01012016 41706 8250 144
25 S01007284 41705 753 68
26 S01010698 41704 1187 5
27 S01010790 41703 557 54
28 S01009028 41702 180 34
29 S01012413 41701 9 75
30 S01010677 41700 91 65
31 S01009021 41699 189 16
32 S01012409 41698 6 53
33 S01012416 41697 5 63
34 S01010771 41696 207 11
35 S01012387 41695 438 44
36 S01007313 41694 307 123
37 E01027503 41693 44 526
38 S01010688 41692 699 37
39 S01007309 41691 126 131
40 S01007308 41690 164 125
41 S01010566 41689 871 89
42 S01012411 41688 1104 136
43 S01007285 41687 634 95
44 S01010671 41686 1541 138
45 S01010676 41685 649 85
46 S01010686 41684 654 10
47 S01009022 41683 36 59
48 S01010530 41682 1033 81
49 S01009024 41681 875 42
50 S01010694 41680 2225 35
51 S01010811 41679 295 1
52 S01012313 41678 2023 1203
53 S01007352 41677 28 173
54 S01011171 41676 296 180
55 S01007288 41675 68 103
56 S01010685 41674 1456 55
57 S01007320 41673 32 109
58 S01007502 41672 3582 344
59 S01012414 41671 17 40
60 S01010506 41670 947 77
61 S01011812 41669 613 104
62 S01010748 41668 1512 161
63 W01000614 41667 2703 2957
64 S01011830 41666 4 80
65 S01011045 41665 3027 105
66 S01009016 41664 414 64
67 S01010810 41663 930 4
68 S01009023 41662 27 60
69 S01013118 41661 528 215
70 S01007510 41660 385 216
71 S01013119 41659 1249 205
72 S01010684 41658 4747 51
73 S01009034 41657 6249 58
74 W01000452 41656 43 1113
75 S01009049 41655 231 124
76 W01000543 41654 788 1111
77 E01027373 41653 1062 652
78 S01012408 41652 271 46
79 S01010528 41651 8057 134
80 E01026538 41650 3256 18490
81 S01012389 41649 2521 101
82 S01011814 41648 998 106
83 S01010798 41647 800 21
84 S01012405 41646 235 133
85 W01000728 41645 4059 2366
86 S01012390 41644 1557 113
87 E01027600 41643 4993 7315
88 W01000723 41642 2234 1929
89 S01006878 41641 3289 220
90 S01010670 41640 73 49
91 S01010757 41639 1745 3
92 S01012412 41638 12 26
93 S01011981 41637 108 142
94 S01007321 41636 892 163
95 S01010796 41635 7070 24
96 S01010508 41634 83 147
97 S01012299 41633 8996 865
98 W01000427 41632 84 1646
99 S01010791 41631 1403 118
100 W01000542 41630 1471 1152
101 S01009048 41629 4892 175
102 E01019229 41628 1050 726
103 S01011956 41627 19707 2782
104 W01000650 41626 893 1523
105 E01027043 41625 1827 13649
106 S01009018 41624 1230 27
107 W01000582 41623 2659 2181
108 S01008282 41622 4960 1692
109 W01000683 41621 1455 2149
110 S01011960 41620 4102 2953
111 S01012407 41619 14 91
112 S01010815 41618 187 8
113 S01006880 41617 8673 954
114 S01011811 41616 691 102
115 W01000559 41615 4400 2596
116 S01011961 41614 15599 3669
117 S01006877 41613 19602 382
118 E01014020 41612 1137 3284
119 S01006999 41611 34964 741
120 W01000085 41610 181 1143
121 E01029338 41609 431 1386
122 S01011809 41608 1509 74
123 E01031990 41607 794 4461
124 S01012388 41606 750 71
125 W01000474 41605 82 1625
126 S01012415 41604 1400 121
127 E01019259 41603 292 876
128 S01007282 41602 2833 335
129 S01010787 41601 10583 92
130 W01000545 41600 4580 2425
131 S01010730 41599 6589 232
132 E01019320 41598 1194 816
133 E01027617 41597 15001 5696
134 W01000538 41596 2098 1556
135 S01010675 41595 1955 18
136 S01012571 41594 1229 467
137 W01000648 41593 1433 2453
138 E01027777 41592 1324 3690
139 S01006993 41591 20507 845
140 S01010764 41590 766 19
141 S01007504 41589 2053 254
142 S01007279 41588 945 265
143 S01012588 41587 9676 1157
144 S01010789 41586 3407 114
145 E01020288 41585 4957 1307
146 W01001932 41584 13792 962
147 S01007004 41583 29825 436
148 E01027512 41582 484 486
149 S01007551 41581 211 248
150 S01007596 41580 1241 349
151 E01020325 41579 11740 2114
152 E01026339 41578 41687 15349
153 S01007571 41577 92 435
154 W01000674 41576 3409 2353
155 S01010665 41575 1466 99
156 E01027773 41574 125 911
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24650 E01023321 17080 3936 28290
24651 E01032094 17079 26585 20338
24652 E01006432 17078 34060 36252
24653 E01032912 17077 29024 36484
24654 E01018365 17076 11080 23382
24655 E01015780 17075 30994 36355
24656 S01011482 17074 19126 10422
24657 E01029985 17073 18200 30209
24658 E01020753 17072 32320 13411
24659 E01023972 17071 24817 25672
24660 E01003664 17070 35161 39516
24661 E01002374 17069 23197 40565
24662 E01020616 17068 30212 8007
24663 E01009103 17067 20934 37341
24664 E01007402 17066 25914 22932
24665 E01018715 17065 4757 20038
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24667 E01005695 17063 13420 36940
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24673 E01016585 17057 2689 32331
24674 S01007008 17056 24142 995
24675 E01017593 17055 35895 22937
24676 E01030382 17054 16725 31161
24677 E01031631 17053 8648 9318
24678 E01026469 17052 23385 20994
24679 E01000764 17051 19472 27162
24680 E01008744 17050 40716 8288
24681 E01017947 17049 7888 25678
24682 E01008610 17048 19056 16175
24683 E01031238 17047 23572 14517
24684 E01008535 17046 23730 19034
24685 E01008134 17045 27248 17815
24686 E01004900 17044 31981 28484
24687 E01016565 17043 821 28375
24688 E01010539 17042 6682 28138
24689 S01008493 17041 32039 12904
24690 W01001488 17040 10822 9146
24691 E01002637 17039 22248 40632
24692 S01009957 17038 8530 8453
24693 E01029094 17037 31152 31322
24694 E01020000 17036 23364 20866
24695 E01031009 17035 16094 18732
24696 E01009490 17034 7755 38028
24697 E01024642 17033 12353 22651
24698 S01007950 17032 12280 1669
24699 E01007052 17031 34276 39011
24700 E01021584 17030 30685 29073
24701 E01015543 17029 26218 26309
24702 E01013183 17028 32956 27426
24703 E01023410 17027 24672 24512
24704 E01012635 17026 19880 17574
24705 E01007780 17025 32072 29687
24706 E01018378 17024 18646 21415
24707 E01030990 17023 559 22068
24708 E01017897 17022 10642 26047
24709 E01018839 17021 13392 13539
24710 E01025239 17020 16898 16552
24711 W01001095 17019 23304 16536
24712 E01030579 17018 3954 33187
24713 S01009095 17017 11048 9429
24714 E01025468 17016 19047 14156
24715 E01028670 17015 11897 15166
24716 E01020870 17014 25036 5422
24717 E01012112 17013 34011 16300
24718 E01026455 17012 40522 14774
24719 E01030468 17011 17446 30298
24720 E01011761 17010 27698 34601
24721 S01009150 17009 2987 7341
24722 E01008202 17008 24009 19203
24723 E01009909 17007 16737 22186
24724 S01010447 17006 14784 10846
24725 E01013983 17005 11120 30373
24726 E01023187 17004 16942 15514
24727 E01007894 17003 40681 24997
24728 S01007033 17002 20146 951
24729 S01008488 17001 4655 11722
24730 E01029484 17000 18120 26778
24731 E01026084 16999 30705 17231
24732 E01017292 16998 11090 13548
24733 E01006048 16997 18904 22306
24734 E01016123 16996 39744 32564
24735 S01008384 16995 8150 6138
24736 E01010786 16994 6835 19062
24737 E01003422 16993 36922 34406
24738 E01029589 16992 30420 25140
24739 W01000962 16991 24760 13391
24740 E01009575 16990 17996 36752
24741 E01010870 16989 22003 27280
24742 E01028090 16988 12883 31882
24743 E01027988 16987 40886 30259
24744 E01008780 16986 31480 12752
24745 E01005497 16985 8992 32504
24746 E01000436 16984 36604 37570
24747 E01010336 16983 20041 40606
24748 E01030801 16982 5333 27807
24749 E01013721 16981 21828 33956
24750 E01004069 16980 29712 37274
24751 E01030938 16979 5929 13943
24752 S01006707 16978 17979 11950
24753 E01006129 16977 7031 33030
24754 E01029226 16976 11181 8580
24755 E01012747 16975 25644 7673
24756 E01009318 16974 29164 39739
24757 E01002947 16973 34967 29747
24758 E01027070 16972 32084 22548
24759 E01009649 16971 40279 31536
24760 E01008409 16970 27364 24481
24761 W01001436 16969 34878 11673
24762 E01010270 16968 25822 40745
24763 E01032173 16967 29767 22761
24764 E01025052 16966 21043 18399
24765 E01006754 16965 7948 33817
24766 E01012895 16964 28801 38189
24767 E01013458 16963 14839 28282
24768 E01007073 16962 20791 23654
24769 E01029413 16961 18900 22635
24770 E01023382 16960 2479 22385
24771 E01031781 16959 34959 29301
24772 E01017939 16958 12979 27914
24773 E01022921 16957 29486 28707
24774 E01021191 16956 14947 8510
24775 E01026962 16955 12438 17063
24776 E01008938 16954 15451 31384
24777 S01009505 16953 35533 7741
24778 E01016598 16952 18296 26532
24779 E01022527 16951 25154 27238
24780 E01030450 16950 22662 35357
24781 W01000861 16949 19479 6906
24782 E01010271 16948 10119 38989
24783 E01015647 16947 36305 27419
24784 E01033733 16946 32429 40755
24785 E01022330 16945 33614 23341
24786 E01031732 16944 13265 14325
24787 E01019095 16943 13307 2398
24788 S01011011 16942 11026 8582
24789 E01008096 16941 35003 31301
24790 E01024023 16940 36947 26303
24791 E01018729 16939 8315 15373
24792 E01020920 16938 10806 18376
24793 E01033668 16937 27009 36745
24794 E01030030 16936 24607 28808
24795 S01007394 16935 422 2389
24796 E01030682 16934 5681 29700
24797 E01015134 16933 27031 11366
24798 E01007036 16932 13467 4115
24799 E01023700 16931 11815 22307
24800 E01005779 16930 16869 27946
24801 E01019232 16929 18859 3820
24802 E01026328 16928 16173 24835
24803 E01004135 16927 32938 35143
24804 E01028377 16926 8654 28225
24805 E01032887 16925 28466 40347
24806 E01024918 16924 7760 19091
24807 E01028481 16923 20953 11816
24808 E01014582 16922 34630 22515
24809 E01003342 16921 38551 38883
24810 E01017811 16920 4087 30487
24811 E01001480 16919 34371 38405
24812 E01011599 16918 38370 30708
24813 E01009024 16917 28396 31660
24814 E01013854 16916 30395 33204
24815 E01010972 16915 23136 18395
24816 E01006648 16914 37340 36965
24817 E01021435 16913 15827 27333
24818 E01007607 16912 13862 27499
24819 E01022555 16911 31110 15149
24820 E01022964 16910 15787 30492
24821 E01007209 16909 33490 22771
24822 E01005369 16908 32458 34304
24823 E01010453 16907 36319 33165
24824 E01026186 16906 29567 26013
24825 E01019426 16905 9102 19761
24826 E01002492 16904 26096 41055
24827 E01023893 16903 36751 31006
24828 E01005970 16902 21211 37173
24829 E01015919 16901 13263 13779
24830 S01006851 16900 35845 4874
24831 E01026432 16899 36123 17571
24832 W01000511 16898 17436 3303
24833 S01012712 16897 8350 4784
24834 E01006607 16896 37181 37434
24835 E01033076 16895 29427 17274
24836 E01020524 16894 27505 4024
24837 E01007309 16893 28934 22896
24838 S01008589 16892 15079 7760
24839 E01009817 16891 17749 20505
24840 E01017755 16890 18177 26546
24841 E01022624 16889 1947 21856
24842 E01012527 16888 10412 30110
24843 E01012806 16887 33993 38770
24844 E01024495 16886 27308 12454
24845 W01001318 16885 15929 12331
24846 E01018575 16884 3885 15374
24847 E01016998 16883 34791 23154
24848 S01007967 16882 9116 2276
24849 E01030325 16881 7010 29748
24850 E01021128 16880 13708 14654
24851 S01012353 16879 13494 1732
24852 S01013133 16878 14852 6307
24853 S01010167 16877 6294 19252
24854 E01025481 16876 33836 18759
24855 E01022498 16875 28836 25408
24856 S01006669 16874 14484 21916
24857 E01000396 16873 28192 36435
24858 E01016670 16872 33850 24569
24859 E01023980 16871 17994 29018
24860 E01029666 16870 9318 16659
24861 E01014685 16869 29853 32865
24862 E01014522 16868 29743 15155
24863 E01007919 16867 22426 18358
24864 E01022494 16866 28957 25408
24865 E01000340 16865 32767 35302
24866 E01021590 16864 18749 27791
24867 E01007924 16863 26510 13073
24868 E01024116 16862 4992 17850
24869 E01008281 16861 25461 14256
24870 E01029350 16860 24894 28610
24871 E01022771 16859 21314 35734
24872 S01010444 16858 14234 10846
24873 E01008268 16857 17883 7851
24874 E01010604 16856 35757 28950
24875 E01010705 16855 25321 11775
24876 S01008982 16854 29055 13625
24877 S01012843 16853 16295 8217
24878 E01011733 16852 31113 32651
24879 E01030793 16851 20421 23551
24880 W01001709 16850 26432 22539
24881 E01024942 16849 16323 15768
24882 E01032605 16848 18032 26585
24883 E01014469 16847 35167 19084
24884 E01032321 16846 20882 9812
24885 E01007435 16845 25272 22645
24886 E01015790 16844 23898 33317
24887 E01007416 16843 20383 21872
24888 S01008903 16842 26266 15606
24889 E01011853 16841 33566 22419
24890 S01012170 16840 18910 14384
24891 E01006270 16839 9765 23250
24892 E01010051 16838 10276 37390
24893 E01024279 16837 21116 37854
24894 E01013284 16836 23851 26906
24895 E01001278 16835 23652 39223
24896 E01006707 16834 38544 29951
24897 E01002966 16833 24397 34637
24898 E01032795 16832 36529 21658
24899 E01006079 16831 2707 25053
24900 E01030516 16830 4918 16939
24901 E01004976 16829 5625 29279
24902 S01008560 16828 25023 9935
24903 E01022933 16827 18266 24003
24904 E01030601 16826 6212 32208
24905 E01019248 16825 2255 6077
24906 E01014128 16824 34593 18374
24907 E01032226 16823 14002 19962
24908 E01016478 16822 10945 36389
24909 E01010174 16821 28315 31568
24910 E01012324 16820 22495 13300
24911 W01001705 16819 29060 16475
24912 E01024219 16818 16952 18308
24913 E01004642 16817 19916 32386
24914 E01025636 16816 20770 35510
24915 E01025289 16815 17019 14990
24916 E01009709 16814 22167 34888
24917 E01006817 16813 30043 30437
24918 E01008526 16812 33697 21079
24919 E01009422 16811 15706 26232
24920 E01010299 16810 15189 38548
24921 E01015254 16809 36932 6582
24922 E01008279 16808 26408 5032
24923 S01007721 16807 39333 8639
24924 E01009724 16806 23415 27870
24925 E01025300 16805 21289 18685
24926 E01006184 16804 12478 32609
24927 E01005186 16803 29915 35388
24928 E01027337 16802 25224 19682
24929 S01008394 16801 12797 7866
24930 E01015286 16800 10866 22890
24931 E01032890 16799 16780 23936
24932 E01004954 16798 8627 32962
24933 W01001446 16797 14815 9799
24934 E01009606 16796 27987 36307
24935 E01006999 16795 37256 10779
24936 E01005705 16794 16148 33826
24937 E01013147 16793 25752 29857
24938 E01005843 16792 19909 28656
24939 E01009498 16791 9483 24633
24940 S01011217 16790 11719 1966
24941 E01010978 16789 16156 13470
24942 E01007141 16788 11169 26130
24943 E01018646 16787 19142 12464
24944 E01010814 16786 41699 30017
24945 E01012167 16785 35984 23405
24946 S01009795 16784 18832 4482
24947 E01021290 16783 32497 28240
24948 E01012876 16782 9095 26264
24949 E01010593 16781 31072 10526
24950 S01011916 16780 25982 5025
24951 E01015333 16779 25424 24292
24952 S01011485 16778 13748 10148
24953 E01028936 16777 16534 6637
24954 S01011350 16776 21031 1205
24955 S01006692 16775 33344 13309
24956 W01001848 16774 33713 26075
24957 E01018531 16773 27293 16694
24958 E01011259 16772 10614 26337
24959 E01017858 16771 12230 30752
24960 E01028022 16770 14420 25526
24961 S01009815 16769 14691 6123
24962 E01002110 16768 37436 34322
24963 E01006297 16767 24344 26752
24964 E01009084 16766 18412 38611
24965 E01031319 16765 11657 19078
24966 E01008637 16764 30028 13363
24967 E01006414 16763 29976 34410
24968 E01029859 16762 6928 29497
24969 S01008885 16761 13581 15338
24970 E01031827 16760 31859 23320
24971 E01007255 16759 24983 13387
24972 E01014278 16758 39877 29924
24973 E01017930 16757 26650 14219
24974 S01011598 16756 13911 16122
24975 S01007922 16755 24086 1959
24976 E01010872 16754 13381 26910
24977 E01003437 16753 2299 37346
24978 E01006093 16752 12231 28641
24979 E01019290 16751 14739 2592
24980 E01009033 16750 26322 31600
24981 S01009847 16749 911 21402
24982 E01009644 16748 41177 29893
24983 S01009959 16747 16269 8990
24984 E01003707 16746 33048 40248
24985 E01016864 16745 20973 21363
24986 E01011992 16744 24381 17469
24987 E01022728 16743 33595 32487
24988 E01029786 16742 7327 16804
24989 S01010355 16741 4881 16035
24990 E01022069 16740 28782 24662
24991 E01010191 16739 13415 27986
24992 E01027948 16738 37386 25720
24993 E01033128 16737 37318 27943
24994 S01012576 16736 19424 1072
24995 E01006757 16735 6577 33629
24996 E01030361 16734 14475 32470
24997 S01013176 16733 358 5199
24998 E01002600 16732 30986 36102
24999 E01003487 16731 32780 40441
[ reached 'max' / getOption("max.print") -- omitted 16730 rows ]Callout
It is important to note that the output from our queries is not saved in the RStudio environment. If needed, query results can be stored as data frames as dbGetQuery() returns the result of a query as a data frame.
For example: ’’’{r}
LANames_Distinct <- dbGetQuery(cdrcDB, “SELECT DISTINCT LANAME FROM imd”)
’’’
Filtering Data
SQL is a powerful tool for filtering data in databases based on a set of conditions. To answer our earlier question: “What are the IMD deciles for the City of London?” we can utilise the WHERE clause.
R
dbGetQuery (cdrcDB, "SELECT LSOA, LANAME, SOA_decile
FROM imd
WHERE LANAME = 'City of London'")
OUTPUT
LSOA LANAME SOA_decile
1 E01000001 City of London 9
2 E01000002 City of London 10
3 E01000003 City of London 5
4 E01000005 City of London 3
5 E01032739 City of London 7
6 E01032740 City of London 6We can add additional conditions by using AND, OR, and/or NOT.
R
dbGetQuery (cdrcDB, "SELECT LSOA, LANAME, SOA_decile
FROM imd
WHERE (SOA_decile < 5) AND (LANAME != 'City of London')
LIMIT 10")
OUTPUT
LSOA LANAME SOA_decile
1 E01000007 Barking and Dagenham 3
2 E01000008 Barking and Dagenham 2
3 E01000009 Barking and Dagenham 3
4 E01000010 Barking and Dagenham 3
5 E01000011 Barking and Dagenham 3
6 E01000012 Barking and Dagenham 2
7 E01000013 Barking and Dagenham 2
8 E01000014 Barking and Dagenham 2
9 E01000015 Barking and Dagenham 2
10 E01000016 Barking and Dagenham 3In this example we modified our query to return only those with a SOA_decile of 1,2, 3 or 4 and from all areas other than City of London. The parantheses are added for readability in this case but can be required by the SQL interpreter in order to disambiguate formulas.
When you do not know the entire value you are searching for, you can use comparison keywords such as LIKE, IN, BETWEEN…AND, IS NULL. For instance, we can use LIKE in combination with WHERE to search for data that matches a pattern.
For example, using the imd table again, let’s SELECT all of the data WHERE the LANAME contains “and”:
R
dbGetQuery (cdrcDB, "SELECT DISTINCT LANAME
FROM imd
WHERE LANAME LIKE '%and%'
LIMIT 10
")
OUTPUT
LANAME
1 Barking and Dagenham
2 Hammersmith and Fulham
3 Kensington and Chelsea
4 Wandsworth
5 Sunderland
6 Sandwell
7 Redcar and Cleveland
8 Rutland
9 Telford and Wrekin
10 Bath and North East SomersetYou may have noticed the wildcard character %. It is used to match zero to many characters. So in the SQL statement above, it will match zero or more characters before and after ‘and’. Because of this you will notice matches with names such as Barking and Dagenham and where it is part of a single word, such as Rutland.
Challenge 2
Write a query that returns lsoa11, ah3h_rnk, ah3g_rnk and ah3e_rnk from the ahah table, where ah3h_rnk is below 500 and ah3e_rnk is between 3500 and 4500. Limit responses to 15.
R
dbGetQuery(cdrcDB, "SELECT lsoa11, ah3h_rnk, ah3g_rnk, ah3e_rnk
FROM ahah
WHERE (ah3h_rnk < 500) OR (ah3e_rnk BETWEEN 3500 AND 4500)
LIMIT 15")
OUTPUT
lsoa11 ah3h_rnk ah3g_rnk ah3e_rnk
1 E01000001 178 40859 41686
2 E01000003 21 40316 41676
3 E01000007 237 26634 41422
4 E01000010 33 37635 41506
5 E01000057 467 17963 40322
6 E01000144 190 38560 39191
7 E01000146 254 40211 39186
8 E01000181 256 40621 37965
9 E01000323 293 33919 37451
10 E01000545 375 38852 39899
11 E01000583 271 31169 40014
12 E01000640 243 41543 40143
13 E01000851 397 41579 41660
14 E01000853 2 39895 41699
15 E01000854 77 41689 41681Calculated fields and Aggregation
SQL contains functions which allow you to make calculations on data in your database for reports. Some of the most common functions are MAX, MIN, AVG, COUNT, SUM, and they will: - MAX (find the maximum value in a field), - MIN (find the minimum value in a field), - AVG (find the average value of a field), - COUNT (count the number of values in a field and present the total), - and SUM (add up the values in a field and present the sum).
Let’s say we wanted to get the average SOA_decile for each of the LANAMEs. We can use AVG and the GROUP BY clause in a query:
R
dbGetQuery (cdrcDB, "SELECT LANAME, AVG(SOA_decile)
FROM imd
GROUP BY LANAME
LIMIT 10
")
OUTPUT
LANAME AVG(SOA_decile)
1 Aberdeen City 6.526502
2 Aberdeenshire 7.173529
3 Adur 5.904762
4 Allerdale 5.083333
5 Amber Valley 6.012821
6 Angus 5.896774
7 Antrim and Newtownabbey 6.722222
8 Ards and North Down 6.813953
9 Argyll and Bute 5.584000
10 Armagh City Banbridge and Craigavon 5.609195GROUP BY is used by SQL to arrange identical data into groups. In this case, we are arranging all the SOA deciles by LANAME. AVG acts on the SOA_decile in parentheses. This process is also called aggregation which allows us to combine results by grouping records based on value and calculating combined values in groups.
As you can see, it is difficult to tell though what LANAME has the highest average SOA decile and the least. We can improve upon the query above by using ORDER BY and DESC.
R
dbGetQuery (cdrcDB, "SELECT LANAME, AVG(SOA_decile)
FROM imd
GROUP BY LANAME
ORDER BY AVG(SOA_decile) DESC
LIMIT 10
")
OUTPUT
LANAME AVG(SOA_decile)
1 Hart 9.385965
2 Wokingham 9.272727
3 Chiltern 8.859649
4 Rushcliffe 8.823529
5 South Northamptonshire 8.784314
6 Mid Sussex 8.767442
7 Waverley 8.719512
8 Epsom and Ewell 8.704545
9 Elmbridge 8.703704
10 Surrey Heath 8.690909Challenge 3
Using the imd table, write a query using an aggregate function that returns the number of LANAMEs per SOA_decile, sorted by LANAME count in descending order. Which SOA_decile has the most LANAMEs? (Hint to choosing which aggregate function to use - it is one of the common aggregate functions MAX, MIN, AVG, COUNT, SUM.)
R
dbGetQuery (cdrcDB, "SELECT SOA_decile, COUNT(LANAME)
FROM imd
GROUP BY SOA_decile
ORDER BY COUNT(LANAME) DESC
LIMIT 10
")
OUTPUT
SOA_decile COUNT(LANAME)
1 10 4263
2 4 4263
3 1 4263
4 8 4262
5 7 4262
6 2 4262
7 9 4261
8 6 4261
9 5 4261
10 3 4261The HAVING keyword
SQL offers a mechanism to filter the results based on aggregate functions, through the HAVING keyword.
For example, we can adapt the last request we wrote to only return information about LANAMEs with an SOA_decile of more than 7:
R
dbGetQuery (cdrcDB, "SELECT LANAME, COUNT(*)
FROM imd
GROUP BY LANAME
HAVING AVG(SOA_decile) > 7
LIMIT 10
")
OUTPUT
LANAME COUNT(*)
1 Aberdeenshire 340
2 Aylesbury Vale 115
3 Basingstoke and Deane 109
4 Bath and North East Somerset 115
5 Blaby 60
6 Bracknell Forest 75
7 Brentwood 46
8 Broadland 84
9 Bromley 197
10 Bromsgrove 58The HAVING keyword works exactly like the WHERE keyword, but uses aggregate functions instead of database fields. When you want to filter based on an aggregation like MAX, MIN, AVG, COUNT, SUM, use HAVING; to filter based on the individual values in a database field, use WHERE.
Note that HAVING comes after GROUP BY. One way to think about this is: the data are retrieved (SELECT), can be filtered (WHERE), then joined in groups (GROUP BY); finally, we only select some of these groups (HAVING).
Calculations
In SQL, we can also perform calculations as we query the database. Also known as computed columns, we can use expressions on a column or multiple columns to get new values during our query. For example, what if we wanted to calculate a new column called Decile_Difference:
R
dbGetQuery (cdrcDB, "SELECT LSOA, LANAME,
SOA_decile - LA_decile as Decile_Difference
FROM imd
ORDER BY Decile_Difference DESC
LIMIT 10
")
OUTPUT
LSOA LANAME Decile_Difference
1 E01004276 Tower Hamlets 9
2 E01005716 Salford 9
3 E01005717 Salford 9
4 E01005739 Salford 9
5 E01005741 Salford 9
6 E01006072 Tameside 9
7 E01006583 Liverpool 9
8 E01008619 South Tyneside 9
9 E01009421 Birmingham 9
10 E01009426 Birmingham 9In this example we used the calculation and AS to represent that the new column is different from the original SQL table data.
We can use any arithmetic operators (like +, -, *, /, square root SQRT or the modulo operator %) if we would like.
Joining Data
The SQL JOIN clause allows us to combine columns from one or more tables in a database by using values common to each. It follows the FROM clause in a SQL statement. We also need to tell the computer which columns provide the link between the two tables using the word ON.
Let’s start by joining data from the ahah table with the imd table. The LSOA and lsoa11 columns in these tables link them.
R
dbGetQuery (cdrcDB, "SELECT *
FROM ahah
JOIN imd
ON ahah.lsoa11 = imd.LSOA
")
OUTPUT
lsoa11 ah3gp ah3dent ah3phar ah3hosp ah3blue ah3gpas
1 E01000001 2.106000 0.400000 0.5616000 0.492000 2.875774 0.10944202
2 E01000002 3.146895 0.887500 0.8791789 1.448895 2.936500 0.08531034
3 E01000003 1.151000 0.000000 0.3475000 0.649500 3.272200 0.13799111
4 E01000005 1.462800 0.565000 0.9426000 1.224050 2.095000 0.07735466
5 E01000006 1.585000 2.150000 1.8675000 1.585000 2.794750 0.33102761
6 E01000007 0.177500 0.647500 1.0775000 0.517500 1.294500 0.20880054
7 E01000008 2.641000 3.111000 3.2585000 2.861000 0.782500 0.44051302
8 E01000009 0.805000 1.370000 1.8675000 0.805000 1.982500 0.20316115
9 E01000010 1.170000 0.275000 0.2750000 0.220400 1.906000 0.13327213
10 E01000011 1.063900 1.960700 1.9607000 1.063900 0.622500 0.22165360
11 E01000012 0.275000 1.706800 1.7068000 0.275000 1.661950 0.24409540
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62 E01000065 1.234500 1.277000 1.3866000 0.634550 5.006450 0.37615857
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130 E01000133 1.485000 1.485000 1.9725000 3.719000 9.855000 0.44167531
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934 E01000951 0.526250 1.449700 1.0261500 0.828800 3.574200 0.41917494
935 E01000952 1.222000 0.866400 1.0764000 0.787000 2.506800 0.33440799
936 E01000953 1.712900 1.693300 1.6909000 1.338350 1.787600 0.18618304
937 E01000954 1.168000 1.313600 0.4811263 1.619600 3.712400 0.31709156
938 E01000955 0.611700 1.456000 0.2717000 1.738100 4.280000 0.18375161
939 E01000956 1.187700 0.927600 0.9875000 1.071800 3.712400 0.22035421
940 E01000957 1.507200 1.850400 0.6631000 1.326300 3.012800 0.34035063
941 E01000958 1.195000 1.525900 1.3692000 0.695000 2.288900 0.17816171
942 E01000959 0.962900 0.866400 0.9084000 0.617500 2.657500 0.30972722
943 E01000960 2.446903 1.524368 2.5015000 1.263600 5.554253 0.31806690
944 E01000961 1.836000 1.025817 2.4058351 1.537467 4.966267 0.36156988
945 E01000962 1.870000 1.663800 2.1985000 1.610000 5.518167 0.40618879
946 E01000963 1.016300 0.494400 1.5529000 1.056000 3.241900 0.28316009
947 E01000964 2.090000 1.669000 2.2090000 0.692500 6.078167 0.51045889
948 E01000965 0.421250 0.397500 1.0877500 0.421250 5.823500 0.43526675
949 E01000966 0.555550 0.555550 1.2700000 0.555000 5.746000 0.49940342
950 E01000967 1.297500 1.543400 1.6475000 1.171600 2.107200 0.50677538
951 E01000968 1.380000 0.696700 1.3464000 0.815000 6.654800 0.35587254
952 E01000969 1.579850 0.289300 0.3651000 1.579850 5.493300 0.27712311
953 E01000970 1.122500 0.413300 0.4716000 1.122500 5.884600 0.24242918
954 E01000971 0.167500 0.803750 0.7950000 0.167500 6.720600 0.28046602
955 E01000972 3.823600 2.469600 2.5795000 2.265600 5.010300 0.24010263
956 E01000973 1.852800 0.708000 0.7080000 1.283200 6.182000 0.22193208
957 E01000974 1.773600 0.957500 0.8450000 1.773600 6.942800 0.23021245
958 E01000975 3.075400 1.494000 1.2596000 2.383500 10.191700 0.30533856
959 E01000976 2.336400 0.621300 0.8756000 1.598800 9.171900 0.27209975
960 E01000977 0.847200 1.577200 0.8472000 1.276700 9.179400 0.47899979
961 E01000978 1.351200 1.917600 1.3512000 1.793500 9.488300 0.49956220
962 E01000979 2.271700 1.302800 1.6232000 2.209100 10.374200 0.34359236
963 E01000980 2.071600 2.578600 1.8901500 1.275700 8.783900 0.35130364
964 E01000981 2.027800 2.198600 0.7485000 1.292400 7.390000 0.36495432
965 E01000982 1.265000 1.552200 1.6365000 0.807500 8.391700 0.36786616
966 E01000983 1.002500 1.380300 1.0025000 1.459000 8.463100 0.33892000
967 E01000984 1.449700 1.145100 1.6017500 0.750700 9.058300 0.35354722
968 E01000985 0.982000 1.111300 1.1331000 0.904500 8.104200 0.46333894
969 E01000986 1.302200 1.182500 1.5326500 1.662500 8.871400 0.51193935
970 E01000987 2.444300 1.344000 2.0038000 2.139000 8.257600 0.37144673
971 E01000989 4.101000 1.339000 1.3390000 3.747800 5.342700 0.40108347
972 E01000990 1.533100 2.303800 2.4038000 0.600000 5.320800 0.40589887
973 E01000991 4.607000 1.975000 1.9750000 4.383800 6.614700 0.46874492
974 E01000992 0.622500 1.812400 2.2975000 1.616300 5.697000 0.46327919
975 E01000993 1.359900 0.761100 0.8565000 2.249600 7.374300 0.36573148
976 E01000994 2.022450 1.559500 1.5263500 1.016250 8.132450 0.42040390
977 E01000995 1.855850 0.934250 1.2704500 0.975500 8.151100 0.30825488
978 E01000996 1.234900 1.307500 1.2349000 0.795000 7.681300 0.31773192
979 E01000997 0.543700 0.550000 0.6613000 0.661300 6.586950 0.29796365
980 E01000998 0.937300 0.912500 1.4477000 1.635200 6.436300 0.32251739
981 E01000999 1.129700 1.381500 1.1297000 0.793700 7.821600 0.28926358
982 E01001000 1.064400 1.359500 0.8230000 1.790000 6.383600 0.30943245
983 E01001001 1.676250 2.374000 1.6110000 1.237200 5.373600 0.40476672
984 E01001002 0.465450 0.824250 0.5242500 0.524250 7.091200 0.32634343
985 E01001003 1.660800 1.958000 1.6342500 1.650000 6.473700 0.37246764
986 E01001004 1.678500 1.493500 2.2950000 1.065500 8.413350 0.34339255
987 E01001005 1.068100 1.224200 0.8090000 1.442500 9.095200 0.27788061
988 E01001006 2.860600 4.708600 2.0881000 3.707000 6.701300 0.31066847
989 E01001007 2.265000 4.625000 2.2650000 4.629000 6.094800 0.29340926
990 E01001008 1.678750 2.993300 2.0264000 3.216000 7.170000 0.34576763
991 E01001009 0.956000 2.037200 1.3530000 2.150000 8.684800 0.27098358
992 E01001010 2.267500 2.683200 2.0304000 2.630100 7.239150 0.27761769
993 E01001011 1.394400 1.380800 0.7378500 1.225500 8.685800 0.23585136
994 E01001012 1.189200 1.030200 0.8131000 0.447600 8.193900 0.29794532
995 E01001013 1.264000 0.845000 1.0917000 1.175600 8.256800 0.28592330
996 E01001014 2.074000 1.465000 1.3255000 1.495500 6.065800 0.13821596
997 E01001015 3.963300 2.911700 3.0396000 1.639400 16.718900 0.56278968
998 E01001016 5.221300 3.596750 4.8688000 3.125000 16.313000 0.54636419
999 E01001017 6.003300 4.582700 4.5827000 3.856900 16.077360 0.61022913
1000 E01001018 2.077000 1.740000 1.9695000 4.691500 20.960100 0.56384778
1001 E01001019 2.731600 2.269100 2.8391000 1.656050 18.328800 0.58616614
1002 E01001020 1.654600 0.797500 1.4964000 3.556100 19.438600 0.46522385
1003 E01001021 3.108900 1.756300 2.3171000 4.602600 20.072300 0.55233610
1004 E01001022 3.037500 1.861000 2.8100000 5.346600 19.851700 0.53857553
1005 E01001023 3.308650 1.809600 2.0820000 4.591200 15.301900 0.39335129
1006 E01001024 2.476600 2.259600 1.3344000 4.414500 15.043000 0.51499116
1007 E01001025 3.454000 4.024450 2.9000500 3.872900 16.582600 0.47632767
1008 E01001026 5.090200 3.978750 1.3008500 3.454800 17.510950 0.45738396
1009 E01001027 8.257600 6.837000 5.6100000 6.473900 17.384300 0.52210885
1010 E01001028 4.655800 3.551500 4.5268000 2.368800 11.409400 0.62198973
1011 E01001029 3.123768 1.349000 1.7377684 1.850250 13.139500 0.59092608
1012 E01001030 4.263200 2.000150 3.4038184 3.031900 13.160600 0.58221102
1013 E01001031 1.401500 1.793400 1.7398000 4.235000 13.630600 0.57052490
1014 E01001032 3.004300 3.933700 1.3327500 3.887150 11.694850 0.57547277
1015 E01001033 2.373500 0.993100 1.4090000 2.139300 10.144800 0.44228229
1016 E01001034 2.055700 1.124300 1.2587000 2.055700 10.462500 0.46810848
1017 E01001035 1.399100 1.770600 2.1748000 3.335650 8.222000 0.50463942
1018 E01001036 3.622000 4.036300 4.5215500 4.521000 10.486550 0.62262189
1019 E01001037 1.747700 1.364400 1.1736000 2.678100 7.094100 0.32206637
1020 E01001038 3.418900 3.684300 3.4665000 4.764800 9.813700 0.51439524
1021 E01001039 2.895300 3.159300 2.8529500 3.927300 9.588400 0.54777628
1022 E01001040 1.380250 1.459550 1.5115000 2.227550 8.196800 0.35243872
1023 E01001041 1.752000 1.110000 1.2444000 2.070600 9.471200 0.43508935
1024 E01001042 1.052500 1.127500 0.9375000 0.771000 6.230300 0.21636939
1025 E01001043 1.111600 0.813200 0.9305000 0.720000 6.694300 0.13282123
1026 E01001044 2.175900 2.750300 3.6010000 3.918500 9.369700 0.55294400
1027 E01001045 1.703100 1.610100 1.3196000 1.416000 8.476800 0.20241745
1028 E01001046 3.069400 3.099300 3.7705000 3.915300 10.263200 0.54258519
1029 E01001047 1.322800 0.333600 1.1843000 1.576800 6.969900 0.39044547
1030 E01001048 1.292250 1.210000 0.7365000 1.117550 8.140050 0.20988958
1031 E01001049 2.459600 2.994500 2.5282000 2.531100 10.330600 0.62810266
1032 E01001050 2.850750 2.291750 2.7923000 3.456350 10.924200 0.49900863
1033 E01001051 3.707500 5.282500 1.3347500 3.676500 22.480300 0.42066468
1034 E01001052 1.790000 4.920500 1.6960000 3.437500 24.052050 0.43014042
1035 E01001053 2.300000 2.576500 1.6172500 2.568750 24.651550 0.47010759
1036 E01001054 3.408500 3.870000 2.0575000 2.204500 22.178300 0.43382233
1037 E01001055 1.162500 3.760500 1.5560000 2.490000 23.981300 0.48960942
1038 E01001056 1.828500 2.398500 0.4375000 2.166000 23.807300 0.49575412
1039 E01001057 1.611000 1.961000 1.4800000 1.316000 23.476300 0.50754231
1040 E01001058 6.292900 3.767800 3.0890000 4.107600 20.790000 0.50053978
1041 E01001059 5.308900 3.949300 3.2705000 3.123600 19.806000 0.53820652
1042 E01001060 6.930400 4.336300 3.6575000 4.745100 21.677500 0.55775547
1043 E01001061 4.006300 2.056400 2.0564000 0.940000 18.503400 0.49464600
1044 E01001062 2.078700 1.387900 1.2453000 2.554300 10.464200 0.53212285
1045 E01001063 1.706300 0.903750 0.8628000 3.364000 11.136050 0.41918996
1046 E01001064 6.650200 3.072000 3.3792000 4.950200 16.405200 0.66509819
1047 E01001065 6.944900 3.727800 3.2390000 4.867600 20.399600 0.56271225
1048 E01001066 4.192550 3.461400 3.4614000 1.976500 18.689650 0.51440251
1049 E01001067 5.610332 4.138200 4.8307579 4.684400 16.559808 0.64185751
1050 E01001068 2.698500 2.257500 2.2575000 7.913963 19.524158 0.61209917
1051 E01001069 4.733500 3.556000 3.5560000 6.197863 17.808058 0.62846386
1052 E01001070 7.662863 5.890700 6.9020079 6.936132 18.965558 0.60692298
1053 E01001071 4.402500 5.120100 3.1451500 10.333763 21.943958 0.54259771
1054 E01001072 7.662500 6.981000 6.9810000 11.690863 23.433058 0.65050399
1055 E01001073 3.332863 2.991363 2.5887579 2.991363 14.601558 0.53534314
1056 E01001074 4.720400 2.696900 3.6832579 3.467300 14.943558 0.48391673
1057 E01001075 3.128500 1.724600 1.7246000 4.789963 16.400158 0.54555917
1058 E01001076 3.385000 2.377500 1.8885000 2.198250 26.283700 0.49965186
1059 E01001077 1.305000 0.477500 0.9625000 0.600000 25.294800 0.36998153
1060 E01001078 2.427500 1.547500 1.4925000 1.790500 24.902550 0.49158016
1061 E01001079 5.053500 4.050000 3.4530000 3.767000 27.595700 0.46647598
1062 E01001080 2.832500 1.825000 1.6175000 2.651500 26.470300 0.46915454
1063 E01001081 4.427500 3.420000 2.7205000 3.422000 25.389700 0.48711097
1064 E01001082 4.391000 4.272500 3.8505000 3.989500 28.185800 0.49188572
1065 E01001083 2.376000 1.713900 1.7907000 2.264800 9.567600 0.39806527
1066 E01001084 3.693000 2.913000 1.5145000 3.346700 8.591500 0.49532148
1067 E01001085 0.747500 0.597100 0.9075000 1.803400 9.248100 0.31173789
1068 E01001086 1.804300 0.906900 1.1853000 1.410900 8.953800 0.34759653
1069 E01001087 1.419300 1.368100 1.0968000 0.920800 9.016400 0.30476311
1070 E01001088 2.248500 2.095000 2.0650000 2.467800 7.225600 0.32879473
1071 E01001089 1.550000 1.527500 1.8631000 1.719600 8.462100 0.31406984
1072 E01001090 1.368100 1.053600 1.0456000 0.686500 8.764600 0.32200667
1073 E01001091 1.269500 1.060000 1.3005000 1.173500 8.414300 0.48169541
1074 E01001092 2.382000 1.806600 1.3529000 2.945500 10.895500 0.58004129
1075 E01001093 2.148900 1.245450 1.8126500 1.876500 12.266800 0.52218223
1076 E01001094 4.517300 3.845400 3.9407000 2.917100 10.248000 0.65094697
1077 E01001095 2.038800 1.322400 1.5816000 0.859200 11.513600 0.37051627
1078 E01001096 3.268900 3.322000 2.3750000 1.976900 12.409900 0.55277896
1079 E01001097 1.343000 0.958050 0.3900000 0.953500 13.199942 0.24641863
1080 E01001098 3.244900 3.939300 2.6438000 3.034400 14.335900 0.61958480
1081 E01001099 3.142500 3.116800 2.7959579 3.305563 14.915758 0.50729203
1082 E01001100 2.425700 2.209700 0.8914000 2.396800 10.832500 0.47173387
1083 E01001101 1.875500 2.170000 3.3942000 2.281900 15.243200 0.59815407
1084 E01001102 3.263000 2.974100 1.1583500 1.743600 15.482100 0.58420226
1085 E01001103 3.891000 4.228200 2.0717000 3.386700 17.485400 0.54460657
1086 E01001104 1.237500 4.376800 2.1390000 3.448300 16.472900 0.59318626
1087 E01001105 4.303800 2.398300 1.6004000 5.030200 19.049400 0.47856033
1088 E01001106 3.397250 1.358150 0.8542500 5.999100 20.018300 0.48050815
1089 E01001107 3.504000 2.384900 2.0225000 3.649300 12.593600 0.62946463
1090 E01001108 3.663000 2.175200 2.1871000 2.775700 13.488200 0.60612986
1091 E01001109 1.016050 2.233300 1.0425000 1.255600 6.596450 0.29044244
1092 E01001110 1.100050 0.875400 0.5856000 0.914400 7.763750 0.34750810
1093 E01001111 1.161500 1.998000 1.1542000 0.885000 3.598000 0.29019356
1094 E01001112 2.163700 2.297400 1.7569000 0.936000 3.905250 0.38916943
1095 E01001113 1.453250 2.769700 1.4748500 0.717900 4.801950 0.36508000
1096 E01001114 1.863600 2.615800 1.8528000 0.370000 5.014400 0.32533020
1097 E01001115 1.216000 1.475600 1.3941000 0.802600 7.469400 0.34349045
1098 E01001116 0.942500 2.023500 1.0913000 1.167350 6.480950 0.32701364
1099 E01001117 1.498500 1.224200 0.8090000 1.204800 9.194600 0.28161770
1100 E01001118 0.492400 1.195300 0.8340000 1.278000 6.689000 0.30338545
1101 E01001119 6.354400 5.108000 4.7925000 4.666600 20.851500 0.45589721
1102 E01001120 2.543000 2.145500 2.0850000 2.547500 17.040100 0.48203835
1103 E01001121 5.395500 4.993500 4.9935000 5.384100 19.926700 0.56786835
1104 E01001122 5.083800 4.970800 5.4247000 5.685200 15.542600 0.63895384
1105 E01001123 5.251500 4.485800 5.9490000 5.685200 15.986100 0.58468640
1106 E01001124 1.084900 2.833700 1.9417000 2.172500 14.154500 0.61050129
1107 E01001125 0.661200 0.968400 0.6975000 1.261200 15.192400 0.46950996
1108 E01001126 3.510500 2.910900 2.9109000 2.360700 18.007600 0.44871739
1109 E01001127 1.216000 3.673600 1.2160000 1.168000 12.796600 0.49894255
1110 E01001128 1.375600 4.363000 1.4005000 1.310500 12.888500 0.50541359
1111 E01001129 1.947300 2.327500 1.9285000 2.188000 12.606600 0.45438162
1112 E01001130 1.795500 5.055500 1.7955000 1.705500 13.581000 0.55535489
1113 E01001131 4.715000 4.472500 2.0587500 6.743800 5.342550 0.41843629
1114 E01001132 3.370000 3.617750 2.9217000 6.269850 7.594650 0.50022295
1115 E01001133 1.166400 1.953400 1.4112000 2.964000 11.339700 0.50602639
1116 E01001134 2.864400 2.201850 2.1396000 3.061700 10.230550 0.48323992
1117 E01001135 1.096250 2.611800 1.6753000 1.096250 11.361600 0.51509225
1118 E01001136 1.812100 1.041700 0.9912000 1.084800 2.580400 0.36602616
1119 E01001137 0.948700 1.455800 1.4959000 3.023100 3.991400 0.55108833
1120 E01001138 1.837100 2.947900 2.6103000 3.537000 4.173700 0.59057516
1121 E01001139 0.658900 1.938800 1.5715000 2.466900 1.546200 0.42829728
1122 E01001140 1.645000 2.130400 2.1891500 3.875850 2.102400 0.57166022
1123 E01001141 2.222300 1.452200 1.9682000 2.913800 0.526000 0.52445930
1124 E01001142 1.413200 1.245900 1.4143500 2.307950 1.284350 0.41054955
1125 E01001143 2.732900 0.682100 1.5725000 2.518100 2.019300 0.41990945
1126 E01001144 1.331200 1.389000 1.1955000 1.550500 2.307600 0.35758884
1127 E01001145 1.777300 0.646000 1.0800000 2.004300 1.944400 0.29136156
1128 E01001146 1.419000 1.847500 1.5825000 3.467400 4.114200 0.32537779
1129 E01001147 1.236000 1.668000 0.6552000 3.002500 5.913000 0.32285601
1130 E01001148 1.736000 2.131700 1.8109000 4.165200 4.059200 0.33942106
1131 E01001149 2.008150 1.787500 1.7189000 3.668800 3.414050 0.39938672
1132 E01001150 1.699800 2.225200 1.6427000 3.026200 1.886700 0.47171718
1133 E01001151 1.173900 1.173900 0.6514500 2.703700 6.334200 0.42363039
1134 E01001152 0.675250 0.734650 0.6839000 2.541300 5.411700 0.29633135
1135 E01001153 1.073000 1.594350 1.2254000 2.208250 5.121500 0.34418914
1136 E01001154 0.743400 1.372300 0.6873000 1.335500 3.916700 0.29087302
1137 E01001155 1.044000 1.376300 0.8779000 1.313000 4.903600 0.25418940
1138 E01001156 1.897500 1.867550 1.6132000 3.810000 4.403150 0.52585402
1139 E01001157 3.784700 3.854000 2.3088000 2.087500 7.065750 0.44619599
1140 E01001158 2.143600 0.955200 0.8196000 4.161300 3.057600 0.52083886
1141 E01001159 3.758000 3.437400 2.6687000 3.792100 5.959200 0.50366676
1142 E01001160 2.558400 3.071000 2.2088000 2.101900 6.176200 0.43418926
1143 E01001161 2.782000 2.767000 2.1767500 0.997200 7.928100 0.54101843
1144 E01001162 2.719700 2.660000 2.5679000 3.666100 6.349700 0.46033591
1145 E01001163 2.571800 2.863200 1.4218500 2.977550 6.962100 0.41161324
1146 E01001164 2.474100 1.125000 1.0188000 2.038200 5.123000 0.28055242
1147 E01001165 5.059500 2.715900 2.9177000 4.224300 1.499100 0.33870389
1148 E01001166 2.395500 2.360500 1.8995000 2.032000 4.503800 0.30537638
1149 E01001167 3.672700 1.066200 2.0148000 2.422800 1.492000 0.38179618
1150 E01001168 4.169000 2.946000 3.2000000 3.238050 3.577050 0.43078048
1151 E01001169 0.722500 0.845000 2.7082000 1.249900 4.604300 0.49395734
1152 E01001170 2.238400 1.195900 1.0595000 2.233050 6.055500 0.46673313
1153 E01001171 1.749400 1.750000 2.2759000 1.945500 5.185300 0.50122118
1154 E01001172 2.405700 1.536000 2.4139000 1.279200 4.163800 0.34694189
1155 E01001173 3.657400 3.449500 3.5839000 3.577500 10.276200 0.53681964
1156 E01001174 1.626900 2.717000 2.5059000 2.416500 7.833800 0.30730972
1157 E01001175 0.923800 0.923800 1.0656000 0.923800 8.393500 0.33043396
1158 E01001176 0.871700 1.947600 1.3079000 1.947600 8.158200 0.28544813
1159 E01001177 2.084300 4.341800 2.0843000 4.448300 6.217300 0.26023462
1160 E01001178 0.939500 0.939500 1.1784000 0.485000 8.532700 0.30455244
1161 E01001179 0.423800 1.989000 0.8790000 1.989000 8.043200 0.29636697
1162 E01001180 0.956000 2.726500 0.9925000 2.726500 7.182300 0.26700848
1163 E01001181 1.067000 1.279100 0.8160000 1.347800 9.094050 0.27894887
1164 E01001182 1.517900 1.087000 1.2110000 1.353400 7.426100 0.34211886
1165 E01001183 1.795800 1.909100 1.7916000 1.567200 8.158200 0.24435942
1166 E01001184 2.329400 2.112000 1.9945000 2.042000 7.371100 0.36280441
1167 E01001185 1.790400 1.545600 1.4850000 1.828500 5.815600 0.39719480
1168 E01001186 1.361000 1.814600 2.9047000 1.442400 5.057200 0.41282311
1169 E01001187 2.847300 3.387350 1.2000000 1.974450 7.900700 0.41679892
1170 E01001188 1.439000 2.143050 3.0588000 1.288250 4.403200 0.34111661
1171 E01001189 1.287400 1.522900 2.8272500 2.108400 5.429400 0.33386307
1172 E01001190 2.464200 1.839200 2.5221000 2.915700 3.419300 0.34445891
1173 E01001191 1.741750 0.958950 1.9144000 1.585500 3.258800 0.26613587
1174 E01001192 1.558200 1.400700 1.9344000 2.009700 3.278800 0.33456871
1175 E01001193 4.142550 4.621250 2.4885000 2.831700 7.357800 0.41173086
1176 E01001194 1.104900 1.335400 2.7795500 1.971200 4.129100 0.30034554
1177 E01001195 2.637000 3.275000 1.2237500 2.676858 6.392258 0.45196596
1178 E01001196 1.615500 2.472500 1.4697000 2.084058 5.523300 0.31144625
1179 E01001197 1.727450 2.011200 1.3968500 3.218650 7.177100 0.43702701
1180 E01001198 1.565000 1.997600 1.4697000 2.084058 5.918300 0.32778150
1181 E01001199 0.702100 1.187500 0.7021000 2.212500 6.554500 0.35317034
1182 E01001200 0.552500 0.715000 1.3125000 0.552500 7.540800 0.29354537
1183 E01001201 0.855000 0.540000 0.8462500 1.572500 7.393300 0.34964766
1184 E01001202 0.676800 0.805000 0.4728000 1.307600 7.616400 0.24084775
1185 E01001203 0.426500 0.270750 0.8187500 0.356250 8.124050 0.26352312
1186 E01001204 0.845000 2.324800 2.4223000 2.280000 2.366400 0.38623255
1187 E01001205 2.035000 2.692500 1.8275000 2.326000 3.500000 0.42145184
1188 E01001206 1.865000 3.041300 2.6365000 3.750000 2.729500 0.43953750
1189 E01001207 1.004500 1.451100 1.1271000 1.197500 3.722950 0.32398506
1190 E01001208 1.597500 1.471300 1.5570000 3.681000 1.392500 0.41172504
1191 E01001209 0.717500 0.843750 0.6192500 4.078800 0.657500 0.40032306
1192 E01001210 2.745000 1.451300 2.9323000 4.492700 1.695600 0.48011279
1193 E01001211 0.855000 0.855000 1.0550000 3.571300 1.432500 0.51550281
1194 E01001212 1.503750 1.568900 1.5368000 3.180200 2.055800 0.45640181
1195 E01001213 0.750000 1.234750 1.1325000 1.313300 2.673750 0.29833755
1196 E01001214 1.237500 2.157500 0.9592500 1.137500 3.102500 0.28610177
1197 E01001215 0.872250 1.422050 0.5574500 1.233900 3.455000 0.22036388
1198 E01001216 1.881000 3.072000 2.1049000 2.267500 4.307500 0.36813641
1199 E01001217 1.678250 2.424250 1.3345000 2.044000 3.143300 0.32534523
1200 E01001218 2.940500 3.545800 1.1218000 2.647600 2.500800 0.41090369
1201 E01001219 1.735000 3.367500 1.4623000 2.647600 3.091900 0.44626999
1202 E01001220 2.773300 3.763250 1.2199000 2.800750 2.843150 0.38467163
1203 E01001221 1.875250 1.296000 1.1471000 1.101100 5.011500 0.22645757
1204 E01001222 0.676750 0.546400 0.7275000 0.290000 4.768600 0.21903351
1205 E01001223 1.207500 1.815000 1.8000000 2.600800 3.935000 0.52168191
1206 E01001224 0.762300 1.534100 2.0834500 1.947700 2.904700 0.46256413
1207 E01001225 0.926000 0.492500 0.5600000 1.066100 4.555000 0.45097959
1208 E01001226 2.015700 1.836000 2.1830000 2.136000 2.960000 0.50232661
1209 E01001227 1.515000 1.763700 2.1177000 1.713600 3.621200 0.43828446
1210 E01001228 1.996900 1.575850 1.9239000 1.102500 4.494400 0.47134587
1211 E01001229 1.973400 1.510000 1.6300000 1.973400 4.979726 0.39294264
1212 E01001230 2.170000 1.178500 2.1145000 2.396000 6.044300 0.35887286
1213 E01001231 1.628800 1.147200 1.2988000 3.442800 6.618189 0.42183155
1214 E01001232 2.468400 2.215850 2.6850000 2.771500 5.985426 0.38110992
1215 E01001233 1.334100 0.660350 0.9557000 1.334100 4.340426 0.32233834
1216 E01001234 2.667650 1.333500 2.2908500 2.807400 7.723313 0.48670891
1217 E01001235 1.484500 0.912400 1.3261000 1.249300 6.033300 0.44359466
1218 E01001236 1.055000 1.553800 1.6740000 1.567300 6.111500 0.43310016
1219 E01001237 1.365000 1.956300 2.6820000 1.928600 6.699000 0.53066146
1220 E01001238 1.196600 3.970258 1.1870000 1.117200 4.144800 0.25498342
1221 E01001239 2.133750 3.288650 1.7416000 2.133750 3.400000 0.27310929
1222 E01001240 0.836250 1.017500 1.0175000 0.893000 4.556750 0.39272381
1223 E01001241 1.815500 2.371150 2.1460000 1.934250 7.341000 0.29823539
1224 E01001242 2.090000 2.347500 2.0900000 1.920000 7.365800 0.45386511
1225 E01001243 0.862250 1.518600 1.0544000 1.105000 7.337750 0.33245364
1226 E01001244 1.182350 1.132800 0.9974000 2.041250 8.041500 0.39101841
1227 E01001245 0.716900 1.477200 1.2778000 2.118500 7.237300 0.23970476
1228 E01001246 2.085900 3.438300 1.8171000 1.851000 1.517500 0.10841702
1229 E01001247 2.132000 4.772500 1.8925000 2.132000 5.047400 0.12914720
1230 E01001248 2.167000 1.452000 1.8345000 2.241250 1.076900 0.34002674
1231 E01001249 0.646450 0.820700 0.2880000 0.484700 3.255800 0.17889467
1232 E01001250 0.695100 0.717100 0.5976000 0.622500 2.579200 0.30677253
1233 E01001251 0.747850 0.747850 0.7478500 0.470000 1.354200 0.30105686
1234 E01001252 1.130600 1.130600 0.8075000 0.875200 1.200000 0.20484816
1235 E01001253 2.176000 1.930800 1.3935000 0.737700 1.350000 0.28080875
1236 E01001254 2.211650 2.211650 1.9640500 1.346000 0.373500 0.38486762
1237 E01001255 0.985000 1.517100 1.0875000 1.674000 2.199700 0.30873008
1238 E01001257 1.910700 1.364900 1.9107000 1.910700 2.105400 0.37380612
1239 E01001258 0.665000 0.665000 0.7878000 0.650300 1.321900 0.41714835
1240 E01001259 0.891200 0.803500 0.7587000 0.921100 2.325400 0.37400050
1241 E01001260 0.825900 0.825900 1.3152000 1.218600 0.819200 0.36706519
1242 E01001261 0.798600 0.798600 0.5136000 1.105800 0.819200 0.24533573
1243 E01001262 2.185200 2.185200 2.2657000 1.011500 0.717500 0.52657276
1244 E01001263 2.887800 2.887800 2.8575000 2.804100 1.092500 0.47345433
1245 E01001264 2.259200 2.259200 2.3013000 2.256500 2.255000 0.41445437
1246 E01001265 3.798947 7.121400 2.6665000 2.386500 3.239700 0.36165875
1247 E01001266 1.260947 4.446689 1.5025000 1.897500 1.904700 0.35575533
1248 E01001267 1.823500 2.461900 2.3053000 1.219300 2.427500 0.36700894
1249 E01001268 2.236300 2.317950 2.5152000 2.088300 2.540000 0.44095391
1250 E01001269 2.047000 2.491100 1.1379000 1.255400 2.165050 0.36054708
1251 E01001270 2.509700 3.054000 3.1173000 3.923800 1.025500 0.37736386
1252 E01001271 2.544600 2.672800 1.9596000 2.417500 2.203600 0.33714646
1253 E01001272 2.132447 4.989789 1.0000000 1.265000 1.839700 0.32649976
1254 E01001273 1.768750 0.827600 0.8625000 3.516750 6.894650 0.45646444
1255 E01001274 1.329500 1.930000 1.0375000 4.281000 7.644368 0.51534677
1256 E01001275 1.195000 1.247500 1.1800000 2.578500 5.122500 0.48266050
1257 E01001276 4.532000 4.977250 3.0731526 5.521500 1.585000 0.36586851
1258 E01001277 1.723200 2.984000 2.4012053 6.837200 2.829800 0.26286888
1259 E01001278 2.720000 2.491600 1.8276526 5.638000 4.506868 0.42134890
1260 E01001279 0.910000 3.200000 2.4625000 5.360800 2.040000 0.47014177
1261 E01001280 2.507500 2.427500 2.6275000 4.185800 3.877500 0.55350244
1262 E01001281 1.160000 1.965000 1.5700000 4.288800 1.255000 0.54904908
1263 E01001282 1.002500 1.826500 1.4237500 3.980000 2.193100 0.43102680
1264 E01001283 0.795000 1.049000 0.8650000 3.766800 1.245000 0.41391110
1265 E01001284 1.081750 1.281500 1.1857500 4.010900 1.050000 0.39653514
1266 E01001285 0.795000 1.656500 1.1225000 3.610000 1.895000 0.40317139
1267 E01001286 1.865000 2.890000 1.7525000 3.392500 3.328100 0.44304377
1268 E01001287 1.858500 2.299000 1.9955000 4.037500 0.998000 0.44671214
1269 E01001288 1.490000 1.921500 0.8425000 2.122500 1.992500 0.35378200
1270 E01001289 1.992500 1.992500 1.6350000 1.992500 3.145000 0.36810672
1271 E01001290 1.487000 1.487000 1.0225000 1.330000 1.622500 0.47909603
1272 E01001291 1.694500 1.529500 1.6411000 1.699000 2.280350 0.32722858
1273 E01001292 0.769250 1.111250 1.1538500 2.021600 2.627350 0.36138762
1274 E01001293 1.338000 1.917500 1.6099000 1.770000 1.657500 0.26717132
1275 E01001294 1.303000 1.898500 2.3330000 1.760750 0.786500 0.23391475
1276 E01001295 0.966500 2.042500 2.0170000 1.257500 1.472500 0.24466969
1277 E01001296 0.685750 1.331250 1.5975000 0.748750 1.702500 0.25787878
1278 E01001297 0.742000 0.892500 0.8665000 1.547500 1.070500 0.28366643
1279 E01001298 0.949000 0.985000 0.6685000 0.725000 1.962500 0.28506178
1280 E01001299 2.005500 1.308850 2.0234000 2.830000 1.318600 0.40691529
1281 E01001300 1.310100 1.074900 0.7045500 0.966900 3.306026 0.33161154
1282 E01001301 0.734400 1.241000 0.5925000 0.541500 3.260226 0.38055837
1283 E01001302 1.838100 0.855950 0.9652000 1.022500 2.807150 0.36046243
1284 E01001303 1.720800 0.954150 1.0986000 1.470300 3.984500 0.32775256
1285 E01001304 1.127600 1.112500 0.9871000 1.127600 3.028100 0.32250285
1286 E01001305 0.715000 1.185000 0.8300000 1.830400 1.568600 0.34793997
1287 E01001306 1.657200 1.042500 1.3500000 2.036400 2.371300 0.32342410
1288 E01001307 0.917500 2.818100 1.5936000 1.711100 1.052500 0.41104831
1289 E01001308 1.130300 2.982700 1.3733000 4.405400 4.195200 0.38743931
1290 E01001309 2.265600 2.048650 2.7453000 3.067800 3.201000 0.37553454
1291 E01001310 1.468100 1.520950 2.4731500 3.709150 4.081000 0.44435841
1292 E01001311 2.784700 2.568800 2.8878000 3.790400 3.358500 0.32517153
1293 E01001312 1.885000 1.053200 1.4725000 1.590000 2.993500 0.39707446
1294 E01001313 1.577300 2.168100 1.7663000 3.097500 3.700400 0.37692898
1295 E01001314 1.130300 2.973600 2.3200000 2.437500 1.887500 0.47994936
1296 E01001315 0.881600 1.249800 3.0061000 4.004600 3.462000 0.39644295
1297 E01001316 1.614800 1.830900 1.7188000 3.912500 4.215100 0.49410743
1298 E01001317 1.075000 1.332500 1.3900000 2.922500 4.191000 0.46279019
1299 E01001318 1.882300 2.012500 0.9725000 3.810000 4.617600 0.47019553
1300 E01001319 0.966200 2.110000 2.9941000 4.495700 2.058500 0.38272104
1301 E01001320 3.145000 3.306250 3.3373000 2.191000 4.883500 0.48457706
1302 E01001321 1.683250 2.135750 1.9106500 2.322000 3.824600 0.38317122
1303 E01001322 1.451950 1.795600 0.9971500 3.798500 1.737500 0.46008110
1304 E01001323 0.672100 0.676500 1.0218000 2.965900 2.168500 0.42260754
1305 E01001324 3.803789 3.201389 3.5313895 3.352000 5.422289 0.39060086
1306 E01001325 1.670000 2.960000 3.0975000 2.487500 1.515000 0.41943373
1307 E01001326 4.337100 3.318600 3.6030000 3.209600 6.366500 0.42839602
1308 E01001327 2.000000 1.152000 1.2090000 1.122100 3.931500 0.41652650
1309 E01001328 3.090100 1.962600 1.3412500 1.056500 5.077500 0.42360675
1310 E01001329 0.970000 1.465000 1.8200000 1.465000 2.927500 0.43469957
1311 E01001330 3.118300 1.532200 2.7824000 2.648100 3.676300 0.34590733
1312 E01001331 1.260000 1.428750 1.0875000 1.428750 3.005000 0.45123132
1313 E01001332 2.303100 0.895000 2.3031000 2.303100 2.668800 0.48327482
1314 E01001333 1.497500 2.141000 1.6175000 0.727500 1.953600 0.31042036
1315 E01001334 1.039000 1.130000 2.0675000 1.130000 1.412100 0.42177039
1316 E01001335 1.587600 1.600150 2.0000000 3.724800 1.439000 0.47309046
1317 E01001336 0.813000 1.541350 1.1025000 3.283700 1.271050 0.37049210
1318 E01001337 1.832400 3.455474 3.9021737 1.166400 1.016000 0.36729394
1319 E01001338 1.748000 3.594100 2.8424000 2.818500 4.720000 0.26477134
1320 E01001339 0.486250 2.197500 1.7847500 2.197500 0.566250 0.38909054
1321 E01001340 2.183100 5.000763 4.8576000 1.596000 2.208000 0.30662781
1322 E01001341 1.192500 0.808000 1.1925000 7.092500 1.773000 0.27272728
1323 E01001342 1.847500 1.005000 1.6325000 6.861350 1.294500 0.33296058
1324 E01001343 0.923750 2.225000 0.9237500 7.027500 1.246500 0.36437085
1325 E01001344 2.375000 1.714000 1.7725000 6.442250 1.278500 0.41064824
1326 E01001345 2.375000 0.982000 1.6460000 7.668300 2.606100 0.29042000
1327 E01001346 1.075000 1.070000 1.0700000 7.407400 3.166800 0.31120458
1328 E01001347 2.544000 1.430000 1.2090000 8.336500 1.249000 0.26462287
1329 E01001348 2.154900 1.378000 1.4462500 6.503700 1.879400 0.32203095
1330 E01001349 1.995737 3.574400 3.4114895 2.556800 3.240100 0.34208882
1331 E01001350 2.239200 1.945200 1.7450000 3.946800 8.430200 0.40968090
1332 E01001351 0.550700 0.279350 0.5508000 1.343100 7.776089 0.22131726
1333 E01001352 1.359500 0.518500 1.9896000 2.866800 7.800400 0.37291682
1334 E01001353 0.956700 1.061500 1.2048000 1.707500 6.965989 0.48755267
1335 E01001354 0.728150 0.837500 1.2000000 2.276000 7.811689 0.32122210
1336 E01001355 1.077100 0.667200 0.8424000 0.806100 7.431100 0.35220903
1337 E01001356 0.273750 0.730300 1.1306000 0.630000 7.972695 0.37527031
1338 E01001357 1.370700 0.834900 1.2513000 1.205700 7.979789 0.29922403
1339 E01001358 2.040700 1.207500 0.8850000 2.425700 7.030989 0.19905084
1340 E01001359 0.887200 1.040700 0.2654000 2.031000 3.077300 0.21812615
1341 E01001360 1.277250 0.496850 0.5247500 1.317000 4.120200 0.21630561
1342 E01001361 0.942300 0.712200 0.6239000 1.234600 3.723500 0.14752756
1343 E01001362 1.896000 0.590000 1.5579000 1.470000 4.161700 0.18052381
1344 E01001363 1.363900 2.066900 0.4915000 2.743300 2.783800 0.24734133
1345 E01001364 1.454500 2.082800 1.1759000 2.759200 3.737500 0.30529064
1346 E01001365 2.035900 0.814000 1.4037500 2.205000 3.720300 0.22211997
1347 E01001366 1.919000 2.469000 1.4665000 2.901500 2.744500 0.23392202
1348 E01001367 0.733500 1.070000 0.8135000 1.401250 2.257800 0.17438278
1349 E01001368 1.583250 2.133250 1.5457500 2.883250 2.303250 0.20643240
1350 E01001369 0.275000 1.917500 0.6125000 1.952000 0.462500 0.20128193
1351 E01001370 2.420500 2.712500 2.1775000 3.812500 1.725000 0.25128144
1352 E01001371 1.363750 1.808750 1.2650000 2.602500 1.707500 0.24701804
1353 E01001372 1.638750 1.973750 1.1537500 2.298750 0.681250 0.20824993
1354 E01001373 0.740000 1.082500 0.8150000 0.825000 2.632500 0.18811834
1355 E01001374 0.952600 1.747100 1.0182000 1.528200 5.960000 0.35550010
1356 E01001375 0.742400 0.526200 0.8675000 0.867500 5.176200 0.35557184
1357 E01001376 0.745900 1.353600 0.8259000 0.867500 6.314400 0.36376506
1358 E01001377 1.365400 1.238700 1.4375000 1.590900 4.440500 0.47931659
1359 E01001379 0.825900 1.459600 0.8259000 1.055700 5.618300 0.33059722
1360 E01001380 1.413200 1.700400 1.2612000 2.142300 5.826900 0.32230796
1361 E01001381 1.048400 0.891600 0.7884000 2.131500 7.738150 0.14019264
1362 E01001382 1.307200 1.000000 1.0625000 1.812500 3.458600 0.36213449
1363 E01001383 0.928950 1.224700 0.9972000 1.166700 3.072000 0.30883056
1364 E01001384 0.589000 0.590500 0.5905000 1.443000 2.938300 0.28303933
1365 E01001385 1.196600 0.672500 0.8894000 1.747400 2.782950 0.33061707
1366 E01001386 2.157600 1.151400 1.7751000 2.157600 5.202526 0.38360822
1367 E01001387 0.940600 1.005500 0.8887500 0.760000 4.501100 0.48238498
1368 E01001388 0.619500 0.497600 0.6726000 0.449000 4.523600 0.30785505
1369 E01001389 0.746450 0.952550 0.6746500 0.637150 3.143100 0.28251757
1370 E01001390 1.381500 1.134600 1.0200000 1.779500 5.521400 0.34214151
1371 E01001391 1.511300 1.610200 0.9075000 3.099300 5.666300 0.40239647
1372 E01001392 1.551450 1.429600 1.5140000 1.597950 5.790550 0.36729711
1373 E01001393 1.556400 1.348550 1.0025000 2.908200 5.678200 0.34316713
1374 E01001394 2.166900 1.002000 1.1246000 3.474400 6.579100 0.31339651
1375 E01001395 3.458800 1.974500 2.1430000 4.766300 7.583500 0.46564373
1376 E01001396 1.148400 1.087050 0.4034500 2.455900 5.688500 0.34479697
1377 E01001397 3.543450 2.628987 2.5459500 4.698400 6.675974 0.40215983
1378 E01001398 1.623000 2.000750 1.4532000 1.060000 3.559650 0.51423207
1379 E01001399 2.048500 2.447700 0.6675000 2.145000 5.009400 0.36136612
1380 E01001400 1.928150 1.276450 1.0541000 1.050000 3.237700 0.38292319
1381 E01001401 0.828500 1.789500 1.5045000 1.886250 4.538900 0.35924947
1382 E01001402 1.761300 0.727300 1.1604000 1.578000 4.101500 0.39965555
1383 E01001403 1.807200 1.796650 1.4710000 1.691000 4.776850 0.36627567
1384 E01001404 2.175000 2.769500 3.4825000 2.769500 5.045000 0.38248700
1385 E01001405 2.150100 2.461900 2.1501000 1.438000 3.155400 0.55066073
1386 E01001406 0.963500 1.739500 1.0775000 1.552500 4.388400 0.40399706
1387 E01001407 3.029900 4.231200 3.0299000 2.848000 2.377500 0.47199580
1388 E01001408 1.424000 2.950000 2.9838500 1.424000 2.490000 0.34421566
1389 E01001409 4.010450 4.562750 4.2708000 1.165700 1.892700 0.36625120
1390 E01001410 3.639900 3.744900 3.6399000 2.763000 2.409700 0.42761046
1391 E01001411 1.181400 3.048500 1.9926000 1.983000 2.480700 0.28651917
1392 E01001412 8.877588 9.702450 10.0166000 8.705750 3.742697 0.59897834
1393 E01001413 2.451900 4.023500 2.9826000 2.497500 1.585000 0.51548606
1394 E01001414 2.495500 3.881500 3.8551000 2.495500 2.855000 0.46961361
1395 E01001415 0.844000 0.843600 0.9667500 4.674500 4.752200 0.40686032
1396 E01001416 3.234500 3.252200 2.3235000 6.214900 2.647500 0.41435768
1397 E01001417 7.129200 7.526400 7.4812000 9.290054 2.601800 0.59335923
1398 E01001418 0.810000 0.675000 0.8655000 4.962900 4.731800 0.44659451
1399 E01001419 1.617000 1.538700 1.3532000 4.659700 4.769400 0.45495354
1400 E01001420 1.534600 1.162500 2.3335000 3.608400 5.936400 0.49467987
1401 E01001421 2.264500 1.237000 1.8765000 2.342400 5.523900 0.47057101
1402 E01001422 8.236500 7.780750 4.7517500 9.894200 3.873000 0.62566963
1403 E01001423 2.048550 1.441550 1.5775763 2.572200 3.709600 0.37259407
1404 E01001424 2.798000 1.912800 0.5983500 2.750000 2.784000 0.30415560
1405 E01001425 2.042150 1.286400 1.3231000 1.702000 2.146500 0.39849702
1406 E01001426 1.485000 1.827500 1.4500000 1.827500 3.066000 0.34024346
1407 E01001427 3.477200 3.936600 3.6672000 3.943900 3.326250 0.15385217
1408 E01001428 3.132500 2.143750 1.5140000 2.167500 1.897500 0.46560676
1409 E01001429 0.964900 0.890400 0.5210000 0.807500 3.952532 0.18868262
1410 E01001430 1.285700 1.483600 1.0125000 1.272600 2.321000 0.37208611
1411 E01001431 1.805000 2.187500 1.8100000 2.372500 3.156500 0.34408164
1412 E01001432 0.897500 1.779900 1.0419500 3.141500 3.039000 0.24783351
1413 E01001433 2.616800 2.880000 2.8800000 4.239800 5.495500 0.41847348
1414 E01001434 2.125000 2.313300 2.3133000 4.749200 5.723000 0.37339947
1415 E01001435 1.555800 1.261800 1.2618000 3.476700 6.385600 0.39657199
1416 E01001436 1.293750 2.323500 2.3235000 4.587200 6.364500 0.35199362
1417 E01001437 5.215500 5.768000 5.6005000 7.270000 3.600500 0.15614471
1418 E01001438 3.272500 3.825000 3.2275000 5.081900 4.234250 0.37534499
1419 E01001439 0.414000 1.624500 0.8206000 3.285150 6.300650 0.30413790
1420 E01001440 0.635450 2.544400 1.0305500 2.265450 6.506300 0.37942184
1421 E01001441 0.893600 0.893600 0.8936000 2.288300 5.882900 0.32698354
1422 E01001442 0.899500 0.899500 1.1195000 0.899500 6.695450 0.38455854
1423 E01001444 1.999200 2.584050 1.8315500 1.999200 6.547500 0.37592971
1424 E01001445 4.796500 4.796500 4.7715000 7.626700 1.938000 0.41542223
1425 E01001446 0.978600 1.415300 0.9306000 0.978600 6.204000 0.33569694
1426 E01001447 2.011700 2.645300 1.9000000 2.011700 5.213000 0.33106315
1427 E01001448 1.933500 1.933500 1.4975000 1.933500 6.602500 0.29947025
1428 E01001449 4.577450 5.203150 4.4657500 4.577450 4.054500 0.41995953
1429 E01001450 1.430400 1.265500 1.4481000 0.840200 1.573800 0.41306622
1430 E01001451 1.933600 2.084200 1.9336000 1.809500 0.996650 0.53514057
1431 E01001452 2.657500 2.480000 2.1548000 2.657500 3.225500 0.55938083
1432 E01001453 3.229500 2.899500 3.1750000 5.104900 3.688500 0.51881707
1433 E01001454 3.525500 2.611100 2.4370000 4.250700 3.506000 0.47109425
1434 E01001455 1.171250 1.002500 0.7529000 1.171250 2.658600 0.46182328
1435 E01001456 1.572900 0.707800 1.5385000 1.572900 3.376750 0.43956055
1436 E01001457 2.376600 1.233600 2.5698000 2.078300 1.375000 0.43295485
1437 E01001458 1.866000 2.484000 1.8675000 1.283500 1.855000 0.33219066
1438 E01001459 2.217500 2.207500 1.8560000 3.073400 5.962500 0.29454938
1439 E01001460 0.968850 0.777700 1.7191868 1.843900 4.497000 0.31869590
1440 E01001461 1.935600 2.348400 2.8860000 2.918400 3.805500 0.43265876
1441 E01001462 1.520000 1.230700 2.4101526 2.575900 5.110000 0.35074613
1442 E01001463 1.601750 0.993750 3.4465000 0.993750 2.910500 0.31354374
1443 E01001464 2.812500 2.122500 2.2425000 2.122500 1.910000 0.46691442
1444 E01001465 1.042500 0.715000 3.1475000 0.725000 2.590000 0.33623052
1445 E01001466 1.867500 2.025000 1.8675000 1.285000 0.828750 0.31375316
1446 E01001467 1.505000 1.817500 2.0800000 1.270000 1.930000 0.31463924
1447 E01001468 2.856500 2.685600 5.1762000 0.994600 5.993200 0.43679494
1448 E01001469 2.364400 2.886900 4.6495000 2.343500 4.871100 0.47594895
1449 E01001470 1.162500 3.472200 1.0175000 4.052900 1.851200 0.45394495
1450 E01001471 0.987500 1.079900 3.3019000 1.977400 3.694100 0.50635672
1451 E01001472 2.122500 1.056000 2.8338500 0.847500 2.306500 0.47241056
1452 E01001473 1.380000 4.674900 1.3812500 6.221650 0.615000 0.51901206
1453 E01001474 1.598500 1.392500 2.8774000 2.078300 2.592800 0.47065669
1454 E01001475 2.549800 2.819000 2.2601000 7.238900 1.485000 0.47563666
1455 E01001476 1.252100 0.780000 0.6624500 2.479350 6.264200 0.32063976
1456 E01001477 1.180000 1.837000 1.3875000 3.209900 6.064300 0.39737368
1457 E01001478 2.988900 1.874500 2.6129500 3.380100 7.144650 0.41582744
1458 E01001479 0.710500 0.710500 0.4468000 0.710500 6.653000 0.28510708
1459 E01001480 3.079000 3.118600 1.8465000 3.134600 6.342900 0.37747151
1460 E01001481 2.077500 1.999200 1.9328000 2.441800 5.658800 0.30765915
1461 E01001482 1.492100 1.492100 1.2477000 1.492100 6.822100 0.34191638
1462 E01001483 2.795000 2.795000 2.7950000 2.037500 4.113400 0.40163845
1463 E01001484 2.857800 1.905000 2.2492500 3.445450 7.879650 0.35969342
1464 E01001485 1.192500 1.030250 1.2902500 1.192500 4.684900 0.28960285
1465 E01001486 2.147500 1.954500 2.5640000 1.930000 4.141000 0.35665846
1466 E01001487 0.953500 0.747500 0.9535000 0.947500 5.814600 0.29497281
1467 E01001488 1.724100 1.724100 1.7241000 1.724100 5.969000 0.31841189
1468 E01001489 2.162500 1.985000 2.1625000 1.715000 4.846400 0.31522501
1469 E01001491 1.403600 1.302400 1.2084000 1.403600 5.607532 0.28368816
1470 E01001492 2.345000 1.824000 2.5065000 1.795100 3.830600 0.26145688
1471 E01001493 1.538300 1.149600 1.7112000 2.752400 3.763200 0.42385673
1472 E01001494 1.240100 2.824584 2.9870842 3.809900 5.745700 0.32790941
1473 E01001495 1.589700 0.900400 0.6456000 1.589700 3.514000 0.37453368
1474 E01001496 0.963600 1.893500 2.4551000 3.228500 4.748700 0.44830149
1475 E01001497 1.817600 3.227584 3.4470842 3.453000 5.301500 0.34742916
1476 E01001498 1.134800 0.594800 0.6278000 1.506700 3.759050 0.23448657
1477 E01001499 1.645900 2.217884 2.4021000 4.009400 5.353384 0.29899603
1478 E01001500 2.235000 1.466250 1.7750000 2.620050 4.889650 0.38036075
1479 E01001501 1.972550 1.631500 0.8528000 2.741150 5.065950 0.36122456
1480 E01001502 1.640000 2.237150 1.1850000 2.996600 6.348200 0.29137921
1481 E01001503 2.344400 1.786750 2.1667000 2.916200 7.986850 0.37927570
1482 E01001504 1.256600 3.470050 0.6987500 1.713250 5.730400 0.33754206
1483 E01001505 0.804000 2.320800 0.8040000 0.804000 6.380400 0.34291685
1484 E01001506 1.617500 4.150700 1.0125000 3.127500 5.040400 0.24373895
1485 E01001507 0.746400 1.445800 0.7020000 1.186800 6.563600 0.22926938
1486 E01001508 0.898800 0.768000 1.0860000 1.756800 7.475600 0.30023280
1487 E01001509 0.862500 2.929800 1.0437500 2.209750 5.122300 0.35923193
1488 E01001510 1.568750 3.195450 0.9387500 3.113750 5.886550 0.19525769
1489 E01001511 1.542000 3.464000 2.7710000 1.542000 6.169350 0.32297459
1490 E01001512 2.532500 2.159400 1.6866000 1.686600 2.554300 0.34729379
1491 E01001513 1.973000 3.258600 2.3870000 2.160500 5.337400 0.33728428
1492 E01001514 2.585000 3.282900 2.6220000 2.501000 4.640900 0.37544337
1493 E01001515 1.467500 2.764250 2.3600000 2.097500 5.310900 0.35161224
1494 E01001516 3.751200 4.181850 3.9582000 1.990500 3.000000 0.37553181
1495 E01001517 1.910500 1.533700 1.5337000 2.723500 5.967400 0.39059436
1496 E01001518 2.532500 2.360150 1.8873500 1.818050 2.685750 0.37494741
1497 E01001519 3.761300 0.674300 0.8082500 1.692000 2.736000 0.24685387
1498 E01001520 5.219000 2.245600 1.8871000 3.336700 3.561400 0.42785215
1499 E01001521 4.059500 1.412900 1.4129000 3.290400 2.364100 0.53446567
1500 E01001522 1.427500 5.386000 1.4275000 7.795400 2.802500 0.49416751
1501 E01001523 2.544750 4.568250 2.5447500 6.415400 3.140500 0.46483365
1502 E01001524 3.569300 2.841900 2.6396000 3.265900 5.628900 0.46681869
1503 E01001525 3.212300 1.585900 1.5078500 1.929400 5.110900 0.40878025
1504 E01001526 5.463900 3.442100 3.4723500 4.853650 4.274900 0.49920610
1505 E01001527 2.552650 1.412400 1.4184000 3.341800 5.598500 0.49475592
1506 E01001528 3.358400 1.550350 1.1708000 3.582800 7.573150 0.35261351
1507 E01001529 3.303400 1.424100 0.7925000 3.565700 7.280500 0.39402449
1508 E01001530 1.323900 1.457600 1.7256000 1.323900 6.017400 0.33791375
1509 E01001531 3.173150 2.146350 2.2834500 3.386250 1.045000 0.52775055
1510 E01001532 2.432300 0.807500 1.2607000 3.672500 2.755000 0.51044023
1511 E01001533 2.983300 1.795200 1.2425000 4.323350 3.818500 0.46645132
1512 E01001534 3.553650 1.352700 1.3657000 3.715550 6.043300 0.41319621
1513 E01001535 1.940300 1.857600 2.1815000 2.540900 5.024300 0.43822640
1514 E01001536 0.688850 0.880300 0.8899000 0.840200 1.265500 0.37376410
1515 E01001537 2.971400 4.313300 3.0746000 2.383200 1.472400 0.45908985
ah3ffood ah3gamb ah3leis ah3pubs ah3tob ah3no2 ah3so2
1 0.0000000 1.3078000 0.2874737 0.07789474 1.6451368 42.34910 3.2393463
2 0.2808000 1.2750000 0.8183000 0.22250000 2.1325000 41.42222 3.1554665
3 0.0625000 1.1400000 0.3696000 0.00000000 1.0350000 41.42222 3.1554665
4 0.0900000 1.2250000 0.5221500 0.05010000 1.2179500 39.63400 2.9787090
5 0.9087500 1.3675000 1.8000000 1.58500000 0.9087500 31.19862 2.2662235
6 1.0000000 0.9225000 1.1775000 1.27375000 1.1775000 28.96450 2.3735695
7 3.5182000 3.3860000 3.6410000 3.73940000 3.6410000 28.70532 2.5423790
8 0.0000000 0.5875000 1.0200000 0.58850000 0.2300000 32.10369 2.2072080
9 0.8104000 0.2204000 0.6525000 1.24250000 1.1604000 29.56014 2.5382052
10 0.7964000 0.6225000 2.2086000 1.43290000 1.8344000 32.10369 2.2072080
11 0.5425000 1.9614000 2.4237000 1.41750000 2.3253000 28.96450 2.3735695
12 0.9412500 1.7610000 4.7750000 2.80840000 1.2505500 24.57481 2.5489963
13 2.1185000 2.8988000 4.2745500 3.97325000 1.6335000 24.88731 2.5142282
14 1.6361000 2.5967000 4.5200000 3.38160000 2.3732000 24.80967 2.6052760
15 1.4485000 2.1075000 3.3690000 3.67150000 2.2743000 22.43436 2.6324030
16 1.6610000 2.3640000 3.3548000 3.56490000 1.9993000 22.43436 2.6324030
17 1.4485000 2.1783000 4.0648000 3.16775000 1.7600000 24.80967 2.6052760
18 1.3091000 1.5349000 1.1855000 3.56765000 3.1655000 22.86327 2.2097390
19 1.2127000 1.4297000 1.5150000 3.41950000 3.4705000 22.86327 2.2097390
20 1.0396000 1.6401000 1.2546000 4.61710000 1.8030000 22.86327 2.2097390
21 1.4243000 1.6265000 0.8000000 3.68360000 2.4325000 22.86327 2.2097390
22 0.6717500 2.1540000 3.1566000 4.44200000 1.4280000 22.86327 2.2097390
23 1.3969000 1.1148000 1.0083000 3.53110000 2.3592000 22.86327 2.2097390
24 1.3539000 1.5519000 1.5948000 3.65795000 2.2779000 22.86327 2.2097390
25 1.5425000 6.4592000 9.3792000 1.49090000 6.5693000 18.91357 1.7160479
26 1.9200000 6.7487000 8.9542000 2.28250000 7.5668000 20.30797 2.1192700
27 2.1975000 2.9250000 6.2630000 1.96760000 3.4826000 21.30377 2.1607128
28 1.4909000 5.9309000 9.1609500 1.41060000 6.5535000 20.81386 2.1766200
29 1.3922000 2.2949000 5.6033000 1.31000000 2.7901000 20.68996 2.0530567
30 0.7095000 1.0929000 4.4637000 1.03010000 1.6505000 22.45754 2.1724340
31 2.7120000 2.7120000 3.7578000 3.45780000 3.7488000 21.84845 2.5535620
32 3.7380000 3.7380000 5.0953000 4.49530000 5.0863000 21.50592 2.3357403
33 0.8589000 0.8589000 2.7813000 1.85880000 2.1498000 22.32613 2.6545290
34 0.5527500 0.9869000 3.3166500 1.41750000 0.8964500 23.19566 2.7524746
35 3.2182000 3.6272000 4.7278000 3.54460000 8.2117789 20.75518 2.1652802
36 1.7433500 1.8617000 3.2529500 2.06975000 6.7369289 20.71029 2.1979227
37 6.0032000 6.4122000 7.5128000 6.39080000 10.9967789 21.58844 2.5235578
38 2.5145000 0.7025000 4.1159000 4.39050000 4.7634000 29.50989 2.5930470
39 1.0322000 1.0322000 2.7346000 2.25200000 7.2508000 28.46542 2.5183515
40 2.9020000 1.7012500 5.2525000 4.23415000 6.0140000 28.10883 2.5218885
41 2.1970000 1.3866000 4.3211000 4.23430000 4.9686000 27.38058 2.5874383
42 2.8921500 1.3740000 3.7444000 4.45145263 4.3919000 29.96242 2.5635392
43 0.5975000 0.5975000 3.4195000 2.25200000 7.4958000 26.70776 2.4507300
44 1.6975000 1.6975000 2.4925000 3.75780000 7.4102500 25.54371 2.3791323
45 2.7995000 2.7586526 2.8925632 2.98290263 3.5400632 28.72622 2.8608550
46 0.8462500 0.9325000 2.3833000 3.00665263 3.0308000 28.72622 2.8608550
47 0.5815000 0.5400000 1.8720500 2.26715263 2.5195500 29.85204 2.6429727
48 1.0310000 1.0310000 2.0518000 1.80250000 2.6993000 28.72622 2.8608550
49 0.7185000 1.7767500 3.0233000 3.75465263 3.6708000 28.72622 2.8608550
50 1.4709000 1.9968000 3.5178000 1.99680000 4.6009000 23.95548 2.6787560
51 3.4262500 1.3235000 1.3235000 4.13090000 5.2085000 23.96287 2.2943520
52 2.5250000 2.0195000 2.0195000 4.40810000 6.5585000 24.37966 2.3075345
53 3.0575000 2.7735000 2.7735000 3.31590000 4.7985000 23.96287 2.2943520
54 3.2877500 0.5520000 0.5520000 4.45850000 5.7155000 24.37966 2.3075345
55 2.3650000 1.7585000 1.7585000 3.62240000 4.1260000 26.13732 2.3751560
56 1.8250000 1.8549000 2.7360000 2.58540000 3.6760000 23.54606 2.2811695
57 2.0006500 1.8556000 1.7624000 2.50465000 3.0301500 21.80139 2.4308560
58 2.1725000 2.0789000 1.8965000 2.02760000 2.5531000 21.43941 2.3148020
59 1.3175000 0.9850000 2.4533000 3.35840000 3.8739000 21.88400 2.5578245
60 0.9266000 0.9266000 1.5867000 1.95230000 3.0173000 22.21570 2.4862583
61 1.4011000 1.7952500 3.4333000 3.70000000 3.9075000 21.88400 2.5578245
62 1.3090500 1.2695000 2.5941500 2.33680000 3.5850500 22.24330 2.5283260
63 2.6548000 1.8825000 5.4428000 2.80730000 4.3409000 27.23490 2.4114595
64 2.0698000 1.2850000 4.8623000 2.20980000 3.8759000 26.04869 2.3280970
65 1.1250000 1.6454000 2.2862500 1.52625000 1.4551000 31.29580 2.3094867
66 2.3126500 1.6025000 4.4655000 2.43855000 3.6532500 28.69211 2.4786997
67 0.6016000 0.9952000 2.9325000 0.74160000 2.4080500 29.71916 2.3444432
68 3.1216500 1.6740000 5.0732500 3.30725000 4.4407500 30.54354 2.4933930
69 0.9146000 0.9146000 1.6450000 0.90100000 5.5180000 26.82840 2.4356430
70 1.3621500 1.3654000 0.9937500 0.62250000 4.4217500 25.66435 2.3640453
71 1.7928000 1.7928000 1.3175000 1.32785000 4.6142500 25.66435 2.3640453
72 2.7850000 1.9708500 1.9959500 2.57660000 5.0825000 25.04597 2.3200170
73 1.3125000 1.3296000 1.7475000 1.06500000 5.4886500 28.46542 2.5183515
74 1.2760000 1.0933000 2.3333000 2.65110000 3.3227000 22.86327 2.2097390
75 0.5325000 1.3085000 3.3475000 1.45570000 4.4369000 22.73294 2.3542832
76 2.1260000 2.7391000 4.4399000 3.41780000 1.7280000 24.42012 2.3925820
77 1.6610000 1.4377500 3.0246000 2.63885000 3.7587000 23.84772 2.3983907
78 1.5631000 2.0636500 4.1216000 1.51010000 4.1960000 22.54258 2.6102770
79 0.8741000 1.1099000 3.1959500 1.01740000 4.6265500 22.60261 2.4988275
80 0.7925000 0.8776000 2.2734000 2.20360000 3.5925000 22.86327 2.2097390
81 0.8274000 0.8274000 3.6785000 1.49250000 2.3885000 26.71526 2.4655895
82 0.5175000 0.5974000 4.7922500 0.88000000 2.8946500 25.45581 2.9245425
83 0.8475000 1.1599000 4.3210000 1.49250000 2.7884000 24.50094 2.6028560
84 1.5129000 0.6600000 5.3262000 0.52750000 4.8036000 24.75708 3.0901167
85 0.9825000 1.5025000 6.3261000 1.50250000 4.7646000 25.45581 2.9245425
86 2.2325000 2.7600000 6.2364500 2.76000000 6.0221000 24.88883 3.4316375
87 2.3600000 2.8875000 5.9493000 2.88750000 6.1496000 23.97034 3.0173793
88 0.9900000 1.5070000 9.6313000 1.97000000 10.2788000 22.62201 2.2399130
89 4.1430000 5.2585000 9.9548000 5.37150000 10.6023000 24.40230 2.4151803
90 0.7350000 0.8450000 7.9493000 1.05300000 8.5968000 25.67412 2.5503840
91 1.4820000 2.9595000 10.4180500 3.42250000 11.7313000 22.62201 2.2399130
92 4.0634000 5.5364000 7.6176000 5.74890000 11.7313000 22.37039 2.4836189
93 3.7294000 3.6511500 7.1912000 2.40075000 10.2453000 22.62201 2.2399130
94 1.2725000 1.3525000 0.7975000 2.82950000 3.6425000 22.81838 2.1613650
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104 1.9775000 2.7699000 7.0527000 3.89790000 2.7554000 22.13842 2.8802085
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108 1.2609000 2.5958000 2.4850000 1.81430000 1.7145000 21.76015 2.2914653
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118 3.5278000 4.1996000 3.9095000 3.73950000 5.7715000 21.46223 1.6040340
119 2.4773000 2.5275000 2.7135000 2.52750000 2.9628000 22.40519 1.7978140
120 2.0534000 2.7300000 2.7709000 2.43320000 3.9478000 22.21660 1.7590580
121 0.9711000 2.4218500 1.2350500 2.41400000 2.5590000 21.46223 1.6040340
122 1.6543000 2.5415000 3.3259000 2.65360000 2.2562000 21.02873 1.5944043
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126 0.8834000 0.7375000 1.3924000 0.74000000 1.0874000 21.25497 1.5878030
127 1.9375000 2.3775000 0.9300000 2.72000000 2.7200000 23.17199 1.5625993
128 1.1500000 1.9599000 1.8425000 1.88320000 2.7461000 21.81196 1.5858550
129 1.0450000 0.9350000 1.4750000 3.17695000 3.1769500 24.39857 1.5117430
130 1.1725000 1.9725000 1.0725000 2.97390000 2.9739000 24.39857 1.5117430
131 2.0472500 2.0412500 2.6125000 2.86200000 2.8620000 21.13732 1.5629105
132 1.9249000 1.6875000 2.0949000 2.08000000 2.6100000 26.10546 1.7254150
133 1.5194000 1.3545000 1.8929000 1.50450000 2.7234000 25.81342 1.7129813
134 1.2828000 1.2828000 2.5514500 3.16915000 4.3184500 25.22936 1.6881140
135 3.0024000 3.5396000 3.3509000 3.44600000 4.4814000 25.41310 1.7677780
136 1.4147000 2.5826000 2.1503000 2.72750000 3.7853000 26.10340 1.6947740
137 0.9950000 0.9950000 2.3363000 2.98430000 4.1336000 25.22936 1.6881140
138 0.6660000 1.1329000 1.5420000 0.44160000 2.4636000 25.84391 1.7857720
139 1.2484500 2.8915000 1.9144500 2.01500000 3.0728000 25.84391 1.7857720
140 1.1438000 2.7850000 2.0282000 1.85850000 2.9163000 25.98751 1.7917700
141 1.2069000 0.9525000 1.0800000 0.62000000 0.6200000 26.97439 1.7524790
142 2.1551000 1.9007000 0.8461000 1.69190000 1.6919000 26.98156 1.7627160
143 0.3884000 0.2616000 0.7824000 0.42200000 1.2069000 26.98156 1.7627160
144 1.3654000 1.3654000 1.3999000 1.32130000 5.0613000 21.96591 1.5560010
145 1.2842000 1.7496000 1.0056000 1.00560000 3.7033500 21.75549 1.5433275
146 2.1011000 1.8213000 2.2124000 1.82130000 6.2513000 22.73528 1.5698787
147 2.5650000 4.6700000 3.2050000 1.87550000 4.8500000 23.01434 1.6108430
148 3.1465000 4.2614000 3.7750000 1.39600000 4.2614000 24.30039 1.5778530
149 2.2425000 4.2614000 3.7100000 2.15250000 4.2614000 24.94342 1.5613580
150 2.3560000 5.1268000 2.4885000 1.11550000 6.0845000 23.01434 1.6108430
151 1.9935000 3.6303000 1.0855000 1.68450000 4.8700000 21.85045 1.5783915
152 0.5659000 1.0795000 2.0125000 1.07950000 6.4370000 22.76873 1.6261810
153 1.0590000 1.5796000 2.3141000 1.57960000 5.9429000 22.76873 1.6261810
154 0.8993000 2.6320000 3.3706000 2.59310000 2.7321000 21.46223 1.6040340
155 1.4520500 2.2298000 3.1040000 2.27345000 2.6563000 21.46223 1.6040340
156 1.4135000 3.5952000 2.5336000 4.09630000 3.6003000 21.76585 1.6245220
157 0.8115000 1.4775000 3.7967000 2.31105000 1.4775000 22.17552 1.6073092
158 0.4056000 0.4056000 3.4572000 1.20430000 0.6360000 22.58519 1.5900965
159 1.8421000 2.4116000 3.0650000 2.41160000 5.6589000 22.06947 1.6450100
160 1.1801000 2.0076000 2.8191000 2.00760000 5.3614000 23.39925 1.6183407
161 2.4006000 2.4006000 5.8578000 3.34740000 2.4006000 22.41328 1.6084010
162 1.7168000 2.1800000 3.5775000 2.48890000 3.5360000 18.12822 1.3360400
163 1.8265000 1.8562500 2.4731500 2.15565000 2.1047500 17.55961 1.2897763
164 1.2450000 1.5875000 3.6395000 3.34920000 4.2947500 18.10178 1.3684853
165 1.0187500 1.7950000 2.2410000 2.09440000 2.0435000 18.30677 1.3419307
166 0.5472000 1.4748000 2.0108000 1.47480000 2.6910000 18.30677 1.3419307
167 0.8190500 1.3441000 1.1587500 1.15875000 1.9810000 18.32437 1.2966605
168 2.3095000 2.4041000 2.4545000 2.80610000 4.8951000 19.47127 1.4670377
169 0.9620000 1.1000000 1.4070000 1.10000000 4.3079000 19.78121 1.4788825
170 0.5770000 0.5770000 2.0401000 0.57700000 4.1732000 19.09348 1.4016913
171 1.4925000 1.5775000 1.8175000 1.57750000 5.0212000 19.33824 1.4067896
172 1.4326000 3.5044000 1.8051000 1.67000000 4.6406000 25.63062 1.6930255
173 0.6335000 1.7605000 0.5275000 0.72100000 5.5462000 25.04558 1.6563020
174 1.0034500 0.9781000 0.5856000 0.91475000 6.6221000 24.87203 1.6534370
175 0.9814000 3.0681000 1.6488000 1.44750000 5.3287000 25.63062 1.6930255
176 1.2171500 1.7802000 1.7087000 0.85055000 6.6763500 23.85637 1.6019800
177 0.4124000 0.1300000 0.3274000 0.15000000 7.1119000 23.85637 1.6019800
178 0.7200000 1.3837000 0.8275000 0.73680000 7.7727000 23.40697 1.5365540
179 0.8225000 2.9038000 1.4461000 0.91330000 5.6975000 23.83725 1.6211050
180 0.3930000 2.9244000 2.4874000 2.59230000 5.9189000 25.06845 1.6547307
181 0.9675500 2.1367500 0.8840000 1.01300000 5.5099500 25.63062 1.6930255
182 0.5660000 1.9900000 2.7747000 3.27900000 3.9447000 20.20190 1.2657390
183 1.5950000 1.4125000 4.1072000 4.47220000 5.2772000 20.20190 1.2657390
184 2.8899000 3.1222500 4.4772500 4.65900000 5.6472500 20.01734 1.2070368
185 3.8318000 4.2218000 4.5208000 3.76470000 5.6908000 19.51296 1.2377460
186 2.2400000 2.7250000 2.9368000 2.28250000 4.1068000 19.85743 1.2517425
187 2.6010000 2.7667500 2.6785500 3.34625000 3.8485500 19.85743 1.2517425
188 0.9960000 1.1275000 1.0674000 2.11810000 2.2374000 20.82551 1.4638533
189 0.8199000 1.1515000 1.1873000 1.17120000 2.3573000 19.87687 1.4067480
190 0.9345000 1.1975000 2.0288000 2.12350000 2.6120000 20.27595 1.4399735
191 3.0725000 1.8275000 5.6222000 5.35260000 6.7922000 21.05297 1.2407220
192 0.5820000 1.6404000 1.1337000 1.12270000 1.8204000 26.29849 1.6861490
193 1.5090000 1.9239500 2.2823500 1.75155000 2.0317500 26.22841 1.7169990
194 2.4151000 3.0953000 3.6935000 3.23780000 4.0688000 26.41751 1.6631868
195 2.0117000 2.8277000 2.9996000 1.71830000 4.1527000 26.66437 1.6696130
196 1.6526000 2.4984000 1.1976000 1.82640000 2.6784000 26.96636 1.6792725
197 2.1010000 3.1375000 2.4062000 3.22320000 3.6144000 26.52723 1.6623233
198 1.4055000 2.7432000 1.3551000 2.19080000 3.0428000 26.29849 1.6861490
199 1.8537000 3.1628000 1.8277000 3.37055000 4.2233000 26.17653 1.6916610
200 0.8146000 1.3284000 1.9796000 0.64320000 2.1931000 25.97094 1.6132870
201 2.0529000 2.7996000 1.4402000 2.75100000 4.7897000 25.39864 1.6765550
202 3.3709500 4.7100500 3.6091500 2.27760000 5.1725000 25.56000 1.7035476
203 1.4030000 3.8400000 1.3037500 1.74850000 3.8150000 25.48446 1.7314814
204 2.2404000 3.4293000 2.1851000 2.60640000 6.5775000 24.11435 1.6536723
205 1.7899000 1.9171000 1.9627000 2.49120000 3.4775000 26.25642 1.6935118
206 0.8225000 4.3215000 0.7925000 1.14000000 5.6550000 24.49356 1.7208953
207 0.8949500 1.1314000 1.7448000 2.29850000 3.3751000 26.25642 1.6935118
208 2.4310000 2.2850000 1.9791000 1.78250000 1.7825000 26.96721 1.7422420
209 1.9275000 5.1238000 2.0225000 2.43600000 4.2750000 25.96000 1.7549230
210 2.1571000 2.1571000 2.6646000 2.01800000 2.0180000 26.97080 1.7473605
211 0.9744000 0.9744000 1.8427000 2.89155000 2.7739500 29.24069 1.7278800
212 1.8634000 1.8009500 0.8500000 1.17250000 1.8950000 26.97080 1.7473605
213 1.2100000 1.3264000 1.4342000 1.68890000 2.7655000 27.11419 1.7104685
214 1.2409000 1.1718500 1.1175000 2.19750000 2.1975000 28.48765 1.7394920
215 1.7271500 1.7271500 2.3010000 3.38100000 3.3676000 29.24607 1.7355577
216 1.5366000 1.5366000 1.1602000 2.24020000 2.2402000 26.97080 1.7473605
217 4.2792000 4.6258000 1.8655000 5.06058684 5.9958500 29.01025 1.7478713
218 3.5075500 3.7647500 3.2384000 3.69650000 4.1852500 27.33227 1.7555067
219 2.7502000 4.0485000 2.5201868 3.12200000 4.2631500 28.94615 1.7820387
220 2.8067000 3.6395000 3.3915000 3.17850000 4.0713000 25.41310 1.7677780
221 1.2675000 1.5379000 2.2512000 2.75670000 3.4948000 27.11419 1.7104685
222 1.8500000 1.5625000 2.7525000 2.85000000 3.3692000 21.13732 1.5629105
223 1.5888000 1.5561000 2.8525000 1.32360000 3.9321000 21.10029 1.4757933
224 2.2577000 2.2577000 2.2577000 3.67044737 5.1964632 22.08330 1.2446286
225 2.8904000 1.6600000 5.0664000 3.86010000 6.2364000 20.87086 1.3615415
226 1.4568000 1.1575000 3.5364000 3.06970000 4.7064000 20.87086 1.3615415
227 1.0830000 1.0830000 1.0830000 2.94512632 4.4953263 23.49405 1.4230165
228 0.9275000 1.3478000 1.6108500 1.13450000 3.7526000 21.92464 1.5116130
229 1.0099000 1.0099000 2.5431000 0.68190000 2.8704000 21.92464 1.5116130
230 0.9012000 1.0089500 2.4230000 1.08190000 2.0679000 24.04251 1.4809470
231 0.8150000 1.1375000 1.7675000 2.95140000 2.9514000 24.39857 1.5117430
232 2.5593000 1.8301000 1.7286000 3.24950000 1.8301000 28.55646 1.7054063
233 1.6455000 0.8960000 0.8382500 1.77715000 1.9351500 26.62774 1.6282925
234 2.0953000 1.8125000 1.5361000 2.86350000 1.8296000 27.87223 1.6829325
235 1.2735000 2.9196000 3.2602500 1.86580000 4.4470000 23.35802 1.5923860
236 2.5481000 3.7301000 3.7135000 3.37050000 5.3642000 24.46013 1.6181283
237 1.7710000 2.0557500 3.4344000 2.33660000 3.7279000 25.46412 1.6328295
238 1.6036000 2.1922000 2.6472000 2.37180000 2.9407000 27.57024 1.6732730
239 0.4739000 0.9390000 1.8204000 1.19985000 2.1139000 28.47610 1.6769330
240 0.3225000 1.5512000 2.8286000 0.89335000 3.1221000 26.08890 1.6254310
241 1.3517000 0.5941000 0.8209000 1.96380000 1.0452000 29.99872 1.7003440
242 2.3704000 2.9421000 3.6661000 2.98805000 4.3064000 17.62247 1.2687403
243 2.0315000 2.8605000 3.1780000 2.86050000 3.6434000 18.41346 1.3292387
244 0.9577000 1.3884000 1.2944000 0.68880000 3.0946500 17.13071 1.2264675
245 2.2629000 2.7529500 3.1743500 1.27625000 5.0330500 17.46760 1.2201827
246 0.6840000 0.8416000 1.3106000 0.69860000 3.1067000 17.83453 1.3193277
247 1.0169000 1.3292000 1.7815000 1.46400000 2.2469000 17.82235 1.2667655
248 1.6030000 2.2415000 2.7215000 2.40400000 3.1869000 17.32034 1.2368705
249 5.4310000 6.3903500 6.5057000 2.93350000 9.1803000 18.44622 1.1733202
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251 3.0585000 5.0275000 4.8140000 3.90010000 6.8891000 23.69552 1.3901202
252 3.1260000 3.9650000 3.5265000 3.70420000 3.9650000 26.39775 1.4708117
253 1.6680000 1.7820000 1.7036000 2.14320000 4.6185000 24.00868 1.4715478
254 1.1636000 1.9500000 2.1974000 1.41000000 1.9500000 26.16039 1.4502810
255 1.9762500 2.6334500 1.9250000 2.53020000 5.4896500 25.14409 1.5454243
256 3.6325000 4.9064104 2.8735000 5.23601045 5.3140000 25.28761 1.5830090
257 3.0036000 3.8111000 4.1010000 1.33090000 4.2957000 24.13026 1.3589900
258 4.1076000 4.5996000 4.3075000 4.63420000 7.2224000 21.69892 1.4320765
259 1.7692000 2.1150000 2.3394000 3.06250000 3.0750000 25.44828 1.3886890
260 0.6607132 0.9431263 1.4400000 1.26995000 1.2699500 24.92342 1.4502160
261 0.5160000 1.5432000 2.3403000 1.13010000 4.6191000 21.46223 1.6040340
262 1.5189000 1.6573000 2.5036500 1.68360000 4.1652000 21.14936 1.5750560
263 2.2400500 2.7464000 3.3720500 2.89530000 4.3319000 18.20887 1.2808830
264 0.9830000 1.3628000 1.8943000 1.40140000 2.3597000 18.03183 1.2502610
265 1.0502000 1.0502000 3.8070000 1.52270000 4.2724000 17.53301 1.1888343
266 1.4532500 1.7150000 2.2565000 1.82700000 2.7219000 18.03183 1.2502610
267 2.1674000 2.1822000 2.8315000 2.85560000 5.0433000 17.82469 1.2202400
268 1.8421000 1.9851000 2.2380000 1.95730000 6.2687000 20.14636 1.4642875
269 1.0650000 1.0372000 1.2346000 1.44370000 6.1246000 19.95814 1.4475777
270 1.0570500 1.1878000 1.2738000 1.11480000 5.2255000 20.62857 1.5142310
271 3.0537500 3.0992000 3.3019000 2.96500000 3.3483000 20.10181 1.4687823
272 3.3725000 4.3561500 4.3833000 3.71125000 3.7462500 20.10704 1.4295115
273 1.8915000 1.8402000 1.9892000 1.92270000 2.1084000 21.96052 1.6679140
274 2.4615000 3.6872000 4.1380000 3.32500000 2.4615000 22.63871 1.5227377
275 4.5239000 5.7175000 6.1571000 2.72640000 9.2477000 18.69497 1.2074537
276 0.8962500 2.4078000 2.5146000 2.20915000 6.2924500 18.18337 1.2490558
277 1.1448000 1.5325000 2.0403000 1.38030000 5.6509000 19.20610 1.3693495
278 0.9734500 1.5584000 1.7544000 2.40260000 5.4159500 18.61973 1.3036555
279 2.2000000 3.6409500 3.6943500 3.28055000 4.9586000 20.29649 1.4910525
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281 3.3110000 3.7238000 4.6957000 3.14530000 6.4918000 17.13888 1.1270527
282 2.8885000 3.9847000 4.5341000 1.54100000 6.3928000 17.12103 1.1294535
283 2.8360000 4.3088000 4.9507000 2.83500000 6.8094000 17.17456 1.1222510
284 1.9950000 2.0698000 4.0753000 2.79220000 5.1093000 17.28868 1.2148006
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286 4.0235000 5.2263000 6.0582000 3.72500000 7.8470000 19.33728 1.1487987
287 3.2941000 3.8575500 4.8909000 3.37755000 6.6870000 17.17456 1.1222510
288 2.0763000 1.5063000 2.5767000 1.13790000 4.3728000 17.18424 1.2192650
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293 1.1840000 2.6018000 2.6937500 2.49180000 2.9312000 27.42399 1.7649460
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296 1.3760000 1.7142000 1.8384000 1.42120000 2.0050000 23.06960 1.6411972
297 1.3637500 2.3842000 2.6185000 1.67000000 1.4752500 22.76381 1.6319495
298 1.1464500 1.3627500 1.7226000 0.88250000 1.7120000 23.06960 1.6411972
299 1.5161000 2.2262000 3.6988000 2.22620000 1.7000000 23.69579 1.5006435
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301 1.1194000 1.6147000 3.4805000 1.11940000 6.1832000 24.90333 1.6766080
302 1.4714000 1.8427000 2.2937500 0.94850000 4.7239500 25.66984 1.6478480
303 2.1801500 2.6817000 2.9012500 2.18640000 5.7314500 28.59559 1.6858015
304 1.2059500 1.6309500 3.4130500 1.24310000 6.3879000 24.06576 1.6294400
305 2.4086000 1.5505000 1.8404000 1.57140000 3.8399000 23.25676 1.5562410
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308 2.7896000 2.5098000 2.9009000 2.50980000 6.9398000 22.46167 1.6110320
309 0.7713000 0.9861000 3.0284000 0.66360000 5.3286000 22.63675 1.5747925
310 1.4220000 0.5450000 0.5712500 0.64750000 2.8417000 27.16659 1.6311540
311 1.1365000 1.4204500 2.8415000 1.13650000 1.6892500 25.30747 1.6580270
312 1.5544000 2.7876000 1.7772000 2.61720000 3.5559000 26.10713 1.6989610
313 1.1464500 1.2912000 1.6767000 0.85450000 1.5559000 24.17869 1.6144805
314 0.8880000 1.4537000 1.5276000 1.26165000 2.6443500 23.37540 1.6504450
315 1.3740000 2.6553000 2.6491000 2.48780000 3.0297000 25.80134 1.6897133
316 2.0480000 1.5083000 1.5083000 1.37780000 2.0615000 21.04507 1.5653967
317 1.8001000 1.1927500 1.2096500 1.07460000 1.9267000 20.83649 1.5460780
318 1.3183000 1.3225000 1.7540000 1.32250000 1.7756500 21.71138 1.6359740
319 0.5587000 0.5516000 0.9071000 0.65200000 1.7954000 23.37540 1.6504450
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543 0.9109000 1.4255000 0.6125000 1.45180000 2.8311500 25.59138 1.8226860
544 1.7800000 1.9955000 1.2600000 2.07850000 3.4437000 27.16836 1.8416170
545 1.7250000 2.3585000 1.8975000 2.01750000 2.4812000 28.04599 1.8785365
546 0.4935000 1.0753000 1.7025000 0.80610000 1.3428000 26.27472 1.8037660
547 1.1205000 1.4942000 2.0484500 1.08875000 1.4410000 25.76966 1.8775940
548 1.3665000 2.1207000 2.4551000 1.58570000 1.2799000 26.45108 1.8364150
549 0.7884500 0.9684500 1.9304500 0.78845000 1.8437000 25.76966 1.8775940
550 1.1166000 1.2966000 2.2586000 1.11660000 1.7174000 26.28073 1.8467098
551 0.6957000 1.5192000 2.4840000 1.51920000 2.1042000 26.79180 1.8158255
552 2.8095500 2.8489000 4.2863000 2.29080000 4.3740000 21.97991 1.6291590
553 1.9450000 1.9616000 4.4156000 3.09880000 5.6685895 21.62936 1.5568413
554 1.3608000 1.1946000 4.5348000 3.73240000 4.5922000 21.98665 1.6144467
555 0.9872000 1.0704000 3.3868000 2.16640000 5.0117000 21.97991 1.6291590
556 1.8400000 2.0896000 4.9848000 3.76440000 5.7841000 22.15990 1.6187015
557 1.6554000 1.6554000 3.5291000 1.18860000 3.8585000 21.97991 1.6291590
558 0.8754500 1.6344000 3.5103500 2.09900000 3.3298500 21.00983 1.4995570
559 1.0575000 2.9346000 5.8298000 4.58520000 7.1040000 21.69525 1.5757382
560 1.7696000 2.3302000 3.0810000 3.09920000 3.0360000 22.27934 1.6312745
561 1.8071000 2.5212000 2.8139500 2.55560000 3.5724500 22.25915 1.6389513
562 2.9000000 2.7235000 5.1823000 2.59500000 3.3650000 21.89293 1.6324290
563 0.7095000 0.7095000 5.6125000 1.06200000 1.6575000 22.00467 1.6263828
564 2.0100000 2.0100000 6.6258000 1.12750000 3.2925000 22.11641 1.6203365
565 0.4720000 0.8700000 5.1500000 0.61450000 1.2825000 22.04192 1.6243673
566 1.8269500 2.4910500 3.6849000 2.26155000 3.2350000 21.89293 1.6324290
567 1.6882500 2.1101500 5.7766000 3.41800000 4.0894500 21.95766 1.6155367
568 1.9913000 2.3034000 3.0314500 2.00500000 3.6555000 23.23960 1.6714647
569 0.7650000 1.6138000 1.3860000 0.77750000 2.6452000 27.55351 1.9476850
570 2.3775000 1.4700000 0.5075000 2.37750000 3.7050000 27.50500 1.9590833
571 1.9210000 1.5775000 1.9210000 1.12800000 3.6938000 27.55351 1.9476850
572 1.2950000 1.3035000 1.3035000 1.50250000 4.3369000 29.01608 1.9287473
573 1.6125000 0.5675000 0.5588000 1.63000000 2.7816000 28.15767 2.0278520
574 1.8490000 0.5350000 1.8625000 1.43650000 2.6013000 27.55351 1.9476850
575 0.8105000 0.8975000 0.8975000 1.26870000 2.6280000 27.55351 1.9476850
576 0.1920000 0.8138000 0.7196000 0.71880000 3.2197000 29.01608 1.9287473
577 2.2125000 2.4425000 2.3810000 2.03350000 3.2409000 21.15520 1.5670043
578 1.3075000 2.0333000 1.5812000 1.38355000 3.4039000 21.21077 1.5733610
579 1.7959000 2.0110000 2.4459500 2.26050000 5.3926500 20.94752 1.5059775
580 2.3390000 3.6765000 3.3185000 2.49500000 4.5469000 21.29456 1.5424725
581 0.7584000 0.9852000 1.3008000 1.19140000 5.2256000 20.91724 1.5399200
582 1.3424000 0.9210000 1.0775000 0.96700000 1.3424000 21.10735 1.5841852
583 1.5350000 2.1205000 2.9530000 1.54875000 3.3550000 21.00392 1.5950095
584 1.3070000 1.4095000 3.5663000 1.96000000 4.1475000 20.95294 1.5492277
585 2.5713500 3.0814500 5.4086000 3.73150000 7.2778500 30.10534 1.9913858
586 3.2665000 3.4700000 4.4729000 5.27465000 8.9961500 31.39761 1.9299320
587 0.9804000 2.2152000 3.5554000 2.11440000 5.8460000 29.41628 1.8561720
588 2.1912000 3.5328000 4.0232000 2.37640000 8.0263579 28.54309 1.8225034
589 2.4800000 4.8538333 5.9617000 4.82383333 8.8720500 29.52400 1.9959398
590 2.9087000 4.8538333 5.0480000 4.85383333 10.0851333 29.82561 1.8976060
591 3.5927000 4.5850000 5.3214000 5.87033333 11.1016333 29.52400 1.9959398
592 3.7437000 4.2356000 3.7954000 6.70383333 10.4930000 28.01138 1.8620470
593 0.8789000 0.8789000 1.3814000 4.78100000 8.0586000 27.89026 1.8604305
594 1.8869000 2.3040000 3.2277000 1.11640000 3.5395000 21.97991 1.6291590
595 1.4484500 1.7249500 3.0396000 1.46325000 2.9464500 21.81003 1.6175480
596 0.7456000 0.9226500 2.7636000 1.14765000 4.1685000 21.98497 1.6181248
597 1.4642000 1.8859000 3.3157000 1.74290000 4.0743000 21.97991 1.6291590
598 1.4347000 1.4134500 2.1916500 1.51025000 1.4929500 21.64015 1.6059370
599 0.6346500 0.5393000 3.1862000 1.12700000 3.0985500 22.12442 1.6200805
600 1.4801500 1.4801500 2.5496500 1.96890000 1.8886000 21.88228 1.6130088
601 1.4253000 1.3044000 3.7419000 2.82020000 3.1392000 21.99002 1.6070905
602 1.3550000 2.2006000 1.8257500 1.35500000 5.7527500 26.36791 1.8062415
603 0.8893000 1.2378000 1.0935000 0.94895000 2.9444500 23.24437 1.6784880
604 1.3386000 1.1881000 1.7634000 1.12500000 3.6090000 24.00340 1.7534487
605 2.5759000 1.9405000 2.4738000 2.60050000 5.0845000 24.38292 1.7909290
606 3.1811000 3.1280000 3.6013000 2.96750000 5.4515000 27.10427 1.8442675
607 2.0225000 1.2332000 2.3650000 2.37900000 4.8630000 26.15529 1.7808740
608 2.4823000 2.0423000 1.8002000 3.51000000 5.9940000 27.89026 1.8604305
609 0.9689000 1.7332000 2.0677000 1.73320000 8.9602000 25.02680 1.6983358
610 1.3198000 1.2225000 2.5942000 0.53130000 8.1725000 24.69597 1.6585155
611 1.2190000 1.2190000 3.8878000 1.25750000 9.1057000 21.80000 1.5313915
612 1.6660500 1.1678500 1.1088000 1.07865000 7.6680000 24.69597 1.6585155
613 0.8134474 1.9427474 1.9522474 1.94274737 9.0227000 28.25361 1.8652800
614 0.9423000 1.8971000 2.4902316 1.89710000 8.4746000 28.25361 1.8652800
615 1.8722711 2.0059921 5.3192632 2.00599210 6.5343500 28.25361 1.8652800
616 0.9090000 0.9090000 3.6540500 0.94500000 9.3480000 21.13833 1.4517510
617 1.0271000 0.5600000 1.3184000 1.13640000 1.3846000 23.24437 1.6784880
618 1.1223000 1.1223000 1.8210000 1.21910000 1.1223000 21.64015 1.6059370
619 0.6974500 0.6974500 1.6234000 2.35930000 2.4673000 25.28324 1.7114200
620 0.9287500 0.7938500 1.3359000 1.02555000 0.9287500 22.44226 1.6422125
621 1.1443000 1.1267000 1.3485000 1.20850000 1.1443000 22.17489 1.6301207
622 0.6548500 0.5423000 0.7462500 0.71720000 1.4395000 22.44226 1.6422125
623 0.6408000 0.6120000 0.7680000 0.60650000 2.5715000 23.81365 1.7347085
624 1.0735000 1.0735000 1.7098000 1.07350000 1.7098000 28.57965 1.9349580
625 0.1950000 0.5025000 2.9674000 0.60200000 2.9674000 29.11683 2.0643943
626 0.6510000 0.7150000 0.9904000 0.65100000 0.9904000 26.30333 1.9340155
627 0.2464000 0.6192000 2.2845000 0.69000000 2.5854000 26.83699 1.9904370
628 0.6164000 0.6825000 2.6104000 0.57250000 2.6104000 28.47097 1.9117320
629 0.2925000 0.5314000 0.9206000 0.33980000 0.9904000 26.30333 1.9340155
630 1.5135000 1.9112500 1.2715000 2.00000000 3.3922000 28.31216 2.0238550
631 0.7200000 0.9720000 1.6546000 0.97200000 1.6546000 26.83699 1.9904370
632 2.9303000 6.6134000 6.1428500 2.93030000 8.1545000 17.62947 1.4126006
633 1.2000000 3.5974000 3.8714500 1.19910000 4.4066000 17.81162 1.4230063
634 1.0352000 4.2034000 3.3160000 1.82990000 5.1216000 17.61830 1.3510950
635 0.9750000 3.9636000 3.0222500 2.11700000 5.5879000 17.53173 1.3947672
636 2.6295500 6.1203000 6.0681000 4.54320000 9.6005000 16.97484 1.3936595
637 2.8139500 3.5587500 4.0212500 3.53900000 8.4363500 16.30157 1.3251695
638 1.8522500 2.4625000 2.4550000 2.29725000 6.4659000 16.53807 1.3077107
639 1.7617500 1.9575000 4.9345000 2.97050000 8.1023000 16.30157 1.3251695
640 3.4365000 5.5823000 6.5261000 3.37680000 7.2965000 18.34931 1.5077170
641 2.7653000 2.7653000 2.7653000 5.51250000 15.7645000 11.34233 0.8333742
642 4.1978000 4.1978000 4.1978000 7.12150000 16.4907500 11.27132 0.8265762
643 3.1198000 3.2323000 3.2323000 6.90125000 12.2675000 11.44369 0.8662601
644 1.0210000 1.3753000 1.3753000 5.40010000 14.8606000 11.22588 0.8236803
645 1.6520000 2.5390000 2.5390000 5.68990000 15.8150000 12.82473 0.8838935
646 3.4343000 3.4343000 3.4343000 7.29785000 13.3250000 11.04771 0.8153740
647 2.9060000 3.7085000 3.9355000 2.43600000 7.5991000 15.62944 1.1905580
648 1.6965000 2.5310000 4.0750000 2.50350000 7.6975000 15.71847 1.2563557
649 3.5130000 4.8490000 3.5130000 4.42250000 3.5130000 15.84440 1.2711600
650 2.3334000 5.2375000 5.8660000 3.12980000 8.3721000 15.68923 1.1840012
651 1.1665000 4.5331000 6.3988000 1.71850000 8.2793500 14.97199 1.0763612
652 4.5927000 4.9743000 7.5417000 2.38280000 7.5172000 13.01036 0.9869451
653 1.9524000 3.0156000 7.7428000 2.56100000 8.0835000 13.96227 0.9785264
654 0.7700000 1.2225000 1.1675000 0.66000000 4.8962000 16.51852 1.3085878
655 0.4312500 1.1000000 1.2100000 0.95250000 5.6088000 16.35772 1.2845135
656 1.8211000 1.8382000 1.8787000 1.70070000 1.8382000 16.73676 1.3347090
657 0.8992000 2.2556000 1.9050000 1.32120000 3.5448000 16.43176 1.3078568
658 2.5735500 2.6060500 1.1955000 3.05015000 3.3046500 18.46504 1.4610270
659 2.3499000 3.3920000 3.8310000 2.31570000 3.3920000 18.34624 1.4641415
660 2.1691000 2.4036000 1.6924000 1.60050000 2.4036000 17.97495 1.4177935
661 0.7525000 0.8300000 0.6775000 0.84950000 0.8630000 17.69190 1.3717987
662 1.0143000 0.8045000 1.3761000 0.29280000 1.5306500 17.33247 1.3815290
663 0.7008000 1.5692000 3.3686000 0.94740000 1.6416000 17.03462 1.3581190
664 1.1773500 2.4457500 2.2757000 1.30850000 2.7188500 17.32646 1.3546070
665 0.8992000 1.8650000 1.3225000 1.03750000 4.0509500 16.23013 1.3030320
666 9.4721000 7.2585000 12.5496000 8.01120000 13.3631000 12.11174 0.8495871
667 3.9561000 3.9689000 4.3444500 2.64775000 4.4510000 14.34014 1.0095687
668 2.6471000 2.8708000 4.8876000 0.78250000 5.3591000 13.03388 0.9220349
669 3.2586000 3.2586000 3.4834000 2.74960000 3.9549000 14.40199 1.0133723
670 3.8783000 2.4200000 5.5109000 2.83500000 5.9824000 14.06284 0.9704730
671 4.1950000 1.3975000 6.0409000 4.16750000 6.5124000 13.58483 0.9804555
672 1.7195000 2.2207000 5.9903000 2.05890000 6.4618000 13.37290 0.9306918
673 1.5925000 1.4994000 6.9914000 1.19250000 7.4629000 12.75829 0.8915580
674 2.8450000 2.0450000 7.5043000 2.87250000 7.9758000 13.16201 0.9231313
675 3.8913000 4.1646500 3.8913000 3.50465000 9.3067211 18.41939 1.5387031
676 2.0481500 2.0609000 2.0481500 1.83665000 10.0787000 18.25263 1.6366060
677 2.1233000 2.8535000 2.1233000 2.39370000 10.0453000 17.71016 1.4761100
678 1.1285000 1.5768000 1.1285000 0.84350000 9.7307105 17.74513 1.4716932
679 4.2120000 4.8456000 4.2120000 1.00355000 7.5639211 16.98919 1.4114087
680 3.5425000 3.7075000 5.2310000 5.71850000 11.5224000 17.96744 1.5485397
681 3.9450000 4.7550000 4.1952000 3.54780000 12.2824000 17.41773 1.4347965
682 3.3738000 4.7460000 4.1124000 2.03280000 9.6704000 16.41372 1.3012253
683 1.6600000 5.7936000 5.1600000 1.20900000 10.1336211 17.40414 1.4173522
684 3.9695000 5.4495000 5.5860000 6.36020000 6.2888000 15.88806 1.3472650
685 0.5520000 1.4701000 0.8057500 2.09390000 3.0525000 20.19111 1.9569830
686 1.3048000 1.3048000 2.5701000 3.01400000 1.3048000 18.98262 1.7826503
687 0.6425000 2.2682500 0.6425000 1.84645000 2.5104000 19.42995 1.8798140
688 1.2623000 1.2623000 2.1062000 1.36080000 1.2623000 19.42995 1.8798140
689 0.8206000 1.0344000 1.1618000 1.79140000 1.0344000 18.70989 1.6766495
690 1.3616000 1.8513000 1.5023000 2.89560000 3.4715000 20.06258 1.9128815
691 0.9725000 1.2112000 1.9278500 2.59755000 3.7374500 20.95228 2.0341520
692 1.9313000 2.0417000 2.2848500 2.10270000 3.3486000 18.98262 1.7826503
693 0.9469000 1.8598000 2.6067000 1.85230000 2.6067000 18.79236 1.7736895
694 0.9990000 1.3231000 3.2681500 1.27595000 3.7339000 18.83351 1.7502623
695 1.6118000 1.6975000 1.2435000 1.65220000 2.0175000 19.32162 1.7648230
696 3.2264000 2.6880000 2.5782000 1.65250000 3.4444000 19.34877 1.6369458
697 3.3218000 2.9876000 2.4700000 1.95210000 3.7425000 19.35252 1.7104907
698 3.1036500 3.0251000 2.9153000 1.98960000 3.7815000 18.71752 1.5104895
699 3.4250000 4.0988000 3.9890000 3.05080000 4.8552000 18.44051 1.4846974
700 1.1934000 0.9128000 0.9281000 0.61560000 1.2695000 18.46987 1.6089280
701 1.2486000 2.6024000 2.4569000 1.23120000 3.0187000 17.98983 1.4734850
702 1.7660000 3.3732000 3.2277000 1.82060000 3.9166500 17.90163 1.4404730
703 1.6435000 3.2139500 4.7076000 1.64350000 3.2151000 17.46812 1.3992960
704 3.9752000 3.4926000 3.1306000 2.71000000 4.3194000 19.40298 1.5900247
705 0.8375000 1.9565000 3.0797000 2.44000000 6.6093000 17.64470 1.6777870
706 2.5193500 4.8527500 5.5589000 4.98010000 7.8010000 15.81470 1.2909646
707 1.0362000 1.5886000 4.0558000 2.88810000 6.4356474 17.46114 1.6062493
708 0.7775000 3.8855000 2.8702000 2.37100000 4.3415000 17.51924 1.6121728
709 4.4080000 4.5280000 6.4502000 4.38050000 6.0490000 16.22604 1.3259990
710 1.3144000 2.0932000 4.6781000 1.96000000 5.5075474 17.37921 1.6143520
711 0.8085000 2.3537000 2.9588474 0.62100000 3.3600474 16.87591 1.4314500
712 1.8572500 2.0160000 4.4850237 2.05700000 4.1320000 17.52135 1.4908967
713 1.4388000 2.2371000 1.4388000 1.80760000 1.8200000 15.65493 1.2595510
714 0.8650000 3.4915000 2.5524000 2.10000000 8.1906000 18.32452 1.5637723
715 0.9650000 1.3270000 1.3270000 4.01540000 8.4409000 17.64470 1.6777870
716 1.5270000 3.5690000 3.5690000 5.43690000 7.4824000 17.64470 1.6777870
717 2.4475000 4.5320000 4.2220000 7.07240000 6.7671000 16.37927 1.4430023
718 2.5562500 4.5070000 4.9764500 4.28225000 4.5070000 15.89413 1.3218367
719 1.3275000 4.5575000 3.6352000 3.31600000 4.8420000 16.33178 1.4108242
720 1.8250000 5.0200000 4.4621000 3.54100000 5.1915000 15.96792 1.3199500
721 2.4550000 2.8315000 2.6895000 4.04800000 7.8506000 18.69358 1.5901260
722 1.7025000 2.2570000 2.2570000 5.70920000 8.7620500 16.34788 1.4573415
723 1.5900000 2.1770000 2.1770000 5.46300000 8.9506000 16.52176 1.4795200
724 1.8737500 2.3120000 2.2220000 3.41170000 7.8136000 18.16914 1.6339565
725 1.3870000 2.0020000 2.0020000 4.70790000 8.8859000 17.64470 1.6777870
726 1.4515000 3.6074000 2.5266000 1.54560000 2.0018000 20.82271 1.8109958
727 2.0081000 3.3408000 2.4112000 1.29170000 1.2917000 20.64144 1.8766640
728 1.5695000 2.6563000 3.6419000 0.95500000 2.5525000 20.71915 1.9160360
729 1.1550000 2.4089000 2.4926000 1.30980000 2.7001000 20.28942 1.9039620
730 0.8788000 1.1913000 2.6576000 2.46190000 3.7546000 20.95228 2.0341520
731 2.7329500 3.0300000 2.9430500 2.05370000 2.9847500 21.12445 1.7516018
732 1.4959000 2.0938000 0.9205000 0.78495000 1.1317000 20.48602 1.7979200
733 9.9367000 10.7233000 11.5570000 5.15040000 12.4123000 12.42615 0.9300183
734 7.6998000 8.4774000 8.4774000 6.34260000 21.2675000 11.54931 0.7968823
735 11.7991000 12.1269000 16.1724000 9.56400000 16.6439000 11.75390 0.8196215
736 4.3639500 4.2996000 9.4027000 2.47125000 9.7862500 14.14724 0.9843434
737 2.7584000 2.8188000 9.1098000 0.95760000 9.2020000 12.68435 0.9016193
738 2.2165000 4.2211000 8.6127000 1.28230000 9.0842000 12.67406 0.8968349
739 3.7189000 3.4082000 6.3748000 2.39210000 6.4670000 15.74975 1.1590745
740 2.4376500 4.4023500 4.5886000 3.27140000 4.4945500 15.19467 1.1588407
741 2.7400000 5.9638000 5.9693500 4.65215000 6.0099000 15.19467 1.1588407
742 2.4806000 2.0990000 7.9293000 1.51110000 8.6872000 15.03947 1.0607142
743 4.5113000 4.7786500 5.4275500 3.46145000 5.5197500 14.43257 1.0226006
744 4.0002000 4.0574000 4.0574000 2.68300000 4.1496000 14.43257 1.0226006
745 3.0050000 3.0050000 6.8899000 4.69735000 2.9350000 14.11519 1.1310454
746 1.9485000 2.0237500 5.6794000 4.74355000 1.9537500 14.92452 1.1991710
747 2.1350000 2.1350000 6.1340500 5.04150000 2.0650000 14.65466 1.1662090
748 0.9475000 2.5800000 0.7375000 3.35440000 4.0408000 16.73676 1.3347090
749 1.8006500 3.0865500 1.6762500 1.67940000 2.4637500 15.81506 1.1856600
750 2.1038000 2.6813000 2.0585000 2.21000000 2.4875000 16.19887 1.2260947
751 1.0250000 2.2395000 1.9678500 1.24000000 1.9678500 15.06317 1.0957801
752 1.8403000 1.9731000 1.8403000 1.97310000 1.8403000 15.66098 1.1174805
753 0.5737500 1.3036000 1.0250000 0.94500000 1.0250000 15.52400 1.1031460
754 0.9910000 2.2500000 2.7828000 1.35900000 2.3885000 15.66098 1.1174805
755 0.6650000 2.6340000 2.7875000 2.22770000 5.0856000 16.63806 1.3301473
756 1.7770000 2.1931000 2.1931000 2.00600000 2.1931000 17.98601 1.5161703
757 0.9670000 1.4306000 1.4330000 1.43060000 1.9548000 18.43232 1.6721073
758 1.7058500 3.0646000 2.9191000 2.07700000 3.3349000 17.98696 1.5054990
759 1.9797000 2.9151000 1.4902500 2.92580000 3.9697000 18.15476 1.6675650
760 0.9245000 1.2594000 2.8321000 1.49110000 4.0055000 17.48586 1.5315555
761 3.0062000 5.1329000 4.8286000 3.02730000 5.5306000 17.16604 1.4112868
762 0.9011000 1.7475000 1.3410000 2.50580000 5.4371500 17.48586 1.5315555
763 1.0356000 1.0356000 2.8262500 2.68200000 6.1279000 18.33255 1.6387847
764 1.3491500 1.5308000 3.0735000 1.86130000 7.3615000 19.60392 1.8168905
765 1.1049000 1.1049000 2.3458000 0.86500000 7.9046000 18.77363 1.7082110
766 1.2100000 1.2100000 2.4083000 1.89510000 9.3871000 17.96314 1.5688535
767 0.5762500 1.0537500 3.6045500 2.55880000 9.8671000 18.50115 1.7067473
768 0.6225000 0.6250000 3.1233000 2.67000000 10.1527000 17.96314 1.5688535
769 2.3836000 2.4075000 2.4960000 2.99710000 10.2932000 17.70264 1.5330510
770 0.5700000 0.9350000 3.6358000 2.98750000 10.0846000 18.09590 1.6370685
771 4.4815000 3.0375000 4.4815000 5.21250000 5.2125000 14.47111 1.0798831
772 2.0436737 2.0065000 3.3047000 2.35325000 2.9035000 17.10105 1.4184808
773 0.8830000 1.6798500 1.2155000 1.22490000 1.1548000 14.96050 1.1324150
774 3.7550000 1.5375000 4.1240000 3.75500000 3.7550000 17.77648 1.3795730
775 0.5225000 1.1735000 0.9505000 1.38100000 0.8620000 14.96126 1.1402680
776 2.2127000 2.1705000 2.6139000 2.21270000 2.2127000 15.44458 1.1770000
777 3.8150000 1.4525000 4.1840000 3.96250000 3.9625000 15.44458 1.1770000
778 3.0948500 2.7136500 3.0948500 3.70780000 3.7083500 14.07484 1.0325557
779 2.7537500 2.7350000 2.7537500 2.76330000 3.2252500 14.32170 1.0259285
780 4.2837500 3.3335000 4.2837500 4.43650000 4.8725000 13.41509 0.9534094
781 0.8625000 1.7535000 2.7797000 1.18990000 2.0860000 20.58544 1.8698592
782 1.9950000 2.1768000 2.9915000 2.05000000 1.9950000 20.21962 1.8670872
783 0.4534000 1.3799500 2.3282500 0.73200000 1.0032000 20.45172 1.8236825
784 0.1680000 1.0296000 2.5104000 0.49440000 0.5448000 20.45172 1.8236825
785 0.9600000 1.9335000 2.2472000 0.86440000 2.2217500 20.58544 1.8698592
786 0.9025000 1.8513000 1.2325000 1.20080000 1.7425000 19.42995 1.8798140
787 0.7655000 1.1485000 3.8448000 1.46640000 1.7566000 21.47349 1.7675510
788 1.6208000 2.0479000 2.1912000 1.55130000 1.6584000 21.16402 1.8254240
789 2.4028000 3.1670000 3.3483000 2.06400000 2.5678000 20.70264 1.7878395
790 0.8645000 1.3213000 3.4425500 1.21650000 1.2165000 21.00928 1.8543605
791 0.3657000 0.7660000 3.8448000 0.87900000 1.4808000 20.97976 1.7827355
792 1.8945000 0.8490000 5.2065000 1.98750000 2.0700000 15.81226 1.3060302
793 3.7106000 3.1175000 4.2965000 3.71060000 3.0350000 14.96866 1.2527137
794 2.2025000 3.8850000 2.2025000 3.04400000 2.2025000 15.24329 1.2576235
795 2.8825000 1.4025000 4.2766500 2.88250000 1.4025000 15.19436 1.2848485
796 2.1975000 2.3470000 2.2812500 2.51200000 1.7400000 15.24329 1.2576235
797 1.5300000 1.9870000 1.7687000 1.63000000 1.5548000 15.34195 1.1991520
798 2.4700000 2.6315000 3.9315000 3.37000000 2.0950000 15.02068 1.2300683
799 1.8025000 2.5496000 2.4625000 2.29610000 1.8025000 15.10159 1.1853905
800 2.7575000 2.5425000 5.6315000 3.77000000 2.5425000 15.40857 1.2858307
801 1.7782000 1.9413000 2.6753500 2.40770000 6.6254500 19.03917 1.8446410
802 2.2713000 2.2713000 3.4815000 3.48150000 7.2838000 18.56771 1.6885408
803 1.2140000 1.2140000 2.8517000 2.85170000 6.4071000 18.91449 1.7231113
804 2.1885000 2.9960000 2.4776000 1.42100000 4.6192000 18.68705 1.5975677
805 1.5106000 2.8645000 2.2256000 1.94940000 3.2313000 18.64128 1.4670550
806 1.1450000 2.1025000 1.7148000 0.92250000 3.4312000 17.99880 1.4307905
807 1.0697500 1.7664000 1.3043000 0.98330000 2.6933000 17.98688 1.4242920
808 1.9175000 2.5244000 3.0000000 0.90750000 3.5817000 18.33469 1.4202463
809 3.6825000 2.5488000 3.8887500 4.35270000 4.8432500 17.14948 1.3489662
810 2.9317000 1.5386000 3.0614000 3.15720000 3.2947000 16.73676 1.3347090
811 2.3464000 3.3544000 4.9439000 2.34640000 3.9180000 17.29422 1.3745663
812 2.5207000 2.5207000 2.7732000 2.38320000 2.5207000 16.73676 1.3347090
813 4.0454000 3.2615500 5.1743000 4.15340000 5.6204000 17.50398 1.4321803
814 2.8849000 2.7667000 3.7414000 2.88490000 3.5912000 16.93533 1.3503157
815 1.0418000 3.0941500 1.2975000 1.29750000 1.9995000 16.22032 1.2691345
816 2.9725000 2.0695000 2.9725000 3.85250000 4.1495000 17.02387 1.3268475
817 3.1963000 3.3051000 3.2236500 3.52040000 3.6772000 16.40434 1.2475965
818 0.5322000 1.7194000 0.7048000 0.64800000 0.7320000 15.73410 1.2668760
819 1.6950000 4.3395000 1.9025000 1.90250000 2.6045000 16.18093 1.2540230
820 0.7677500 1.3294500 1.3904000 1.83840000 1.3346000 16.26605 1.3030320
821 1.6765500 3.3710000 2.8992000 2.78100000 3.1771000 15.90301 1.2136800
822 1.7736000 1.9657000 1.9484000 1.59500000 1.8768000 15.35487 1.2322172
823 2.8748000 3.4010000 3.6533000 2.67750000 3.2792000 15.19490 1.1901436
824 0.9461500 2.3477000 1.8946000 1.14745000 1.8230000 15.73410 1.2668760
825 0.8825000 2.6646000 2.1450000 0.84000000 3.2809000 29.79406 1.8451450
826 0.7984000 2.7170000 2.3354000 0.71600000 3.2391000 30.22826 1.8180470
827 1.8025000 2.4306000 0.7175000 1.68400000 1.8096500 29.79406 1.8451450
828 0.5950000 2.9526000 1.9437500 0.71550000 2.9178000 30.22826 1.8180470
829 1.1124500 3.2388667 1.6650000 1.30495000 2.5039000 30.22826 1.8180470
830 1.4886500 2.9649833 0.8525000 1.67765000 1.8889000 29.79406 1.8451450
831 1.5297000 2.1584000 2.2864500 1.37435000 3.4307368 28.86319 1.8034355
832 1.2850000 1.9562000 2.0882000 0.84500000 3.8948000 29.45890 1.8342845
833 0.0000000 0.2976000 0.7477000 0.00000000 0.6275000 40.09833 3.8749800
834 0.1000000 0.7842211 0.8820000 0.03500000 0.8625000 39.76570 3.3333300
835 0.6760000 1.4035842 1.1735000 0.82700000 1.8200842 40.39435 3.9219075
836 0.8705000 0.1900000 0.0000000 0.00000000 2.5392000 40.39435 3.9219075
837 0.1361000 0.8806211 0.4692211 0.07750000 0.7520842 39.50629 3.7811250
838 0.2488000 0.9210500 0.6610000 0.25890000 1.1688000 40.39435 3.9219075
839 0.4522000 1.0172000 1.4393000 0.36290000 1.0075000 31.31097 2.0769153
840 1.6100000 3.7453500 1.1750000 0.76500000 2.8175000 32.78207 1.9265475
841 0.6145000 0.9175000 1.1544000 0.36250000 0.6803000 31.07003 1.9123065
842 2.2425000 3.4106500 0.8750000 0.41750000 2.4300000 31.92605 1.9194270
843 2.1293500 2.8144000 1.4144000 0.58125000 2.1293500 31.92605 1.9194270
844 0.4584000 0.7608000 1.2569000 0.49500000 0.8293000 32.89796 2.1181050
845 0.5725000 1.8169000 0.8437500 0.19125000 0.8787500 31.07003 1.9123065
846 0.1250000 0.7582500 0.7095000 0.01875000 0.4117000 31.84586 2.0512092
847 0.8628000 2.1764500 1.8252000 0.70500000 0.8628000 32.02897 2.1960940
848 1.1566000 1.8310000 1.9431000 0.55200000 1.8577000 30.44173 2.0061530
849 0.6475000 1.6173000 1.6178000 0.00000000 2.0306500 29.56564 1.9283375
850 0.6875000 1.2888000 1.8378000 0.22960000 1.5495000 30.44173 2.0061530
851 1.1849000 2.6968000 2.4644000 0.86240000 1.1849000 32.02897 2.1960940
852 0.6384000 1.6061000 0.9068000 0.55200000 1.8132000 30.44173 2.0061530
853 0.8300000 1.4823000 1.1928000 0.60750000 2.3394500 29.56564 1.9283375
854 1.4800000 2.9354000 1.6158000 1.61750000 2.1667000 26.33350 1.6704393
855 1.1605000 1.9668000 2.0502000 1.16110000 0.8400000 26.27472 1.8037660
856 0.5200000 2.6608000 0.6900000 0.81000000 2.8902000 26.91957 1.7681937
857 0.7950000 1.8420000 0.3672000 0.79500000 4.0588000 27.17511 1.6729300
858 1.1793000 2.0028000 1.9926000 1.67760000 2.2002000 26.79180 1.8158255
859 0.8623000 1.5034000 2.4521000 1.46030000 2.8902000 26.89063 1.8015735
860 0.6403000 2.5717000 0.8160000 1.57810000 4.1475000 26.97744 1.7014340
861 1.4639500 2.6565000 1.3353500 1.99490000 5.2843000 26.11036 1.6406900
862 0.9537000 2.8168000 0.8565000 0.75835000 4.6815368 27.17511 1.6729300
863 1.8655000 3.2375000 1.5250000 1.65460000 5.7397368 27.17511 1.6729300
864 1.0151000 1.6970500 1.4436000 1.56110000 3.9733368 28.26748 1.7725865
865 1.5425000 1.6176000 2.3881000 1.03250000 2.7752368 28.26748 1.7725865
866 0.2550000 1.5035000 1.5972500 1.31040000 2.8323368 29.35985 1.8722430
867 1.3569000 1.8527000 2.2922000 2.98300000 5.0003000 26.11036 1.6406900
868 2.3036000 3.6154000 1.8243000 1.79510000 6.1202368 26.68166 1.6518503
869 1.6025000 1.9550000 1.7900000 1.61300000 2.7595000 28.68954 1.8505220
870 0.8170000 0.6984000 0.7359000 0.73590000 2.9344000 28.68954 1.8505220
871 1.4496000 1.3272000 1.1952000 1.19520000 2.4619000 28.68954 1.8505220
872 0.8475000 1.5762500 1.6350000 1.38390000 1.3050000 28.68954 1.8505220
873 0.4000000 0.6919000 2.0030000 0.70390000 0.9016000 28.68954 1.8505220
874 0.2500000 0.8054000 1.4900000 0.48140000 0.7714000 28.68954 1.8505220
875 1.4155000 1.5432000 1.4567000 1.32520000 3.0296000 29.45890 1.8342845
876 1.6195000 1.5100000 1.6420000 1.61950000 4.7183000 26.72168 1.6585765
877 1.2300000 2.3814500 1.1325500 0.54875000 5.2083000 27.73182 1.7255143
878 1.2531000 2.7246000 1.0238000 0.24500000 5.2338368 27.25296 1.6630105
879 1.0385000 1.7696000 1.1742000 0.57250000 4.8067368 27.93232 1.7617260
880 1.0151000 1.4657000 1.4086000 1.34570000 3.9385184 27.93232 1.7617260
881 0.7440000 1.4602000 1.5922000 1.34570000 3.8892368 27.93232 1.7617260
882 1.9750000 3.1789000 1.5815000 0.48600000 5.5971000 26.32938 1.6618950
883 0.2762500 1.1082000 1.8382000 0.38500000 0.8950000 29.20245 1.8396970
884 0.6029000 0.8054000 1.3625000 0.46640000 0.8629000 28.68954 1.8505220
885 0.8820000 1.3574000 2.5814000 0.82450000 1.5608500 29.07422 1.8424033
886 0.4950000 0.8344000 2.1679000 0.63620000 1.0514000 29.20245 1.8396970
887 0.4236500 0.6174000 0.9012500 0.20805000 0.9075000 28.68954 1.8505220
888 0.3161000 1.2624000 0.9100000 0.31610000 1.3734000 28.68954 1.8505220
889 0.7160000 1.7779000 1.1707000 0.78890000 2.2999000 29.45890 1.8342845
890 0.6062500 2.1144000 1.9400000 0.43250000 3.2554500 28.09135 1.9197460
891 1.2475000 3.0705000 2.3950000 1.09500000 4.1624000 26.30164 1.7699425
892 1.8850000 3.5575000 2.2670000 1.58200000 4.9517000 25.89130 1.6887545
893 1.5367000 2.4258000 0.6600000 0.62750000 3.1333000 28.39044 1.8851340
894 1.3208000 2.0064000 0.6944000 0.16250000 2.6422000 28.33413 1.9179305
895 1.6656000 2.1144000 0.9120000 1.16240000 2.7619000 27.29042 1.7696383
896 2.9480000 4.7710000 3.3943000 1.62840000 4.6542000 25.40506 1.6201317
897 0.0000000 0.7332000 0.5848500 0.16875000 1.0325000 42.25588 3.8441620
898 0.4042500 1.0345000 0.6767500 0.17625000 0.9587500 41.28240 4.0626900
899 0.0000000 0.2475000 0.2650000 0.00000000 0.4925000 44.20285 3.4071060
900 0.0000000 0.6852000 0.7943000 0.34900000 0.7809000 42.74262 3.7348980
901 0.0000000 0.9089500 0.3264000 0.00000000 0.9098000 41.28240 4.0626900
902 0.0000000 0.9181000 0.2904000 0.00000000 0.5521500 39.89249 3.3918042
903 0.4450000 1.2992000 0.5614000 0.34800000 1.3015000 42.25588 3.8441620
904 0.2220000 0.9344000 0.4200000 0.00000000 1.3342000 28.48368 1.9006245
905 0.9387500 0.6312500 0.5275000 0.37500000 1.7150000 29.02466 1.9144810
906 0.6350000 0.9244000 0.8328000 0.33250000 1.8892000 28.48368 1.9006245
907 0.7700000 2.1002500 0.8472000 0.71065000 2.6421500 28.27782 1.9507270
908 1.3714500 1.6819000 1.5722000 1.12730000 2.6014000 29.35977 1.9784400
909 0.5411500 1.8784000 0.8568000 0.63140000 2.4230000 29.35977 1.9784400
910 0.8818000 0.6912500 0.7387500 0.27510000 1.3175000 28.68954 1.8505220
911 0.5520000 1.2336000 0.5520000 0.50640000 1.4783000 28.87529 1.9217302
912 0.9144000 1.5828000 0.5640000 0.94000000 1.2912000 29.69346 1.8396560
913 0.5780000 0.8252000 0.2300000 0.63000000 0.7152000 29.69346 1.8396560
914 0.9046000 0.5925000 2.1997000 0.53500000 2.0640000 27.76703 1.8810273
915 0.8723000 1.0055000 1.7111000 0.66940000 1.9672000 26.80382 1.9017130
916 1.0392000 0.7785000 1.2166000 0.34800000 1.2312000 28.24864 1.8706845
917 2.8450000 1.6230000 1.5990000 1.89150000 3.4014667 29.58226 1.8505183
918 1.3072000 1.7396000 0.9144000 1.24480000 2.0224000 29.58226 1.8505183
919 0.7275000 1.5336000 0.8210000 0.20640000 1.7209000 42.74262 3.7348980
920 1.0451500 0.8604000 0.6677000 0.42000000 2.5142000 41.28240 4.0626900
921 0.2554000 0.8515000 0.8973000 0.00000000 1.9632000 40.59637 3.6664415
922 0.2554000 0.6775000 0.5248000 0.07920000 2.6448000 41.28240 4.0626900
923 1.0623000 1.3385000 0.9600000 0.38070000 2.2877000 41.28240 4.0626900
924 0.6735000 0.8960000 0.2675000 0.50250000 2.9205000 41.28240 4.0626900
925 0.5550000 1.0560000 0.8325000 0.26000000 2.9097842 40.39435 3.9219075
926 0.5472000 0.8668500 0.7025000 0.37375000 2.6858000 40.39435 3.9219075
927 0.7813000 1.2145000 2.0098000 0.85105000 1.9463842 39.89541 3.1094325
928 0.2950000 0.9790842 0.6610000 0.42250000 1.0435842 38.19748 2.8643120
929 0.7813000 0.9805000 1.6965000 0.78130000 1.6330842 37.74711 2.7309853
930 0.3060000 0.6350000 0.9132000 0.10500000 0.3575000 34.12608 2.1740810
931 0.8003500 1.0585000 1.0079500 0.50615000 0.7479000 34.12608 2.1740810
932 1.7141526 1.2182500 2.0500000 1.26040000 2.1472053 37.01074 2.6417567
933 1.2385000 1.1815000 1.6430000 0.54095263 1.5620842 35.91948 2.7097623
934 1.4185263 0.7372500 1.6225000 0.88015000 1.6240842 39.89541 3.1094325
935 1.0764000 2.0404000 1.7119000 0.97300000 1.5686000 34.80163 2.3740710
936 1.2144000 2.6601000 1.9320000 1.05970000 2.7938000 36.59310 2.9800445
937 0.5594500 1.7854000 1.7683026 0.71840000 1.3136000 37.15396 3.0775980
938 0.6054000 2.3539000 2.3249000 0.06500000 1.8888000 37.15396 3.0775980
939 0.8829000 1.8180000 1.9381000 0.22550000 2.6662842 38.87517 3.3720198
940 1.0497000 1.5849000 2.1161000 0.17400000 1.8100000 32.62168 2.1901120
941 1.3636000 2.0450000 1.8966000 0.70410000 1.7744000 32.62168 2.1901120
942 0.5775000 1.2710000 1.4969000 0.30600000 0.9084000 34.80163 2.3740710
943 0.6675000 1.5894000 0.8631500 1.29690000 2.8885667 29.35985 1.8722430
944 1.1861500 0.8483333 0.7951000 0.90755000 2.2374667 29.52666 1.8559495
945 1.0325000 1.0028000 0.6978000 0.71030000 2.7893667 28.08184 1.8869780
946 1.9918368 1.6248667 0.7999000 1.40673684 0.9600000 31.15436 1.8912485
947 0.6925000 1.5990000 0.6925000 1.27030000 3.5202000 28.08184 1.8869780
948 0.9515000 1.1271000 1.1125000 0.39750000 1.8174500 28.24864 1.8706845
949 1.0806500 1.4471000 1.0350000 0.51250000 1.9852000 28.88765 1.8633170
950 1.8016000 2.2158000 1.7550000 1.91000000 2.3209000 31.75253 1.8975837
951 0.6391000 1.3083000 1.6656000 0.69670000 2.6095000 26.80382 1.9017130
952 0.3812500 1.1698000 0.7064500 0.46830000 4.3364000 27.05135 1.7491910
953 0.5122000 1.1642000 0.5568000 0.36500000 4.1002000 26.98947 1.7873215
954 0.7950000 1.8658000 0.7950000 0.68500000 3.4052000 26.91957 1.7681937
955 0.8819000 3.2888500 1.2022000 2.50860000 5.4663368 27.62847 1.7799540
956 0.7080000 0.7416000 1.0272000 0.70800000 3.5280000 27.65583 1.8918897
957 0.9528000 0.8450000 1.7880000 1.13280000 3.4102000 26.80382 1.9017130
958 0.7332000 1.6632000 0.9189000 0.56500000 4.4010000 22.02659 1.6565845
959 0.2422000 1.0668000 1.1803000 0.65040000 3.6589000 24.68185 1.9007465
960 0.9360000 1.2330000 2.6639000 1.23300000 2.1458000 21.05855 1.5831635
961 1.0414000 1.3726000 2.7821000 1.54190000 2.4547000 22.33492 1.4842635
962 1.1336000 1.3781500 2.2134000 1.67195000 3.5973000 22.33492 1.4842635
963 1.5830000 1.6718000 3.4475000 2.10410000 2.9683000 24.10341 1.9153785
964 1.3901000 1.3150000 2.9402000 1.26800000 1.5072000 22.43600 1.9450903
965 1.3872000 1.3950000 2.5152000 1.90080000 2.5488000 26.76488 1.6532640
966 0.9774000 0.8815000 2.2740000 0.90900000 1.5984000 24.21213 1.8510640
967 1.0404000 1.1451000 2.2731000 1.57145000 2.9263500 26.76488 1.6532640
968 0.9672000 2.3425000 2.3397000 1.31680000 3.0099000 18.02886 1.4389215
969 1.9330000 1.8225000 2.3746000 1.82250000 2.0517500 19.78218 1.6820635
970 1.5065000 1.5565000 1.7608000 2.03150000 2.0945000 19.78218 1.6820635
971 1.3390000 4.5906000 4.5638000 5.20550000 5.7860000 18.42145 1.6243945
972 2.3530000 2.4753000 2.2710000 2.94910000 2.9491000 20.52104 1.9342823
973 1.9750000 5.0726000 5.2418000 5.95970000 5.7860000 17.91993 1.4580392
974 1.8124000 1.8299000 1.6256000 2.64960000 2.6824000 19.80393 1.7808985
975 0.2043000 0.2043000 0.9194000 1.38030000 0.9875000 21.65939 2.0488640
976 1.0960000 1.0960000 1.9339000 2.04710000 1.5654000 20.25098 2.1457340
977 0.8312500 0.8312500 1.9536000 1.82570000 1.2864000 20.26819 2.0350815
978 1.3267000 2.0225000 3.0369000 2.22250000 2.4617000 20.53232 2.2343780
979 0.2778000 1.8742000 2.5369500 1.25565000 2.5369500 20.53232 2.2343780
980 0.2300000 1.7713000 2.3275000 1.10500000 2.3863000 20.57993 2.2387505
981 1.3779000 1.6550000 3.0627000 1.66000000 2.3955000 20.53232 2.2343780
982 0.8230000 0.8611000 2.4288000 0.86100000 2.4288000 21.07275 2.2150270
983 0.9180000 1.6110000 2.4276000 1.26225000 2.4276000 21.61318 2.1956760
984 0.7510500 2.0267000 3.0412000 1.46385000 2.9744000 20.53232 2.2343780
985 1.3505000 1.8531000 2.9813000 1.38175000 2.9813000 21.07275 2.2150270
986 0.8220000 2.6020000 3.9084000 2.85960000 4.6128000 21.56556 2.1913035
987 0.1056000 1.2242000 1.7074000 1.22550000 2.2992000 20.21872 1.6334550
988 1.5885000 2.1104000 4.4165000 3.72690000 3.3348000 17.78906 1.4821750
989 0.6943000 2.2429000 5.6372000 3.61090000 2.0263000 18.82774 1.6409190
990 1.1844000 1.0533000 3.3390500 1.95340000 3.3523500 19.00389 1.5578150
991 1.0375000 1.8940000 2.7824000 0.89400000 3.3745000 20.37552 1.9339165
992 1.6515500 2.4511000 2.5009000 2.39400000 2.6832000 19.00389 1.5578150
993 0.3368000 1.2069000 1.0939000 0.73785000 1.5267000 20.21872 1.6334550
994 0.9705000 0.6419000 0.8225000 0.81310000 1.7400000 21.40876 1.8908420
995 0.5262500 1.0802500 0.9175000 0.82365000 0.8450000 20.96849 1.7311802
996 0.7975000 1.2935000 1.4880000 1.08470000 1.0100000 20.33260 1.6813792
997 2.8681000 2.9117000 4.6773000 2.91170000 3.6621000 13.15925 1.0018458
998 4.1157500 4.7588000 6.9617500 4.75880000 5.4620000 13.96659 1.0157719
999 3.9087000 4.5827000 5.7179000 4.58270000 4.7027000 13.19670 0.9931761
1000 5.6613000 2.6399000 5.6614000 2.63990000 8.7350000 12.96343 0.9751119
1001 4.2943500 2.2691000 6.1035500 2.26910000 5.0883500 13.14161 1.0035675
1002 4.2513000 1.4964000 4.2514000 1.54240000 7.5996000 13.05968 0.9795440
1003 4.7735000 2.3171000 4.7736000 2.95880000 8.7805000 13.66947 0.9772527
1004 4.4617000 2.8837000 4.5989000 3.19750000 9.3901000 12.27511 0.9547159
1005 2.1155000 2.7285000 4.3123000 2.72850000 2.6265000 13.44093 1.0416653
1006 1.1620000 1.3344000 2.1912000 1.27800000 2.2568000 12.55410 1.0607110
1007 2.2038000 2.9000500 2.9000500 3.16885000 4.0043000 12.55410 1.0607110
1008 1.3008500 1.3008500 1.3008500 1.40235000 3.8767500 12.41571 1.0383532
1009 5.4211000 5.6100000 5.8891000 5.47870000 6.9570000 12.69008 1.0213613
1010 3.9217000 4.8177000 5.3892000 4.81770000 4.7157000 14.43773 1.0604543
1011 1.0347000 2.8578342 3.1158342 1.77038421 2.2698500 15.18210 1.0793627
1012 2.1637000 4.2779000 4.8869000 3.86933421 3.8114000 14.48580 1.0714847
1013 1.1347000 2.1764000 3.1948000 2.17640000 2.0744000 13.62871 1.0682117
1014 4.0959000 4.0970000 6.9669500 4.07765000 5.3211500 15.99378 1.1845430
1015 1.3060000 1.3060000 3.0365000 2.92165000 4.2922000 16.91397 1.2387553
1016 1.8597000 1.8277000 3.8274000 3.10650000 4.4876000 16.91386 1.2956107
1017 2.1560500 2.1748000 3.7758500 2.12980000 2.2315000 17.73816 1.4779010
1018 4.6144000 4.5558500 5.8246000 4.20310000 4.6601000 16.71135 1.3265155
1019 1.1736000 1.1736000 3.5964000 0.47520000 1.1736000 17.73816 1.4779010
1020 3.4665000 3.4415000 5.7314000 2.85170000 3.4665000 17.73816 1.4779010
1021 3.2412000 3.0762000 5.7999000 2.13510000 3.2412000 17.06394 1.3909294
1022 1.4443000 1.2555500 4.1215000 0.96420000 2.4994000 17.73816 1.4779010
1023 1.1100000 1.0986000 3.7848000 2.25960000 3.8038000 17.77510 1.3307495
1024 0.5801000 0.9300000 0.4250000 0.42500000 1.0175000 19.59819 1.5403127
1025 0.2850000 0.8350000 0.8675000 0.28500000 1.4200000 19.28793 1.4937415
1026 3.4987000 3.6010000 4.0690500 3.49870000 3.6671000 18.55475 1.4451618
1027 1.1196000 1.4291000 1.3517263 1.12920000 2.3418000 19.76991 1.6127437
1028 3.0477000 3.3839000 3.9004000 3.45200000 4.5606000 17.90497 1.3152630
1029 1.1468000 1.1843000 2.0368000 0.67680000 1.5507000 19.28793 1.4937415
1030 0.7650000 1.0446500 0.8925000 0.71880000 2.0085000 21.71825 1.8289055
1031 3.2249000 3.1681000 3.9412000 3.16810000 3.5130000 17.30816 1.3208893
1032 2.3853500 2.6136500 3.0966000 2.53350000 4.2841000 19.37133 1.4124225
1033 6.4735000 6.4735000 6.4735000 4.28250000 6.9435000 14.23237 1.1306535
1034 5.6810000 5.6810000 5.6810000 2.52200000 6.0285000 14.23237 1.1306535
1035 3.4622500 3.4622500 3.4622500 1.68700000 3.8097500 13.07011 1.0256295
1036 5.0610000 5.0610000 5.0610000 3.38050000 5.5310000 14.24755 1.1330660
1037 4.7335000 4.7335000 4.7335000 1.55600000 5.0810000 14.24755 1.1330660
1038 3.8910000 3.8910000 3.8910000 0.43750000 4.2385000 13.37206 1.0536949
1039 3.2295000 3.2295000 3.2295000 1.49000000 3.6995000 13.37206 1.0536949
1040 5.5621000 3.0890000 4.1076000 6.09040000 5.5621000 12.82246 0.9712440
1041 4.5781000 3.3505000 3.1236000 5.10640000 4.5781000 13.14836 0.9681643
1042 6.1996000 3.6575000 4.7451000 6.72790000 6.1996000 12.31094 0.9635155
1043 3.2755000 2.4376000 0.9400000 3.80380000 3.2755000 14.10641 1.0417629
1044 2.1933000 2.1272000 4.6997000 1.08950000 2.1674000 16.16416 1.1954990
1045 1.7327000 0.9037500 5.4533500 1.64225000 0.9054000 14.56774 1.0682353
1046 5.9384000 3.9476000 5.7620000 3.88920000 5.9194000 14.74355 1.1080260
1047 6.7106000 3.2390000 4.8676000 5.74040000 6.7106000 13.96469 1.0806827
1048 3.4617500 3.8426000 1.9765000 3.99005000 3.4617500 13.66490 1.0066055
1049 3.6249000 5.1119947 6.3101474 4.89502895 5.1119947 14.35265 1.0356507
1050 2.2575000 6.8177474 8.0055947 2.25750000 7.5736000 13.20139 1.0264165
1051 3.5560000 6.0314947 6.2894947 3.55600000 6.0314947 13.61929 0.9996774
1052 5.3774000 7.2494947 7.5074947 5.17425000 7.2494947 13.23126 0.9903663
1053 5.1201000 3.5002000 8.2482474 5.12010000 4.7951000 13.09321 1.0898089
1054 6.8029000 11.6564947 11.9144947 4.90100000 11.6564947 13.08620 1.0668173
1055 2.1278105 2.8544947 3.1124947 2.58875790 2.8544947 15.10685 1.0674993
1056 2.2124000 4.3881000 5.1928000 3.79770000 4.2495684 14.83772 1.0485429
1057 1.7246000 4.6235947 4.8815947 1.72460000 4.6235947 13.64497 1.0010872
1058 1.2280000 1.8885000 2.2435000 5.23100000 1.8885000 12.14397 0.9531321
1059 0.9625000 0.9625000 0.9625000 3.67350000 1.3100000 12.49657 0.9743237
1060 1.4925000 1.4925000 1.4925000 3.71325000 1.8400000 12.28713 0.9625115
1061 2.9525000 3.4530000 3.8720000 7.08300000 3.4530000 12.51343 1.0120471
1062 1.6175000 1.6175000 1.6470000 5.21600000 1.6175000 12.28713 0.9625115
1063 2.7205000 2.7205000 3.1395000 6.76100000 2.7205000 11.93100 0.9398152
1064 0.6750000 3.8505000 4.2695000 5.10250000 3.8505000 13.48935 1.1200372
1065 2.8341000 3.1080000 2.2551000 2.25510000 2.6808000 20.34270 2.1075195
1066 3.3029000 2.0427000 3.6222000 1.66020000 1.9920000 21.51935 2.0435773
1067 0.5971000 0.9846000 1.1540000 0.76650000 1.3725000 20.34270 2.1075195
1068 1.6245000 1.3028000 0.9069000 1.60050000 1.1853000 20.11891 2.0460858
1069 0.5634000 0.4645000 1.4248000 0.51180000 0.5718000 20.21834 2.0907097
1070 1.6617500 1.6617500 2.7852500 1.69950000 2.0833000 19.93539 1.8808513
1071 0.8175000 0.8575000 2.0686000 0.90480000 1.1975000 19.96963 2.0570900
1072 0.7825000 0.7152000 1.0536000 0.69360000 0.6672000 19.98111 1.9833217
1073 1.6530000 1.1830000 1.3075000 1.26180000 1.3005000 20.16867 2.0424177
1074 2.3154000 3.7887421 3.5875000 2.44740000 2.3154000 15.40296 1.0768152
1075 2.1354500 2.3166211 1.9265000 2.37135000 2.9451500 16.06514 1.0977107
1076 4.0920000 5.4386421 5.7499421 4.24440000 4.1124000 14.58366 1.0567172
1077 1.9317000 2.2195000 0.8904000 2.55000000 3.1238000 16.06514 1.0977107
1078 3.4485105 3.5711000 1.9769000 3.60195789 4.1414000 15.79162 1.1113483
1079 0.3389474 1.2457763 1.5037763 0.98920000 0.8060000 15.08816 1.0471477
1080 3.6100105 4.3071947 3.0344000 3.84945790 4.3071947 14.62210 1.0575218
1081 2.4420105 3.1391947 3.3971947 2.79595789 3.1391947 14.62210 1.0575218
1082 2.2297000 2.1977000 3.0544000 3.62090000 5.1362000 17.81205 1.1835980
1083 3.5622000 3.5622000 7.0542000 6.41660000 7.2043000 14.04981 1.0440388
1084 1.4448000 1.4868000 5.5104000 5.07120000 4.6779000 13.98696 1.0298181
1085 2.0717000 2.0717000 3.8852000 6.22330000 3.8852000 13.57924 1.0311217
1086 4.3653000 4.8278000 5.2987000 4.76170000 5.6634947 13.65327 1.0754327
1087 1.6004000 1.7574000 1.6004000 5.24220000 1.6004000 13.05981 1.0982022
1088 0.8542500 1.0112500 0.8542500 4.25885000 0.8542500 13.05981 1.0982022
1089 3.9908000 3.9588000 5.5349000 5.06610000 6.3998000 15.37931 1.1054863
1090 3.2267000 3.2267000 6.5130500 5.36750000 6.5182000 14.36708 1.0430430
1091 0.8513000 1.2501000 3.0792000 0.73790000 3.8084000 23.35111 2.0318037
1092 0.7356500 1.2786000 1.7411000 0.55740000 2.7029000 22.59881 2.1482290
1093 0.6830000 1.4066000 1.4066000 0.46105000 1.4066000 21.51962 2.1787860
1094 1.4304000 1.7412000 2.7447000 0.99380000 2.7447000 21.42606 2.1618960
1095 1.0369000 1.4722500 2.0165000 0.92000000 2.0165000 21.51962 2.1787860
1096 0.3692000 1.8528000 2.0684000 1.30080000 2.0684000 22.02038 2.1628610
1097 1.1368500 1.0886000 2.2298000 1.39410000 3.0811000 21.48717 2.0410728
1098 0.8151000 1.6409500 3.1542000 0.98310000 3.5349500 22.59881 2.1482290
1099 0.6312000 0.9986000 1.8127000 1.26360000 2.4242000 21.48717 2.0410728
1100 0.1839000 1.6388000 2.6231000 0.83400000 3.4913500 22.59881 2.1482290
1101 5.6236000 5.1145000 4.6666000 6.15190000 5.9017000 12.62006 0.9480243
1102 2.0217000 2.3405000 3.0850000 2.34050000 2.0472000 13.20240 0.9796972
1103 4.9935000 5.5935000 7.1907000 5.59350000 6.3807000 13.00257 1.0179297
1104 5.9490000 5.8807000 8.2753000 5.07900000 6.8907000 15.79867 1.2183051
1105 5.9490000 5.9490000 8.5791000 5.19400000 7.4972000 14.47449 1.0674563
1106 2.8337000 2.8359000 6.5122000 2.83590000 4.2209000 14.69644 1.0760648
1107 0.6972000 0.9492000 4.3738000 0.94920000 2.0484000 13.49357 0.9955337
1108 2.7797000 3.1680000 2.3607000 3.30800000 2.7797000 13.14836 0.9681643
1109 1.2160000 2.4450000 4.2011000 1.21600000 3.6251000 14.68900 1.1322527
1110 1.3305000 3.0460000 4.2930000 1.40050000 4.1446000 14.97565 1.1975585
1111 1.9450000 2.1250000 4.5311000 2.24600000 2.4701000 14.94103 1.1581645
1112 1.7955000 3.7681000 4.9855000 1.79550000 4.8371000 14.97565 1.1975585
1113 2.0587500 2.4803500 3.4362500 4.01895000 5.5991000 17.00059 1.3290835
1114 2.9414500 3.4535500 5.3521500 4.70585000 3.8116000 16.45043 1.2570917
1115 1.4112000 1.8585000 4.9786000 2.95270000 2.0460000 15.66609 1.1560370
1116 2.8908000 2.2901500 4.7793000 2.64760000 2.1475500 15.97081 1.1759082
1117 1.0325000 1.0918000 2.7661000 2.16850000 2.5752000 15.70009 1.2114565
1118 0.9456000 1.0347000 2.6211000 0.87780000 2.4723000 21.26813 2.1193147
1119 1.4959000 2.4317000 2.4317000 2.04440000 2.7533000 20.79518 2.0072405
1120 3.1420000 3.4348500 3.2922000 2.39565000 2.5307000 20.83362 1.9440727
1121 1.7996000 2.0634000 3.0973000 1.94770000 3.0763000 21.41016 2.1462990
1122 2.3301500 3.2808000 3.9495000 3.14320000 3.9495000 21.18122 2.0902255
1123 1.8074000 1.8074000 3.3938000 1.88670000 3.2450000 21.18122 2.0902255
1124 1.2535500 1.2535500 2.8399500 1.33285000 2.6911500 21.18122 2.0902255
1125 0.8975000 1.3037000 2.5504000 1.29010000 2.4341000 20.95228 2.0341520
1126 1.0347000 1.5830000 2.7038500 1.11400000 2.5902000 21.41016 2.1462990
1127 0.0975000 0.7800000 1.5864000 0.64050000 1.4376000 21.18122 2.0902255
1128 1.1620000 1.9702000 2.6254000 2.62540000 2.7044000 20.62755 2.2431230
1129 0.6552000 0.7388000 1.3940000 1.39400000 1.9416000 20.43926 2.1944285
1130 0.9075000 2.4008000 3.0560000 2.63445000 2.9367000 20.62755 2.2431230
1131 1.4225000 2.9058000 2.9058000 2.76480000 2.9058000 20.88842 2.2108483
1132 1.7460000 2.6307000 2.7507000 2.37720000 2.7507000 21.01885 2.1947110
1133 0.6862500 0.7780000 1.4332000 1.43320000 2.0641000 20.43926 2.1944285
1134 0.3648500 1.0932000 1.4686000 1.58170000 1.8434500 20.62755 2.2431230
1135 1.0572000 1.4160500 1.4452500 1.84390000 1.4452500 20.62755 2.2431230
1136 0.0156000 0.8620500 1.0246500 0.76855000 1.0246500 21.01885 2.1947110
1137 0.7630000 0.8779000 0.8971000 0.97450000 0.8971000 21.61318 2.1956760
1138 1.6132000 3.4743500 2.8726000 1.58530000 3.4449000 20.79518 2.0072405
1139 2.2125000 2.3105500 3.1451000 2.33350000 1.9292500 20.49248 2.0749455
1140 0.8196000 3.3727000 3.3983000 2.49470000 3.6003000 21.01885 2.1947110
1141 3.0212000 3.1875000 4.2058000 2.01780000 3.0443000 20.66676 2.0808973
1142 1.0650000 1.6513000 1.8860000 1.84800000 1.2975000 20.41805 2.0472777
1143 2.0353000 1.4647500 1.6303000 1.73930000 1.1142500 19.96963 2.0570900
1144 2.5679000 3.4756000 2.7247000 1.94400000 3.0470000 20.65697 1.8416200
1145 2.4401000 1.5493500 3.6700500 1.26825000 1.4218500 20.67657 1.9470630
1146 0.9573000 2.2368000 1.0044000 0.69620000 1.8720000 20.57149 1.8197700
1147 0.7380000 4.2545000 3.4203000 1.79550000 4.8645000 19.00389 1.5578150
1148 1.2475000 1.8995000 1.8945000 2.04450000 2.0715000 18.97392 1.4956220
1149 1.4520000 2.0732000 1.6802000 1.75800000 4.7922000 18.05250 1.4596825
1150 1.8875000 3.3288000 2.6880000 2.31480000 4.6930500 18.36963 1.4923933
1151 2.4610000 2.7100000 2.2432000 2.46520000 2.7535000 16.46565 1.2577290
1152 0.9768000 1.0595000 2.4372000 0.61320000 1.3891000 17.52581 1.4391173
1153 1.9741000 2.2176000 2.7040000 1.99320000 2.2176000 17.10190 1.3678150
1154 2.4139000 2.7859000 1.3272000 2.34720000 3.7782000 16.53307 1.2584855
1155 3.4495000 3.4495000 5.5588000 4.50670000 6.0509000 16.64303 1.2175435
1156 1.3293000 1.3293000 3.6890000 2.12600000 2.7932500 20.26819 2.0350815
1157 0.2688000 1.4175000 3.6079000 1.41750000 3.7175000 20.53232 2.2343780
1158 0.2496000 0.5839000 3.9758000 1.50310000 3.3086000 20.26819 2.0350815
1159 0.9402000 2.0204000 5.4147000 3.38840000 2.4066000 18.82774 1.6409190
1160 0.2400000 1.8371000 3.3504000 2.23350000 3.9639000 21.56556 2.1913035
1161 1.0410000 1.5319500 3.7761000 1.55060000 3.8025500 20.26819 2.0350815
1162 0.8901000 1.1856000 4.1647000 1.71550000 3.1138000 19.63604 1.7964483
1163 0.8544000 1.9506000 3.0123500 1.28900000 3.6044500 20.37552 1.9339165
1164 1.2649000 1.0870000 1.6305000 1.51790000 1.2110000 20.26819 2.0350815
1165 0.8133000 0.9409000 3.5112000 0.96300000 2.8795000 20.26819 2.0350815
1166 1.5541000 1.5541000 2.6617000 2.57600000 1.9945000 20.26819 2.0350815
1167 0.4584000 0.4584000 2.1180000 0.54720000 0.5472000 20.76859 1.9748020
1168 1.3894000 1.3894000 1.5554000 1.47820000 1.4782000 19.87779 1.9007400
1169 2.2255000 2.3143000 4.0900000 2.22550000 2.2255000 20.99304 2.0423657
1170 1.2900000 1.2479000 1.3273500 1.24790000 1.4407000 20.92055 2.0646710
1171 1.7738500 1.8161000 0.7787500 1.71875000 1.9110500 19.95187 1.8769915
1172 1.7036000 1.6916000 1.7178000 1.39000000 1.5690000 19.93405 1.8687800
1173 0.3402000 0.5150000 1.0873000 0.87780000 0.9385000 20.41503 1.9674460
1174 0.9057000 0.8118000 0.8118000 0.32160000 0.6875000 19.94296 1.8728858
1175 3.1390000 3.2278000 4.6674000 3.13900000 3.2510000 20.65987 2.0391165
1176 1.1532000 0.8772000 0.5475000 0.65095000 0.9991000 19.94296 1.8728858
1177 2.1750000 3.5832000 2.6768579 3.30770000 5.4230000 28.11921 1.7962608
1178 0.9518000 0.8829000 2.0840579 2.48000000 3.2070000 26.55678 1.8326660
1179 1.8715000 2.2506000 2.4128500 2.09960000 3.6714000 26.14136 1.8151308
1180 1.3468000 0.8900000 2.2875000 2.35810000 2.7215000 26.55678 1.8326660
1181 1.3250000 1.4428000 1.9775000 1.58000000 2.4205500 26.44084 1.7843267
1182 0.9925000 0.5525000 1.5975000 0.84500000 0.9790000 26.84957 1.8505630
1183 0.9200000 1.2400000 1.5725000 1.17500000 1.7765000 26.84957 1.8505630
1184 0.2760000 0.6238000 0.9360000 0.47280000 1.8320000 26.08075 1.8150915
1185 0.8150000 0.4265000 1.1037500 0.00000000 0.5140000 26.84957 1.8505630
1186 2.3248000 3.2956000 3.4700000 2.21580000 5.3297000 25.71552 1.8357550
1187 2.6925000 3.2240000 3.1800000 2.53620000 4.7575000 24.55072 1.8130600
1188 3.2015000 3.7176000 3.4858000 3.82240000 5.0615000 24.37373 1.8069790
1189 1.4511000 2.5949000 2.9612500 1.35135000 4.7773000 24.74149 1.8354880
1190 1.5570000 1.9685000 3.4338000 1.70000000 5.6873000 23.82719 1.8057035
1191 0.9025000 0.7675000 4.3203000 0.73890000 4.8171000 25.27618 1.8015215
1192 3.0331000 3.4446000 1.7008000 3.71290000 4.9139000 23.19774 1.7956863
1193 1.4635000 1.1430000 3.6219000 1.05500000 3.9654000 25.98217 1.7804643
1194 1.5368000 1.8954500 3.6950000 1.11450000 4.6994000 24.50074 1.8209697
1195 1.2347000 1.1861000 1.9941000 1.29500000 7.4067500 25.79127 2.0512070
1196 2.0657500 2.1265000 0.7675000 1.03575000 5.7147500 23.95871 1.9326985
1197 0.5515500 0.8785000 1.8650000 0.42490000 7.4480000 25.79127 2.0512070
1198 2.1049000 2.4984000 1.6875000 1.68000000 7.2490000 25.37328 2.0138150
1199 3.3145000 1.7219000 3.3590000 1.39400000 3.7845000 22.67770 1.8981020
1200 3.1601000 1.1218000 3.4675000 2.71950000 3.5458000 23.68114 1.8664217
1201 3.4171000 1.4623000 2.2825000 2.56500000 4.1839000 24.53514 1.8894860
1202 3.4320500 1.2199000 3.0937500 3.41600000 3.9351500 24.42094 1.8832282
1203 0.7812000 0.8258500 0.2416000 0.73020000 1.0342000 24.66206 1.9352563
1204 0.5952000 0.8583000 0.6982000 0.61010000 2.8296000 24.63242 1.9253123
1205 1.8260000 1.8000000 2.6792000 1.55000000 2.6036000 24.86435 1.7378215
1206 1.5425000 2.7897500 3.1200000 1.64450000 4.0629500 25.17200 1.7991080
1207 0.4356000 0.4650000 1.1169000 0.28850000 1.0661000 24.77160 1.8797378
1208 2.0256000 2.1830000 2.3088000 2.02560000 2.7489000 24.62848 1.7624610
1209 1.7736000 2.1471000 2.0225000 1.81500000 3.1892000 24.70382 1.8111457
1210 1.5250000 1.8727000 1.3290000 1.76640000 2.6173000 24.63143 1.8845995
1211 1.9345000 1.6300000 1.8270000 1.80060000 2.7571000 28.71426 1.8499125
1212 1.5007000 1.9644000 1.9644000 0.79570000 1.5388500 26.69656 1.9357833
1213 1.2988000 2.8280000 3.0868000 2.54170000 4.4144000 27.82468 1.9137012
1214 2.6457000 2.6850000 2.6857500 2.24050000 2.9631000 27.38061 1.9569500
1215 1.2952000 0.9021500 1.1877000 0.90650000 1.9228000 28.71426 1.8499125
1216 2.1231000 1.6269000 2.8890000 0.99750000 2.8074000 25.02182 1.8257645
1217 1.0997000 1.0997000 1.3368000 0.67800000 1.2493000 25.02182 1.8257645
1218 1.2493000 1.3118000 1.1130000 0.55180000 1.3118000 24.67885 2.0216540
1219 1.9286000 1.9286000 1.6870000 1.15750000 1.9286000 27.38061 1.9569500
1220 0.8320421 1.1784000 1.0924000 1.18800000 5.0434000 27.89602 1.8436314
1221 2.1224000 2.0600000 3.9317500 2.21965000 5.8422500 28.15764 1.8418985
1222 1.0175000 1.0175000 3.8105000 1.44050000 5.3145000 28.55706 1.9248900
1223 2.0800000 2.2274000 2.0950000 2.31250000 3.2190000 27.55692 1.8787780
1224 1.9375000 2.1850000 1.9400000 2.17000000 2.6690000 27.55692 1.8787780
1225 0.9095000 1.6753000 2.1520000 1.82835000 3.9380000 26.42783 1.9678960
1226 0.9974000 1.1328000 1.2701500 2.02820000 2.7415000 27.35497 1.8968427
1227 0.7525000 1.7640000 0.9995000 1.70400000 4.0056000 27.60768 1.9199825
1228 2.0627500 2.3927000 3.2494500 1.52750000 6.8434579 28.62821 1.8458212
1229 1.6125000 3.0992000 2.0208000 2.42520000 6.8263579 28.11921 1.7962608
1230 2.7868500 1.4652000 1.4376500 0.92000000 2.9140000 24.61167 1.6949802
1231 0.2736000 0.4390000 0.7737500 0.61750000 2.3137000 23.76745 1.8352210
1232 0.5976000 0.6432000 0.9168000 0.67390000 1.6371000 25.13297 1.7466083
1233 0.7615500 0.8406000 1.1082000 0.78250000 1.3218000 25.68800 1.8030610
1234 0.4284000 0.6973000 0.8580000 0.45230000 0.8276000 25.86312 1.7198010
1235 1.1050000 1.4784000 1.4784000 0.90120000 1.3935000 26.03824 1.6365410
1236 0.8100000 1.3560500 1.6716500 0.86570000 1.9640500 26.22951 1.7453843
1237 1.7299000 1.7614000 1.8142000 1.07250000 2.5646000 25.35928 1.7190915
1238 2.6962000 4.5988000 2.5554000 2.69620000 6.0058000 22.60412 1.7262800
1239 0.8425000 2.2665000 2.4973000 0.94320000 3.1542000 22.18029 1.7954280
1240 1.1459000 1.3099500 3.1515000 0.90380000 2.3923000 22.97360 1.7978725
1241 0.4817000 0.9592000 3.9749000 1.51090000 0.8016000 23.40307 1.7441630
1242 0.5136000 0.3007000 3.6324000 0.70930000 0.7093000 23.10717 1.8443925
1243 1.3225000 3.5183500 2.4305500 1.32250000 4.6321000 22.18029 1.7954280
1244 2.3051000 3.9496000 2.4130000 2.30510000 5.6147000 22.32156 1.7723787
1245 2.2775000 3.3967000 4.1208000 2.60800000 3.2391000 22.79168 1.7697955
1246 2.4040000 2.6665000 6.8738000 2.76150000 7.1214000 24.09233 1.6846583
1247 1.5075000 1.6897000 5.4046000 1.14000000 4.4531895 24.93931 1.7365753
1248 1.0375000 2.1360000 5.2073000 2.08890000 2.4619000 23.40307 1.7441630
1249 1.3800500 2.6647000 4.7120500 2.74550000 2.5071000 22.79168 1.7697955
1250 1.1379000 0.9562000 2.0593000 1.38060000 2.3711000 25.13249 1.6853558
1251 1.2998000 1.2998000 3.1552000 2.63650000 4.7269000 24.55875 1.6415533
1252 1.2998000 1.3110000 3.1991000 1.94430000 3.5844000 25.26911 1.6954320
1253 0.7676000 1.0000000 5.1163000 1.09500000 4.9897895 25.70744 1.7327815
1254 2.9870000 2.7903000 3.2623000 1.42770000 3.5167500 26.73411 1.7833060
1255 3.8057000 3.7115000 4.1830000 2.61120000 4.5165000 26.21907 1.7027685
1256 2.0835000 1.8300000 2.8201000 0.96600000 2.5785000 24.77160 1.8797378
1257 4.7915500 3.7819026 5.6231395 3.64525000 9.1272184 29.74202 1.8143900
1258 2.9840000 1.9215000 4.1516000 1.69100000 6.7275000 27.11622 1.7581457
1259 2.7754000 1.8276526 2.7754000 1.24200000 5.9126000 27.60380 1.7631713
1260 3.3725000 2.7009158 4.8365000 2.46250000 5.3608000 25.60786 1.7330005
1261 3.2335000 2.7600000 4.0271000 2.30500000 4.1858000 25.60786 1.7330005
1262 2.1925000 1.8000000 4.3094000 1.57000000 4.5086000 26.11549 1.7528190
1263 1.4237500 1.1675000 2.0787000 4.03665000 3.8678000 23.21750 1.7611830
1264 0.8650000 1.0490000 2.0762000 3.26230000 2.9197000 23.16233 1.8027878
1265 1.1857500 1.2702500 2.8981000 3.63855000 3.2959500 23.16233 1.8027878
1266 1.1475000 0.8300000 2.4562000 3.91230000 3.5697000 23.21750 1.7611830
1267 2.5875000 1.8650000 2.6775000 3.94750000 4.1200000 24.35996 1.7906320
1268 1.9955000 1.8585000 2.9235000 4.56500000 4.4042000 22.92160 1.8614125
1269 2.1900000 2.0325000 1.0675000 2.85000000 2.8500000 24.35996 1.7906320
1270 2.7200000 2.7231000 1.5225000 2.72000000 2.7200000 24.35996 1.7906320
1271 1.7767000 1.7767000 0.9045000 2.05750000 2.0993000 24.30480 1.8322368
1272 1.3747000 1.2467500 2.2307500 1.39740000 3.3237000 22.56413 1.8098147
1273 2.0062000 1.3147500 3.3812500 0.92700000 2.2936000 22.82566 1.8479873
1274 2.2015000 1.0380000 2.1700000 1.65825000 3.7612000 22.54414 1.8515820
1275 2.0197500 2.0707500 2.1037500 2.81200000 5.0579500 22.55914 1.8202565
1276 2.3885000 1.7515000 2.4725000 2.55600000 4.8002000 22.54414 1.8515820
1277 2.9815000 1.8902500 2.6512500 1.98600000 5.2468500 22.54414 1.8515820
1278 2.7595000 0.8665000 2.8475000 2.56700000 6.1582000 24.37671 1.9700905
1279 2.1125000 1.2410000 1.8200000 1.14000000 5.8830000 24.16771 1.9513945
1280 2.3082000 1.5586000 1.0998500 0.75940000 3.1679000 24.77389 1.6887120
1281 1.0630500 0.6404000 1.2741000 0.65310000 0.8895000 27.61072 1.7242720
1282 0.3979000 0.5467000 0.5880000 0.54670000 1.4820000 27.64909 1.8273032
1283 1.2984000 1.0475500 1.8485000 0.70000000 0.7000000 26.19231 1.7064920
1284 1.1514000 0.9975000 1.7917500 0.90335000 1.2371000 27.61072 1.7242720
1285 0.9871000 1.3815000 1.2740000 0.95500000 1.6070000 27.61072 1.7242720
1286 1.6220000 2.1289000 1.8970000 0.99000000 3.2364000 25.99085 1.6190420
1287 1.0425000 2.0934000 2.6111000 0.60000000 2.4212000 26.77708 1.6629075
1288 1.4025000 1.1841000 2.3863000 0.91250000 2.6981000 24.46493 1.6982407
1289 2.4852000 1.3733000 4.4003000 2.98270000 4.4345000 23.66294 1.6656278
1290 2.0235500 2.0855000 3.4211500 2.74530000 3.5101000 22.25317 1.6493115
1291 1.5460500 2.4284500 4.0007500 3.10035000 5.2856500 21.70776 1.6378760
1292 2.2430000 2.2430000 3.8899000 2.90280000 3.9776000 22.25317 1.6493115
1293 0.8850000 1.3639000 1.0532000 0.88500000 0.8850000 24.99585 1.6752795
1294 2.3000000 2.3291000 2.8997000 2.55470000 3.2115000 22.07625 1.6231067
1295 1.4061000 2.0666000 2.5418000 0.91500000 2.8536000 23.56014 1.6476800
1296 2.0443500 2.4020500 2.9560000 2.50840000 4.8110000 23.64134 1.6327370
1297 1.8358000 2.8006000 2.7946000 3.02790000 6.5151000 22.01356 1.5700420
1298 2.8043000 3.0783000 1.0750000 2.66820000 8.2050000 22.26252 1.5307350
1299 2.5783000 3.2031000 2.1700000 3.29540000 7.3226000 22.01356 1.5700420
1300 2.3674000 2.6680000 2.1577000 1.84400000 5.6285000 23.13803 1.5337960
1301 3.2425000 3.3373000 3.5675000 3.28250000 9.8925000 22.72328 1.4388860
1302 1.9362500 2.0310500 2.7469000 2.20680000 9.0753000 23.36897 1.5514240
1303 1.7387500 2.2305500 1.2208000 1.76715000 7.8456000 24.27502 1.5927595
1304 0.4525000 1.0020000 1.3556000 0.84100000 7.8986000 22.92310 1.5939795
1305 3.2013895 3.1413895 5.3997895 4.73388947 10.4769895 22.60412 1.7262800
1306 3.9575000 3.9575000 8.0154000 7.39150000 7.7890000 20.79778 1.6570878
1307 5.2543895 3.6030000 7.3677895 6.78688947 11.2658000 22.55768 1.5189180
1308 3.5765000 2.9700000 5.7614000 5.90220000 8.9050000 20.48883 1.6674047
1309 4.6265000 1.8180000 5.9359000 6.07670000 9.3863000 21.47499 1.6826510
1310 3.5925000 3.3025000 6.6479000 6.78870000 9.0715000 20.56032 1.6815960
1311 3.9696000 3.9858500 4.1263000 4.26710000 7.5767000 21.47499 1.6826510
1312 2.6500000 2.6500000 5.9704000 6.11120000 8.4825000 20.34585 1.6390220
1313 3.2596000 4.1571000 3.1188000 3.25960000 6.5692000 22.60412 1.7262800
1314 1.7350000 1.5756000 1.0350000 2.37750000 10.6153000 24.59090 2.0610690
1315 2.8725000 2.3446000 1.1300000 3.20250000 12.0480790 26.12968 2.1482447
1316 3.6582000 2.5151500 4.2128000 1.16480000 10.6997737 25.69712 2.0744665
1317 2.8626000 1.7001000 3.4172000 1.49560000 10.3802500 26.64260 2.1773033
1318 3.2574737 3.7560000 4.9484000 3.32040000 5.4648000 24.95553 1.8045993
1319 3.1275000 3.2096000 2.1630000 3.31750000 9.6718737 25.44108 1.9471130
1320 3.9500000 3.7146000 2.1975000 4.45096316 12.8005790 25.53009 1.9122990
1321 4.8027632 4.6920000 6.5673737 5.60910000 7.0837737 26.32515 1.7998060
1322 0.8080000 0.7740000 4.3994000 3.17650000 6.9753000 24.63881 1.6770733
1323 0.9302500 0.8050000 4.2471000 3.53250000 6.6620500 24.62132 1.6745570
1324 1.9105000 1.7450000 5.6684000 3.31250000 7.3018500 24.04634 1.6605555
1325 3.0074500 3.3675000 4.5130500 1.87750000 6.8481000 23.74503 1.7636540
1326 2.1492000 2.1492000 4.8931000 2.98420000 7.4690000 27.60250 1.7431770
1327 1.0750000 6.0818000 2.9419000 2.97670000 7.4789000 23.40307 1.7441630
1328 2.7574000 2.8665000 4.6471000 2.45850000 8.4250000 25.75925 1.7582883
1329 2.1549000 5.2793000 2.0382000 2.81975000 6.5752000 23.65954 1.7587812
1330 2.3840000 3.5399895 5.7946000 2.13550000 3.9944000 23.57405 1.7539085
1331 1.8936000 2.0677000 2.5669000 1.94520000 4.1066000 25.12767 1.8589835
1332 0.4227500 0.5778000 0.8826500 0.22140000 2.4186000 28.63250 1.8487305
1333 0.8168000 0.5185000 1.6872000 0.35520000 2.8668000 25.12767 1.8589835
1334 1.0655000 1.8651000 1.6966500 1.20750000 3.6170000 28.26875 1.8704525
1335 0.5699000 0.8984500 0.8976000 0.74270000 3.2851000 27.16031 1.8930840
1336 1.3475000 1.2504000 1.8036000 0.83360000 1.9972000 28.99626 1.8270085
1337 0.5475000 1.1409500 1.4629000 0.54750000 2.6920000 28.63250 1.8487305
1338 1.9325000 2.0262000 2.8150000 1.61500000 3.1486000 29.73937 1.8717673
1339 1.8182000 2.8126000 2.7414000 2.28880000 3.9883000 31.18426 1.8823695
1340 0.7178000 0.5642000 2.0220000 1.20760000 9.6061000 27.66894 2.1382660
1341 0.4852500 0.7781000 0.8995000 2.00535000 9.0549500 25.40009 2.0748340
1342 0.4575000 0.4609500 1.3166500 1.57560000 8.6252000 25.19109 2.0561380
1343 0.9375000 1.5605000 2.5581000 2.49450000 10.4572000 26.64292 2.1125337
1344 1.1992000 1.0409000 3.0482000 0.82950000 10.1574000 27.66894 2.1382660
1345 1.7470000 1.2817000 3.0641000 2.35030000 10.1733000 24.37671 1.9700905
1346 0.7350000 1.8913000 3.0906000 1.93580000 10.8409000 27.37010 2.1327850
1347 2.2340000 1.2115000 3.9425000 2.40400000 9.2685789 29.12860 2.1879330
1348 0.7730000 0.8135000 2.1785000 1.00825000 9.4773289 27.16927 2.1949950
1349 1.8982500 0.8350000 3.8312500 2.06825000 8.9805789 27.18994 2.3313553
1350 1.2092500 0.4450000 2.0855000 1.45750000 10.5468290 26.18961 2.1985260
1351 2.5925000 1.6200000 4.0030000 2.98750000 8.3035789 28.23649 2.5636760
1352 1.4412500 0.8875000 3.5147500 1.60000000 8.8080789 27.33953 2.3325123
1353 1.2245000 1.1537500 2.7722500 1.29000000 10.0443290 26.18961 2.1985260
1354 0.8475000 0.6625000 1.8660000 1.28625000 9.4805789 26.85975 2.1245010
1355 0.9625000 2.4900000 2.6774000 0.71070000 2.7748000 31.14295 1.8034540
1356 2.2311000 3.1339000 3.2299000 2.04040000 3.4561000 29.96523 1.8377615
1357 1.3320000 2.1360000 2.5812000 1.29030000 2.7748000 31.14295 1.8034540
1358 2.0248000 2.2052000 1.9698000 0.93000000 1.9007000 29.96523 1.8377615
1359 0.9607000 2.9104000 2.7200000 0.96070000 2.6509000 29.96523 1.8377615
1360 1.2125000 2.3984000 2.1564000 0.92250000 2.7223000 31.18426 1.8823695
1361 0.8962000 1.3577000 1.2028000 2.10700000 2.8280000 28.30197 1.8734955
1362 0.8085000 1.9375000 2.0200000 0.79350000 2.5048000 25.43398 1.8164992
1363 1.1475000 1.2044000 1.2466000 0.71500000 2.7226500 24.85545 1.7183820
1364 0.5510000 1.9469000 2.1069000 0.52750000 2.9598000 24.85545 1.7183820
1365 0.5577000 1.9461000 2.6328000 0.54235000 2.1564000 26.77708 1.6629075
1366 1.4923000 1.7751000 1.8848000 0.48600000 1.3143000 26.01250 1.9146165
1367 0.8850000 0.8850000 0.6164500 0.88375000 2.2344000 25.26415 1.8881513
1368 0.4976000 0.6726000 0.9115000 0.53980000 2.7999500 24.70839 1.8472417
1369 0.6371500 0.7396500 0.7992500 0.81750000 2.2012000 24.85545 1.7183820
1370 1.5795000 1.5795000 2.2432000 1.38150000 4.6912000 22.92204 1.7462725
1371 1.1148000 0.7525000 1.5550000 0.90500000 3.4691000 23.13526 1.6742430
1372 2.0233500 2.0233500 2.2744500 1.70325000 4.0047000 22.70881 1.8183020
1373 1.0000000 1.5025000 1.5012500 1.45515000 4.9837000 23.13526 1.6742430
1374 1.2467000 0.9675000 1.8488000 1.14770000 3.5068000 23.57603 1.7597577
1375 2.3423000 2.1275000 3.2347000 2.44720000 4.8391000 22.99750 1.8433732
1376 0.5532500 0.3933000 1.7841000 0.88690000 3.4935000 23.50472 1.7574930
1377 1.9040789 2.5407500 3.2828000 2.65440000 3.4562000 23.33726 1.8440063
1378 1.3512500 1.3512500 1.5025000 1.37750000 4.3047500 20.71864 1.7878185
1379 0.6675000 0.6675000 2.0250000 1.25250000 4.2824000 20.57238 1.7318023
1380 1.0900000 1.0900000 2.2821000 1.27325000 3.0336500 20.02354 1.6635555
1381 1.0385000 1.1637500 1.8925000 1.89250000 5.5179000 20.53840 1.8050217
1382 0.6518000 0.6518000 1.0087000 1.00870000 1.4259000 19.81132 1.5572495
1383 1.4710000 1.4710000 2.4818000 1.65390000 2.4183000 22.15580 1.7297693
1384 2.2080000 3.4865000 3.4825000 3.48650000 3.5645842 23.80519 1.8918112
1385 1.6841000 2.1962000 3.2905000 2.52940000 3.4479000 19.27748 1.6491215
1386 0.5825000 0.7980000 1.9250000 1.92500000 5.3149000 20.17792 1.8394280
1387 2.6777000 4.1335000 3.6158000 2.46140000 5.0063000 17.74799 1.4621543
1388 0.8025000 0.9552500 4.8603500 1.05400000 4.6900000 17.62719 1.3475545
1389 1.3457000 4.8244000 1.3485000 1.34570000 5.1145000 19.07986 1.6537510
1390 2.5106000 4.2338000 2.4925000 2.51060000 4.2338000 19.07986 1.6537510
1391 0.3350000 1.2680000 4.2680000 0.97000000 4.1475000 17.73225 1.4512883
1392 9.0148500 9.2417000 11.1277500 3.37200000 11.5300000 17.53985 1.1826598
1393 1.3950000 2.2315000 5.3455000 2.08250000 5.6225000 16.88987 1.3841130
1394 1.8450000 1.4650000 6.1357000 2.12300000 5.9050000 17.09061 1.2980153
1395 0.9419000 0.6915000 3.8152000 3.25760000 5.2150000 18.10178 1.3684853
1396 2.3330000 2.3185000 5.0807500 2.41450000 5.9209000 19.33113 1.4324230
1397 7.0056000 7.2666000 5.6962500 7.08050000 10.3140537 16.89012 1.1917346
1398 1.4982000 1.9113000 3.8655000 2.49240000 4.7410000 18.38720 1.3557462
1399 1.9088500 2.2014000 3.5623000 2.20140000 4.3657000 18.60728 1.3639770
1400 3.0840000 3.3994000 2.6255000 3.42120000 3.3144000 19.70289 1.4488150
1401 3.0840000 3.0840000 1.2355000 3.42120000 2.0484000 19.81424 1.4910413
1402 8.0445500 8.2056000 2.1842500 7.61515000 9.3887500 16.82713 1.2047372
1403 1.9282500 1.4872500 1.4415500 1.39265000 6.1507000 28.75335 2.3779370
1404 1.9467500 0.6315500 1.9128000 0.97975000 6.6447500 28.75335 2.3779370
1405 0.7134000 0.9377500 3.3406000 2.25310000 7.4667500 28.75335 2.3779370
1406 1.6032000 1.1675000 2.1450000 2.15850000 9.1012000 27.74501 2.2917582
1407 3.0133000 3.1498500 4.2021000 4.11740000 9.2838500 28.16407 2.1249844
1408 1.0987500 1.5140000 2.6268000 1.51400000 5.7200000 28.75335 2.3779370
1409 0.7500000 1.1682000 1.0075000 1.56650000 8.5681000 28.75335 2.3779370
1410 1.0057000 0.6275000 2.0250000 2.16220000 8.4816000 28.75335 2.3779370
1411 2.2132000 1.3560000 2.6900000 2.47850000 9.2312000 26.28864 2.2337495
1412 1.7799000 1.6340000 3.4590000 1.24475000 8.9494000 28.75335 2.3779370
1413 1.7725000 1.9475000 3.8469000 3.15590000 3.2684000 20.52662 1.7228480
1414 1.5630000 1.6900000 3.9915000 3.30600000 3.4115000 20.90770 1.6916965
1415 1.2618000 2.0600000 2.7190000 2.03350000 2.2860000 20.21735 1.6487460
1416 1.4665000 2.1530000 4.5740000 2.68750000 2.8400000 21.18314 1.8610775
1417 3.3755000 3.6645000 7.1101000 5.78300000 6.8295000 20.57349 1.7368154
1418 1.3412500 1.3412500 5.4057500 5.21810000 4.8865000 21.18073 1.7879630
1419 0.5190000 0.7775000 3.2840000 1.44985000 1.5937500 20.86121 1.7903003
1420 0.6297000 0.7324000 2.4790500 1.59865000 1.6230000 20.69038 1.8025822
1421 0.5925500 1.3169000 1.6020500 0.98340000 1.3169000 20.16948 1.7189150
1422 0.1080000 0.9463000 2.4816500 0.55870000 1.1235500 20.21735 1.6487460
1423 1.5267500 2.4392500 5.0095000 2.22750000 3.6026500 19.98788 1.5140193
1424 3.6690000 5.8862500 4.7965000 2.54200000 9.2709000 21.60040 1.8705255
1425 0.9750000 1.9092000 3.7920000 1.61520000 2.4339000 20.18508 1.6328038
1426 1.0672500 1.3860000 5.0220000 1.16300000 3.6639000 19.54532 1.7811635
1427 0.6145000 1.8800000 4.3102000 1.18350000 2.9521000 20.14554 1.7539995
1428 2.7717500 2.7717500 6.9657500 1.85075000 6.2296500 20.07373 1.8592530
1429 0.6125000 1.2691000 2.7325000 1.18030000 1.1803000 19.27748 1.6491215
1430 1.5889000 2.1390000 3.4453500 2.56245000 2.7232500 18.63110 1.5228165
1431 1.3795000 2.4248000 1.9125000 1.91250000 3.1965000 18.59887 1.4615146
1432 2.3725000 3.5405000 2.2950000 2.29500000 2.8995000 19.50158 1.5168862
1433 1.1045000 3.2480000 1.0270000 1.02700000 2.5230000 18.37251 1.4473900
1434 0.7925000 0.9473000 2.9294000 1.97320000 2.8865000 19.61160 1.6393377
1435 0.3025000 0.5302000 0.6402000 0.64020000 0.5302000 19.09191 1.5023197
1436 1.6450000 1.6450000 1.2336000 1.47600000 2.6263000 17.98473 1.3965115
1437 1.6375000 3.6610000 5.7768000 1.24200000 4.2225000 25.36577 2.1097055
1438 1.8560000 1.4085000 2.2075000 1.44750000 5.9684000 22.49861 1.9759280
1439 1.6530263 0.9688500 0.7777000 0.89335000 6.5280500 27.08152 2.3238403
1440 2.7324000 2.6256000 2.3484000 2.37820000 4.6220000 25.00635 2.0570730
1441 2.4101526 1.5200000 1.2307000 1.50570000 6.4812000 25.62598 2.1769325
1442 0.9267500 3.6120000 4.6318000 2.67550000 4.0480000 25.92356 2.0813530
1443 1.0025000 2.3515000 3.1493000 2.16700000 4.7425000 28.75335 2.3779370
1444 0.9335000 3.4550000 5.1318000 2.26900000 3.4550000 26.10327 2.1076692
1445 1.0850000 2.8865000 4.0830500 1.63275000 4.1675000 28.75335 2.3779370
1446 1.3250000 3.1890000 5.0268000 1.30950000 3.4350000 26.49497 2.1991160
1447 5.3794500 5.3992000 5.6914000 1.54555000 7.0841000 16.35856 1.2112580
1448 3.0670000 4.2651000 4.5693000 2.68200000 5.9620000 17.81759 1.3492390
1449 3.6546000 3.6546000 3.7368000 1.18450000 5.1961000 16.85390 1.2343431
1450 3.1001000 3.1001000 3.3923000 2.24760000 4.7850000 17.42787 1.2994580
1451 1.4535000 1.4535000 1.7457000 1.34205000 3.1384000 17.90116 1.3728753
1452 2.6079000 2.6350000 2.6375000 2.32880000 5.8775000 18.30127 1.3817440
1453 2.5438000 2.5438000 2.6260000 2.25600000 4.0187000 17.59242 1.3342080
1454 1.9483000 2.3278000 4.5750000 2.37530000 6.8369000 18.77304 1.3818067
1455 0.6424500 0.7904000 3.6895000 2.49120000 6.5178000 22.45064 2.0860328
1456 0.8468000 1.3000000 4.9114000 3.62500000 7.6516000 20.75325 1.8298460
1457 2.4012000 2.4812000 3.7780500 2.82500000 7.0348000 21.95789 2.0275375
1458 0.4468000 0.3107000 3.2971000 2.96020000 7.6174000 23.73786 2.2156470
1459 1.8465000 1.8465000 3.1085000 2.19250000 5.9924000 21.33826 1.9076780
1460 1.5465000 1.1405000 4.9114000 3.78720000 7.8138000 23.73786 2.2156470
1461 1.2477000 0.8777000 4.0980000 3.59450000 7.6547000 23.73786 2.2156470
1462 2.4650000 0.7060000 4.4865000 4.83880000 8.8654000 25.21622 1.9530133
1463 2.2492500 2.4092500 3.6517500 2.97800000 6.7192000 21.95789 2.0275375
1464 0.8550000 1.1967500 0.8750000 1.79900000 8.7894316 26.24561 2.2967920
1465 0.5575000 2.0545000 1.8300000 2.75900000 10.0744316 29.20138 2.3497670
1466 0.7526000 0.7259000 2.2555000 2.39610000 8.1571000 25.40969 2.2697437
1467 1.5081000 1.5081000 2.5415316 1.42200000 7.5784000 26.24561 2.2967920
1468 2.0685000 0.8200000 3.8340000 4.25130000 9.0804000 26.46962 2.2827070
1469 1.0289000 1.0864000 1.9530316 1.68950000 7.7684000 26.24561 2.2967920
1470 1.1003500 1.4650000 2.1320000 3.06100000 9.6690158 29.20138 2.3497670
1471 2.0697947 1.9986000 2.7663000 1.57440000 2.7407000 24.61918 1.7615100
1472 1.9472947 2.9870842 3.4670000 3.30500000 3.0370842 23.45320 1.8374015
1473 0.6400000 0.8797000 1.6897000 1.03630000 1.1763000 23.85494 1.7474575
1474 1.8473947 2.5185000 3.3285000 2.21320000 2.8151000 23.65407 1.7924295
1475 2.3572947 3.4550000 4.3405000 4.07750000 3.4550000 23.45320 1.8374015
1476 0.3182000 0.6725000 0.7034000 0.39615000 0.7675000 23.86828 1.7379120
1477 1.3375000 2.2178842 4.0575000 3.45500000 2.2178842 22.68895 1.8233490
1478 1.1612500 1.5182000 1.5450000 1.60445000 1.8498000 23.64734 1.7620225
1479 0.9875000 1.1888500 0.6398000 0.89720000 1.9681500 23.64734 1.7620225
1480 1.8968000 2.2388000 3.2102000 2.01060000 6.0372000 22.14892 2.0734090
1481 2.2346000 2.2050000 2.7896000 2.20500000 5.6933000 21.16342 1.9564185
1482 2.5580500 1.3936000 2.1668500 2.55805000 3.9373000 21.45377 1.8842295
1483 1.4088000 1.1650000 0.8870000 1.40880000 3.1938000 21.16342 1.9564185
1484 3.3287000 1.6181000 3.5358000 3.23870000 6.3213000 20.68423 1.7934904
1485 0.6240000 0.8146000 1.4004000 0.68400000 4.1406000 21.49192 1.9954153
1486 0.6720000 1.0860000 1.9704000 0.68400000 4.7106000 21.16342 1.9564185
1487 2.1713000 1.5320000 2.4233500 2.17130000 5.1053000 22.14892 2.0734090
1488 2.7730500 2.1337500 3.3513500 2.54505000 6.1585500 20.90355 1.8729570
1489 1.7182500 2.0662500 2.4516500 2.58000000 5.3016500 20.17792 1.8394280
1490 1.3391000 1.6866000 2.2800000 2.06820000 1.6866000 19.57762 1.7125570
1491 1.5272000 1.8797000 2.4542000 2.63690000 2.5403000 20.19369 1.7631552
1492 0.5825000 1.5680000 2.6425000 3.09820000 4.0781000 20.17792 1.8394280
1493 0.9772500 1.3350000 2.3861500 2.84750000 4.7634000 20.17792 1.8394280
1494 1.7077000 3.6729500 1.6525000 1.70770000 4.1802500 20.20421 1.7123067
1495 1.5337000 2.2313000 2.9767000 2.30000000 2.5403000 20.21735 1.6487460
1496 1.4941000 1.6866000 1.2944500 2.12990000 1.8873500 19.73870 1.7651572
1497 0.8748000 0.8952000 0.8082500 0.92210000 1.3728000 21.30760 1.6931042
1498 2.4384000 2.3520000 1.8007000 2.30880000 3.0118000 20.58562 1.6332030
1499 1.4129000 1.4993000 1.4129000 1.54250000 1.2054000 22.04700 1.7464695
1500 0.6637500 0.6637500 0.6637500 3.71850000 5.4355000 19.06086 1.4393220
1501 2.9967500 2.9405000 2.9967500 3.80975000 4.5992500 20.53072 1.5620173
1502 3.3291000 3.2427000 2.3840000 3.52620000 2.9719000 20.23916 1.5516953
1503 2.6710000 2.6710000 0.9605000 2.95870000 1.6354000 19.84727 1.5032000
1504 3.4723500 3.3859500 3.3859500 3.34275000 4.0039000 20.43511 1.5759430
1505 1.3296000 2.3178000 1.5149000 1.76520000 2.4944000 23.63725 1.8127643
1506 0.8687500 1.2762500 3.0273000 1.27625000 1.1312500 22.23733 1.7214120
1507 0.4108000 1.3490000 2.4990000 1.34900000 1.2040000 22.40519 1.7978140
1508 2.4028000 2.4147000 1.3239000 2.40280000 2.5597000 23.10419 1.7851417
1509 2.2349000 2.2139500 2.3045000 2.16585000 2.0341000 23.66863 1.7278780
1510 1.0800000 0.8430000 0.8430000 1.30320000 1.4891000 23.63725 1.8127643
1511 1.2425000 1.7952000 1.7952000 2.01960000 1.8096000 23.45498 1.9036887
1512 1.3768500 1.5231000 2.3487000 1.52310000 1.6694500 22.71951 1.8624073
1513 2.1415000 2.1962000 1.7634000 2.19620000 2.6071000 23.56497 1.8574717
1514 0.8402000 0.8402000 1.8072000 0.00000000 0.9627000 18.86590 1.5541710
1515 2.7781000 4.7950000 3.0658000 2.57060000 5.0363000 17.94237 1.6587560
ah3pm10 ah3gp_rnk ah3dent_rnk ah3phar_rnk ah3hosp_rnk ah3leis_rnk
1 20.31892 12492 277 785 392 50
2 20.46719 20665 2564 2999 7333 914
3 20.46719 3716 1 222 933 101
4 20.27525 6479 713 3633 5163 250
5 20.44019 7668 13959 14749 8677 4973
6 20.76831 37 1066 5104 459 2177
7 21.23929 17000 21396 27384 18893 13756
8 20.44019 1276 6695 14749 1790 1608
9 20.92170 3876 128 130 41 475
10 20.44019 2977 12207 15903 3740 6937
11 20.76831 62 9868 12809 66 7996
12 19.31425 2111 10383 6778 6476 18414
13 19.46905 4823 21179 17667 3512 16494
14 19.22788 10612 17688 11921 16413 17445
15 19.05607 3083 15337 12294 3179 12490
16 19.05607 2869 16635 12260 2296 12427
17 19.22788 2303 14786 6119 5245 15596
18 19.67501 14001 6160 7315 11902 2212
19 19.67501 15032 9332 5493 3810 3731
20 19.67501 8203 7385 8070 10865 2501
21 19.67501 8820 7976 5773 2702 847
22 19.67501 12904 15715 18053 18655 11456
23 19.67501 8138 7312 5493 5185 1571
24 19.67501 7357 6533 10890 14250 4056
25 18.41872 7267 5764 7367 5169 29292
26 19.13962 10854 8485 10960 8412 28694
27 19.06077 7188 9411 20498 8176 23202
28 18.88195 6763 10388 13460 7410 28992
29 18.84130 1738 1133 11359 492 21287
30 19.51363 5500 542 1613 6174 17223
31 18.27768 3498 26023 28185 18108 14252
32 17.60556 7803 30285 32884 23713 19624
33 18.50547 7814 20641 26581 4443 9707
34 18.52070 8884 13441 23134 2944 12258
35 17.33821 15544 22873 29484 16110 18223
36 17.26831 10016 11330 14677 19071 11957
37 17.87292 19307 33285 36221 19489 26254
38 21.02212 15416 25439 2232 18016 15838
39 20.08826 14384 25862 4582 15381 9497
40 20.08744 11216 30119 13012 3742 20198
41 19.96986 14980 26416 8834 18898 16668
42 20.81311 18315 23554 8675 21213 14192
43 19.15276 21057 27451 929 20706 12731
44 19.15276 13532 21148 12707 12082 8330
45 20.76801 3388 5210 22398 5027 10240
46 21.18603 4688 13325 3532 13073 7788
47 20.93742 1957 8690 688 8630 5338
48 20.76801 4807 6512 4570 6414 6209
49 21.18603 7572 18695 13649 18016 10866
50 18.40374 19391 8803 873 3347 13189
51 18.95190 707 11673 8067 9681 2825
52 19.15276 6615 17730 16541 8950 6031
53 18.95190 8511 20978 22576 20192 9673
54 19.15276 2693 3058 737 1871 289
55 19.79518 4388 11141 13430 13486 4783
56 18.75103 5549 13720 19342 18682 9505
57 18.44688 11126 6039 18482 13014 4803
58 17.72147 3138 14798 5544 6012 5446
59 18.68244 5015 6226 22541 5939 8141
60 19.03063 2061 1770 3016 2080 4020
61 18.68244 4329 11406 19513 10351 12799
62 18.97622 4432 5875 8834 867 8831
63 20.16967 17008 18195 14936 15565 20795
64 20.19681 16051 13218 7611 16941 18751
65 20.90195 9697 9194 20692 10692 7335
66 20.33456 3046 15959 16622 3069 17233
67 20.79527 12697 854 4200 13972 10450
68 20.26422 7942 23528 20745 5060 19546
69 19.88163 4693 27784 4158 10599 4266
70 19.88163 1274 25772 11063 6670 1520
71 19.88163 71 26689 14664 1744 2802
72 19.75512 4256 20103 16457 5099 5915
73 20.08826 2215 25565 7660 6344 4739
74 19.67501 11870 16109 6019 5918 7560
75 19.47251 3776 11865 11263 10343 12397
76 19.64113 5133 18662 17827 944 17139
77 19.68747 13643 18616 13792 10282 10873
78 19.29915 10883 12860 17882 8316 15855
79 19.27000 1854 4342 6430 4133 11648
80 19.67501 9598 14430 1966 2786 7254
81 19.57244 1521 2131 8392 12338 13910
82 18.60563 7161 833 3002 9132 18480
83 18.67833 5345 4795 6300 10699 16666
84 18.25992 15119 10635 10410 3966 20412
85 18.60563 3622 3692 24874 12955 23352
86 18.25023 1737 14695 31784 21575 23135
87 18.05434 485 15783 32035 21459 22383
88 18.21727 13201 14295 18413 13989 29612
89 18.91952 30274 30762 24819 28432 30006
90 19.91066 1218 1926 2248 1715 27094
91 18.21727 23691 24552 25235 23072 30525
92 18.01092 35259 28418 32959 26456 26459
93 18.21727 30066 33195 29604 29142 25558
94 19.63612 8112 7746 8425 18674 836
95 19.63612 12028 5813 688 14057 2570
96 19.43849 3222 12750 15493 13590 4273
97 19.24085 1985 12947 14207 2708 7503
98 19.24085 4500 818 6831 8961 1749
99 19.45793 7558 12659 3916 7934 8046
100 18.47377 24700 19991 28154 4997 27014
101 17.75183 22337 14511 20431 13470 25180
102 19.64278 6971 3998 3002 6266 20649
103 18.69731 1692 13908 3837 2272 24415
104 17.97489 27913 14981 23731 1396 25208
105 18.53085 21763 3832 5441 12717 22030
106 19.24085 8044 19476 22571 18984 7417
107 18.47561 12022 8704 13333 9284 21842
108 18.74829 15361 17943 7845 23402 8302
109 19.39484 11768 2811 1429 9473 16110
110 19.44544 13240 2827 2207 15767 10195
111 18.67279 10219 13339 3861 20730 2547
112 17.17227 8101 3419 19147 16527 7013
113 17.72125 17812 6989 17005 23053 4252
114 17.24116 21398 24090 12082 24417 1490
115 17.53091 16175 18974 17333 26204 6378
116 17.81871 22695 3536 10905 6649 4376
117 17.62488 18745 3640 12354 12068 4594
118 18.01948 13553 29622 31943 24881 14930
119 18.40017 29030 15804 21330 23555 9387
120 18.24789 26778 25071 23916 25264 9657
121 18.40017 21239 15411 18307 19572 2421
122 17.69514 6532 6898 12092 13984 12303
123 18.10269 18082 17634 29467 22473 7267
124 17.98810 1176 2239 11895 23358 847
125 18.10269 6956 10310 11583 18642 3936
126 17.79279 5761 6658 3432 20438 3131
127 18.35303 4522 5591 20341 23010 1310
128 17.86151 13012 14646 5331 21284 5193
129 18.60337 6356 1178 3550 23199 3551
130 18.60337 6709 7767 16013 23421 1786
131 17.69514 12074 2239 15944 15610 8918
132 18.89473 5694 6901 9443 7760 6406
133 18.77665 13886 7558 9943 12631 5420
134 19.01812 9294 516 1873 1394 8629
135 18.90971 7887 21068 18339 5532 12411
136 18.90086 3218 10025 6391 1012 6645
137 19.01812 9153 524 538 525 7574
138 18.79983 4798 3994 2968 14433 3834
139 18.79983 6907 12715 7187 1703 5534
140 18.76320 7247 11248 8536 13500 6090
141 18.85173 1259 127 1035 713 1817
142 19.24899 2806 9294 7490 4145 1003
143 18.77135 2545 237 321 3022 787
144 17.82797 1176 2315 3132 12992 3162
145 17.60356 3314 5144 8669 19572 1560
146 17.72975 13371 11261 9788 2320 6953
147 18.21728 27143 23494 19865 24331 11703
148 18.55107 26464 26040 29653 26940 14339
149 18.71796 25630 26392 32162 26940 14057
150 18.21728 26880 16504 4735 19708 8313
151 17.85312 18471 9347 14186 15642 1831
152 18.58976 1495 485 3597 28333 5998
153 18.58976 2212 3135 11260 27075 7475
154 18.70606 11927 16702 18746 17563 12500
155 18.43924 12807 16088 18868 12866 11229
156 18.85900 23391 21068 23663 22206 8545
157 19.17656 3041 6180 7908 15485 14441
158 19.49412 3934 347 1133 13097 12920
159 19.31783 7715 8797 20399 26207 11056
160 19.13009 3367 4325 9511 25193 9886
161 19.12947 15627 14971 8916 6813 22095
162 16.75243 13303 19214 24203 24118 13459
163 16.70723 11507 16707 14616 21167 8237
164 16.89648 9146 12549 20757 24618 13745
165 16.84771 5598 14771 13852 15727 7086
166 16.84771 1259 6490 2543 4496 5991
167 16.69563 1387 2058 4018 9161 2105
168 17.04234 14353 1829 17995 23309 8148
169 17.04234 13554 8811 3787 14304 3213
170 16.77109 12369 8884 2628 13181 6156
171 16.71684 19064 15954 13706 19253 5062
172 19.32172 11876 16410 13092 20810 5002
173 18.90434 1579 8892 7835 10915 255
174 19.09586 4649 4503 6856 10474 350
175 19.32172 9914 14395 11047 17914 4281
176 18.69565 9759 2816 10703 22491 4565
177 18.69565 4073 50 328 15238 70
178 17.68221 733 1726 2342 22717 943
179 19.32172 6537 11017 4913 23102 3411
180 19.25668 14349 3062 26680 2807 8309
181 19.32172 6136 8438 20359 8344 1130
182 17.02434 9190 444 810 28630 9678
183 17.02434 19768 1588 3027 30979 15794
184 16.86657 15052 14776 14578 30977 17284
185 16.65531 28498 25723 13728 30304 17449
186 16.83982 22189 17223 17904 27094 10481
187 16.83982 5948 10079 17228 28390 9229
188 17.80798 2005 185 738 23035 1763
189 17.05899 14373 4313 893 20507 2222
190 17.21326 10206 7051 10701 13040 6097
191 17.62000 25841 13618 17133 32749 21351
192 18.99144 8016 2382 4353 29500 2011
193 19.32172 5650 5058 16259 28215 7315
194 18.57238 8111 17470 24354 18947 13989
195 18.66116 13997 2456 24201 27120 10774
196 18.66116 13575 10955 16915 26088 2264
197 18.88135 5076 19926 22119 18448 7899
198 18.99144 2185 14324 9057 28382 2977
199 19.10153 7711 22172 21862 28472 5116
200 18.61150 13040 1041 14761 29513 5834
201 19.16711 16071 19381 19567 26652 3382
202 18.22560 24470 23225 28672 25123 13610
203 18.83658 10455 11425 8205 22597 2737
204 18.22985 10404 10211 18389 28912 6808
205 19.15948 14906 11895 11062 20903 5756
206 18.95890 4714 6363 2236 28273 814
207 19.15948 9693 10353 2898 20308 4724
208 18.98291 3901 7912 15796 7852 5832
209 18.51315 16363 17398 16582 24631 6055
210 18.65310 6127 6888 20422 7113 9166
211 19.64252 9246 3998 5021 14946 5194
212 19.04943 4105 2883 3815 8888 1014
213 19.15184 9693 4753 2254 14187 3348
214 19.51134 2392 1436 2050 8974 1956
215 19.54414 12327 8638 11173 18479 7408
216 19.44575 2478 3719 4629 9360 2115
217 19.59009 27301 28646 30681 27540 5305
218 19.17773 4657 24200 3334 20305 11884
219 19.57744 16978 21464 19137 21256 8477
220 18.90971 7267 21810 8544 18133 12593
221 19.15184 16327 12178 8242 16792 7137
222 17.69514 13242 1486 11035 17048 9573
223 17.85301 7495 6371 10701 25582 10044
224 17.70515 26087 14911 19167 26774 7174
225 18.01089 27185 16810 18442 31973 19513
226 18.01089 18387 2536 4423 29965 13271
227 19.05273 20102 4105 5187 26598 1826
228 18.99743 8798 4275 3483 26295 4129
229 18.49276 1516 2118 5904 22561 8591
230 18.85571 4927 5734 9134 18390 7991
231 18.60337 8149 7834 5845 23199 4824
232 19.15184 8009 7306 13083 4403 4662
233 18.45113 10027 1671 2253 15362 977
234 18.66116 2770 10986 10695 1225 3813
235 18.06398 16173 15714 14726 23389 11998
236 18.26304 23423 23566 26958 26326 14074
237 18.36257 12670 23787 16965 1004 12806
238 18.66116 5927 19133 10852 16510 9078
239 18.66116 626 13630 1851 8831 5082
240 18.28592 1774 14986 1788 15537 9933
241 19.15184 2507 3792 435 5809 924
242 16.77893 12683 16537 25498 16203 13849
243 16.99094 14951 20530 24576 20933 11570
244 16.62026 12412 1339 8626 10830 2683
245 16.59791 21067 13489 21639 9946 11554
246 16.82719 2036 1188 3793 6036 2781
247 16.63010 1065 6173 7547 14729 4888
248 16.56457 3859 7414 18607 7302 9420
249 16.98214 34200 31626 31774 26694 23832
250 16.62688 21274 9400 11643 21068 4428
251 18.18755 32478 21037 26049 30228 18564
252 19.21865 24508 8955 25469 23730 13226
253 17.88760 28136 13890 12775 32434 4539
254 19.21865 4410 5094 6992 5244 6873
255 18.40755 30769 13036 11584 31958 5589
256 18.70660 30180 10195 29510 25165 10151
257 18.61702 23365 21301 26362 22802 15769
258 17.41676 34227 27507 31746 33332 16615
259 19.10804 14642 10447 13547 15323 7587
260 19.10804 1659 964 1336 2223 3373
261 18.01948 3546 27294 10790 788 7597
262 17.91039 14714 21357 12199 16497 8400
263 16.22859 14531 8967 19490 15223 12511
264 16.61632 2391 7822 8033 15490 5427
265 16.38134 14486 18081 4514 17897 14492
266 16.61632 7136 6232 12791 15897 7165
267 16.34315 21773 12329 18153 25254 9951
268 16.98974 17917 14546 16158 21922 7074
269 16.97221 12024 3351 4045 22794 2420
270 17.24346 6374 23999 6472 9756 2595
271 17.19878 12858 11420 26075 12436 12198
272 17.16517 27104 17029 32520 25869 16920
273 17.63568 9066 2170 14104 13212 5879
274 17.63528 24541 21722 30444 26944 15911
275 16.80219 32690 29768 35395 30873 22945
276 16.58462 23393 8878 20629 24183 8447
277 16.63892 17031 15453 10638 23796 6158
278 16.66174 18091 3351 10986 22021 4771
279 17.27355 18916 6039 29547 18172 13993
280 17.30801 3056 3008 17963 4543 6691
281 16.45842 23003 21935 13980 2410 18114
282 16.48609 27346 23590 5302 12717 17505
283 16.40307 27163 25236 6149 7521 19097
284 16.53227 4252 5273 16580 5094 15649
285 16.43039 2897 3874 23602 3661 16202
286 16.88216 31748 29983 21098 20994 22686
287 16.40307 18849 19800 26954 7605 18857
288 16.53724 10241 3586 15931 9868 8741
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292 18.42153 1121 1013 2626 28328 9623
293 19.32172 2900 16773 6552 22212 9299
294 18.83169 1421 392 3903 24702 10051
295 17.87852 2953 311 1243 4806 1066
296 17.87179 13334 4032 13124 14669 5165
297 17.74365 16304 10606 21575 22130 8944
298 17.87179 7439 1658 11846 17123 4634
299 17.85162 15113 15080 22788 27784 14017
300 18.42153 12146 13210 20206 30335 13303
301 18.96333 9007 5422 5629 6536 13031
302 18.73447 10084 2081 9909 2985 7367
303 19.18849 16342 14763 18299 5576 10287
304 18.73447 8767 9310 5065 3481 12700
305 17.75042 19673 1748 11139 19192 5175
306 19.18849 2531 6919 9335 19286 3795
307 19.64252 14101 9986 14784 11016 5329
308 17.59017 18244 18861 13163 4936 10286
309 17.59017 2976 3664 2727 864 10890
310 18.61635 11361 1066 708 18143 324
311 19.11877 12278 7179 12613 16424 9987
312 18.84295 7734 16028 21150 21903 4871
313 18.10790 5953 691 11717 18523 4424
314 17.99994 5054 5874 9461 10538 3780
315 18.71481 3957 13945 11727 23270 9087
316 18.00092 5536 4919 10366 9836 3700
317 17.34247 1493 1435 6538 3798 2307
318 18.47676 5925 3159 6191 6748 4768
319 17.99994 750 694 1151 1306 1223
320 18.74703 14472 1524 10167 14526 8941
321 17.12667 12632 22724 2382 13137 19884
322 16.96603 28930 26155 11472 24086 19505
323 17.49860 3806 14241 8015 9965 12330
324 17.07436 13270 24494 28155 14055 19248
325 16.98127 4126 16411 21269 4956 8067
326 17.62703 7819 13979 15196 2349 6465
327 16.52579 13450 19826 27435 13299 12661
328 17.12644 10810 11484 14131 31797 26348
329 17.24693 1327 22982 2457 31524 27531
330 17.36743 8723 26099 12678 30670 26664
331 17.19931 27833 32629 34790 32211 12725
332 17.31699 20892 2476 4225 32071 24803
333 17.31699 9023 17402 11035 31608 25185
334 17.26605 9876 11484 6841 32042 25707
335 16.78768 6368 8692 11264 21949 10095
336 17.27315 28267 10170 13761 27636 8963
337 16.71372 23855 7135 14641 21425 15084
338 16.71372 19983 13877 14951 22063 13384
339 16.71372 15310 2775 2567 14519 17398
340 16.74677 5538 5224 6730 21347 7632
341 16.71372 9801 15032 18116 20802 11401
342 16.59370 10377 19813 17060 3930 16122
343 16.71372 14952 11961 10621 12713 19189
344 16.61468 24467 27447 18628 20699 16572
345 16.53011 17815 20893 25493 22344 11316
346 16.71372 8838 20430 7112 4284 13965
347 16.55370 25944 27864 23254 18107 18249
348 16.55370 24083 21147 12460 19852 20611
349 17.36225 11808 9282 10950 13860 18110
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351 17.37016 4671 7718 10027 5576 20248
352 17.57981 15313 3271 10916 18074 9517
353 17.36808 10905 14459 7889 18955 11255
354 17.36225 13555 3539 12000 14305 11496
355 17.31509 14251 24623 19704 28617 21033
356 17.54692 8334 3595 4942 2837 1612
357 17.34430 9162 10821 14989 8272 4468
358 17.22306 6102 13211 17899 7086 6274
359 17.38238 13072 14636 18669 12534 6947
360 16.50358 16836 24486 29721 17898 13690
361 17.65239 13559 5813 7400 13061 3986
362 17.68567 9819 8101 5192 8103 3726
363 17.24109 23045 21387 7524 5697 5149
364 16.93108 30019 27295 14259 19525 13198
365 16.96064 18532 17096 17257 17417 12122
366 17.37016 16313 2498 2774 18206 15145
367 16.93108 23216 17272 12100 22854 18630
368 17.49343 9714 15075 839 344 2132
369 18.08246 26111 23625 35121 25119 23098
370 16.89826 29596 19423 31509 22950 19625
371 17.10798 19830 17596 19250 16343 7575
372 16.88638 26670 12074 27715 18315 16803
373 16.95911 23604 1966 23264 12537 13939
374 16.94235 16896 4029 12113 5062 8746
375 17.37613 22568 21427 23821 19833 13883
376 16.66940 32044 27827 20784 26613 23246
377 16.12555 32960 33732 36430 31496 22592
378 16.42074 18856 20096 28358 19305 13205
379 16.29808 32209 34636 31061 31382 15217
380 15.93535 2412 15542 11356 15133 4032
381 16.56437 23498 29872 10808 27143 3846
382 15.80482 16928 26168 1414 23717 533
383 16.32366 29079 31131 34404 28786 17263
384 17.60037 4990 6919 8932 19352 3280
385 17.34430 8853 7356 15186 1182 1943
386 17.18288 20768 23015 24867 17526 10030
387 16.96798 8084 15475 18273 25961 13717
388 17.66103 7917 4709 7650 11421 2699
389 17.81145 15247 15270 19563 5885 2699
390 17.74856 11291 13421 15639 8147 3843
391 17.61586 13093 12437 12422 27276 16384
392 18.08798 13258 13418 17177 27799 15750
393 17.20025 16063 17196 15448 19717 16266
394 17.38907 4060 5247 4710 24218 12034
395 17.32227 7418 12778 3687 19541 9336
396 17.18865 5492 7147 2977 6439 2519
397 17.10919 16962 19213 19690 29027 22330
398 17.68626 5934 28487 10950 1017 6648
399 17.62331 12835 30901 19447 9456 10460
400 17.45676 16237 31642 25283 27065 20314
401 17.10919 22812 28428 19383 27678 21123
402 17.33877 3489 10327 18468 4253 6640
403 17.03185 9869 28396 32480 29972 22958
404 17.45963 9146 10304 14107 24608 8784
405 17.62989 15420 8162 10565 29455 18837
406 17.27315 3664 4491 5696 28710 17548
407 17.62989 24612 17953 22892 30699 20797
408 17.08667 21245 2893 12377 23549 15099
409 17.44984 5799 8901 5326 17323 4930
410 17.83258 11996 13069 13175 27186 14767
411 18.22317 10380 11371 10376 11255 8784
412 17.68924 13944 19211 22557 24806 16219
413 17.84650 23136 22500 19847 24923 13973
414 17.26503 13020 17305 18216 24161 22536
415 17.27452 16702 27767 22407 28892 25000
416 17.26503 15361 26949 20954 29143 23200
417 18.22317 7756 8837 8612 8761 9442
418 16.77982 2822 16283 9119 29608 1288
419 16.33553 2746 13638 6916 17267 2667
420 16.82859 15461 23535 6955 27453 3443
421 16.48936 19352 21668 864 25734 1962
422 16.34413 19608 16511 9604 22471 4558
423 15.69625 11753 10735 13876 16477 2686
424 18.08246 4940 33242 23508 5870 15344
425 16.91823 10989 31445 20620 24794 24468
426 17.28327 23988 19150 29369 24987 19170
427 17.35846 4179 27705 15584 27740 26544
428 17.11712 23926 12975 23300 28200 21705
429 17.19504 5954 29526 6907 27297 26210
430 16.63445 23988 22831 14829 29910 23936
431 17.26956 5382 27432 8284 28224 22498
432 17.08871 18554 24620 24482 23529 21172
433 17.05423 6044 2216 5354 11459 10519
434 17.16218 2626 2520 547 7756 7745
435 17.27107 18676 19715 23427 20207 22638
436 17.21220 18621 14034 18106 22229 17329
437 17.17263 16025 27607 21716 26581 23726
438 16.64506 27949 28704 15397 11885 15926
439 15.83113 22253 17061 26432 22838 13961
440 16.46925 23431 26650 22751 16686 11900
441 16.67271 27354 28884 23448 10407 17512
442 16.15498 9318 203 1624 29101 497
443 16.52181 9936 15321 17951 22309 3951
444 16.45423 1639 3011 9531 28323 2081
445 17.26502 16372 1678 22069 10503 21438
446 17.27169 13762 12698 19111 21566 15205
447 17.31655 10063 15408 4456 23891 17291
448 17.27392 13762 15710 4456 19506 13240
449 17.27837 12617 8096 10840 13421 8997
450 17.27837 3852 5648 6120 4631 5001
451 17.36808 12835 14036 12551 13517 9608
452 16.32692 4918 4875 3641 10904 900
453 16.41453 8559 10160 16134 11089 6160
454 16.36441 2579 5676 9562 6322 4234
455 16.65793 12375 17572 20758 13334 6689
456 16.55504 24309 19817 28047 20268 10697
457 16.65793 2979 10211 7912 12779 915
458 16.79030 5204 15911 20331 16237 7734
459 17.84650 23379 24243 24285 22816 16041
460 17.31699 23824 24674 24408 23178 15892
461 17.68797 13799 14913 9421 14526 11682
462 17.43698 31072 31492 35116 29072 21429
463 17.62539 33631 33888 36569 31148 24749
464 17.58249 33448 33750 36479 30999 22054
465 18.04834 5702 6749 10334 6649 3605
466 19.43379 9588 11088 29368 31197 15608
467 19.28805 634 1117 23008 30043 12134
468 18.82558 322 5164 426 23320 2561
469 18.21736 5987 10225 9986 22810 8376
470 18.79655 17459 8493 14166 29542 13135
471 18.90414 5126 11064 11035 25633 6117
472 18.90414 16512 19700 24342 29641 10316
473 18.82558 832 6236 6244 26101 2752
474 18.08789 10489 20252 14797 18924 5873
475 17.96731 4881 14654 17301 5800 14807
476 18.33991 1333 10951 10690 3332 10795
477 18.64069 1801 10839 12699 11189 6486
478 18.74329 1259 23473 24687 22451 2252
479 17.30578 6104 13618 20914 12762 7832
480 17.16158 1650 7966 18555 3002 9176
481 17.43139 12370 10798 18484 20278 21425
482 17.76280 6418 4559 11146 13351 17363
483 18.66887 10221 11913 9370 6970 2636
484 18.87269 1736 14041 2555 7135 939
485 18.56545 13542 8768 12076 14384 6790
486 18.56367 14675 17345 18865 18719 5985
487 18.39372 2893 12787 4456 2852 3295
488 18.39372 14007 5793 19781 9918 9091
489 18.68995 11717 18752 14028 12046 4714
490 18.68995 12669 8768 15356 14785 8748
491 19.55575 2095 24423 21972 28893 6919
492 19.87877 24963 22584 26043 29612 18577
493 19.87877 18159 26870 15966 29553 12454
494 19.87877 6998 19381 25465 28625 14006
495 19.67029 13561 8174 26490 23383 20932
496 19.42031 5179 16756 24852 27518 13290
497 19.32618 3978 10071 8286 9892 7488
498 19.46236 12300 5376 11664 7823 7005
499 19.27178 10458 5622 12912 2826 18636
500 19.97513 18880 10827 12057 8725 10714
501 18.80883 15686 1727 19806 1501 18679
502 19.41363 12254 13321 6870 19939 16911
503 19.41363 2424 3367 539 12030 17733
504 19.46181 2777 3745 10040 5303 20747
505 19.46181 16001 15669 1735 13790 16389
506 17.58333 12651 8435 2608 5956 4517
507 17.46101 10083 13562 15491 3523 7146
508 17.29097 13406 19563 22512 11506 12348
509 17.53228 2591 7419 6355 11676 3528
510 17.09072 1358 1546 6735 10734 3606
511 17.84467 17619 20273 23440 13688 13581
512 17.37319 14073 15177 17422 21320 15213
513 17.35772 12068 22056 19418 4488 12464
514 18.72465 4331 2234 339 1440 17079
515 18.47126 16132 15029 13245 9379 11198
516 18.27335 7446 5292 1145 4267 13679
517 18.27335 4208 2035 1870 5693 16303
518 18.27335 2002 648 4120 2875 15940
519 18.66918 4057 761 11989 1249 19666
520 18.47126 10953 7904 10238 2336 16267
521 18.47126 5650 3867 10953 2336 19666
522 18.13175 5464 11386 19781 9918 7980
523 18.11098 6670 13957 22459 20455 9190
524 18.12033 14244 11878 13711 21417 4896
525 18.16537 9059 8309 3107 5073 9246
526 18.05739 2009 11851 12157 5994 7520
527 18.13339 1453 3724 4920 5953 10631
528 16.96641 4932 1925 2580 2347 10635
529 17.07090 15558 10109 22549 16119 15357
530 17.07090 9765 5144 18365 10704 14276
531 16.94646 16257 10246 20330 14954 15019
532 16.93686 2662 2586 2114 3473 2066
533 17.00982 6412 2336 3429 2991 1310
534 19.89307 6664 1032 1166 7955 6615
535 19.31275 594 1028 333 911 7021
536 18.56545 2047 3682 1654 2700 4698
537 19.15173 3440 3104 2576 1845 3891
538 19.15173 4514 227 4205 1976 4141
539 19.34817 7865 4833 8474 2406 2281
540 20.02768 758 5267 1742 3747 142
541 19.58696 3493 2988 2382 4254 2230
542 20.50527 4742 6092 6067 50 3612
543 18.91368 7306 6607 8535 16838 397
544 19.26750 11949 13582 19278 14120 2530
545 19.44639 6050 9741 17487 7852 5456
546 18.68995 181 62 1275 17362 4531
547 18.91765 145 2039 6209 14468 6195
548 18.61404 1731 5897 6059 16962 8154
549 18.91765 831 10493 1498 6653 5624
550 18.68995 647 10059 4476 9813 7184
551 18.46224 2420 3822 9869 13672 8297
552 17.06046 17384 12965 14780 20968 16543
553 17.21548 25087 7962 7889 24716 17053
554 17.52270 22475 19836 9159 25842 17511
555 17.31584 21599 6408 2079 21895 12574
556 17.36909 27798 13363 14566 27240 19205
557 17.22620 15766 5144 6620 17612 13237
558 16.94703 3358 6783 15467 5144 13153
559 17.14780 30571 3903 4881 28273 22011
560 18.08141 15165 12597 19853 20112 11137
561 18.16523 9322 3936 14712 13641 9858
562 16.94478 18859 17830 21784 19315 19934
563 17.64317 2130 1418 2748 21189 21313
564 17.38735 16557 12668 21369 25959 24135
565 17.87597 418 2443 476 18964 19821
566 17.89899 8039 12609 11117 13048 13944
567 17.99758 15853 15151 17150 27159 21851
568 18.33289 10290 12259 15017 9999 10906
569 18.14838 15871 16065 21776 16795 3105
570 18.44567 3677 10958 2811 4459 228
571 18.20611 15572 326 14528 19239 5565
572 18.42295 13451 7922 9063 14231 2736
573 18.66866 691 3973 726 1022 306
574 18.20611 14007 4289 11620 16326 5292
575 18.17724 19090 5794 3186 20609 1182
576 18.42295 11797 2977 10015 12600 630
577 17.57647 1634 16429 12667 24200 7777
578 17.68362 6225 11696 7860 22500 3997
579 17.36218 7163 9370 13870 7395 8111
580 17.37066 88 24502 5514 22429 12264
581 17.22645 3163 920 1977 8933 2722
582 17.53290 10265 6658 9008 23274 1807
583 17.38218 5464 7037 9074 19031 10553
584 17.37551 3398 6139 12306 6609 13404
585 18.93978 8968 9906 21484 7343 20669
586 19.58514 10726 11678 27428 23201 17262
587 19.23143 6832 10379 3546 12922 13362
588 18.71014 14926 26474 10484 14038 15421
589 19.03783 10130 10634 19648 22123 22417
590 19.26682 1229 1942 23594 23758 19455
591 19.03783 5341 6393 29303 26176 20397
592 18.91700 16603 17642 29946 27826 14432
593 18.90125 18838 13659 2995 22566 3094
594 17.33218 12275 9605 10264 17095 11826
595 17.77667 15590 7431 18531 19344 10940
596 17.57288 15233 2106 4209 18244 9617
597 17.54414 17157 4956 7573 20845 12251
598 17.82992 6932 7304 13099 10103 6843
599 17.72342 4306 4507 8722 20442 11606
600 17.77258 6840 7735 12350 9440 8621
601 17.82992 18638 18771 10536 21931 14184
602 18.64069 23315 23274 20184 6445 5100
603 18.33289 19125 1365 5896 5386 1856
604 18.29438 18119 7283 5696 7553 4807
605 18.27512 6918 9160 10217 19436 8240
606 18.77097 8773 17809 21317 21501 13572
607 18.62892 20506 12868 15238 17983 7699
608 18.90125 7969 1795 1396 24053 4974
609 19.00947 15578 28506 29739 26851 6271
610 18.14016 6510 8464 1735 24858 8832
611 18.60531 4840 5937 7599 25987 14833
612 18.14016 7037 17407 13389 23485 1914
613 19.25858 17250 27700 28757 25060 5719
614 19.18106 17858 24056 24426 20483 8325
615 18.94849 7840 8909 16382 2663 20392
616 17.33184 1864 2717 3305 24634 13802
617 18.27512 5098 2766 7337 10035 2806
618 17.82174 3246 4194 5335 526 5084
619 18.65176 2405 1367 373 13876 4180
620 18.04843 1083 440 2561 6564 2877
621 17.99212 3648 4668 8374 10613 2940
622 18.08141 6113 1573 1639 6567 681
623 18.27512 16308 1087 979 2923 737
624 19.73472 3837 5517 4418 4583 4571
625 19.37954 3387 855 831 4497 10620
626 19.20598 5166 8317 3695 2867 1512
627 19.49431 924 176 122 1628 7324
628 19.47264 4334 737 856 1965 8906
629 19.20598 6673 12624 1553 1515 1275
630 18.54007 9106 8027 9634 1054 2581
631 19.49431 2713 1769 716 1178 4318
632 15.90160 30101 30533 25098 30239 22908
633 15.79553 8059 22367 20596 20526 14763
634 15.83615 13501 22525 20033 21107 12253
635 15.81769 22207 25914 25339 24578 10859
636 15.75676 33498 32556 33943 28007 22708
637 15.63062 32760 27352 31116 27560 15408
638 15.63060 27620 23507 25673 24353 8152
639 15.63062 30813 11714 15280 19675 19041
640 16.14747 28212 30874 29350 30107 23880
641 14.46569 20699 8584 26698 37692 9627
642 14.42734 27204 20652 32496 37987 16173
643 14.60683 9605 25775 13906 36047 11853
644 14.73765 3261 7607 5571 37314 3070
645 14.72339 11483 12454 18485 37716 8569
646 14.55097 12294 24673 17487 36590 12805
647 15.37425 14231 21085 28593 7893 15038
648 15.44017 26895 12987 19311 8981 15644
649 15.50391 23126 28064 35841 31804 13168
650 15.30505 14284 15556 35184 28845 22127
651 15.04332 11807 4856 32486 25009 23558
652 14.83375 31120 28721 33745 29349 26312
653 15.14158 24693 12127 24489 23229 26716
654 15.58684 14990 6663 6363 6012 2142
655 15.37425 17422 661 1075 2870 2309
656 15.64330 17211 5824 17338 17597 5361
657 15.56009 10177 19292 22458 11096 5485
658 16.22998 13251 21011 21853 24961 2256
659 16.17910 17799 16580 26729 22222 14599
660 15.96839 4106 9562 22306 20068 4480
661 15.87176 4314 2153 2098 1770 522
662 15.77706 8136 2037 4397 3087 3075
663 15.77706 11356 3023 22141 12564 12487
664 15.80660 10289 16587 24411 14374 7276
665 15.61113 16710 18140 19426 14682 2820
666 14.85507 30160 34478 36908 30706 32477
667 15.42059 27706 21986 22179 19432 16766
668 15.54096 18726 19718 761 20146 18842
669 15.18511 14103 14873 23598 14808 13050
670 15.20830 7953 12281 15985 24061 21010
671 15.01406 7931 6944 8965 27266 22639
672 15.28359 11073 14590 10638 25288 22494
673 15.20965 6842 7902 10247 28207 25066
674 15.26798 12519 13002 16835 29356 26233
675 16.07573 23934 27039 29771 26063 14860
676 16.06828 5409 12276 18568 15243 6194
677 16.07287 13495 13793 18994 16682 6513
678 15.85691 1751 8664 5391 5334 1998
679 15.45086 22306 29587 27689 18308 16232
680 16.40624 23214 12068 34557 30910 20117
681 15.99853 26941 19743 29047 23728 16160
682 15.58655 25785 27097 25892 20155 15820
683 15.81298 29872 28438 14799 24485 19864
684 15.47527 30190 30281 34982 25571 21241
685 17.39821 10924 15499 10842 12813 868
686 16.90373 23277 15796 26764 9489 8699
687 16.79448 7743 15499 15490 7916 451
688 16.90373 12830 8871 22079 4734 6447
689 17.01297 8916 3272 9050 4134 2121
690 17.25104 19425 20235 19738 20317 3672
691 17.70761 17872 12687 16820 18571 5605
692 16.90373 19555 22218 18970 23123 7326
693 17.01297 9550 2400 1950 12310 8879
694 16.94014 10141 6496 6635 20472 12047
695 16.91920 10854 10997 10458 5493 2445
696 16.78791 21306 20643 19419 23609 8747
697 16.87231 23181 22593 21224 20021 8221
698 16.63106 23299 22830 21583 25591 10356
699 16.46026 24976 27811 29236 24754 15285
700 16.68414 7115 5701 1234 12774 1302
701 16.51972 6228 16676 6379 20932 8161
702 16.02647 9337 17690 13909 11762 11826
703 15.90176 11657 11215 22931 12457 18155
704 16.73165 25747 26306 27001 20523 11337
705 16.04674 19350 20795 15847 18096 11131
706 15.90396 29750 29738 33793 28423 21157
707 15.92896 16125 17179 11354 23546 15559
708 16.04674 4364 19381 6985 13976 10137
709 15.34267 18421 29294 32571 18717 23691
710 15.84316 7853 8927 13918 23173 18056
711 15.83826 2228 3161 1035 13933 10579
712 15.83826 8871 16426 14632 9759 17310
713 15.49662 10368 7350 18520 11381 3368
714 16.08249 27943 28911 28734 11346 8631
715 15.55128 9142 6298 8103 10817 2835
716 16.04674 19868 24187 29163 14019 13415
717 15.55440 27383 27277 32015 17325 16275
718 15.55440 5969 24268 22403 6945 19176
719 15.67749 4692 24268 11491 11434 13729
720 15.67749 3361 25150 14240 6063 17213
721 15.42379 23290 19459 23194 19458 9280
722 15.25902 20310 2539 19155 16636 7167
723 15.46825 19557 12709 18295 15642 6772
724 15.69519 7129 15366 19712 12942 7003
725 15.67151 7306 12593 16335 4631 5946
726 17.66170 13868 15133 11453 7020 8508
727 17.73244 16817 16184 9065 12092 7930
728 17.76663 13771 16998 19304 8230 13760
729 17.44258 2973 5607 6992 1845 8332
730 17.70761 17428 11801 18381 18433 9128
731 17.55495 4246 6570 23844 5082 10515
732 17.59768 10752 5219 7209 11572 1274
733 14.64167 37291 36794 38263 36340 31669
734 14.40591 35888 34959 37421 38429 28002
735 14.77059 36982 37557 38328 36238 34544
736 15.45426 7038 27853 31762 17279 29329
737 15.25349 1504 18896 22894 5330 28920
738 15.42025 6226 27274 6925 24710 28218
739 15.36646 19016 19035 28793 20830 23484
740 15.28102 29392 11423 8369 20421 17721
741 15.28102 30243 19918 17155 26384 22434
742 15.25482 15559 16766 19234 12745 27054
743 15.39098 26009 11455 29235 21660 20745
744 15.39098 28048 17039 26905 16989 15570
745 15.16305 28461 33424 25136 28153 24833
746 15.36126 15999 31174 15816 16542 21540
747 15.33663 24488 32994 17048 23723 22887
748 15.50955 22125 17181 22982 21865 661
749 15.42306 14108 15288 26285 24894 4423
750 15.49882 15748 17320 23118 27761 6237
751 15.26787 5215 6782 18957 30585 5783
752 15.48809 10092 12311 16023 29789 5173
753 15.48809 784 6062 7822 29809 1628
754 15.48809 17646 16136 19453 27284 9716
755 15.74096 25831 22485 15020 29814 9736
756 16.68414 10955 8543 7822 20685 6857
757 17.01297 13064 727 3720 13865 3341
758 16.51972 8895 17733 4095 24557 10376
759 17.01297 21985 10785 16090 21743 3624
760 16.55800 13510 8743 4809 21934 9955
761 16.02663 30042 22052 27622 32075 18616
762 16.48718 27011 21798 5767 27861 2902
763 16.40634 23075 24888 10608 29031 9924
764 17.00714 26958 21067 8384 26901 11097
765 16.36070 17737 15955 5451 27952 7621
766 16.36070 7626 9043 18754 27801 7914
767 16.73864 3556 1073 26123 29058 13592
768 16.36070 1528 6226 26766 28076 11308
769 16.40859 16482 8954 21477 21439 8351
770 16.73864 1213 858 27571 29017 13731
771 15.06301 19880 20591 25904 18236 17299
772 15.73403 10778 17100 16388 12427 12211
773 15.42131 3196 5996 12250 9945 2334
774 15.42131 7207 8278 10706 5561 15866
775 15.36536 2669 1250 1394 1902 1373
776 15.42131 7014 15094 19768 14612 8924
777 15.42131 6378 7466 9653 4741 16113
778 15.15995 20130 16311 25620 18443 11192
779 15.24416 19730 8131 22270 16652 9581
780 14.63724 23190 19428 27817 26132 16530
781 17.51247 814 11027 6564 1380 9698
782 17.06531 21201 7560 25216 9542 10732
783 17.25831 1468 3458 8470 1604 7544
784 17.25831 7327 1473 9116 7816 8427
785 17.51247 712 7270 3532 2762 7116
786 16.79448 959 8371 10452 1362 2407
787 17.56613 17409 5918 14023 17787 14655
788 17.28797 22887 15649 13997 20993 6838
789 17.14889 20914 17077 27795 20841 12401
790 17.22689 13741 4373 12254 14464 12850
791 17.62673 9060 3752 10646 10041 14655
792 15.53081 14424 12437 19823 29608 20034
793 15.29520 12365 18164 30001 23356 16569
794 15.41756 17711 20947 34934 32174 6900
795 15.32860 4452 15456 24748 23026 16502
796 15.41756 7584 17013 30657 30345 7310
797 15.31574 4874 8556 16835 6323 4833
798 15.38091 9829 22256 21784 29287 15020
799 15.33839 13822 9760 16363 9800 8192
800 15.32860 14108 17880 23743 18207 21374
801 17.11657 20366 7814 6510 24220 9207
802 16.76189 23648 12686 15836 29664 13039
803 16.82079 15757 5191 6678 26933 10041
804 16.49682 20735 21920 26510 22608 8256
805 16.19448 4077 12132 19025 20719 7023
806 16.00314 11317 10972 15796 13294 4591
807 15.98577 3282 2020 14083 11412 2741
808 16.02249 9068 17985 21723 13898 10776
809 15.78556 29784 10989 20991 30461 14837
810 15.69102 25567 13521 8119 25114 11041
811 15.86020 19914 16247 28195 19986 19074
812 15.77706 21946 17060 23392 21695 9671
813 16.15907 27441 10776 23244 27382 19903
814 15.69102 26364 18356 25192 25320 14180
815 15.53155 9890 11763 12538 25210 2708
816 15.66935 28572 3797 17130 29839 10640
817 15.50352 24024 13307 27663 31146 11807
818 15.45417 2924 1127 669 16983 594
819 15.48707 20815 17761 25889 29529 5475
820 15.60041 1101 7543 8854 7337 3127
821 15.47113 17301 22650 23310 21603 10275
822 15.37001 7058 9423 13603 16625 5696
823 15.32510 14685 23011 24961 21912 13799
824 15.45417 5239 8923 7434 20858 5433
825 19.12341 8167 13030 2674 8883 6624
826 18.79848 10371 2562 1661 11208 7567
827 19.12341 4770 10806 5043 7163 623
828 18.79848 3702 4417 1802 4477 5683
829 18.79848 1327 9818 7752 1863 4363
830 19.12341 5906 10710 4450 8366 1019
831 18.86222 13102 15403 1726 13657 7337
832 18.70076 11746 10847 7363 12312 6374
833 20.64087 2349 7532 101 3387 687
834 20.47913 1220 2193 1604 570 1121
835 20.46371 4018 3522 7144 1830 2163
836 20.46371 1 76 69 364 1
837 20.60815 985 3700 339 52 180
838 20.65723 1723 1749 612 5070 494
839 19.53971 2217 2688 3428 5637 3369
840 19.43582 1344 15289 6300 4864 2167
841 19.50979 5818 961 3568 6723 2088
842 19.47280 1673 16207 2958 11858 1090
843 19.47280 6481 12068 9809 14273 3244
844 20.01391 1910 6194 2445 178 2513
845 19.50979 10447 2921 8512 5985 995
846 19.71006 6738 2160 2414 440 608
847 19.87486 7230 7128 5809 5898 5095
848 19.59954 9117 8990 6381 12291 5679
849 19.19901 6289 3173 1092 9310 4160
850 19.59954 3721 6289 1280 5837 5158
851 19.87486 12298 14317 7747 8728 8203
852 19.59954 5970 2101 1146 13814 1221
853 19.19901 7681 4011 5190 7141 2244
854 18.89791 3031 7999 7555 13517 4150
855 18.68995 2203 2217 559 16908 6205
856 18.67648 1273 771 2419 6160 550
857 19.10495 2887 1440 2366 5190 98
858 18.46224 3172 5686 9489 15025 5896
859 18.86944 8585 3106 6381 13255 8137
860 18.78359 1031 1104 11449 10220 901
861 19.11574 10233 2844 11582 15079 2873
862 18.59904 11579 6465 2601 9732 1033
863 18.85199 18634 4673 7912 16066 3767
864 19.02369 14459 14866 15364 11545 3397
865 19.02369 119 17510 19171 4826 7813
866 19.44833 14037 15507 21708 5570 4067
867 19.11574 11428 3754 9461 7219 7360
868 18.98926 20243 8668 13341 12013 5094
869 18.66696 7521 9544 3157 5532 4926
870 18.60303 455 5953 2484 239 655
871 18.66696 912 10743 5636 641 2255
872 18.76469 3842 3574 6751 1109 4224
873 18.66696 1208 4411 1929 3130 5955
874 18.76469 1259 649 2071 4569 3621
875 18.70076 4655 9994 11942 2828 3451
876 18.38157 1943 2816 11695 9193 4250
877 18.77620 5133 1996 2298 5087 2008
878 18.86278 7118 2162 1536 5634 1625
879 18.60103 414 1352 772 1198 2164
880 18.60103 5196 7176 6650 8199 3219
881 18.60103 5430 9155 9094 8732 4045
882 18.68790 14747 3538 10361 3243 3999
883 18.77595 1485 1523 903 5957 5161
884 18.76469 209 588 2018 3138 3016
885 18.73272 7921 7476 4837 10925 8768
886 18.71080 3221 3919 1661 5979 6731
887 18.79848 10531 3527 2745 3726 1200
888 18.79848 7892 761 2548 1933 1234
889 18.79848 9917 3123 6360 10320 2153
890 17.90825 426 12376 13598 13740 5664
891 17.90825 6249 12340 11835 21774 7846
892 17.55297 11341 20882 4366 22090 7222
893 18.31957 7220 14917 8076 11710 489
894 18.31957 3925 12234 5393 6201 560
895 18.10996 3813 10352 1392 12804 1238
896 17.93868 20037 9861 13189 22105 12611
897 20.47835 4048 1414 2430 8949 348
898 20.70632 1019 1248 2471 6108 519
899 20.46719 2016 194 4946 4024 42
900 20.58675 934 528 438 4126 826
901 20.70632 674 447 545 11108 69
902 20.49101 1190 236 803 6837 52
903 20.77487 151 1443 396 727 308
904 18.73089 4402 744 841 5376 134
905 18.96495 572 2465 2944 890 255
906 18.73089 5303 2203 2653 6029 962
907 18.73089 2557 4617 4822 3050 1005
908 19.16521 1344 7879 10296 1880 3960
909 19.16521 5105 2957 3447 8825 1035
910 18.79848 2408 2553 3072 925 663
911 18.75361 3673 5382 1471 7558 289
912 19.82124 246 2311 1010 1615 313
913 20.02768 850 77 1758 1088 29
914 19.31275 1055 1104 1810 682 6884
915 19.44833 2172 1350 6704 1088 4578
916 19.73801 1150 77 3116 321 2336
917 19.69693 8611 17975 18421 18201 4075
918 19.69693 416 5587 3347 4699 1248
919 20.80915 587 4940 2743 923 925
920 20.70632 1002 695 3624 1121 510
921 20.81576 8294 2002 7586 144 1179
922 20.70632 7877 555 3177 3546 253
923 20.70632 4874 447 6524 2891 1405
924 20.70632 4531 1183 3177 4328 44
925 20.46371 4238 2302 3608 2050 960
926 20.46371 1943 257 2895 1700 587
927 20.22110 1364 5172 8924 3666 5986
928 20.22110 163 2224 490 25 494
929 20.22110 1268 5172 7816 3666 4506
930 20.22110 6069 221 1740 3383 1244
931 20.22110 7803 1845 3718 4905 1567
932 20.22110 4794 11896 7517 7411 6201
933 20.22110 570 7432 7537 2019 4258
934 20.22110 305 7442 4523 1959 4176
935 20.22110 4316 2416 5096 1658 4581
936 20.30391 8882 9751 12631 6294 5629
937 20.22110 3862 6194 498 8996 4830
938 20.22110 508 7494 127 10101 7527
939 20.51843 4018 2866 4113 3794 5656
940 19.91032 6908 11171 1304 6179 6480
941 19.91032 4083 8160 8609 1126 5448
942 20.22110 2226 2416 3295 797 3652
943 19.44833 15415 8138 21525 5570 1060
944 19.53156 10049 3638 20603 8207 829
945 19.44833 10380 9471 18536 8909 574
946 19.48369 2614 492 10904 3681 846
947 19.44833 12333 9534 18644 1113 554
948 19.73801 162 273 5254 222 1935
949 19.63478 384 689 7425 579 1666
950 19.49547 4962 8351 12057 4683 4774
951 19.44833 5737 1350 8351 1863 4369
952 19.05077 7625 144 247 8632 601
953 19.27664 3482 306 471 4247 301
954 19.00517 35 1979 2254 30 827
955 19.15016 24682 16678 22214 14585 2280
956 19.11963 10212 1405 1604 5758 1636
957 18.95528 9443 3106 2711 10432 4914
958 17.62112 20154 7850 7314 15526 1270
959 18.35053 14471 932 2966 8804 2188
960 17.52334 1520 8667 2727 5692 9158
961 17.66899 5473 11796 8416 10604 9709
962 17.66899 13930 6114 11750 14172 6964
963 18.34017 12186 17536 15026 5688 12873
964 18.10209 11804 14388 1909 5839 10497
965 18.44627 4671 8443 11922 1806 8454
966 18.15514 2518 6795 4277 7437 7260
967 18.44627 6355 4680 11515 1435 7253
968 16.53602 2359 4368 5801 2447 7591
969 17.37768 5013 4981 10644 9392 7738
970 17.37768 15392 6450 16353 13557 4794
971 16.10303 25991 6411 8257 23545 17622
972 17.27701 7174 15305 20586 739 7242
973 15.99194 28185 12329 16039 26019 20157
974 17.00146 534 10826 19567 8972 4187
975 17.86400 5548 1722 2789 14456 1271
976 17.68510 11752 8506 10572 3339 5643
977 17.68510 10234 2917 7436 2992 5727
978 17.68510 4435 6141 7018 1722 10929
979 17.58845 341 661 1287 978 8559
980 17.95192 2042 2742 9592 9138 7540
981 17.58845 3539 6803 5756 1716 11046
982 17.90743 2979 6583 2537 10570 8018
983 18.22641 8527 15895 11604 5287 8013
984 17.58845 211 2116 641 477 10949
985 17.90743 8381 12184 11889 9264 10694
986 17.86294 8553 7848 19543 3747 14926
987 16.33531 3021 5368 2410 7270 4555
988 16.13777 18635 29148 17308 23372 17057
989 16.74852 13861 28829 19237 26818 21388
990 16.23654 8554 20594 16626 21000 12357
991 16.91355 2176 12931 8438 13672 9711
992 16.30745 13890 18300 16673 17314 8386
993 16.33531 5870 6798 1819 5180 1857
994 17.29505 4031 3661 2447 286 928
995 16.99195 4665 2266 5291 4726 1265
996 16.84770 12208 7583 8090 7796 3612
997 14.65836 25349 20001 25926 9172 18052
998 14.61962 30167 24336 33881 20494 25006
999 14.80304 32142 28684 33172 24057 21679
1000 14.55106 12228 10171 15981 26995 21478
1001 14.64635 17670 15008 24405 9341 22807
1002 14.72835 8328 1947 10213 22706 16392
1003 15.25759 20396 10324 19767 26729 18407
1004 14.83445 19880 11270 24178 28648 17770
1005 14.71961 21684 10805 17240 26696 16634
1006 14.46458 15688 14922 8195 26118 6838
1007 14.46458 22592 26389 24882 24141 10283
1008 14.27081 29816 26199 7794 22225 2723
1009 14.55483 35533 33934 35219 30707 22200
1010 14.83869 28375 24094 32989 15421 20601
1011 15.07685 20509 6488 13191 11109 11276
1012 14.93064 26775 12576 28248 19934 18841
1013 14.76044 5934 10655 13218 25522 11642
1014 14.99404 19648 25973 8176 24207 25018
1015 15.21605 14782 3375 9093 13562 10922
1016 15.24417 12041 4487 7302 12857 14582
1017 15.49856 5905 10464 18270 21617 14346
1018 15.18321 23595 26442 32973 26460 21997
1019 15.83924 9223 6635 6290 17665 13546
1020 15.58427 22361 24778 28602 27196 21718
1021 15.43109 18921 21692 24518 24379 21919
1022 15.83924 5745 7527 10395 14300 15853
1023 15.32880 9250 4343 7144 12985 14390
1024 16.40565 2874 4511 3572 1556 137
1025 16.36548 3392 2046 3518 1253 1072
1026 16.19514 13098 18835 29346 24343 15617
1027 16.96936 8791 8980 8017 7023 2956
1028 16.89172 20108 21320 30154 24327 14895
1029 16.36548 5202 197 6424 8609 6143
1030 17.57325 4908 5232 1808 4210 1163
1031 16.02471 15524 20603 21770 16629 15059
1032 16.89172 18567 15196 24032 22231 11199
1033 15.08965 24062 30824 8202 23233 23751
1034 15.08965 9607 29801 12691 22141 21546
1035 14.65547 14169 17519 11675 16897 12945
1036 15.06475 22302 25643 16960 14131 19498
1037 15.06475 3815 25141 10941 16320 18243
1038 14.74609 9975 16104 381 13807 14857
1039 14.74609 7919 12211 10017 6080 11832
1040 14.39022 32687 25174 26306 25046 15797
1041 14.56577 30438 26053 27454 20486 11310
1042 14.46010 33833 27748 29638 27137 18294
1043 14.75749 25545 13112 16949 2714 1347
1044 15.65826 12243 6861 7158 16781 18129
1045 15.00103 8815 2687 2850 21778 20830
1046 15.00536 33371 21121 28101 27692 21819
1047 14.84091 33862 24981 27266 27475 18772
1048 14.67066 26446 23603 28571 12152 5816
1049 14.86702 31260 26931 33790 26974 23320
1050 14.38653 17436 14904 19158 32460 27193
1051 14.62794 28658 24119 29088 30261 23268
1052 14.32619 34848 32271 36650 31329 26245
1053 14.26826 27371 30387 26654 34623 27619
1054 14.47960 34845 34120 36713 35555 31993
1055 15.13532 21840 20582 22295 19700 11259
1056 15.03992 28613 18409 29749 22284 19974
1057 14.69458 20537 10028 13030 27277 18826
1058 14.45999 22141 15919 15007 14077 7107
1059 14.42743 5040 449 3819 739 1414
1060 14.46124 15234 8399 10173 10577 3632
1061 14.58976 29710 26517 28520 23639 14764
1062 14.38886 18418 10943 11676 17476 4271
1063 14.62068 27467 23345 23453 22079 11386
1064 14.87428 27329 27494 30512 24607 16464
1065 17.90843 14802 9932 13798 14576 7160
1066 18.04131 23985 20012 10428 21670 13667
1067 18.04410 1004 832 3283 10686 2087
1068 17.68510 9744 2703 6445 6980 1222
1069 17.92443 6082 6678 5363 2577 3297
1070 17.52780 13725 13452 17048 16155 9726
1071 17.68510 7339 8174 14696 9935 6276
1072 17.68510 5637 3871 4744 1084 1722
1073 17.68510 4722 3925 7790 4705 2761
1074 15.13280 14847 10779 8437 19431 13512
1075 14.93316 12854 5601 14081 11313 5598
1076 14.91556 27827 25537 30921 19244 21782
1077 14.93316 11888 6262 11285 2135 1155
1078 14.90446 21437 22736 20319 12160 5821
1079 15.09727 5407 3118 279 2828 3684
1080 14.90610 21293 26005 22820 19943 10916
1081 14.90610 20635 21431 24061 21469 12624
1082 14.81836 15222 14492 3122 15640 11010
1083 14.66157 10448 14151 28193 14717 25214
1084 14.84614 21409 20468 6101 10149 21007
1085 14.84469 24997 27300 17125 21894 14821
1086 14.63411 4452 27897 17883 22193 20324
1087 14.68794 26955 16101 11499 27893 4088
1088 14.68794 22227 6569 2777 29926 1025
1089 14.81836 22905 15976 16582 23112 21085
1090 14.91194 23815 14197 18411 18323 23849
1091 18.29230 2612 14699 4694 5488 11127
1092 18.25478 3306 2480 878 2529 4712
1093 18.22700 3806 12544 6052 2308 3212
1094 18.22760 12976 15246 13411 2683 9537
1095 18.22700 6389 18981 9953 1246 6010
1096 18.23408 10309 17835 14580 147 6273
1097 17.57899 4270 7679 8921 1779 7036
1098 18.23408 2077 12812 5289 4629 11446
1099 17.57899 6835 5368 2410 4995 5040
1100 18.24443 245 5111 2624 5702 8965
1101 14.59313 32814 30344 33712 26924 18012
1102 14.76537 16212 13908 17275 16730 11156
1103 14.78110 30690 30026 34133 28744 25555
1104 15.05472 29795 29950 34944 29360 27655
1105 14.87293 30255 28297 35698 29360 28176
1106 14.93645 3152 19480 15673 13860 23846
1107 14.84769 651 3196 1522 5554 16877
1108 14.56577 22950 19991 24966 15353 7686
1109 15.09022 4270 24719 6802 4646 16187
1110 15.28585 5700 27851 8999 6025 16562
1111 15.06292 11105 15504 15510 13992 17492
1112 15.28585 9656 30194 13866 9810 19210
1113 15.84497 28593 28244 16979 31072 12810
1114 15.63410 22066 24441 25034 30377 20495
1115 15.12928 3846 12138 9120 19545 19185
1116 15.41182 18671 14423 17892 20117 18431
1117 15.29172 3265 17809 12438 3996 9635
1118 17.95616 9828 3759 4150 3896 8958
1119 17.89153 2122 7490 10208 19879 8032
1120 17.85461 10059 20261 22490 22614 12142
1121 18.22112 642 11997 11141 16145 11201
1122 18.11153 8238 13778 18433 24155 15101
1123 17.96436 13500 7465 15969 19226 12609
1124 17.96436 6029 5603 9169 14940 9981
1125 17.70761 17682 1259 11153 16533 8625
1126 18.22112 5277 6865 6577 8337 9346
1127 17.81719 9489 1060 5134 12405 4019
1128 18.21874 6081 11141 11295 22286 8979
1129 17.95192 4443 9524 1252 19777 3140
1130 18.21874 9106 13788 14054 25277 11019
1131 18.21953 11638 10606 12941 23197 10302
1132 18.21993 8754 14628 11999 19903 9566
1133 17.95192 3915 4913 1231 17838 3342
1134 18.21874 702 1562 1431 16708 3513
1135 18.21874 3059 8832 6917 14165 3409
1136 18.21993 982 6708 1454 6260 1627
1137 18.22641 2810 6751 2989 6052 1178
1138 17.89153 10642 11349 11634 23835 10143
1139 17.80661 24494 25572 19683 13130 11410
1140 18.21993 12810 3092 2508 25265 12633
1141 17.84712 24334 23457 23025 23759 16204
1142 17.78868 16338 21111 18641 13258 5387
1143 17.68510 18058 18959 18293 3178 4204
1144 17.80528 17588 18140 22116 23186 9435
1145 17.82366 16444 19655 9267 19620 13871
1146 17.56312 15664 4491 4446 12705 1557
1147 16.37835 29725 18577 25008 25493 12737
1148 16.22315 14969 15790 15147 12649 5431
1149 16.02700 23867 3979 16489 15801 4431
1150 16.14412 26319 20248 27028 21118 9277
1151 15.67565 891 2266 23352 5413 7102
1152 15.78471 13631 5114 4904 14334 8065
1153 15.75745 9234 10266 19360 11883 9347
1154 15.60202 15059 8267 20698 5709 2836
1155 15.33095 23787 23541 29246 22796 21156
1156 17.58845 8072 18582 21568 15760 13967
1157 17.58845 1954 2833 4977 2605 13606
1158 17.49179 1657 12082 7871 11900 15218
1159 16.74852 12283 27768 17268 26233 20693
1160 17.86294 2053 2962 6351 379 12410
1161 17.49179 164 12455 2996 12273 14350
1162 16.86416 2176 18659 4164 17995 16022
1163 16.91355 3002 5891 2471 6385 10818
1164 17.68510 7030 4129 6749 6434 4206
1165 17.58845 9660 11710 13811 8501 13157
1166 17.58845 14418 13612 16270 12741 9145
1167 17.86400 9611 8377 10074 10918 6490
1168 17.86400 5566 10856 24919 7269 3897
1169 17.98736 18535 23146 6620 12118 15723
1170 17.93312 6246 13889 26053 5797 2839
1171 16.98352 4873 8122 24318 13321 777
1172 17.10388 15564 11079 21719 19237 4605
1173 17.63864 9166 3120 15334 8687 1835
1174 17.04369 7436 6983 15588 12453 891
1175 18.04904 26202 28813 21406 18713 18013
1176 17.04369 3344 6379 23926 12089 286
1177 18.28010 16974 22430 6896 17655 9216
1178 18.77896 7962 16696 9882 13099 6351
1179 18.33809 9022 12683 8959 21014 7941
1180 18.77896 7483 12539 9882 13099 7341
1181 18.38982 802 5038 1553 14201 5824
1182 18.77896 370 1448 7918 570 4068
1183 18.77896 1555 620 2723 8565 3961
1184 18.25296 705 1986 472 5993 1331
1185 18.77896 166 124 2504 135 1896
1186 17.96066 1504 15481 20775 14702 12984
1187 17.52822 11859 18376 14259 15086 11576
1188 17.69780 10323 20923 22744 23560 13063
1189 17.65966 2537 7457 5720 4942 10593
1190 17.61416 7778 7641 10954 23264 12803
1191 18.27539 869 2256 1033 24930 16663
1192 17.49866 17768 7458 25113 26379 4524
1193 18.49182 1555 2339 4858 22766 13665
1194 17.98642 6875 8603 10704 20822 13995
1195 17.98318 1013 5477 5781 6054 5907
1196 18.21725 4452 14025 3789 4379 735
1197 17.98318 1658 7188 760 5264 5304
1198 18.21725 10489 21121 17501 14596 4461
1199 17.82610 8550 16304 8200 12765 12449
1200 17.51730 19211 24068 5663 17446 12967
1201 17.77807 9095 23032 9788 17446 7316
1202 17.62556 17997 25149 6839 18491 11189
1203 18.20304 10446 6054 5955 4046 34
1204 17.80826 704 646 1742 79 576
1205 18.25183 4183 10860 13918 17114 9230
1206 18.16658 1068 8240 17254 11902 11294
1207 18.18507 1970 488 772 3751 1952
1208 18.37249 11699 11046 18367 13541 7453
1209 17.89727 6986 10408 17658 9886 6055
1210 17.94931 11538 8654 15456 4056 2845
1211 18.87625 11355 7988 11824 12110 5108
1212 18.49728 13032 4952 17619 15636 5769
1213 18.58413 8095 4689 7774 22163 11164
1214 18.74838 15604 14547 23154 18298 9266
1215 18.87625 5314 1140 3758 6244 2227
1216 18.13117 17206 6358 19507 18545 10225
1217 18.13117 6699 2741 8096 5407 2880
1218 18.11832 2900 8465 12412 8503 1939
1219 18.74838 5602 12168 23128 11742 4457
1220 18.48056 4103 26159 6458 4199 1848
1221 18.40596 12729 22524 13240 13530 15022
1222 18.77896 1463 3564 4431 2368 14510
1223 18.77896 9861 15877 17968 11789 6407
1224 18.77896 12333 15682 17324 11685 5664
1225 18.77896 1591 8075 4853 4086 6654
1226 18.64061 3979 4573 4223 12734 2576
1227 18.57144 865 7690 7535 13411 1533
1228 18.39268 12301 23470 14137 11114 11934
1229 18.28010 12710 29378 15051 13512 6040
1230 17.59013 12999 7462 14342 14394 3363
1231 17.35865 602 2102 147 378 759
1232 17.43581 781 1460 934 826 1258
1233 17.35865 1008 1642 1902 332 1911
1234 17.47439 3552 4552 2382 2244 1040
1235 17.59013 13099 11909 8912 1353 3572
1236 17.59809 13413 14513 15929 6370 4397
1237 17.47439 2382 8061 5239 9502 5050
1238 17.70793 10774 6639 15298 11617 8642
1239 17.31623 670 1164 2205 940 8362
1240 17.41166 1761 1976 1981 2579 11430
1241 17.50710 1392 2127 7966 5127 15214
1242 17.47102 1242 1954 601 4098 13718
1243 17.31623 13187 14281 19250 3300 8026
1244 17.44680 18871 19830 24556 18520 7942
1245 17.41166 13814 14919 19609 14515 15850
1246 18.07012 24569 34308 23007 15552 24791
1247 18.09840 4648 28159 10285 11511 20656
1248 17.48305 9937 16621 19655 5135 20038
1249 17.41166 13621 15412 21663 13136 18173
1250 18.27787 11966 16845 5855 5484 6243
1251 18.27400 15916 21005 26489 24361 11451
1252 18.27787 16223 18237 15887 15763 11667
1253 18.37152 12714 30010 4257 5576 19701
1254 18.32865 9404 2136 2837 22506 12013
1255 18.20279 5262 11901 4637 25679 16109
1256 18.18507 4083 5616 6363 16962 9894
1257 19.22252 27878 29967 26189 29044 21355
1258 19.33663 8977 20537 20559 31194 15975
1259 18.61313 17590 16849 14267 29261 9681
1260 18.76994 1869 21948 21151 28680 18644
1261 18.76994 15900 16335 22648 25348 15429
1262 18.75740 3791 12240 11117 25710 16623
1263 17.43494 2518 10956 9287 24573 6323
1264 17.45298 1220 3833 2866 23637 6307
1265 17.45298 3123 5915 6448 24691 10265
1266 17.43494 1220 9407 5669 22941 8158
1267 17.39680 10323 19850 13359 21929 9220
1268 17.43494 10265 15261 16280 24783 10392
1269 17.39680 6751 11830 2695 13439 1764
1270 17.39680 11507 12478 11895 12295 3753
1271 17.28206 6729 7787 4485 6209 1214
1272 17.74714 8710 8193 11982 9739 7040
1273 17.61888 1102 4366 6048 12559 12549
1274 17.76674 5357 11790 11586 10401 6740
1275 17.74763 5024 11604 19945 10315 6437
1276 17.76087 2259 12975 16515 5504 8232
1277 17.98318 742 6331 11455 1419 9094
1278 17.74912 970 2615 2890 8302 10015
1279 17.98318 2124 3312 1337 1283 5074
1280 17.59013 11613 6158 16597 18697 1878
1281 17.94731 5096 4046 1579 2940 2599
1282 18.65645 942 5545 906 533 354
1283 17.76872 10074 2347 3858 3392 5221
1284 18.38690 8953 3080 5388 7549 4933
1285 17.50773 3522 4375 4108 4299 2596
1286 17.59013 854 5011 2590 10936 5451
1287 17.98851 8346 3767 8392 12688 8912
1288 18.05098 1919 19357 11412 9866 7806
1289 18.04161 3547 20528 8665 26092 16986
1290 17.36486 13873 13046 23653 20152 12742
1291 17.81556 6526 8104 21255 23386 15334
1292 17.36486 18080 17453 24793 23751 14847
1293 18.27787 10525 3866 9920 8715 1719
1294 17.60390 7603 14130 13520 20333 10279
1295 18.00064 3547 20460 19794 15905 8584
1296 18.27207 1711 5638 25671 24673 10571
1297 18.26626 7951 11006 12940 24315 9762
1298 18.20509 3069 6345 8872 19286 1796
1299 18.26626 10503 12693 3927 23835 6740
1300 18.26626 2255 13594 25587 26388 6683
1301 17.56189 20652 22640 27835 14019 13407
1302 17.92592 8604 13830 15297 15050 9544
1303 18.22932 6375 10683 4221 23782 2361
1304 17.85859 688 1225 4478 19554 2981
1305 17.70793 24593 21959 28953 21700 20636
1306 17.11490 8461 20351 26370 16304 27210
1307 17.26631 27096 22719 29360 20970 25960
1308 17.15260 11562 4722 6730 4244 21816
1309 17.47386 20263 12225 8289 3685 22336
1310 17.19327 2285 7583 14174 7497 24204
1311 17.47386 20468 8218 23959 17451 15874
1312 17.23978 4640 7252 5239 7152 22436
1313 17.70793 14199 2626 19629 14898 11289
1314 17.38076 6826 13875 11676 1295 1666
1315 17.68789 2765 4541 17079 4320 1999
1316 17.74985 7695 8889 16319 23443 16236
1317 17.70998 1323 8325 5422 21357 12720
1318 17.47050 10007 23575 30739 4622 19093
1319 17.54479 9226 24321 24431 18622 6708
1320 17.58733 239 14373 13738 14070 6874
1321 17.37260 13174 30049 33853 8771 23983
1322 18.38569 4060 2011 6524 31531 16981
1323 18.47793 10161 3469 11865 31225 16378
1324 18.22012 1953 14625 3450 31451 21502
1325 17.80817 14794 9935 13590 30653 17418
1326 19.14231 14794 3291 12047 32220 18866
1327 17.59721 3069 4003 5025 31922 10507
1328 18.52798 16219 7261 6730 32901 17940
1329 17.71486 12916 6771 9567 30753 6148
1330 17.64561 11530 24215 28295 16798 21905
1331 17.92906 13644 12055 13280 24448 8686
1332 18.72071 366 132 735 6342 1128
1333 17.92906 5545 561 16210 18932 4459
1334 18.41987 2179 3936 6677 9823 4508
1335 18.32364 920 2208 6620 14667 1187
1336 19.02155 3085 1175 2693 1798 4994
1337 18.72071 61 1542 5768 850 3483
1338 19.05196 5657 2183 7214 5008 9862
1339 19.18846 11907 5210 3052 15822 9528
1340 17.67607 1738 3751 120 12633 6050
1341 17.44452 4778 497 643 6086 1193
1342 17.68197 2075 1434 1062 5269 2800
1343 17.78529 10632 797 10980 7540 8661
1344 17.67607 5592 13195 537 18104 10982
1345 17.74912 6400 13348 6316 18218 11052
1346 17.89770 11866 2050 9041 14136 11178
1347 18.46684 10850 16671 9849 19138 15066
1348 17.80491 940 4003 2449 6899 6780
1349 17.61036 7656 13805 10831 19031 14600
1350 17.47394 62 11790 998 11931 6358
1351 17.72396 15188 18539 18301 23853 15343
1352 17.65976 5591 10798 7367 17124 13177
1353 17.47394 8187 12316 6045 14858 9665
1354 17.80338 961 4095 2457 1933 5309
1355 19.26413 2153 10241 4441 8117 9219
1356 18.81403 972 580 2900 2192 11837
1357 19.26413 994 6532 2557 2192 8764
1358 18.82387 5613 5523 9468 8724 5787
1359 18.81403 1392 7529 2557 3680 9408
1360 19.18846 6029 9806 7340 13590 6677
1361 18.79649 2837 2608 2207 13511 2282
1362 17.86029 5061 3422 4931 10761 6035
1363 17.47439 1986 5375 4222 4625 2467
1364 17.47439 459 810 899 7275 6449
1365 17.98851 4103 1203 3102 10186 9012
1366 18.24618 12935 4720 13630 13746 5381
1367 17.95034 2070 3472 3098 1486 407
1368 17.68475 525 503 1366 287 1237
1369 17.47439 998 3071 1377 879 844
1370 18.79730 5755 4584 4456 10473 7102
1371 18.58248 6943 8982 3283 20347 3891
1372 19.01213 7355 7258 10419 8797 7265
1373 18.58248 7406 6478 4277 19188 3669
1374 18.89013 12998 3446 5694 22325 5222
1375 19.08022 22625 12321 17931 27201 11864
1376 18.67403 3693 4130 311 16055 4904
1377 19.34183 23152 17917 21921 27013 12104
1378 18.36734 8035 12581 9671 3715 3673
1379 18.06365 11977 16502 1326 13617 6067
1380 17.91180 10921 5869 4851 3619 7313
1381 18.56832 1414 10623 10309 11410 5418
1382 17.64104 9341 1528 6135 8622 1572
1383 18.59132 9778 10692 9900 9655 8282
1384 19.02341 13085 18975 28686 18287 13046
1385 17.49886 12863 16621 18013 7231 12135
1386 18.50861 2228 10167 5104 8355 5589
1387 17.19530 19827 27316 25850 18805 13641
1388 16.80648 6123 20276 25497 7110 18741
1389 17.61998 25561 28605 32193 4613 2940
1390 17.61998 23690 25064 29542 18238 8330
1391 17.06934 3972 20967 16248 12218 16454
1392 17.09916 36111 36465 38195 33240 31266
1393 17.10693 15450 26385 25486 16373 20473
1394 16.90662 15809 25703 30534 16361 22888
1395 16.75983 1500 2255 3872 26946 14530
1396 17.26210 21238 22272 19839 30288 19568
1397 16.79167 34119 34806 37059 33765 21601
1398 16.99958 1301 1218 2880 27716 14741
1399 17.10283 7974 8297 8439 26906 13394
1400 17.07258 7183 4817 19948 22934 8981
1401 17.16247 13854 5504 14868 15215 2422
1402 16.36199 35508 35040 33618 34277 6806
1403 20.77278 11978 7378 11244 16917 3387
1404 20.77278 18165 11749 938 18153 5525
1405 20.45506 11922 5956 8066 9771 12370
1406 21.22588 6709 10967 9617 10909 6624
1407 20.74270 22743 25987 29689 24432 16190
1408 20.77278 20565 13898 10419 13818 8988
1409 21.22588 2241 2600 628 1806 1564
1410 21.22588 4861 7755 4378 5667 6067
1411 21.22588 9754 14295 14035 15444 9282
1412 21.22588 1793 10543 4687 20592 12926
1413 18.18348 16821 19784 24723 25543 14664
1414 18.28079 12653 15379 19728 27156 15293
1415 18.29062 7402 5740 7343 22334 9405
1416 18.48524 4926 15471 19839 26683 17656
1417 18.07285 30151 32013 35197 31752 25342
1418 18.30964 21463 25444 27196 28009 20660
1419 18.35549 152 9119 2521 21366 12110
1420 18.22018 568 17270 4565 14584 8265
1421 18.21919 1770 2621 3146 14776 4095
1422 18.09600 1806 2662 5631 2409 8281
1423 18.29200 11555 17571 14309 12356 19302
1424 17.77651 28883 29450 33663 32180 18498
1425 18.19476 2338 7119 3521 3024 14420
1426 18.17281 11668 18038 15150 12463 19354
1427 18.08617 10972 11937 10222 11782 16626
1428 18.07633 28059 30627 32792 26650 25017
1429 17.49886 6167 5771 9597 2033 9480
1430 17.33587 10973 13359 15582 10736 12864
1431 17.15108 17145 16756 18059 17519 5520
1432 17.24649 21199 19911 26856 28062 7374
1433 17.22942 23049 17806 20892 25575 1634
1434 17.65316 3890 3448 1947 4678 10436
1435 17.43523 7565 1403 10728 8574 449
1436 16.92014 14805 5464 22127 13054 2415
1437 19.33938 10342 16795 14749 5762 21852
1438 18.82901 13461 14467 14612 20182 6931
1439 20.17195 2277 1824 12945 11052 775
1440 19.50371 10998 15690 24783 19256 7629
1441 19.80090 7050 5435 20665 16944 2399
1442 19.42154 7828 3382 28486 3151 17874
1443 20.31968 18272 13700 18984 13439 11423
1444 19.65710 2792 1448 26669 1283 19753
1445 19.68424 10354 12828 14749 5772 15690
1446 19.66614 6881 10875 17214 5639 19373
1447 16.65871 18607 18326 34520 3157 21585
1448 16.87479 14709 19822 33351 15225 17639
1449 16.66842 3815 23659 4431 24843 14160
1450 16.73228 2398 4072 27637 12163 12595
1451 16.89746 12636 3894 24372 2069 4731
1452 17.12389 5737 29019 8766 30306 9038
1453 16.94309 7788 6901 24696 13054 8984
1454 17.20172 16262 19362 19193 31717 17659
1455 18.97029 4579 1833 1296 16253 13971
1456 18.57493 3957 11052 8841 20971 18951
1457 18.97029 19538 11404 22518 21860 14362
1458 18.97029 837 1428 403 1205 12169
1459 18.66881 20178 21447 14490 20542 11245
1460 18.97029 12232 12559 15572 15950 18951
1461 18.97029 6782 7831 7176 7758 15752
1462 19.40879 18147 19179 24051 12693 17317
1463 18.97029 18621 11661 19060 22181 13790
1464 20.09809 4060 3662 7678 4891 1090
1465 21.22588 12835 12148 22081 11751 5124
1466 19.72215 2159 1634 3732 2767 7162
1467 20.09809 8988 10025 13021 9975 8583
1468 20.09809 12963 12415 18162 9899 14613
1469 20.09809 5946 6107 6723 6915 5723
1470 21.22588 14548 10937 21570 10620 6558
1471 19.62995 7222 4706 12855 18171 9636
1472 19.62995 4489 19407 25522 23834 12965
1473 19.62995 7710 2672 1197 8714 4471
1474 19.62995 2230 11563 21075 21071 12317
1475 19.62995 9887 22132 28491 22218 16752
1476 19.28079 3584 824 1088 7913 592
1477 19.62995 8254 14563 20569 24689 15571
1478 19.10621 13596 7595 13620 17238 3847
1479 19.10621 11347 9179 2768 18089 448
1480 18.97029 8196 14737 6431 19737 11733
1481 18.97029 14543 10602 18200 19241 9739
1482 18.33849 4616 23647 1530 9883 6724
1483 18.22018 1270 15439 2348 1785 1141
1484 18.46493 7983 26985 4378 20506 13267
1485 18.47021 997 7415 1548 4831 3171
1486 18.59523 1801 1763 5229 10269 5789
1487 18.72777 1594 20125 4720 14177 7992
1488 18.92469 7525 21918 3595 20423 12415
1489 18.14185 7256 23619 23856 8251 8133
1490 17.51306 16116 14055 12572 9609 7299
1491 18.19216 11349 22317 20420 13767 8146
1492 18.20410 16557 22491 22597 16403 9053
1493 18.50861 6510 18943 20195 13212 7803
1494 17.79870 24298 27095 30991 12283 4307
1495 18.22018 10772 8237 10657 17975 10670
1496 17.82946 16116 15787 14991 10826 2684
1497 17.59870 24354 1215 2401 9669 882
1498 17.47615 30156 14807 14990 21623 4979
1499 18.06696 25787 7097 9154 21390 3239
1500 17.27036 6148 31083 9335 32359 501
1501 17.39112 16225 28632 21905 30611 10759
1502 17.36179 23327 19523 22783 21264 7791
1503 17.28261 21096 8755 10363 11749 1410
1504 17.40138 30881 23491 28629 27446 12566
1505 18.63267 16294 7087 9223 21653 3730
1506 18.93556 21996 8429 6266 22823 10884
1507 18.40017 21645 7206 2236 22746 8374
1508 18.86891 5213 7510 13041 6154 2828
1509 18.91537 20841 13922 19440 21889 7424
1510 18.63267 15286 2004 7335 23217 992
1511 18.57190 19493 10679 7121 25828 4950
1512 18.40017 23221 6526 8574 23408 7630
1513 18.57455 11039 11244 18353 16703 4807
1514 17.09958 757 2511 3104 2033 5011
1515 17.51947 19432 27653 26201 15524 11061
ah3gpas_rnk ah3blue_rnk ah3no2_rnk ah3so2_rnk ah3pm10_rnk ah3gamb_rnk
1 41618 14033 41717 41459 41254 36496
2 41703 14376 41706 41400 41440 36745
3 41410 16345 41706 41400 41440 37818
4 41720 9255 41625 41224 41210 37130
5 34750 13600 41197 38387 41416 35999
6 40106 4333 40832 39299 41600 39414
7 19845 1647 40741 40253 41716 21072
8 40258 8527 41301 37800 41416 41102
9 41453 8060 40946 40225 41655 41671
10 39732 994 41301 37800 41416 40975
11 39028 6530 40832 39299 41600 31040
12 34870 24520 39300 40270 40370 32720
13 31693 17162 39433 40137 40544 24005
14 25477 27950 39399 40471 40260 26115
15 30945 25737 38174 40567 40115 29828
16 31340 25168 38174 40567 40115 27811
17 26642 26081 39399 40471 40260 29264
18 26064 2297 38445 37831 40710 34635
19 31714 7766 38445 37831 40710 35495
20 32114 11795 38445 37831 40710 33704
21 32503 11774 38445 37831 40710 33815
22 19986 14968 38445 37831 40710 29449
23 33749 15943 38445 37831 40710 38028
24 34923 19573 38445 37831 40710 34480
25 18471 28205 34702 30336 39352 11272
26 18415 23454 36346 36859 40183 10797
27 33652 33060 37320 37340 40120 23846
28 11632 28164 36851 37524 39936 12255
29 31615 33602 36742 36087 39898 28335
30 35766 30532 38199 37479 40581 38210
31 22095 24156 37752 40287 39167 25268
32 24411 16987 37495 39006 38057 19248
33 36795 22934 38102 40635 39460 39831
34 38149 18137 38622 40869 39477 39012
35 27753 16917 36800 37393 37426 19804
36 28270 14898 36758 37734 37228 31874
37 23672 5253 37557 40170 38567 11358
38 34753 10642 40940 40432 41684 40665
39 26983 6182 40647 40151 41015 38683
40 21684 1573 40526 40163 41014 33182
41 26781 11497 40337 40407 40913 35843
42 37579 17287 41029 40326 41611 35936
43 28216 8742 40049 39822 40198 41068
44 27109 15334 39644 39350 40198 33206
45 31997 11516 40750 41051 41597 24939
46 34586 10329 40750 41051 41700 39340
47 38395 14317 41011 40603 41666 41255
48 41249 15336 40750 41051 41597 38686
49 33369 15797 40750 41051 41700 32586
50 33966 28634 39049 40718 39338 30768
51 27620 15923 39052 38675 40007 36378
52 27771 19542 39212 38800 40198 30579
53 30443 23671 39052 38675 40007 24840
54 28098 11177 39212 38800 40198 41218
55 26608 18373 39866 39319 40805 32745
56 31612 23494 38838 38551 39796 31930
57 24042 19700 37711 39669 39393 31925
58 37176 11953 37429 38843 38298 30076
59 30317 22939 37778 40306 39682 39022
60 26331 21599 38020 40004 40089 39381
61 33041 25676 37778 40306 39682 32429
62 30253 25298 38036 40182 40033 36794
63 31253 846 40284 39557 41100 31689
64 26410 4589 39834 38938 41122 36674
65 35966 10225 41208 38817 41632 33662
66 33550 3588 40738 39963 41314 34024
67 30039 5051 40985 39080 41607 38948
68 34147 5542 41102 40037 41199 33406
69 31840 2254 40123 39694 40858 39474
70 31347 4765 39684 39215 40858 36022
71 27343 5678 39684 39215 40858 32447
72 19794 1342 39480 38874 40774 30955
73 25122 4295 40647 40151 41015 36335
74 29399 16955 38445 37831 40710 38204
75 33237 19165 38369 39151 40554 36488
76 31870 21237 39238 39444 40692 25066
77 27253 22399 38995 39481 40727 35416
78 30146 26647 38248 40494 40341 30211
79 31718 22105 38285 40061 40310 38074
80 27905 14011 38445 37831 40710 39723
81 24743 22473 40059 39892 40625 40027
82 32688 20566 39618 41146 39588 41071
83 33339 21487 39261 40465 39679 37672
84 34294 12648 39382 41332 39134 40827
85 35869 5003 39618 41146 39588 34884
86 34225 1925 39434 41550 39120 24925
87 38683 3780 39054 41262 38845 24070
88 21126 25763 38294 38181 39057 34846
89 34696 13530 39226 39573 39970 13720
90 24896 18078 39687 40278 40883 39908
91 32080 27296 38294 38181 39057 23604
92 35480 26453 38130 39984 38786 13077
93 38870 27062 38294 38181 39057 19689
94 31872 8070 38416 37346 40686 36134
95 32966 6612 38416 37346 40686 41255
96 35853 14021 38269 38528 40505 31641
97 20248 18604 38326 39410 40271 34989
98 30921 16496 38326 39410 40271 37505
99 31083 13500 38383 38716 40521 38969
100 34464 3395 39401 41337 39445 21447
101 35498 7604 38007 41206 38348 25797
102 34917 22974 40303 40301 40695 39099
103 26705 18324 39375 40881 39705 29520
104 24918 2338 37972 41086 38724 24861
105 33928 6234 39043 40835 39490 38260
106 38519 19643 38085 39470 40271 25578
107 31632 35526 37321 37949 39446 23712
108 35912 24428 37679 38652 39792 26127
109 37512 29425 38003 38424 40464 34210
110 38458 24445 38104 38083 40510 41528
111 38208 18204 37786 39174 39672 31396
112 19137 28286 35916 26424 36887 29089
113 22564 31670 37097 27191 38297 31911
114 24595 32504 36993 26855 37138 31327
115 26784 33959 37097 27191 37901 28712
116 27707 20474 37403 29658 38470 33286
117 32700 25445 36810 27561 38090 34675
118 15663 36903 37445 28042 38796 17159
119 9622 27917 38150 31847 39325 26593
120 11789 32977 38021 31168 39118 25114
121 32068 33549 37445 28042 39325 27379
122 36716 33043 37047 27874 38251 26496
123 21453 38484 37818 28273 38899 18278
124 15893 37090 37390 27288 38752 33741
125 14995 36401 37818 28273 38899 32730
126 32281 35117 37283 27757 38424 40520
127 18773 37843 38610 27268 39259 27712
128 29104 33871 37724 27711 38538 31052
129 28947 36787 39222 26146 39584 39328
130 19613 38126 39222 26146 39584 30941
131 26890 33273 37146 27270 38251 30379
132 24225 34774 39851 30506 39944 33293
133 8945 29458 39740 30282 39829 36125
134 29563 32030 39539 29779 40080 36695
135 27113 36706 39603 31315 39961 20243
136 20372 35088 39849 29900 39946 26213
137 35700 30461 39539 29779 40080 38949
138 39158 34432 39757 31649 39860 37877
139 32705 35897 39757 31649 39860 24043
140 31068 37029 39819 31755 39812 24762
141 32893 34724 40187 31014 39903 39225
142 30141 35089 40191 31235 40285 31525
143 38006 32575 40191 31235 39821 41648
144 36237 25103 37842 27111 38490 36022
145 38299 29733 37676 26830 38054 32815
146 36811 19228 38370 27402 38307 32202
147 23393 38778 38537 28223 39060 15429
148 30607 39435 39170 27540 39517 16896
149 25705 39435 39453 27238 39754 16896
150 36842 37715 38537 28223 39060 14056
151 38506 34950 37754 27555 38524 19780
152 33365 18261 38391 28518 39561 38315
153 29153 19677 38391 28518 39561 34216
154 28032 36059 37445 28041 39723 25837
155 7257 33503 37445 28042 39380 28869
156 21805 37182 37682 28490 39907 19968
157 27459 36379 37998 28122 40218 35096
158 33219 34830 38280 27788 40565 41521
159 19457 23554 37925 28909 40391 27456
160 27314 22365 38760 28357 40178 30670
161 21090 35832 38156 28152 40177 27552
162 11111 9168 33567 22225 35328 29253
163 8602 3897 32712 21094 35165 31922
164 24646 17187 33525 22994 35851 34152
165 17068 9365 33825 22364 35693 32432
166 24378 17500 33825 22364 35693 35124
167 37531 15485 33847 21258 35106 36215
168 7839 28421 35385 25248 36410 27516
169 23124 25224 35754 25481 36410 38148
170 25571 25435 34913 23823 35394 41140
171 14593 28405 35231 23940 35202 34226
172 18789 37553 39669 29869 40396 20420
173 27733 35793 39479 29151 39951 32722
174 32163 34134 39427 29094 40141 39069
175 28380 37292 39669 29869 40396 22940
176 22034 34270 38998 28001 39702 32551
177 39272 31575 38998 28001 39702 41700
178 34584 30798 38767 26676 38213 35864
179 7169 36648 38993 28425 40396 23972
180 22781 36579 39484 29125 40289 23855
181 18416 36802 39669 29869 40396 29582
182 27390 23799 36228 20469 36359 30824
183 27577 29457 36228 20469 36359 35629
184 3962 21678 36020 18759 35749 22595
185 33129 13335 35433 19675 34947 17054
186 27375 9141 35852 20070 35656 25147
187 24615 18816 35852 20070 35656 24884
188 32717 20679 36862 25168 38443 37928
189 35445 12673 35879 23939 36473 37738
190 38198 24075 36316 24641 37041 37347
191 21431 34048 37069 19748 38083 32153
192 35640 34196 39920 29736 40052 33702
193 23594 34666 39888 30356 40396 31332
194 22880 34574 39963 29289 39538 22773
195 6110 33393 40034 29409 39639 24461
196 13783 36054 40181 29612 39639 26795
197 15405 36410 39990 29272 39935 22513
198 23224 36663 39920 29736 40052 25034
199 19081 38270 39878 29844 40149 22373
200 14125 30615 39807 28272 39595 36347
201 1560 39370 39588 29557 40212 24648
202 1328 30891 39646 30086 39091 15295
203 4840 37849 39626 30636 39894 18726
204 4306 37206 39106 29101 39102 20819
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1270 31312 15619 39193 31734 37605 25174
1271 13261 6296 39173 32454 37280 32588
1272 35021 10428 38270 32081 38337 36962
1273 32070 12586 38424 32771 38079 36438
1274 38148 6498 38251 32856 38376 38635
1275 39377 1668 38266 32283 38338 30137
1276 39011 5381 38251 32856 38363 32800
1277 38516 6777 38251 32856 38743 31631
1278 37428 3099 39208 34987 38341 39778
1279 37363 8406 39125 34690 38743 37005
1280 25713 4476 39392 29790 38019 34399
1281 34708 16530 40416 30480 38692 40900
1282 29698 16289 40426 32398 39637 41230
1283 32161 13667 39881 30161 38382 38557
1284 34978 20291 40416 30480 39310 38928
1285 35350 14929 40416 30480 37849 35877
1286 33375 5974 39820 28382 38019 29658
1287 35282 11031 40083 29282 38753 29959
1288 25013 3002 39246 29972 38840 37458
1289 28746 21443 38899 29352 38827 35946
1290 30332 15961 38047 29018 37512 30020
1291 19130 20834 37638 28740 38466 27331
1292 35169 16844 38047 29018 37512 28748
1293 27287 14713 39467 29537 39168 36034
1294 30167 18770 37934 28456 38055 28092
1295 13161 7933 38847 28961 38769 30176
1296 27379 17415 38888 28634 39151 27539
1297 11080 21547 37892 27405 39143 24643
1298 15895 21423 38060 26540 39042 22879
1299 14654 23544 37892 27405 39143 22111
1300 29419 9002 38594 26614 39143 25569
1301 12442 24732 38360 24616 37958 21373
1302 29356 19439 38746 27015 38650 30473
1303 16375 6965 39163 27838 39101 28863
1304 22984 9718 38493 27859 38533 38907
1305 28259 27167 38286 30529 38274 22486
1306 23578 5628 36839 29166 36693 18189
1307 22003 30671 38265 26284 37224 19923
1308 24090 19997 36522 29379 36815 23541
1309 22808 25636 37462 29674 37781 32234
1310 20819 14325 36610 29648 36959 21560
1311 33555 18626 37462 29674 37781 18049
1312 17923 14802 36377 28769 37129 25700
1313 12636 12842 38286 30529 38274 17318
1314 36071 8344 39313 36213 37560 34246
1315 23179 5024 39864 37184 38237 27969
1316 14197 5186 39704 36362 38344 26674
1317 30981 4165 40027 37529 38279 33192
1318 31401 2803 39457 31986 37779 19163
1319 38241 23990 39612 34611 37920 22073
1320 28517 830 39637 33983 38004 19365
1321 36293 9954 39933 31886 37535 15349
1322 37917 7198 39336 29569 39309 40324
1323 34619 4333 39322 29516 39448 40145
1324 31739 4029 39085 29233 39073 32849
1325 25089 4217 38950 31254 38444 21171
1326 37090 12453 40406 30826 40186 29491
1327 36027 15747 38762 30845 38041 11950
1328 38244 4040 39720 31139 39486 24198
1329 35379 7873 38898 31162 38286 13660
1330 33903 16194 38862 31042 38138 20241
1331 25273 36032 39503 32997 38656 30165
1332 39744 34635 40713 32783 39760 41133
1333 30665 34698 39503 32997 38656 41312
1334 11987 32514 40597 33236 39355 31838
1335 35429 34723 40260 33685 39222 39572
1336 32984 33816 40839 32396 40083 36935
1337 30376 35086 40713 32783 39760 37815
1338 36637 35099 40986 33270 40110 30516
1339 40348 32690 41192 33480 40226 24560
1340 39845 15218 40434 37047 38198 41178
1341 39898 21046 39590 36364 37714 40301
1342 41312 18911 39528 36128 38212 41434
1343 40798 21244 40028 36761 38414 34380
1344 38919 13539 40434 37047 38198 38616
1345 36349 18984 39208 34987 38341 36709
1346 39717 18896 40332 36993 38613 31622
1347 39376 13258 40862 37641 39435 37256
1348 40915 10271 40263 37697 38437 40101
1349 40165 10582 40270 38971 38066 39969
1350 40309 548 39879 37738 37783 41462
1351 38755 6895 40581 40327 38302 33867
1352 38930 6806 40315 38977 38160 39653
1353 40125 1210 39879 37738 37783 37724
1354 40628 12628 40138 36905 38436 40822
1355 32660 29281 41180 31964 40296 26874
1356 32654 26107 41030 32565 39879 22534
1357 31793 30479 41180 31964 40296 29586
1358 13229 22702 41030 32565 39885 29045
1359 34785 27937 41030 32565 39879 23937
1360 35361 28763 41192 33480 40226 27569
1361 41386 34535 40609 33319 39849 36093
1362 31972 17390 39611 32195 38536 31219
1363 36171 15191 39418 30380 37785 37306
1364 37461 14385 39418 30380 37785 31147
1365 34783 13529 40083 29282 38753 31155
1366 29298 26228 39825 34027 39117 32598
1367 12770 22979 39547 33601 38697 39667
1368 36230 23092 39360 32758 38220 40778
1369 37479 15598 39418 30380 37785 40512
1370 33892 27567 38492 30888 39851 34217
1371 26447 28140 38591 29503 39552 40430
1372 31400 28626 38351 32217 40066 30543
1373 33802 28186 38591 29503 39552 34884
1374 35897 31354 38863 31181 39941 39131
1375 15414 34194 38522 32674 40134 29671
1376 33659 28234 38824 31122 39675 41536
1377 26489 31676 38727 32690 40430 26503
1378 8650 17984 36766 31687 39277 36150
1379 32072 25313 36625 30643 38856 40800
1380 29389 16176 36027 29302 38640 38227
1381 32285 23165 36586 31996 39535 37645
1382 26891 20946 35805 27147 38128 40856
1383 31522 24244 37983 30608 39565 35155
1384 29446 25478 38975 33661 40086 20520
1385 5772 15681 35150 29012 37839 29124
1386 26178 22438 36199 32604 39464 40177
1387 14363 11072 33016 25136 36968 17421
1388 33708 11781 32835 22499 35544 39200
1389 31529 7964 34894 29102 38081 14929
1390 22158 11276 34894 29102 38081 17014
1391 37280 11714 32988 24896 36498 36802
1392 3575 19021 32676 18039 36627 8205
1393 8520 6057 31580 23380 36660 28852
1394 14754 13917 31960 21301 35893 35207
1395 25723 24152 33525 22994 35352 40715
1396 24434 12732 35223 24475 37211 28166
1397 3770 12427 31581 18320 35477 10087
1398 18760 24054 33946 22699 36256 31440
1399 17238 24212 34252 22902 36641 29075
1400 10999 29190 35641 24829 36525 20997
1401 14600 27581 35808 25740 36857 22838
1402 2644 19699 31468 18684 33581 9038
1403 30704 18833 40763 39329 41603 35019
1404 36411 13540 40763 39329 41603 40937
1405 27065 9601 40763 39329 41435 39310
1406 34038 15151 40449 38655 41708 37607
1407 41240 16657 40541 36915 41588 22441
1408 15422 7991 40763 39329 41603 34785
1409 40617 20111 40763 39329 41708 37595
1410 30777 10705 40763 39329 41708 40954
1411 33718 15688 39913 38106 41708 36110
1412 38899 14990 40763 39329 41708 33752
1413 23753 27459 36565 30452 39014 31137
1414 30606 28376 36942 29845 39173 33275
1415 27357 30745 36243 28995 39187 30235
1416 33013 30661 37200 33037 39453 29459
1417 41211 18218 36626 30719 38870 19615
1418 30361 21656 37189 31696 39210 36243
1419 36414 30436 36888 31731 39261 40303
1420 29839 31110 36743 31944 39074 40546
1421 35042 29005 36194 30393 39067 36417
1422 29162 31740 36243 28995 38892 39263
1423 30278 31255 36001 26193 39191 27263
1424 24264 8254 37569 33239 38396 12339
1425 34412 30122 36210 28635 39025 31464
1426 34745 26257 35473 31550 39005 35848
1427 36620 31432 36166 31045 38886 31716
1428 23477 20689 36088 33003 38871 24849
1429 24657 6003 35150 29012 37839 36797
1430 6818 2689 34287 26358 37420 29561
1431 5280 16104 34235 25122 36811 27357
1432 8214 18708 35420 26242 37155 20236
1433 14518 17664 33921 24806 37104 21848
1434 16075 12790 35540 28776 38152 39258
1435 20023 16961 34911 25944 37699 41279
1436 21148 4822 33372 23678 35937 33666
1437 34668 7691 39574 36739 40422 19631
1438 36883 29293 38222 35054 39889 35659
1439 35600 22967 40223 38903 41101 39126
1440 21212 19349 39469 36143 40573 25890
1441 33127 25809 39668 37526 40806 34730
1442 35888 14227 39781 36448 40488 19872
1443 15217 8091 40763 39329 41256 27910
1444 34374 12361 39848 36708 40699 20664
1445 35881 1846 40763 39329 40722 24075
1446 35836 8203 39986 37744 40704 22217
1447 20475 29410 30626 18893 34960 13379
1448 13753 24675 33111 22539 35766 16877
1449 17411 7665 31519 19565 35000 19670
1450 9491 18737 32469 21340 35257 22735
1451 14304 10609 33233 23110 35854 35299
1452 8195 976 33813 23317 36720 25811
1453 14591 12374 32761 22201 36023 26480
1454 13798 5451 34507 23319 36990 28100
1455 35465 30313 38192 36502 40020 40212
1456 27246 29664 36798 32423 39545 36565
1457 24200 33010 37827 35754 40020 26941
1458 37359 31606 38944 37912 40020 41611
1459 30104 30589 37341 33917 39660 31999
1460 36239 28115 38944 37912 40020 37816
1461 33920 32084 38944 37912 40020 39721
1462 26585 21013 39533 34723 40471 40652
1463 32247 34887 37827 35754 40020 27479
1464 37124 23853 39893 38694 41024 37354
1465 32553 21135 40871 39114 41708 30285
1466 36860 28724 39596 38422 40748 40577
1467 35620 29322 39893 38694 41024 34833
1468 35800 24540 39984 38565 41024 40057
1469 37426 27891 39893 38694 41024 38263
1470 38376 19474 40871 39114 41708 35207
1471 22770 19125 39320 31206 40676 30761
1472 34966 28454 38798 32559 40676 23432
1473 30466 17706 38997 30914 40676 39712
1474 18472 24135 38896 31763 40676 26656
1475 33431 26642 38798 32559 40676 20664
1476 39360 19110 39016 30740 40322 40779
1477 36647 26859 38341 32322 40676 28945
1478 29727 24759 38894 31218 40155 34749
1479 32090 25575 38894 31218 40155 37414
1480 37042 30605 37978 36351 40020 28794
1481 29865 35112 37170 34776 40020 29049
1482 34262 28402 37441 33513 39242 35768
1483 33825 30716 37170 34776 39074 37628
1484 39047 25459 36735 31777 39430 33883
1485 39522 31313 37483 35314 39437 40093
1486 36581 33943 37170 34776 39567 38266
1487 32287 25866 37978 36351 39767 34656
1488 40442 29015 36941 33311 39977 29612
1489 35316 30004 36199 32604 38968 30180
1490 33446 12164 35506 30275 37860 33305
1491 34281 26812 36223 31245 39024 31720
1492 30346 23647 36199 32604 39041 34313
1493 33050 26680 36199 32604 39464 36285
1494 30333 14768 36231 30267 38434 19560
1495 28260 29313 36243 28995 39074 28854
1496 30418 12925 35699 31278 38492 33305
1497 38937 13216 37327 29872 38047 39590
1498 22117 17991 36645 28648 37791 27903
1499 6870 10980 37913 30890 38861 34904
1500 11074 13646 34879 24629 37235 40821
1501 15548 15585 36568 27260 37596 23722
1502 15233 27989 36276 27024 37502 21889
1503 25424 25811 35840 25970 37282 25552
1504 10391 21850 36445 27513 37623 21073
1505 10988 27857 38883 32133 39613 28174
1506 32942 34170 38034 30437 39993 36741
1507 27735 33388 38150 31847 39325 36167
1508 34234 29496 38572 31629 39915 27442
1509 7420 2954 38904 30558 39964 28976
1510 9057 13339 38883 32133 39613 39930
1511 15292 19399 38800 33843 39537 32430
1512 24618 29594 38358 33068 39325 34702
1513 20245 25394 38856 32973 39544 29124
1514 30561 4133 34646 27082 36628 39946
1515 16530 5379 33318 29198 37881 15017
ah3pubs_rnk ah3tob_rnk ah3ffood_rnk ah3gp_pct ah3dent_pct ah3phar_pct
1 41454 38271 41576 29 0 1
2 41168 36088 41082 49 6 7
3 41513 40430 41543 8 0 0
4 41484 39853 41521 15 1 8
5 31004 40809 36238 18 33 35
6 33932 39982 35215 0 2 12
7 15712 29201 16725 40 51 65
8 39543 41702 41576 3 16 35
9 34215 40042 37228 9 0 0
10 32434 37448 37367 7 29 38
11 32579 35216 39676 0 23 30
12 20932 39725 35872 5 24 16
13 14607 38310 24511 11 50 42
14 17504 34996 28592 25 42 28
15 16034 35456 30415 7 36 29
16 16551 36709 28352 6 39 29
17 18711 37789 30415 5 35 14
18 16536 31345 31849 33 14 17
19 17274 29940 32926 36 22 13
20 12210 37618 34787 19 17 19
21 15973 34733 30673 21 19 13
22 12792 39069 38588 30 37 43
23 16727 35075 30944 19 17 13
24 16100 35441 31378 17 15 26
25 31899 19159 29458 17 13 17
26 24878 16840 26128 26 20 26
27 27608 29887 23935 17 22 49
28 32647 19206 30000 16 24 32
29 33588 33073 30989 4 2 27
30 36105 38251 38208 13 1 3
31 17061 28673 20650 8 62 67
32 12615 23483 15875 18 72 78
33 28559 36015 36753 18 49 63
34 32579 40841 39603 21 32 55
35 16653 15589 18020 37 54 70
36 26725 18733 27626 24 27 35
37 8399 11721 10532 46 79 86
38 12976 24668 21808 36 60 5
39 25139 17536 34886 34 61 10
40 13563 20615 19615 26 72 31
41 13562 23920 23941 35 63 21
42 12756 26029 19675 43 56 20
43 25139 16993 39239 50 65 2
44 15608 17170 28032 32 50 30
45 19803 29644 20151 8 12 53
46 19653 31948 36869 11 31 8
47 25014 34347 39370 4 20 1
48 29017 33520 34893 11 15 10
49 15631 29051 38124 18 44 32
50 27336 25245 30190 46 21 2
51 13950 23041 17096 1 27 19
52 12912 19186 21739 15 42 39
53 17876 24523 18790 20 50 54
54 12742 21431 17709 6 7 1
55 16265 27077 22749 10 26 32
56 22518 29026 26923 13 32 46
57 23099 31952 25433 26 14 44
58 27081 34179 24109 7 35 13
59 17628 28128 31770 12 14 54
60 27745 32011 36038 4 4 7
61 15897 27980 30899 10 27 46
62 24460 29475 31852 10 14 21
63 20941 26213 20954 40 43 35
64 25512 28116 24911 38 31 18
65 31568 38976 33877 23 22 49
66 23642 29143 23106 7 38 39
67 38480 34855 39194 30 2 10
68 17920 25858 18497 19 56 49
69 37241 22051 36177 11 66 9
70 39326 25932 31292 3 61 26
71 33423 25192 27226 0 63 35
72 22574 23496 20231 10 48 39
73 35803 22145 31817 5 61 18
74 22020 30613 32193 28 38 14
75 32238 25872 39734 9 28 26
76 17283 37918 24446 12 44 42
77 22119 28620 28352 32 44 33
78 31727 26800 29255 26 30 42
79 36206 25150 36588 4 10 15
80 25555 29436 37391 23 34 4
81 31881 34938 37070 3 5 20
82 37431 32579 39848 17 1 7
83 31881 33086 36848 12 11 15
84 39884 24504 29779 36 25 24
85 31797 24661 35400 8 8 59
86 21276 20587 23687 4 35 76
87 20412 20245 22783 1 37 76
88 27586 12578 35325 31 34 44
89 10188 12173 14542 72 73 59
90 35903 14982 37937 2 4 5
91 17248 10964 30086 56 58 60
92 9418 10964 14814 84 68 78
93 23964 12621 15907 72 79 70
94 20778 29191 32237 19 18 20
95 19120 26587 39857 28 13 1
96 26436 27473 31703 7 30 37
97 37512 30165 36960 4 31 34
98 34128 36279 35268 10 1 16
99 25483 26741 38156 18 30 9
100 12561 29368 27512 59 47 67
101 19571 32942 37095 53 34 48
102 36075 32029 38430 16 9 7
103 25152 25357 37407 4 33 9
104 14959 33234 25628 66 35 56
105 21809 40212 34093 52 9 13
106 22567 30008 27078 19 46 54
107 32251 29821 28062 28 20 31
108 28930 37971 32369 36 42 18
109 37587 37964 38487 28 6 3
110 34168 41481 40755 31 6 5
111 33988 40654 35662 24 31 9
112 25115 35699 23921 19 8 45
113 28567 30530 26659 42 16 40
114 27971 22417 28481 51 57 28
115 25176 24856 26054 38 45 41
116 29611 40275 28648 54 8 26
117 31541 38153 29612 44 8 29
118 15709 21267 16689 32 70 76
119 22931 32248 22027 69 37 51
120 23691 27811 25026 64 60 57
121 23850 34155 35538 50 36 43
122 22005 35549 28430 15 16 28
123 15348 27121 26697 43 42 70
124 23019 34363 30397 2 5 28
125 29382 37789 30107 16 24 27
126 38490 40257 36493 13 15 8
127 21535 33412 25977 10 13 48
128 28328 33282 33622 31 35 12
129 18650 31287 34729 15 2 8
130 19861 32205 33362 16 18 38
131 20557 32722 25073 28 5 38
132 26627 33917 26087 13 16 22
133 31784 33388 29715 33 18 23
134 18700 26299 32129 22 1 4
135 17120 25701 19069 18 50 43
136 21488 28511 30768 7 24 15
137 19795 27038 35273 21 1 1
138 40349 34588 38634 11 9 7
139 27187 31756 32519 16 30 17
140 28566 32468 33715 17 26 20
141 39342 41431 32994 3 0 2
142 29998 38069 24226 6 22 17
143 40452 39892 40598 6 0 0
144 33504 23595 31257 2 5 7
145 36295 28884 32115 7 12 20
146 28869 19990 24654 32 26 23
147 28399 24351 21488 65 56 47
148 32799 26519 18388 63 62 71
149 25977 26519 23599 61 63 77
150 35380 20411 22812 64 39 11
151 30064 24286 25494 44 22 33
152 35692 19518 39485 3 1 8
153 31065 20819 34578 5 7 26
154 22464 33356 36343 28 40 44
155 24958 33716 30378 30 38 45
156 14097 29404 30777 56 50 56
157 24655 38890 37219 7 14 18
158 34578 41411 40517 9 0 2
159 23869 21598 26793 18 21 48
160 27238 22556 33285 8 10 22
161 17693 34879 22507 37 35 21
162 23235 29668 27842 31 46 58
163 25957 36225 26910 27 40 35
164 17684 26404 32558 21 30 49
165 26511 36497 35010 13 35 33
166 32052 33561 39646 3 15 6
167 34977 36800 37149 3 4 9
168 20953 24187 23133 34 4 43
169 35509 26338 35650 32 21 9
170 39605 26884 39403 29 21 6
171 31082 23724 29981 45 38 32
172 30201 25106 30583 28 39 31
173 38649 21964 38937 3 21 18
174 37132 19018 35179 11 10 16
175 32302 22663 35419 23 34 26
176 37659 18894 32894 23 6 25
177 41336 17829 40497 9 0 0
178 38531 16414 38107 1 4 5
179 37135 21480 37107 15 26 11
180 22470 20889 40573 34 7 63
181 36237 22079 35576 14 20 48
182 18074 27821 39482 22 1 1
183 12696 22824 28937 47 3 7
184 12077 21635 19684 36 35 34
185 15581 21504 15566 68 61 32
186 24878 27150 23619 53 41 42
187 17701 28240 21277 14 24 41
188 26283 35635 35263 4 0 1
189 34874 35086 37140 34 10 2
190 26243 33910 35943 24 16 25
191 10234 18609 18716 61 32 41
192 35325 37526 39362 19 5 10
193 29449 36542 29816 13 12 38
194 18297 27289 22413 19 41 58
195 29738 26958 25348 33 5 57
196 28824 33614 28444 32 26 40
197 18376 29338 24655 12 47 53
198 25669 31893 30848 5 34 21
199 17559 26674 26698 18 53 52
200 39211 35829 37199 31 2 35
201 21337 24562 25030 38 46 46
202 24923 23170 17356 58 55 68
203 29477 28390 30875 25 27 19
204 22354 19132 23616 24 24 44
205 23219 29912 27252 35 28 26
206 35145 21609 37107 11 15 5
207 24765 30367 36393 23 24 6
208 29189 37702 22322 9 18 37
209 23663 26472 26062 39 41 39
210 27164 36612 24208 14 16 48
211 20387 33151 35504 22 9 12
212 34858 37194 26615 9 6 9
213 30023 33179 32952 23 11 5
214 25613 35797 32607 5 3 4
215 17508 30404 27745 29 20 26
216 25245 35618 29532 5 8 11
217 10928 20674 14107 65 68 73
218 15915 26840 16766 11 57 7
219 18970 26515 20411 40 51 45
220 18643 27282 20104 17 52 20
221 21303 29843 32294 39 29 19
222 20633 30400 26729 31 3 26
223 33479 27880 29004 17 15 25
224 16040 23092 23495 62 35 45
225 15142 20030 19682 65 40 44
226 19253 24860 30324 44 6 10
227 20045 25653 34322 48 9 12
228 35207 28652 36017 21 10 8
229 38932 32691 35115 3 5 14
230 35675 36392 36314 11 13 21
231 20015 32304 37181 19 18 14
232 18243 37478 21528 19 17 31
233 29227 37019 28504 24 4 5
234 20546 37485 24703 6 26 25
235 28484 25834 32229 38 37 35
236 17560 22544 21596 56 56 64
237 24462 28771 27408 30 57 40
238 24191 32354 28872 14 45 26
239 34609 36181 40124 1 32 4
240 37312 31527 40920 4 35 4
241 27642 40408 31405 6 9 1
242 19769 26342 22704 30 39 61
243 20562 29188 25188 35 49 58
244 38891 31653 35688 29 3 20
245 33905 23690 23455 50 32 51
246 38827 31612 38457 4 2 9
247 32148 35589 35027 2 14 18
248 23940 31236 28877 9 17 44
249 20111 14069 11450 81 75 76
250 30347 32504 22809 50 22 27
251 14945 18357 18783 77 50 62
252 15880 27737 18479 58 21 61
253 26074 25173 28285 67 33 30
254 32654 36950 33456 10 12 16
255 22905 22142 25638 73 31 27
256 10494 22709 16281 72 24 70
257 33397 26399 19062 55 51 63
258 12144 17595 14662 82 65 76
259 19303 31741 27423 35 25 32
260 33977 39654 38689 3 2 3
261 35255 25172 39857 8 65 25
262 30073 26907 29723 35 51 29
263 20356 26246 23618 34 21 46
264 32747 35071 35396 5 18 19
265 31599 26484 34672 34 43 10
266 28819 33398 30363 17 14 30
267 20594 23658 24142 52 29 43
268 27698 19946 26793 42 34 38
269 32338 20303 34511 28 8 9
270 35387 22993 34603 15 57 15
271 19919 30501 18809 30 27 62
272 15842 28682 17345 64 40 77
273 27984 36205 26386 21 5 33
274 17828 34597 22123 58 52 72
275 21499 13973 13406 78 71 84
276 25518 19880 36375 56 21 49
277 32947 21621 33705 40 37 25
278 23953 22387 35515 43 8 26
279 18067 23963 23921 45 14 70
280 29215 32792 23654 7 7 43
281 18851 19372 17600 55 52 33
282 31425 19626 19686 65 56 12
283 20735 18579 19964 65 60 14
284 21049 23399 25478 10 12 39
285 19631 21401 23410 6 9 56
286 15786 16268 14930 76 71 50
287 17526 18868 17678 45 47 64
288 35170 26102 24866 24 8 38
289 30259 25882 33740 8 10 34
290 33089 24658 37780 43 25 42
291 34466 40206 36070 8 8 13
292 39926 40420 38478 2 2 6
293 23215 32401 33252 6 40 15
294 39679 39687 40561 3 0 9
295 39866 38021 39549 7 0 2
296 32542 36682 31160 31 9 31
297 30201 38902 31274 39 25 51
298 37401 37981 33671 17 3 28
299 25363 38038 29753 36 36 54
300 30292 36471 28350 29 31 48
301 35350 20158 33945 21 12 13
302 36837 24798 30182 24 4 23
303 25709 21382 24059 39 35 43
304 34211 19637 33002 21 22 12
305 31156 28289 22454 47 4 26
306 31325 29040 25763 6 16 22
307 17456 36845 23121 33 23 35
308 23065 18236 20202 43 45 31
309 39064 22664 37607 7 8 6
310 39188 32836 30696 27 2 1
311 35188 38082 33770 29 17 30
312 22269 29590 29349 18 38 50
313 37624 38602 33671 14 1 28
314 34048 33767 36457 12 14 22
315 23240 31953 31188 9 33 28
316 32978 36421 25068 13 11 24
317 35729 37059 27152 3 3 15
318 33487 37731 31758 14 7 14
319 39146 37649 39549 1 1 2
320 32971 38545 31671 34 3 24
321 20061 24899 32608 30 54 5
322 15968 25403 28467 69 62 27
323 33523 30567 35760 9 34 19
324 20194 28343 21371 31 58 67
325 37341 34709 29777 9 39 50
326 39000 36005 38276 18 33 36
327 28477 32530 20931 32 47 65
328 28329 34859 30095 25 27 33
329 35164 37968 36839 3 55 5
330 32879 37727 27730 20 62 30
331 12115 14838 13064 66 78 83
332 37474 30085 40877 50 5 10
333 34148 36758 28399 21 41 26
334 37057 36340 33028 23 27 16
335 31527 24712 31130 15 20 26
336 32299 33585 27530 67 24 32
337 37958 35929 24966 57 17 35
338 28323 33868 24237 47 33 35
339 31806 40372 38073 36 6 6
340 34526 26409 32967 13 12 16
341 26228 30396 23392 23 36 43
342 26524 34189 28753 24 47 40
343 27888 38435 29080 35 28 25
344 31477 21508 30611 58 65 44
345 19504 22144 19011 42 50 61
346 32026 35842 32599 21 48 17
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ah3g ah3e ah3r ah3h_rnk ah3g_rnk ah3e_rnk
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1320 -0.7895579985 1.2942486353 -0.4142980469 5268 4735 38621
1321 0.2070075319 1.2381705331 -0.4399221925 22906 25522 38221
1322 0.1940019408 1.2327794870 0.6935388451 8327 25180 38172
1323 -0.1537291053 1.2403720320 0.6242567547 12287 16294 38248
1324 -0.2966673229 1.1925799308 0.1838151483 10653 13063 37864
1325 -0.5095512798 1.1954687037 0.0578861250 16558 8888 37892
1326 0.3456495748 1.4274203316 0.1136590293 14262 28937 39435
1327 0.3915125065 1.1530123463 0.0183810273 7360 29992 37488
1328 0.0408737378 1.3116713246 -0.0036135224 14772 21169 38749
1329 0.0721283542 1.1815342265 -0.0869013399 10922 22008 37766
1330 0.3012853879 1.1687180367 0.2016960955 20785 27848 37637
1331 0.6819870629 1.2904075704 0.4362655560 12950 35760 38599
1332 1.3114439974 1.4783206313 1.8101800743 235 41283 39709
1333 0.7938190989 1.2904075704 1.5784539733 4829 37467 38599
1334 0.1039532406 1.4449886956 0.7837035993 3246 22829 39515
1335 0.9973455240 1.4102825413 1.3215909669 1929 39722 39349
1336 0.8435536631 1.5145694700 1.0939160298 1177 38096 39870
1337 0.8021353237 1.4783206313 1.3738286710 455 37586 39709
1338 1.0819372911 1.5658886509 0.5617106346 3754 40360 40151
1339 1.3103126657 1.6261398765 0.3149321980 6437 41281 40399
1340 0.6738578576 1.4850271377 1.0175606236 1443 35613 39743
1341 0.8590476867 1.3563762469 0.8899322320 716 38304 39050
1342 1.1042565147 1.3673456329 1.1366907640 984 40502 39108
1343 1.0153750701 1.4433971508 0.4042497675 4580 39867 39510
1344 0.5202450993 1.4850271377 0.7663762610 5571 32741 39743
1345 0.5090943233 1.3120770159 0.3225490177 8896 32538 38752
1346 0.7718656497 1.4938885688 0.4753991895 6923 37171 39779
1347 0.5558044621 1.6430684312 0.2921718397 12935 33420 40454
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1350 -0.1990837621 1.4407227895 0.8743606872 1730 15212 39496
1351 0.2465447400 1.7131862468 0.1283852708 17874 26506 40668
1352 0.2579964606 1.5672248765 0.6303286167 8674 26770 40159
1353 -0.0634863051 1.4407227895 0.6185223601 8207 18460 39496
1354 0.7098469106 1.4607442585 0.9100950752 1251 36242 39593
1355 0.6552218395 1.5890769921 0.9266310862 4407 35293 40253
1356 0.5504923398 1.5338498974 0.3065830264 1108 33316 39985
1357 0.6631803680 1.5890769921 0.7363921901 1884 35416 40253
1358 -0.1827524869 1.5343622109 0.8047980335 5065 15559 39990
1359 0.7034378122 1.5338498974 0.8223416150 2546 36146 39985
1360 0.7595291800 1.6261398765 0.8190238857 6606 36999 40399
1361 1.6715810175 1.4866772693 0.8441304624 2155 41672 39751
1362 0.2580055229 1.2700342336 1.0497521789 3930 26771 38450
1363 0.3818275139 1.1716288426 1.1033225735 1987 29776 37669
1364 0.4344845377 1.1716288426 1.1891285884 834 30958 37669
1365 0.2561161538 1.2507663611 1.2661240624 2920 26724 38327
1366 0.4291777635 1.3733255952 1.1837591591 7733 30839 39146
1367 -0.1899310056 1.3131616582 1.2776737937 700 15398 38763
1368 0.6260706312 1.2498577190 1.5567952621 145 34757 38319
1369 0.4745851369 1.1716288426 1.4459491478 425 31804 37669
1370 0.6500421144 1.2535579601 0.6202926074 4420 35180 38344
1371 0.3968881635 1.2022478074 1.1427299522 5757 30133 37949
1372 0.5833811912 1.2988238640 0.4676761495 6295 33967 38654
1373 0.6664874065 1.2022478074 0.7293968375 5478 35463 37949
1374 0.8800623947 1.2899215281 0.9674444945 6940 38546 38596
1375 0.2898156523 1.3267891944 0.2638294799 17921 27566 38860
1376 0.6618074134 1.2640745514 1.5151037961 2356 35402 38412
1377 0.5239300457 1.3697755008 0.3311169880 20629 32802 39122
1378 -0.4949175302 1.1498727787 0.7337981590 5140 9119 37465
1379 0.5022910586 1.0912353698 1.1752728965 6526 32404 36955
1380 0.1256133711 1.0241774303 0.9774951479 4389 23382 36370
1381 0.4447957193 1.1690880496 0.6985404631 4984 31177 37643
1382 0.1875659711 0.9407083185 1.5380460400 2816 25003 35594
1383 0.4479625371 1.1974878539 0.7934797726 7866 31233 37911
1384 0.4107126560 1.3765522199 0.1173051320 18056 30421 39158
1385 -0.7022787712 0.9453091141 0.4196740790 11694 5782 35645
1386 0.2096987735 1.1652458569 0.9790048727 3980 25592 37614
1387 -0.5140499778 0.7583231617 0.0303906906 21588 8814 33623
1388 0.1468599466 0.6459690321 1.0310963087 13609 23925 32152
1389 -0.0913696608 0.9508598659 0.3270731794 16329 17795 35699
1390 -0.2672184932 0.9508598659 0.0774831929 21134 13709 35699
1391 0.3319540997 0.7337780382 1.1915042901 11782 28609 33298
1392 -0.7394853731 0.5918676623 -0.6469076477 36900 5320 31391
1393 -0.9421785606 0.6717371747 0.3878638351 21231 3196 32502
1394 -0.4030085087 0.6108214338 0.4261707113 23245 10832 31671
1395 0.2474171784 0.6687939488 0.7546684624 5302 26526 32465
1396 -0.1468664815 0.8218838407 0.1905104348 23755 16462 34294
1397 -0.9347369927 0.5265688744 -0.7280107439 35023 3253 30363
1398 0.0329815218 0.7073512233 0.4091657257 4412 20984 32956
1399 -0.0085991394 0.7354841919 0.3630413153 10893 19886 33324
1400 -0.0547056655 0.8154233729 0.0707863963 10246 18696 34225
1401 0.0146763525 0.8534239676 0.2282106559 7456 20483 34647
1402 -0.7986748361 0.4715555454 -0.7615984685 32136 4638 29468
1403 0.2540169132 2.1042287341 0.5164823049 7705 26689 41412
1404 0.3416282005 2.1042287341 0.8557160970 6968 28849 41412
1405 -0.1785700326 2.0075513535 0.7426976318 7646 15671 41314
1406 0.2743774822 2.2006053581 0.4217977166 7028 27204 41475
1407 1.0051598277 1.9364645867 -0.2177533593 25212 39790 41181
1408 -0.6027228449 2.1042287341 0.6536060177 11954 7305 41412
1409 0.9435053002 2.2834679089 0.7282621134 622 39234 41518
1410 -0.0091705554 2.2834679089 0.7617012828 3865 19865 41518
1411 0.2772115791 2.1178973615 0.2512879194 10875 27269 41428
1412 0.5657878799 2.2834679089 0.4474233232 6742 33621 41518
1413 0.2907117952 1.0939777996 0.3952969799 20531 27589 36982
1414 0.5454592757 1.1048802254 0.4444323901 17582 33219 37076
1415 0.5169115591 1.0586775363 0.6906514052 8042 32672 36667
1416 0.7187764139 1.2162721361 0.4968764108 15441 36389 38058
1417 1.0420172914 1.0939741548 -0.2971942368 33417 40091 36981
1418 0.3264967158 1.1631235428 0.3368670018 26097 28470 37595
1419 0.8748690019 1.1548607382 1.4218114561 3800 38487 37500
1420 0.6143233041 1.1421829735 1.3631174467 5009 34534 37398
1421 0.7518284696 1.0817681680 1.3657691997 2593 36897 36881
1422 0.6146532791 1.0399587034 1.8834019492 2086 34545 36505
1423 0.6353949475 0.9887213128 0.4396163825 13850 34909 36071
1424 -0.3219667260 1.1727981926 -0.2839533259 31149 12492 37684
1425 0.7607537344 1.0388098823 0.8298761215 3409 37011 36494
1426 0.6471770967 1.0807391144 0.8791092841 14234 35127 36872
1427 0.9237692247 1.0853905645 0.9880887561 10656 39042 36909
1428 0.0734888888 1.1328942188 0.1610700515 31031 22045 37331
1429 -0.4167074159 0.9453091141 1.3525264332 4235 10543 35645
1430 -1.2496552205 0.8403211893 0.5023372948 11134 1208 34500
1431 -0.7165032430 0.7870580334 0.5442499774 13346 5615 33937
1432 -0.4914671877 0.8628819199 0.2705290069 20633 9173 34747
1433 -0.2922397415 0.7831909826 0.7487207944 14988 13163 33899
1434 -0.3988233998 0.9686057449 1.0030677138 2704 10918 35871
1435 -0.1436509725 0.8639368945 2.1424783123 2411 16544 34757
1436 -0.5902824426 0.6986926278 0.7389122605 8422 7522 32839
1437 0.0290640468 1.5558641100 0.4197530260 12018 20888 40096
1438 0.8622846020 1.3592609322 0.5394591468 12301 38345 39074
1439 0.5882379376 1.8197257014 0.7899961614 2405 34062 40947
1440 -0.0351728168 1.5431479063 0.1861104877 14282 19191 40030
1441 0.5606675637 1.6465554079 0.4201904497 7273 33522 40458
1442 0.3352211728 1.5683398070 0.3745543613 8569 28694 40182
1443 -0.6048675928 1.9489580206 0.4961564231 14030 7266 41200
1444 0.1971723301 1.6109938857 0.4767196478 4994 25269 40342
1445 -0.3119980274 1.8477183223 0.5266097341 9929 12706 41010
1446 0.1104229754 1.6684112074 0.5584058808 9725 23001 40529
1447 0.2573755064 0.4971041156 -0.1396798280 18125 26755 29897
1448 -0.1051050489 0.6621880964 -0.0798501049 20661 17449 32390
1449 -0.5552227502 0.5341345603 0.1858394813 11114 8097 30511
1450 -0.4377544191 0.6030102384 0.1153375143 8296 10138 31556
1451 -0.5330844595 0.6802611639 0.7866363691 5839 8483 32626
1452 -1.4215825251 0.7338428596 0.1381111949 14833 665 33299
1453 -0.4603515884 0.6549424344 0.2644059048 10091 9732 32293
1454 -0.7808065068 0.7659080957 0.2031327766 21459 4833 33715
1455 0.8189526402 1.4207551594 0.8314473634 3841 37807 39407
1456 0.4745517581 1.1895498338 0.4529148488 10277 31803 37834
1457 0.5058705253 1.3750080897 0.0741728649 17377 32474 39152
1458 0.9764912529 1.5238929564 1.0694864341 682 39546 39928
1459 0.6045073273 1.2632139534 0.3427059541 16919 34371 38405
1460 0.7846202422 1.5238929564 0.3128966811 13929 37336 39928
1461 0.8117661548 1.5238929564 0.4766476403 6978 37709 39928
1462 0.1797707219 1.4869149752 0.2595450456 17875 24813 39752
1463 0.8631097904 1.3750080897 0.0957964330 16311 38354 39152
1464 0.7025204074 1.7612949995 0.6425488996 2186 36132 40833
1465 0.3943633384 2.2856000494 0.4372419650 10665 30059 41525
1466 0.8414069864 1.6766668207 0.7759603828 1668 38065 40559
1467 0.7920201095 1.7612949995 0.5163124992 8322 37441 40833
1468 0.6467654761 1.7619301912 0.2820596736 12160 35117 40838
1469 0.8496702925 1.7612949995 0.6694612452 4434 38172 40833
1470 0.6594875409 2.2856000494 0.3393972574 10874 35356 41525
1471 0.0049856377 1.3991369084 0.5944103881 8209 20235 39291
1472 0.7294281768 1.4008954111 0.2516643534 15656 36569 39299
1473 0.2110711555 1.3706471953 1.4944501882 2574 25621 39125
1474 0.0267312673 1.3858027701 0.4506971126 10669 20810 39217
1475 0.5999857020 1.4008954111 0.0680252510 19847 34270 39299
1476 0.7383741083 1.3251778435 2.0476004371 784 36731 38848
1477 0.7671275788 1.3689120722 0.5084922944 15697 37108 39116
1478 0.3982034868 1.3124654353 0.9277475473 8778 30164 38757
1479 0.5111798650 1.3124654353 1.1805473729 4100 32571 38757
1480 0.9186905430 1.4041954708 0.3006081397 10131 39001 39322
1481 0.7851737001 1.3125248911 0.2513875790 13085 37345 38759
1482 0.6943961411 1.2255711608 0.4128134225 5702 35999 38117
1483 0.7556486330 1.2409800485 0.8449645894 1423 36944 38253
1484 0.8996657499 1.1616379013 0.1161590971 12322 38766 37580
1485 1.1465163729 1.2969445157 1.2865617035 1529 40715 38642
1486 1.0243824066 1.2751441066 1.1394438227 2589 39946 38495
1487 0.5281110057 1.3824576608 0.4023234095 6233 32875 39189
1488 1.1896713794 1.2550053803 0.1488328278 10509 40881 38356
1489 0.8003080095 1.1320066126 0.3095986151 12126 37557 37324
1490 0.1489614523 0.9878421074 0.8122275852 10101 23983 36056
1491 0.6431485518 1.1010465260 0.5634841341 13776 35046 37036
1492 0.3861384576 1.1365892965 0.6982387236 16576 29871 37359
1493 0.5850587128 1.1652458569 0.5945239374 11283 33990 37614
1494 0.1143020093 1.0429259067 0.3238526749 18891 23113 36528
1495 0.4956911714 1.0513171594 0.5503301469 9855 32265 36611
1496 0.0564738367 1.0515998388 0.7440988896 9456 21601 36618
1497 0.5110893554 1.0576579986 1.3936878564 3039 32567 36659
1498 -0.0491139270 0.9886798091 0.3704751559 15966 18833 36069
1499 -0.8047061027 1.1537141820 1.0014204211 10358 4574 37493
1500 -0.5375452119 0.8147851489 0.8119767138 10879 8388 34219
1501 -0.3238498172 0.9459313049 -0.0008553416 22345 12454 35657
1502 0.0484342575 0.9253699556 0.0887373646 18356 21376 35423
1503 0.2894925415 0.8772567040 0.4055342379 7348 27559 34919
1504 -0.3092194047 0.9478960361 -0.0006732794 26249 12775 35669
1505 -0.1000039105 1.2886920407 0.6561590145 8928 17571 38587
1506 0.8576789431 1.2309637330 1.2501131243 12045 38291 38158
1507 0.6335660773 1.2196055861 1.3844349275 9132 34875 38078
1508 0.7304812268 1.2820617011 0.3998748551 4578 36588 38532
1509 -1.1968971739 1.2790994519 0.5337839580 15571 1424 38517
1510 -0.6254740057 1.2886920407 1.2477460055 5251 6935 38587
1511 -0.2147259479 1.3255298293 0.8028399353 11164 14860 38852
1512 0.3891918969 1.2632321027 0.9229552971 11619 29936 38406
1513 0.1191238415 1.3045196669 0.4770323069 10281 23223 38695
1514 -0.3335662318 0.8338441834 1.8563106231 1073 12246 34418
1515 -0.6975315517 0.8955667930 -0.0299320410 20010 5836 35099
ah3r_rnk ah3h_pct ah3g_pct ah3e_pct ah3r_pct ah3ahah ah3ahah_rn
1 41111 1 98 100 99 64.76672 41700
2 40437 8 100 100 97 65.80176 41703
3 41376 1 97 100 100 64.26736 41695
4 41260 3 100 100 99 67.73922 41710
5 38120 19 65 100 92 42.07205 40256
6 38715 1 64 100 93 42.41398 40320
7 20297 48 9 100 49 31.54224 36169
8 41630 6 78 100 100 54.35274 41556
9 40626 1 91 100 98 54.39178 41558
10 38980 14 39 100 94 40.04882 39798
11 36495 3 64 100 88 39.75039 39720
12 35102 15 83 98 85 39.72754 39713
13 27284 24 64 98 66 32.45936 36704
14 28020 33 71 98 68 34.63505 37851
15 29430 16 77 98 71 34.25933 37685
16 28913 15 76 98 70 33.95019 37536
17 31127 14 69 98 75 34.43643 37757
18 30173 14 17 97 73 26.23945 31538
19 30652 12 43 97 74 28.50593 33834
20 32103 13 54 97 77 30.45828 35411
21 30533 7 55 97 74 29.37231 34607
22 33509 35 36 97 81 31.17331 35922
23 32659 8 66 97 79 32.25683 36598
24 31292 16 76 97 75 33.68321 37388
25 23156 20 58 88 56 22.19611 25545
26 18849 28 49 94 46 23.88855 28384
27 26997 28 92 95 65 36.43948 38612
28 24003 27 45 95 58 25.06813 30126
29 32836 6 90 94 79 35.71361 38344
30 38747 7 92 96 93 44.49510 40661
31 22968 40 57 97 56 29.09044 34350
32 16688 58 48 94 40 26.34685 31642
33 37275 28 85 97 90 42.39206 40314
34 39769 23 83 98 96 45.92046 40897
35 16430 50 55 92 40 24.55348 29345
36 27055 29 52 92 65 25.34186 30481
37 9079 72 23 96 22 26.13970 31435
38 28665 31 58 100 69 36.78816 38736
39 31758 29 30 99 77 32.91338 36951
40 21831 33 10 99 53 27.92678 33226
41 25377 40 42 99 61 31.87489 36371
42 24543 40 80 100 59 39.47892 39631
43 35628 31 38 98 86 34.49293 37788
44 24039 29 50 98 58 28.97912 34244
45 23887 15 53 100 58 33.04148 37035
46 34804 15 57 100 84 39.40648 39610
47 38421 6 78 100 93 45.78751 40877
48 35803 10 95 100 86 50.06662 41315
49 31169 30 65 100 75 39.34973 39596
50 29323 13 87 98 71 36.99764 38811
51 23478 9 52 97 57 26.55450 31891
52 20806 22 60 97 50 27.96611 33271
53 21215 37 72 97 51 30.94367 35783
54 27997 2 44 97 68 27.16403 32459
55 25442 17 55 98 61 30.22018 35241
56 28501 28 74 96 69 32.46576 36711
57 29158 20 53 96 70 28.60833 33937
58 30139 11 69 94 73 29.35484 34588
59 31734 17 71 97 77 33.39030 37216
60 35904 3 61 97 87 33.97358 37546
61 27847 23 80 97 67 34.15507 37638
62 32375 8 75 97 78 34.27820 37695
63 25640 40 15 99 62 29.49179 34701
64 30443 32 25 99 73 30.70017 35595
65 36163 23 61 100 87 40.62388 39943
66 28559 19 34 100 69 31.72269 36274
67 39089 12 32 100 94 40.23270 39851
68 24571 32 42 100 59 32.30548 36626
69 36342 17 24 99 88 33.78712 37449
70 35412 12 34 98 85 32.63661 36807
71 30921 7 29 98 75 29.07704 34337
72 24791 18 8 98 60 25.27198 30381
73 33489 15 22 99 81 32.34428 36640
74 32916 18 58 97 79 31.81893 36330
75 35963 19 71 97 87 36.70647 38702
76 28016 19 71 98 68 33.06114 37058
77 30049 29 64 98 73 33.35269 37197
78 30623 28 77 98 74 35.93234 38427
79 36014 8 72 98 87 36.71327 38706
80 35677 11 49 97 86 32.28060 36614
81 37696 11 59 99 91 38.10557 39218
82 39689 10 72 99 96 43.57944 40514
83 36324 16 75 98 88 38.44863 39344
84 37399 24 61 99 90 39.13149 39539
85 33354 25 46 99 80 33.87987 37498
86 22570 39 27 99 55 29.76248 34906
87 21657 35 52 98 52 30.06618 35141
88 29311 42 58 95 71 30.28061 35277
89 11087 75 64 97 27 33.18554 37114
90 35726 6 51 99 86 35.10982 38095
91 19971 66 81 95 48 34.26632 37689
92 10476 78 87 96 26 37.55927 39030
93 16949 77 94 95 41 41.52425 40137
94 31327 13 44 96 76 28.63771 33954
95 36802 9 43 96 89 32.21494 36564
96 30466 18 69 97 74 32.08311 36498
97 36406 12 43 97 88 32.82498 36909
98 37023 5 61 97 89 35.06032 38078
99 35052 14 55 97 84 32.91748 36956
100 22729 50 35 99 55 30.86107 35722
101 30851 46 53 98 74 33.37116 37207
102 37923 13 81 99 91 43.16298 40441
103 31203 12 55 98 75 32.35025 36643
104 25420 38 15 97 61 27.04513 32347
105 36617 25 44 98 88 35.24603 38139
106 26990 33 86 97 65 36.25156 38539
107 29517 27 93 95 71 37.69903 39070
108 33274 31 85 96 80 37.30154 38942
109 38270 12 94 96 92 45.64763 40857
110 41254 14 91 96 99 51.90769 41450
111 37533 17 83 96 90 39.65699 39694
112 29896 20 60 84 72 23.37792 27608
113 30546 28 73 87 74 27.53308 32828
114 28420 33 78 86 69 27.47511 32757
115 26806 38 84 87 65 29.38364 34617
116 35509 16 61 89 86 28.57277 33900
117 35199 19 79 87 85 31.10489 35869
118 16655 59 75 88 40 27.08189 32392
119 26730 48 40 92 65 25.45985 30620
120 25937 55 56 91 63 27.35710 32654
121 31934 31 90 89 77 34.65681 37865
122 29490 21 96 87 71 35.41653 38224
123 21679 45 88 89 52 30.83236 35709
124 31943 8 76 88 77 27.84108 33127
125 34230 19 72 89 83 29.70107 34863
126 40124 12 93 88 97 43.05702 40427
127 28167 17 83 90 68 29.19133 34445
128 32928 23 87 88 79 32.75591 36870
129 33778 10 92 91 81 35.80720 38382
130 30531 19 85 91 74 31.40267 36079
131 28213 20 83 87 68 28.28845 33618
132 31404 13 82 94 76 32.59869 36791
133 34214 19 41 93 82 28.02449 33339
134 30285 4 84 93 73 31.87539 36373
135 20080 26 90 94 49 32.32227 36633
136 27518 7 77 94 66 29.08967 34348
137 32991 2 92 93 80 36.32062 38561
138 39269 9 99 94 95 50.99703 41389
139 30074 11 94 94 73 37.49627 39015
140 31251 18 94 94 75 38.65077 39406
141 40215 1 93 94 97 46.43090 40957
142 32975 6 90 95 80 37.06315 38834
143 41385 1 97 94 100 54.63135 41564
144 32807 5 86 88 79 31.20472 35950
145 34040 11 95 87 82 36.92090 38781
146 27301 15 80 89 66 27.37686 32673
147 22393 53 91 90 54 33.65775 37374
148 24158 64 98 91 58 41.79733 40204
149 23351 65 95 92 56 38.93399 39484
150 23895 32 99 90 58 39.88920 39755
151 25465 22 99 88 62 38.04513 39196
152 36232 8 70 91 87 30.92290 35767
153 31858 16 63 91 77 27.20545 32501
154 31317 35 90 90 76 34.59127 37833
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1215 37977 5 80 96 92 38.63701 39404
1216 33648 31 61 93 81 30.41409 35390
1217 39090 8 63 93 94 34.81000 37955
1218 38676 10 67 94 93 35.86185 38404
1219 34150 22 42 96 82 30.07951 35153
1220 35322 12 88 95 85 38.11347 39221
1221 25915 35 80 95 63 32.22951 36575
1222 34521 7 67 96 83 32.77333 36884
1223 28209 26 96 95 68 40.26987 39859
1224 29831 26 69 95 72 30.99645 35806
1225 33162 7 94 95 80 39.61654 39678
1226 35170 8 88 95 85 38.01925 39186
1227 33791 8 98 95 81 45.13130 40771
1228 26383 32 92 95 64 36.97782 38803
1229 23637 33 100 94 57 44.87789 40736
1230 33374 20 33 91 80 25.09009 30160
1231 40872 1 93 91 98 46.28999 40940
1232 40319 1 67 91 97 36.73382 38715
1233 39822 1 47 92 96 33.20925 37126
1234 41135 3 63 91 99 39.50650 39642
1235 37761 12 51 91 91 30.29204 35289
1236 38009 21 9 92 92 28.37535 33694
1237 34111 10 61 91 82 28.15427 33480
1238 19026 21 44 90 46 20.33600 21916
1239 35158 2 21 89 85 23.70686 28086
1240 36825 4 48 90 89 28.04580 33366
1241 40021 8 22 90 96 31.08445 35860
1242 41340 4 42 91 100 37.98828 39178
1243 28837 22 2 89 70 20.12417 21461
1244 21747 42 9 90 53 19.77286 20725
1245 24924 36 35 90 60 22.27179 25715
1246 21551 64 63 91 52 28.14611 33463
1247 32533 32 46 92 78 27.51724 32808
1248 32940 30 51 90 79 27.06412 32371
1249 29400 38 31 90 71 23.81550 28253
1250 36798 17 49 92 89 30.00585 35099
1251 30635 48 24 91 74 25.71135 30910
1252 33025 35 55 92 80 29.22905 34474
1253 36311 29 51 93 88 31.13660 35895
1254 27442 15 65 94 66 27.26310 32578
1255 20284 25 52 93 49 23.18399 27285
1256 33674 15 42 93 81 27.46980 32750
1257 14115 70 38 97 34 28.63309 33950
1258 25586 47 77 95 62 32.57314 36781
1259 28185 41 57 94 68 29.06320 34324
1260 22009 39 19 94 53 22.48395 26056
1261 23768 46 19 94 57 23.70321 28082
1262 29349 28 4 94 71 23.50352 27793
1263 29696 19 30 90 72 22.45238 26015
1264 34167 9 20 90 82 23.85435 28327
1265 31284 17 21 90 75 22.65552 26362
1266 32794 15 33 90 79 24.07877 28647
1267 24176 33 38 91 58 22.64765 26346
1268 24339 34 11 91 59 20.72205 22745
1269 27984 11 48 91 68 23.33851 27553
1270 26025 20 60 91 63 24.65757 29516
1271 32385 8 13 91 78 22.43135 25972
1272 34379 18 59 91 83 28.38607 33706
1273 35422 11 55 91 85 28.47311 33799
1274 32577 18 60 91 79 27.60633 32899
1275 25568 20 44 91 62 22.61024 26278
1276 26439 15 61 91 64 24.73939 29651
1277 26021 7 62 92 63 24.54535 29331
1278 28534 6 43 93 69 24.22691 28867
1279 31588 3 62 93 76 27.76804 33055
1280 33993 19 23 91 82 24.68843 29569
1281 40388 4 70 93 97 39.02996 39506
1282 40915 1 57 95 99 40.02933 39790
1283 39765 7 58 92 96 34.84550 37980
1284 38787 10 77 94 93 37.66207 39056
1285 37777 6 69 93 91 33.41807 37235
1286 33013 6 42 91 80 24.77633 29703
1287 36560 15 61 92 88 31.25146 35980
1288 36263 17 18 92 87 26.51346 31837
1289 27163 31 65 91 66 26.51664 31841
1290 27383 39 58 88 66 25.05413 30105
1291 25175 32 45 89 61 22.39399 25911
1292 25666 48 72 88 62 27.52059 32813
1293 39250 11 49 92 95 32.94745 36977
1294 27035 28 63 88 65 24.80242 29733
1295 34288 27 15 90 83 24.75347 29665
1296 25538 24 55 91 62 24.01833 28564
1297 22556 28 32 89 55 20.22981 21688
1298 19589 12 41 89 47 18.89629 18793
1299 19084 22 42 89 46 19.75316 20683
1300 25123 28 41 89 61 22.09830 25391
1301 16482 48 40 87 40 20.31206 21870
1302 24435 26 63 89 59 24.09499 28665
1303 26190 15 17 91 63 20.19705 21604
1304 37020 5 32 89 89 26.32857 31623
1305 14783 60 74 90 36 27.35387 32652
1306 12365 47 23 86 30 17.80022 16325
1307 10912 65 70 87 27 25.21802 30316
1308 14351 17 53 86 35 18.40835 17708
1309 15670 26 61 88 38 21.14911 23623
1310 13217 20 37 87 32 16.78875 13848
1311 14535 39 71 88 35 23.50199 27790
1312 16250 16 33 86 39 16.69607 13621
1313 17141 24 22 90 42 18.19243 17209
1314 25357 9 57 94 61 24.86005 29814
1315 18393 8 22 95 45 20.68349 22670
1316 22905 31 12 95 55 22.48155 26054
1317 25197 15 31 96 61 24.15164 28763
1318 18578 39 26 92 45 21.01281 23347
1319 16875 37 90 93 41 32.07684 36496
1320 12679 13 12 93 31 17.57537 15746
1321 12278 55 62 92 30 25.26253 30373
1322 32767 20 61 92 79 28.45692 33775
1323 31782 30 40 92 77 26.30408 31591
1324 24084 26 32 91 58 21.63789 24568
1325 21587 40 22 91 52 21.35532 24030
1326 22699 35 70 95 55 28.95148 34214
1327 20793 18 72 90 50 24.62326 29468
1328 20360 36 51 93 49 24.52565 29297
1329 18736 27 53 91 45 22.18083 25519
1330 24459 50 67 91 59 27.74645 33035
1331 28662 32 86 93 69 33.41337 37230
1332 40848 1 99 96 98 57.19284 41620
1333 40157 12 90 93 97 44.45077 40655
1334 33972 8 55 95 82 29.97246 35076
1335 38812 5 96 95 94 46.14638 40923
1336 37155 3 92 96 90 42.08654 40262
1337 39179 2 91 96 94 43.84385 40564
1338 30846 9 97 97 74 43.04199 40422
1339 26574 16 99 97 64 46.11297 40918
1340 36443 4 86 96 88 38.39844 39329
1341 35173 2 92 94 85 38.74819 39435
1342 37487 3 98 94 90 45.79139 40878
1343 28150 11 96 95 68 39.11623 39534
1344 33734 14 79 96 81 34.75695 37923
1345 26713 22 78 93 65 29.83363 34970
1346 29351 17 90 96 71 36.26595 38542
1347 26175 31 81 97 63 34.71902 37901
1348 35602 5 87 96 86 38.15887 39233
1349 29904 28 81 97 72 34.99084 38049
1350 35003 5 37 95 84 28.57574 33902
1351 22979 43 64 98 56 32.13834 36523
1352 31875 21 65 97 77 32.36823 36651
1353 31707 20 45 95 76 28.16251 33494
1354 35379 3 87 95 85 37.64736 39051
1355 35565 11 85 97 86 39.04858 39510
1356 26427 3 80 96 64 31.47804 36121
1357 33340 5 85 97 80 37.13340 38875
1358 34212 13 38 96 82 29.67488 34840
1359 34394 7 87 96 83 37.88167 39137
1360 34358 16 89 97 83 40.48303 39911
1361 34655 6 100 96 84 50.78608 41371
1362 36749 10 65 93 89 31.84162 36342
1363 37225 5 72 91 90 32.24588 36587
1364 37893 2 75 91 91 33.47049 37267
1365 38454 7 65 92 93 33.61386 37346
1366 37853 19 74 94 91 36.62786 38673
1367 38534 2 37 93 93 30.94675 35785
1368 40080 1 84 92 97 40.57583 39933
1369 39569 2 77 91 95 36.63176 38675
1370 31735 11 85 92 77 32.54044 36759
1371 37524 14 73 91 90 33.68884 37390
1372 29215 16 82 93 71 31.16476 35913
1373 33243 14 85 91 80 33.27475 37161
1374 35971 17 93 93 87 39.97065 39773
1375 25701 43 67 94 62 29.09103 34352
1376 39900 6 85 93 96 41.08524 40040
1377 26864 50 79 94 65 33.17586 37109
1378 33309 13 22 90 80 23.55561 27876
1379 37789 16 78 89 91 34.14266 37633
1380 36065 11 57 88 87 27.60683 32901
1381 32850 12 75 91 79 29.75409 34901
1382 40011 7 60 86 96 32.97941 36998
1383 34080 19 75 91 82 31.39231 36070
1384 22769 44 73 94 55 29.95205 35060
1385 28394 29 14 86 69 19.76276 20702
1386 36085 10 62 91 87 29.63896 34819
1387 21032 52 22 81 51 18.53201 17976
1388 36576 33 58 78 88 26.77267 32099
1389 26793 40 43 86 65 22.42291 25957
1390 21979 51 33 86 53 21.15623 23637
1391 37913 29 69 80 91 30.33979 35327
1392 9398 89 13 76 23 21.87907 24978
1393 27872 51 8 78 67 19.07504 19201
1394 28494 56 26 76 69 20.68814 22684
1395 33578 13 64 78 81 23.93875 28463
1396 24232 57 40 83 59 22.06323 25308
1397 8447 84 8 73 21 19.16126 19376
1398 28237 11 51 79 68 19.61078 20363
1399 27420 27 48 80 66 20.30752 21851
1400 21843 25 45 83 53 18.66958 18266
1401 24994 18 50 84 60 19.91514 21028
1402 8082 78 12 71 20 16.96410 14251
1403 30091 19 64 100 73 36.41825 38601
1404 34808 17 70 100 84 39.96982 39772
1405 33416 19 38 100 81 34.54853 37817
1406 28429 17 66 100 69 36.20014 38510
1407 16154 61 96 99 39 45.28653 40799
1408 32221 29 18 100 78 33.63061 37357
1409 33228 2 95 100 80 47.20620 41040
1410 33669 10 48 100 81 36.47635 38628
1411 25445 27 66 100 61 35.43944 38242
1412 28859 17 81 100 70 39.84198 39738
1413 27989 50 67 89 68 28.08676 33403
1414 28803 43 80 89 70 30.57555 35506
1415 32726 20 79 88 79 29.90356 35024
1416 29774 38 88 92 72 34.20817 37655
1417 14734 81 97 89 36 40.43095 39900
1418 26967 63 69 91 65 30.45293 35410
1419 39438 10 93 90 95 42.48194 40335
1420 39106 13 83 90 94 37.79900 39112
1421 39125 7 89 89 94 38.98709 39496
1422 41034 5 83 88 99 41.79460 40202
1423 28717 34 84 87 69 29.90120 35022
1424 14949 75 30 91 36 24.96298 29982
1425 34468 9 89 88 83 33.61348 37345
1426 35055 35 85 89 85 34.56979 37828
1427 36168 26 94 89 87 39.44270 39620
1428 23646 75 53 90 57 28.90317 34164
1429 39029 11 26 86 94 27.66578 32958
1430 29854 27 3 83 72 18.70250 18344
1431 30554 32 14 82 74 19.71045 20583
1432 25816 50 22 84 62 20.60171 22489
1433 33501 36 32 82 81 23.01084 27002
1434 36309 7 27 86 88 24.20757 28837
1435 41438 6 40 84 100 35.66819 38321
1436 33372 21 19 79 80 19.98365 21165
1437 28395 29 51 97 69 29.29353 34534
1438 30474 30 92 94 74 37.81013 39114
1439 34046 6 82 99 82 39.06165 39512
1440 24130 35 46 96 58 27.58956 32879
1441 28401 18 81 97 69 34.63926 37854
1442 27631 21 69 97 67 31.20723 35953
1443 29766 34 18 99 72 31.51389 36144
1444 29380 12 61 97 71 30.52291 35464
1445 30259 24 31 99 73 31.00142 35810
1446 30791 24 56 98 74 31.83446 36335
1447 17661 44 65 72 43 19.15338 19356
1448 18887 50 42 78 46 18.67713 18283
1449 24121 27 20 74 58 15.19156 10086
1450 22734 20 25 76 55 15.15935 10018
1451 33995 14 21 79 82 20.01086 21228
1452 23179 36 2 80 56 16.05531 12136
1453 25710 25 24 78 62 16.75878 13771
1454 24496 52 12 81 59 18.93488 18873
1455 34494 10 91 95 83 38.66917 39414
1456 28938 25 77 91 70 29.21406 34464
1457 21904 42 78 94 53 30.62598 35541
1458 36912 2 95 96 89 44.34111 40643
1459 27065 41 83 93 65 32.20496 36559
1460 26542 34 90 96 64 36.94783 38798
1461 29378 17 91 96 71 37.28109 38933
1462 25627 43 60 96 62 29.80829 34946
1463 22385 40 92 94 54 35.78938 38371
1464 32059 6 87 98 77 38.98296 39495
1465 28684 26 73 100 69 38.51149 39362
1466 33870 4 92 98 82 41.20354 40063
1467 30088 20 90 98 73 40.30156 39866
1468 26020 30 85 98 63 37.09828 38852
1469 32435 11 92 98 78 41.85066 40218
1470 27014 27 85 100 65 41.15172 40057
1471 31347 20 49 95 76 28.00648 33317
1472 25455 38 88 95 61 34.73036 37907
1473 39804 7 62 94 96 36.97329 38802
1474 28904 26 50 94 70 27.28859 32601
1475 21787 48 83 95 53 32.63472 36805
1476 41315 2 89 94 100 47.99252 41123
1477 29953 38 89 94 72 36.75584 38725
1478 35577 22 73 93 86 33.41403 37233
1479 37838 10 79 93 91 36.30400 38558
1480 26322 25 94 95 64 37.18836 38896
1481 25449 32 90 93 61 34.08004 37603
1482 28304 14 87 92 68 31.50072 36136
1483 34671 4 89 92 84 35.49142 38258
1484 22746 30 93 91 55 33.36735 37206
1485 38594 4 98 93 93 47.32575 41055
1486 37504 7 96 93 90 43.45488 40495
1487 28107 15 79 94 68 30.89570 35751
1488 23408 26 98 92 57 39.57240 39666
1489 26499 30 91 90 64 32.54972 36765
1490 34294 25 58 87 83 26.99198 32302
1491 30874 34 84 89 74 31.96243 36431
1492 32844 40 72 90 79 30.90933 35756
1493 31350 28 82 91 76 31.61362 36207
1494 26738 46 56 88 65 25.18328 30271
1495 30655 24 78 88 74 28.79207 34076
1496 33436 23 52 88 81 26.13147 31428
1497 39290 8 79 88 95 35.73374 38353
1498 27553 39 46 87 67 23.21450 27323
1499 36292 25 11 90 87 26.04689 31335
1500 34289 27 21 83 83 22.09601 25381
1501 20420 54 30 86 49 20.78606 22876
1502 22228 44 52 85 54 22.07787 25342
1503 28174 18 67 84 68 23.53275 27840
1504 20424 63 31 86 49 22.11329 25413
1505 32258 22 43 93 78 26.75586 32083
1506 38346 29 92 92 92 42.55909 40345
1507 39240 22 84 92 95 39.84381 39739
1508 28070 11 88 93 68 32.40221 36666
1509 30393 38 4 93 73 24.05146 28602
1510 38330 13 17 93 92 29.45302 34662
1511 34194 27 36 94 82 28.21970 33541
1512 35527 28 72 93 86 33.22691 37130
1513 29388 25 56 93 71 27.21011 32504
1514 40969 3 30 83 99 31.78051 36315
1515 19879 48 14 85 48 18.39062 17655
ah3ahah_pc LSOA LANAME Rank SOA_pct SOA_decile LA_Rank
1 100 E01000001 City of London 29199 89 9 208
2 100 E01000002 City of London 30379 92 10 208
3 100 E01000003 City of London 14915 45 5 208
4 100 E01000005 City of London 8678 26 3 208
5 97 E01000006 Barking and Dagenham 14486 44 5 5
6 97 E01000007 Barking and Dagenham 7256 22 3 5
7 87 E01000008 Barking and Dagenham 5010 15 2 5
8 100 E01000009 Barking and Dagenham 6736 21 3 5
9 100 E01000010 Barking and Dagenham 6900 21 3 5
10 96 E01000011 Barking and Dagenham 7698 23 3 5
11 96 E01000012 Barking and Dagenham 5990 18 2 5
12 96 E01000013 Barking and Dagenham 4573 14 2 5
13 88 E01000014 Barking and Dagenham 5650 17 2 5
14 91 E01000015 Barking and Dagenham 6405 20 2 5
15 91 E01000016 Barking and Dagenham 6739 21 3 5
16 90 E01000017 Barking and Dagenham 4570 14 2 5
17 91 E01000018 Barking and Dagenham 6504 20 2 5
18 76 E01000019 Barking and Dagenham 6410 20 2 5
19 82 E01000020 Barking and Dagenham 5520 17 2 5
20 85 E01000021 Barking and Dagenham 4611 14 2 5
21 83 E01000022 Barking and Dagenham 6098 19 2 5
22 87 E01000023 Barking and Dagenham 5243 16 2 5
23 88 E01000024 Barking and Dagenham 8333 25 3 5
24 90 E01000025 Barking and Dagenham 5303 16 2 5
25 62 E01000027 Barking and Dagenham 5097 16 2 5
26 69 E01000028 Barking and Dagenham 4240 13 2 5
27 93 E01000029 Barking and Dagenham 12389 38 4 5
28 73 E01000030 Barking and Dagenham 4760 14 2 5
29 92 E01000031 Barking and Dagenham 12267 37 4 5
30 98 E01000032 Barking and Dagenham 8037 24 3 5
31 83 E01000033 Barking and Dagenham 4879 15 2 5
32 76 E01000034 Barking and Dagenham 5575 17 2 5
33 97 E01000035 Barking and Dagenham 10070 31 4 5
34 99 E01000036 Barking and Dagenham 15028 46 5 5
35 71 E01000037 Barking and Dagenham 16128 49 5 5
36 74 E01000038 Barking and Dagenham 14671 45 5 5
37 76 E01000039 Barking and Dagenham 12542 38 4 5
38 93 E01000040 Barking and Dagenham 6028 18 2 5
39 89 E01000041 Barking and Dagenham 6601 20 3 5
40 80 E01000042 Barking and Dagenham 3842 12 2 5
41 88 E01000043 Barking and Dagenham 8992 27 3 5
42 95 E01000044 Barking and Dagenham 8825 27 3 5
43 91 E01000045 Barking and Dagenham 5639 17 2 5
44 83 E01000046 Barking and Dagenham 8138 25 3 5
45 89 E01000048 Barking and Dagenham 3117 9 1 5
46 95 E01000049 Barking and Dagenham 3928 12 2 5
47 98 E01000050 Barking and Dagenham 5994 18 2 5
48 100 E01000051 Barking and Dagenham 5228 16 2 5
49 95 E01000052 Barking and Dagenham 6549 20 2 5
50 94 E01000053 Barking and Dagenham 4249 13 2 5
51 77 E01000054 Barking and Dagenham 8124 25 3 5
52 80 E01000055 Barking and Dagenham 7604 23 3 5
53 86 E01000056 Barking and Dagenham 5571 17 2 5
54 78 E01000057 Barking and Dagenham 6712 20 3 5
55 85 E01000058 Barking and Dagenham 7176 22 3 5
56 88 E01000059 Barking and Dagenham 6950 21 3 5
57 82 E01000060 Barking and Dagenham 5475 17 2 5
58 83 E01000061 Barking and Dagenham 2802 9 1 5
59 90 E01000062 Barking and Dagenham 9781 30 3 5
60 90 E01000063 Barking and Dagenham 6520 20 2 5
61 91 E01000064 Barking and Dagenham 5791 18 2 5
62 91 E01000065 Barking and Dagenham 4296 13 2 5
63 84 E01000066 Barking and Dagenham 10329 31 4 5
64 86 E01000067 Barking and Dagenham 13573 41 5 5
65 96 E01000068 Barking and Dagenham 10421 32 4 5
66 87 E01000069 Barking and Dagenham 17580 54 6 5
67 96 E01000070 Barking and Dagenham 13531 41 5 5
68 88 E01000071 Barking and Dagenham 15370 47 5 5
69 90 E01000072 Barking and Dagenham 3974 12 2 5
70 89 E01000073 Barking and Dagenham 4645 14 2 5
71 83 E01000074 Barking and Dagenham 5870 18 2 5
72 73 E01000075 Barking and Dagenham 5215 16 2 5
73 88 E01000076 Barking and Dagenham 5451 17 2 5
74 88 E01000077 Barking and Dagenham 3967 12 2 5
75 93 E01000078 Barking and Dagenham 5874 18 2 5
76 89 E01000079 Barking and Dagenham 6057 18 2 5
77 90 E01000080 Barking and Dagenham 6596 20 3 5
78 93 E01000081 Barking and Dagenham 7738 24 3 5
79 93 E01000082 Barking and Dagenham 9100 28 3 5
80 88 E01000083 Barking and Dagenham 6111 19 2 5
81 94 E01000084 Barking and Dagenham 4315 13 2 5
82 98 E01000085 Barking and Dagenham 5838 18 2 5
83 95 E01000086 Barking and Dagenham 4822 15 2 5
84 95 E01000087 Barking and Dagenham 6122 19 2 5
85 90 E01000088 Barking and Dagenham 8574 26 3 5
86 84 E01000089 Barking and Dagenham 8508 26 3 5
87 85 E01000090 Barking and Dagenham 8873 27 3 5
88 85 E01000091 Barking and Dagenham 3669 11 2 5
89 89 E01000092 Barking and Dagenham 6348 19 2 5
90 92 E01000093 Barking and Dagenham 2669 8 1 5
91 91 E01000094 Barking and Dagenham 8930 27 3 5
92 94 E01000095 Barking and Dagenham 6984 21 3 5
93 97 E01000096 Barking and Dagenham 3997 12 2 5
94 82 E01000097 Barking and Dagenham 4866 15 2 5
95 88 E01000098 Barking and Dagenham 4455 14 2 5
96 88 E01000099 Barking and Dagenham 8373 25 3 5
97 89 E01000100 Barking and Dagenham 7152 22 3 5
98 92 E01000101 Barking and Dagenham 4126 13 2 5
99 89 E01000102 Barking and Dagenham 3557 11 2 5
100 86 E01000103 Barking and Dagenham 6708 20 3 5
101 90 E01000104 Barking and Dagenham 6002 18 2 5
102 97 E01000105 Barking and Dagenham 3229 10 1 5
103 88 E01000106 Barking and Dagenham 3355 10 2 5
104 78 E01000107 Barking and Dagenham 8865 27 3 5
105 92 E01000108 Barking and Dagenham 8940 27 3 5
106 93 E01000109 Barking and Dagenham 10373 32 4 5
107 94 E01000110 Barking and Dagenham 16365 50 5 5
108 94 E01000111 Barking and Dagenham 8544 26 3 5
109 98 E01000112 Barking and Dagenham 10925 33 4 5
110 100 E01000113 Barking and Dagenham 10601 32 4 5
111 96 E01000114 Barking and Dagenham 11855 36 4 5
112 67 E01000115 Barnet 29174 89 9 187
113 79 E01000116 Barnet 27318 83 9 187
114 79 E01000117 Barnet 24958 76 8 187
115 83 E01000118 Barnet 24743 75 8 187
116 82 E01000119 Barnet 22657 69 7 187
117 86 E01000120 Barnet 29572 90 10 187
118 78 E01000121 Barnet 5463 17 2 187
119 74 E01000122 Barnet 24308 74 8 187
120 79 E01000123 Barnet 23278 71 8 187
121 91 E01000124 Barnet 11634 35 4 187
122 92 E01000125 Barnet 9759 30 3 187
123 86 E01000126 Barnet 6407 20 2 187
124 80 E01000127 Barnet 9275 28 3 187
125 84 E01000128 Barnet 9555 29 3 187
126 97 E01000129 Barnet 7554 23 3 187
127 83 E01000130 Barnet 7621 23 3 187
128 89 E01000131 Barnet 13623 41 5 187
129 92 E01000132 Barnet 10459 32 4 187
130 87 E01000133 Barnet 7660 23 3 187
131 81 E01000134 Barnet 10969 33 4 187
132 89 E01000135 Barnet 21585 66 7 187
133 80 E01000136 Barnet 25840 79 8 187
134 88 E01000137 Barnet 8611 26 3 187
135 88 E01000138 Barnet 9114 28 3 187
136 83 E01000139 Barnet 21727 66 7 187
137 93 E01000140 Barnet 17164 52 6 187
138 100 E01000141 Barnet 8601 26 3 187
139 94 E01000142 Barnet 17305 53 6 187
140 95 E01000143 Barnet 7380 22 3 187
141 99 E01000144 Barnet 15833 48 5 187
142 94 E01000145 Barnet 19310 59 6 187
143 100 E01000146 Barnet 15647 48 5 187
144 87 E01000147 Barnet 21282 65 7 187
145 93 E01000148 Barnet 9213 28 3 187
146 79 E01000150 Barnet 18371 56 6 187
147 90 E01000151 Barnet 4606 14 2 187
148 97 E01000152 Barnet 6908 21 3 187
149 95 E01000153 Barnet 3826 12 2 187
150 96 E01000154 Barnet 6805 21 3 187
151 94 E01000155 Barnet 13700 42 5 187
152 86 E01000156 Barnet 26669 81 9 187
153 78 E01000157 Barnet 21431 65 7 187
154 91 E01000158 Barnet 14606 44 5 187
155 73 E01000159 Barnet 17696 54 6 187
156 87 E01000160 Barnet 22025 67 7 187
157 94 E01000161 Barnet 19434 59 6 187
158 99 E01000162 Barnet 15689 48 5 187
159 72 E01000163 Barnet 8744 27 3 187
160 78 E01000164 Barnet 10557 32 4 187
161 84 E01000165 Barnet 20782 63 7 187
162 45 E01000166 Barnet 19054 58 6 187
163 43 E01000167 Barnet 8854 27 3 187
164 59 E01000168 Barnet 28357 86 9 187
165 56 E01000169 Barnet 20813 63 7 187
166 70 E01000170 Barnet 14031 43 5 187
167 82 E01000171 Barnet 11210 34 4 187
168 43 E01000172 Barnet 26533 81 9 187
169 77 E01000173 Barnet 24872 76 8 187
170 87 E01000174 Barnet 17685 54 6 187
171 64 E01000175 Barnet 27536 84 9 187
172 88 E01000176 Barnet 7768 24 3 187
173 93 E01000177 Barnet 26742 81 9 187
174 94 E01000178 Barnet 27008 82 9 187
175 93 E01000179 Barnet 26462 81 9 187
176 86 E01000180 Barnet 19391 59 6 187
177 100 E01000181 Barnet 26821 82 9 187
178 91 E01000182 Barnet 27057 82 9 187
179 80 E01000183 Barnet 23760 72 8 187
180 89 E01000184 Barnet 7110 22 3 187
181 89 E01000185 Barnet 10299 31 4 187
182 68 E01000186 Barnet 30326 92 10 187
183 69 E01000187 Barnet 21042 64 7 187
184 29 E01000188 Barnet 27036 82 9 187
185 57 E01000189 Barnet 11051 34 4 187
186 51 E01000190 Barnet 24311 74 8 187
187 47 E01000191 Barnet 28527 87 9 187
188 82 E01000192 Barnet 18475 56 6 187
189 81 E01000193 Barnet 17828 54 6 187
190 90 E01000194 Barnet 14920 45 5 187
191 75 E01000195 Barnet 9593 29 3 187
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850 98 E01000867 Camden 8822 27 3 132
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925 100 E01000942 Camden 18602 57 6 132
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958 98 E01000975 Croydon 16380 50 5 106
959 100 E01000976 Croydon 10317 31 4 106
960 85 E01000977 Croydon 8864 27 3 106
961 83 E01000978 Croydon 13895 42 5 106
962 96 E01000979 Croydon 16495 50 6 106
963 96 E01000980 Croydon 9879 30 4 106
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967 97 E01000984 Croydon 7716 23 3 106
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969 73 E01000986 Croydon 21003 64 7 106
970 91 E01000987 Croydon 25290 77 8 106
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978 95 E01000996 Croydon 14397 44 5 106
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980 97 E01000998 Croydon 6849 21 3 106
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982 97 E01001000 Croydon 8917 27 3 106
983 90 E01001001 Croydon 5065 15 2 106
984 95 E01001002 Croydon 12648 39 4 106
985 92 E01001003 Croydon 10779 33 4 106
986 95 E01001004 Croydon 9626 29 3 106
987 99 E01001005 Croydon 11930 36 4 106
988 89 E01001006 Croydon 7710 23 3 106
989 93 E01001007 Croydon 15344 47 5 106
990 91 E01001008 Croydon 7840 24 3 106
991 97 E01001009 Croydon 11542 35 4 106
992 92 E01001010 Croydon 3792 12 2 106
993 99 E01001011 Croydon 7617 23 3 106
994 99 E01001012 Croydon 5032 15 2 106
995 99 E01001013 Croydon 2836 9 1 106
996 99 E01001014 Croydon 7895 24 3 106
997 57 E01001015 Croydon 11187 34 4 106
998 64 E01001016 Croydon 19580 60 6 106
999 56 E01001017 Croydon 27025 82 9 106
1000 61 E01001018 Croydon 28945 88 9 106
1001 55 E01001019 Croydon 30069 92 10 106
1002 83 E01001020 Croydon 26497 81 9 106
1003 66 E01001021 Croydon 5720 17 2 106
1004 66 E01001022 Croydon 25335 77 8 106
1005 91 E01001023 Croydon 11765 36 4 106
1006 78 E01001024 Croydon 25960 79 8 106
1007 80 E01001025 Croydon 29173 89 9 106
1008 90 E01001026 Croydon 21373 65 7 106
1009 78 E01001027 Croydon 23880 73 8 106
1010 32 E01001028 Croydon 29249 89 9 106
1011 56 E01001029 Croydon 18934 58 6 106
1012 44 E01001030 Croydon 27962 85 9 106
1013 59 E01001031 Croydon 28476 87 9 106
1014 37 E01001032 Croydon 31701 97 10 106
1015 73 E01001033 Croydon 19477 59 6 106
1016 62 E01001034 Croydon 19092 58 6 106
1017 59 E01001035 Croydon 15799 48 5 106
1018 46 E01001036 Croydon 22193 68 7 106
1019 95 E01001037 Croydon 14015 43 5 106
1020 66 E01001038 Croydon 15646 48 5 106
1021 57 E01001039 Croydon 26259 80 8 106
1022 92 E01001040 Croydon 18763 57 6 106
1023 78 E01001041 Croydon 13451 41 5 106
1024 99 E01001042 Croydon 5333 16 2 106
1025 100 E01001043 Croydon 7324 22 3 106
1026 52 E01001044 Croydon 24251 74 8 106
1027 98 E01001045 Croydon 5615 17 2 106
1028 60 E01001046 Croydon 24801 76 8 106
1029 89 E01001047 Croydon 12736 39 4 106
1030 99 E01001048 Croydon 8534 26 3 106
1031 40 E01001049 Croydon 21805 66 7 106
1032 72 E01001050 Croydon 12739 39 4 106
1033 91 E01001051 Croydon 4553 14 2 106
1034 91 E01001052 Croydon 3683 11 2 106
1035 89 E01001053 Croydon 6916 21 3 106
1036 91 E01001054 Croydon 5919 18 2 106
1037 87 E01001055 Croydon 4623 14 2 106
1038 87 E01001056 Croydon 4911 15 2 106
1039 84 E01001057 Croydon 4109 13 2 106
1040 81 E01001058 Croydon 22615 69 7 106
1041 70 E01001059 Croydon 18690 57 6 106
1042 75 E01001060 Croydon 13900 42 5 106
1043 73 E01001061 Croydon 11605 35 4 106
1044 61 E01001062 Croydon 24671 75 8 106
1045 88 E01001063 Croydon 28486 87 9 106
1046 49 E01001064 Croydon 21223 65 7 106
1047 73 E01001065 Croydon 18054 55 6 106
1048 71 E01001066 Croydon 4602 14 2 106
1049 56 E01001067 Croydon 28333 86 9 106
1050 56 E01001068 Croydon 16728 51 6 106
1051 56 E01001069 Croydon 24807 76 8 106
1052 70 E01001070 Croydon 19494 59 6 106
1053 83 E01001071 Croydon 21108 64 7 106
1054 78 E01001072 Croydon 26813 82 9 106
1055 64 E01001073 Croydon 17617 54 6 106
1056 76 E01001074 Croydon 15845 48 5 106
1057 60 E01001075 Croydon 22665 69 7 106
1058 91 E01001076 Croydon 5461 17 2 106
1059 95 E01001077 Croydon 15639 48 5 106
1060 89 E01001078 Croydon 5536 17 2 106
1061 93 E01001079 Croydon 6279 19 2 106
1062 92 E01001080 Croydon 2247 7 1 106
1063 90 E01001081 Croydon 6015 18 2 106
1064 95 E01001082 Croydon 6659 20 3 106
1065 91 E01001083 Croydon 20660 63 7 106
1066 85 E01001084 Croydon 19960 61 7 106
1067 99 E01001085 Croydon 15555 47 5 106
1068 97 E01001086 Croydon 17278 53 6 106
1069 100 E01001087 Croydon 11394 35 4 106
1070 94 E01001088 Croydon 17821 54 6 106
1071 99 E01001089 Croydon 8631 26 3 106
1072 99 E01001090 Croydon 11770 36 4 106
1073 87 E01001091 Croydon 18543 56 6 106
1074 35 E01001092 Croydon 14497 44 5 106
1075 51 E01001093 Croydon 22543 69 7 106
1076 28 E01001094 Croydon 26468 81 9 106
1077 86 E01001095 Croydon 17663 54 6 106
1078 38 E01001096 Croydon 28195 86 9 106
1079 99 E01001097 Croydon 12443 38 4 106
1080 36 E01001098 Croydon 27652 84 9 106
1081 69 E01001099 Croydon 14611 44 5 106
1082 56 E01001100 Croydon 26012 79 8 106
1083 33 E01001101 Croydon 30394 93 10 106
1084 50 E01001102 Croydon 28156 86 9 106
1085 67 E01001103 Croydon 28082 86 9 106
1086 38 E01001104 Croydon 29727 91 10 106
1087 87 E01001105 Croydon 13713 42 5 106
1088 92 E01001106 Croydon 21553 66 7 106
1089 26 E01001107 Croydon 28273 86 9 106
1090 31 E01001108 Croydon 30386 93 10 106
1091 97 E01001109 Croydon 7046 21 3 106
1092 97 E01001110 Croydon 3477 11 2 106
1093 96 E01001111 Croydon 8781 27 3 106
1094 87 E01001112 Croydon 7851 24 3 106
1095 92 E01001113 Croydon 8829 27 3 106
1096 95 E01001114 Croydon 3866 12 2 106
1097 95 E01001115 Croydon 3186 10 1 106
1098 96 E01001116 Croydon 8560 26 3 106
1099 99 E01001117 Croydon 9323 28 3 106
1100 98 E01001118 Croydon 4115 13 2 106
1101 90 E01001119 Croydon 25971 79 8 106
1102 81 E01001120 Croydon 24489 75 8 106
1103 75 E01001121 Croydon 28016 85 9 106
1104 61 E01001122 Croydon 25084 76 8 106
1105 64 E01001123 Croydon 25485 78 8 106
1106 36 E01001124 Croydon 29636 90 10 106
1107 89 E01001125 Croydon 22109 67 7 106
1108 86 E01001126 Croydon 28547 87 9 106
1109 68 E01001127 Croydon 25246 77 8 106
1110 65 E01001128 Croydon 5944 18 2 106
1111 78 E01001129 Croydon 30882 94 10 106
1112 54 E01001130 Croydon 5163 16 2 106
1113 61 E01001131 Croydon 21386 65 7 106
1114 51 E01001132 Croydon 25449 77 8 106
1115 62 E01001133 Croydon 22956 70 7 106
1116 64 E01001134 Croydon 24648 75 8 106
1117 69 E01001135 Croydon 26298 80 9 106
1118 88 E01001136 Croydon 6706 20 3 106
1119 64 E01001137 Croydon 11694 36 4 106
1120 61 E01001138 Croydon 15577 47 5 106
1121 69 E01001139 Croydon 14729 45 5 106
1122 58 E01001140 Croydon 12982 40 4 106
1123 67 E01001141 Croydon 9313 28 3 106
1124 78 E01001142 Croydon 13217 40 5 106
1125 80 E01001143 Croydon 7941 24 3 106
1126 85 E01001144 Croydon 5183 16 2 106
1127 95 E01001145 Croydon 4281 13 2 106
1128 89 E01001146 Croydon 14580 44 5 106
1129 97 E01001147 Croydon 6270 19 2 106
1130 88 E01001148 Croydon 11948 36 4 106
1131 78 E01001149 Croydon 17888 54 6 106
1132 69 E01001150 Croydon 13899 42 5 106
1133 92 E01001151 Croydon 4019 12 2 106
1134 97 E01001152 Croydon 5158 16 2 106
1135 93 E01001153 Croydon 12275 37 4 106
1136 98 E01001154 Croydon 8530 26 3 106
1137 98 E01001155 Croydon 3291 10 2 106
1138 67 E01001156 Croydon 10027 31 4 106
1139 85 E01001157 Croydon 15973 49 5 106
1140 68 E01001158 Croydon 13982 43 5 106
1141 77 E01001159 Croydon 19487 59 6 106
1142 89 E01001160 Croydon 20215 62 7 106
1143 81 E01001161 Croydon 3575 11 2 106
1144 75 E01001162 Croydon 8850 27 3 106
1145 90 E01001163 Croydon 17644 54 6 106
1146 93 E01001164 Croydon 13940 42 5 106
1147 66 E01001165 Croydon 11281 34 4 106
1148 83 E01001166 Croydon 7025 21 3 106
1149 44 E01001167 Croydon 12891 39 4 106
1150 54 E01001168 Croydon 13421 41 5 106
1151 24 E01001169 Croydon 6795 21 3 106
1152 81 E01001170 Croydon 9544 29 3 106
1153 45 E01001171 Croydon 11031 34 4 106
1154 53 E01001172 Croydon 3467 11 2 106
1155 49 E01001173 Croydon 14566 44 5 106
1156 97 E01001174 Croydon 12417 38 4 106
1157 98 E01001175 Croydon 7742 24 3 106
1158 99 E01001176 Croydon 12219 37 4 106
1159 94 E01001177 Croydon 7251 22 3 106
1160 98 E01001178 Croydon 1096 3 1 106
1161 96 E01001179 Croydon 13775 42 5 106
1162 96 E01001180 Croydon 9127 28 3 106
1163 97 E01001181 Croydon 3607 11 2 106
1164 96 E01001182 Croydon 13038 40 4 106
1165 99 E01001183 Croydon 11301 34 4 106
1166 92 E01001184 Croydon 17067 52 6 106
1167 98 E01001185 Croydon 14358 44 5 106
1168 85 E01001186 Croydon 8461 26 3 106
1169 88 E01001187 Croydon 13847 42 5 106
1170 92 E01001188 Croydon 8950 27 3 106
1171 87 E01001189 Croydon 16383 50 5 106
1172 84 E01001190 Croydon 9331 28 3 106
1173 97 E01001191 Croydon 5914 18 2 106
1174 94 E01001192 Croydon 9166 28 3 106
1175 87 E01001193 Croydon 6123 19 2 106
1176 94 E01001194 Croydon 15918 48 5 106
1177 77 E01001195 Ealing 19967 61 7 91
1178 95 E01001196 Ealing 4857 15 2 91
1179 84 E01001197 Ealing 12321 38 4 91
1180 95 E01001198 Ealing 19095 58 6 91
1181 93 E01001199 Ealing 12563 38 4 91
1182 100 E01001200 Ealing 17969 55 6 91
1183 97 E01001201 Ealing 16425 50 6 91
1184 100 E01001202 Ealing 6344 19 2 91
1185 100 E01001203 Ealing 6778 21 3 91
1186 67 E01001204 Ealing 20285 62 7 91
1187 66 E01001205 Ealing 7545 23 3 91
1188 61 E01001206 Ealing 3637 11 2 91
1189 82 E01001207 Ealing 17745 54 6 91
1190 64 E01001208 Ealing 22354 68 7 91
1191 80 E01001209 Ealing 28190 86 9 91
1192 47 E01001210 Ealing 2075 6 1 91
1193 74 E01001211 Ealing 24028 73 8 91
1194 71 E01001212 Ealing 20550 63 7 91
1195 86 E01001213 Ealing 8943 27 3 91
1196 84 E01001214 Ealing 18010 55 6 91
1197 96 E01001215 Ealing 7934 24 3 91
1198 83 E01001216 Ealing 12636 38 4 91
1199 81 E01001217 Ealing 17865 54 6 91
1200 72 E01001218 Ealing 5429 17 2 91
1201 68 E01001219 Ealing 5527 17 2 91
1202 75 E01001220 Ealing 2523 8 1 91
1203 99 E01001221 Ealing 11345 35 4 91
1204 98 E01001222 Ealing 12874 39 4 91
1205 72 E01001223 Ealing 22559 69 7 91
1206 67 E01001224 Ealing 25604 78 8 91
1207 96 E01001225 Ealing 12984 40 4 91
1208 68 E01001226 Ealing 20668 63 7 91
1209 73 E01001227 Ealing 24152 74 8 91
1210 76 E01001228 Ealing 22860 70 7 91
1211 88 E01001229 Ealing 7923 24 3 91
1212 95 E01001230 Ealing 13358 41 5 91
1213 85 E01001231 Ealing 20102 61 7 91
1214 90 E01001232 Ealing 11537 35 4 91
1215 95 E01001233 Ealing 11472 35 4 91
1216 85 E01001234 Ealing 12109 37 4 91
1217 91 E01001235 Ealing 19722 60 7 91
1218 93 E01001236 Ealing 17674 54 6 91
1219 85 E01001237 Ealing 16963 52 6 91
1220 94 E01001238 Ealing 11044 34 4 91
1221 88 E01001239 Ealing 6813 21 3 91
1222 89 E01001240 Ealing 13977 43 5 91
1223 96 E01001241 Ealing 12616 38 4 91
1224 86 E01001242 Ealing 9639 29 3 91
1225 96 E01001243 Ealing 10522 32 4 91
1226 94 E01001244 Ealing 8569 26 3 91
1227 98 E01001245 Ealing 18507 56 6 91
1228 93 E01001246 Ealing 7075 22 3 91
1229 98 E01001247 Ealing 13338 41 5 91
1230 73 E01001248 Ealing 16655 51 6 91
1231 99 E01001249 Ealing 3848 12 2 91
1232 93 E01001250 Ealing 5176 16 2 91
1233 89 E01001251 Ealing 15489 47 5 91
1234 95 E01001252 Ealing 10397 32 4 91
1235 85 E01001253 Ealing 18300 56 6 91
1236 81 E01001254 Ealing 19351 59 6 91
1237 81 E01001255 Ealing 20547 63 7 91
1238 53 E01001257 Ealing 4021 12 2 91
1239 68 E01001258 Ealing 18071 55 6 91
1240 80 E01001259 Ealing 14241 43 5 91
1241 86 E01001260 Ealing 13738 42 5 91
1242 94 E01001261 Ealing 12265 37 4 91
1243 52 E01001262 Ealing 7386 22 3 91
1244 50 E01001263 Ealing 6069 18 2 91
1245 62 E01001264 Ealing 11124 34 4 91
1246 81 E01001265 Ealing 13878 42 5 91
1247 79 E01001266 Ealing 17834 54 6 91
1248 78 E01001267 Ealing 7140 22 3 91
1249 68 E01001268 Ealing 15642 48 5 91
1250 85 E01001269 Ealing 20420 62 7 91
1251 75 E01001270 Ealing 18289 56 6 91
1252 83 E01001271 Ealing 17106 52 6 91
1253 87 E01001272 Ealing 15184 46 5 91
1254 79 E01001273 Ealing 25179 77 8 91
1255 66 E01001274 Ealing 26422 80 9 91
1256 79 E01001275 Ealing 15212 46 5 91
1257 82 E01001276 Ealing 13885 42 5 91
1258 89 E01001277 Ealing 16527 50 6 91
1259 83 E01001278 Ealing 11526 35 4 91
1260 63 E01001279 Ealing 28128 86 9 91
1261 68 E01001280 Ealing 20279 62 7 91
1262 67 E01001281 Ealing 27738 84 9 91
1263 63 E01001282 Ealing 5881 18 2 91
1264 68 E01001283 Ealing 4237 13 2 91
1265 64 E01001284 Ealing 18191 55 6 91
1266 69 E01001285 Ealing 11937 36 4 91
1267 64 E01001286 Ealing 11665 36 4 91
1268 55 E01001287 Ealing 7443 23 3 91
1269 67 E01001288 Ealing 17925 55 6 91
1270 71 E01001289 Ealing 18420 56 6 91
1271 63 E01001290 Ealing 21401 65 7 91
1272 81 E01001291 Ealing 14947 46 5 91
1273 81 E01001292 Ealing 20084 61 7 91
1274 79 E01001293 Ealing 16678 51 6 91
1275 63 E01001294 Ealing 12398 38 4 91
1276 72 E01001295 Ealing 16799 51 6 91
1277 71 E01001296 Ealing 12764 39 4 91
1278 70 E01001297 Ealing 11800 36 4 91
1279 80 E01001298 Ealing 9045 28 3 91
1280 71 E01001299 Ealing 27061 82 9 91
1281 95 E01001300 Ealing 25967 79 8 91
1282 96 E01001301 Ealing 14321 44 5 91
1283 92 E01001302 Ealing 22524 69 7 91
1284 94 E01001303 Ealing 24632 75 8 91
1285 90 E01001304 Ealing 19885 61 7 91
1286 72 E01001305 Ealing 27464 84 9 91
1287 87 E01001306 Ealing 26685 81 9 91
1288 77 E01001307 Ealing 23210 71 8 91
1289 77 E01001308 Ealing 22868 70 7 91
1290 73 E01001309 Ealing 18839 57 6 91
1291 63 E01001310 Ealing 15589 47 5 91
1292 79 E01001311 Ealing 8519 26 3 91
1293 89 E01001312 Ealing 17313 53 6 91
1294 72 E01001313 Ealing 20272 62 7 91
1295 72 E01001314 Ealing 23394 71 8 91
1296 69 E01001315 Ealing 15913 48 5 91
1297 52 E01001316 Ealing 7159 22 3 91
1298 46 E01001317 Ealing 9896 30 4 91
1299 50 E01001318 Ealing 5532 17 2 91
1300 61 E01001319 Ealing 16095 49 5 91
1301 53 E01001320 Ealing 3831 12 2 91
1302 69 E01001321 Ealing 10147 31 4 91
1303 52 E01001322 Ealing 11458 35 4 91
1304 76 E01001323 Ealing 12015 37 4 91
1305 79 E01001324 Ealing 6468 20 2 91
1306 40 E01001325 Ealing 9812 30 3 91
1307 73 E01001326 Ealing 6645 20 3 91
1308 43 E01001327 Ealing 7636 23 3 91
1309 57 E01001328 Ealing 6406 20 2 91
1310 34 E01001329 Ealing 11307 34 4 91
1311 67 E01001330 Ealing 3501 11 2 91
1312 33 E01001331 Ealing 5126 16 2 91
1313 42 E01001332 Ealing 4277 13 2 91
1314 72 E01001333 Ealing 4369 13 2 91
1315 55 E01001334 Ealing 3919 12 2 91
1316 63 E01001335 Ealing 13665 42 5 91
1317 69 E01001336 Ealing 10825 33 4 91
1318 56 E01001337 Ealing 5627 17 2 91
1319 88 E01001338 Ealing 9484 29 3 91
1320 38 E01001339 Ealing 5657 17 2 91
1321 73 E01001340 Ealing 4859 15 2 91
1322 81 E01001341 Ealing 21235 65 7 91
1323 76 E01001342 Ealing 19108 58 6 91
1324 59 E01001343 Ealing 18564 57 6 91
1325 58 E01001344 Ealing 15761 48 5 91
1326 82 E01001345 Ealing 16547 50 6 91
1327 71 E01001346 Ealing 22171 68 7 91
1328 71 E01001347 Ealing 15517 47 5 91
1329 62 E01001348 Ealing 14879 45 5 91
1330 80 E01001349 Ealing 6422 20 2 91
1331 90 E01001350 Ealing 17789 54 6 91
1332 100 E01001351 Ealing 9030 27 3 91
1333 98 E01001352 Ealing 18684 57 6 91
1334 85 E01001353 Ealing 11787 36 4 91
1335 99 E01001354 Ealing 12592 38 4 91
1336 97 E01001355 Ealing 11088 34 4 91
1337 98 E01001356 Ealing 2863 9 1 91
1338 97 E01001357 Ealing 3722 11 2 91
1339 99 E01001358 Ealing 2888 9 1 91
1340 95 E01001359 Ealing 10824 33 4 91
1341 95 E01001360 Ealing 8447 26 3 91
1342 98 E01001361 Ealing 6178 19 2 91
1343 95 E01001362 Ealing 8413 26 3 91
1344 91 E01001363 Ealing 10083 31 4 91
1345 84 E01001364 Ealing 3672 11 2 91
1346 93 E01001365 Ealing 9026 27 3 91
1347 91 E01001366 Ealing 8743 27 3 91
1348 95 E01001367 Ealing 7890 24 3 91
1349 92 E01001368 Ealing 8520 26 3 91
1350 82 E01001369 Ealing 10823 33 4 91
1351 88 E01001370 Ealing 10253 31 4 91
1352 88 E01001371 Ealing 9509 29 3 91
1353 81 E01001372 Ealing 7551 23 3 91
1354 94 E01001373 Ealing 9995 30 4 91
1355 95 E01001374 Ealing 23089 70 8 91
1356 87 E01001375 Ealing 29992 91 10 91
1357 94 E01001376 Ealing 11416 35 4 91
1358 84 E01001377 Ealing 26779 82 9 91
1359 94 E01001379 Ealing 28867 88 9 91
1360 96 E01001380 Ealing 21610 66 7 91
1361 100 E01001381 Ealing 16099 49 5 91
1362 88 E01001382 Ealing 26572 81 9 91
1363 88 E01001383 Ealing 22673 69 7 91
1364 90 E01001384 Ealing 24713 75 8 91
1365 90 E01001385 Ealing 26344 80 9 91
1366 93 E01001386 Ealing 24623 75 8 91
1367 86 E01001387 Ealing 17508 53 6 91
1368 96 E01001388 Ealing 5956 18 2 91
1369 93 E01001389 Ealing 13509 41 5 91
1370 89 E01001390 Enfield 23838 73 8 68
1371 90 E01001391 Enfield 10400 32 4 68
1372 87 E01001392 Enfield 23651 72 8 68
1373 90 E01001393 Enfield 15156 46 5 68
1374 96 E01001394 Enfield 9612 29 3 68
1375 83 E01001395 Enfield 5795 18 2 68
1376 96 E01001396 Enfield 15197 46 5 68
1377 89 E01001397 Enfield 10992 33 4 68
1378 67 E01001398 Enfield 25510 78 8 68
1379 91 E01001399 Enfield 23079 70 8 68
1380 79 E01001400 Enfield 24050 73 8 68
1381 84 E01001401 Enfield 21705 66 7 68
1382 89 E01001402 Enfield 25812 79 8 68
1383 87 E01001403 Enfield 18070 55 6 68
1384 85 E01001404 Enfield 15105 46 5 68
1385 50 E01001405 Enfield 22069 67 7 68
1386 84 E01001406 Enfield 11086 34 4 68
1387 44 E01001407 Enfield 15675 48 5 68
1388 77 E01001408 Enfield 17296 53 6 68
1389 63 E01001409 Enfield 5926 18 2 68
1390 57 E01001410 Enfield 2967 9 1 68
1391 85 E01001411 Enfield 20608 63 7 68
1392 60 E01001412 Enfield 8853 27 3 68
1393 47 E01001413 Enfield 27340 83 9 68
1394 55 E01001414 Enfield 3518 11 2 68
1395 69 E01001415 Enfield 18476 56 6 68
1396 61 E01001416 Enfield 27463 84 9 68
1397 47 E01001417 Enfield 26756 81 9 68
1398 49 E01001418 Enfield 13494 41 5 68
1399 53 E01001419 Enfield 18716 57 6 68
1400 44 E01001420 Enfield 9953 30 4 68
1401 51 E01001421 Enfield 9728 30 3 68
1402 35 E01001422 Enfield 27233 83 9 68
1403 93 E01001423 Enfield 7161 22 3 68
1404 96 E01001424 Enfield 2918 9 1 68
1405 91 E01001425 Enfield 2455 7 1 68
1406 93 E01001426 Enfield 3965 12 2 68
1407 98 E01001427 Enfield 3582 11 2 68
1408 90 E01001428 Enfield 4845 15 2 68
1409 99 E01001429 Enfield 2781 8 1 68
1410 93 E01001430 Enfield 3702 11 2 68
1411 92 E01001431 Enfield 3388 10 2 68
1412 96 E01001432 Enfield 4375 13 2 68
1413 81 E01001433 Enfield 5499 17 2 68
1414 86 E01001434 Enfield 8928 27 3 68
1415 84 E01001435 Enfield 10023 31 4 68
1416 91 E01001436 Enfield 8730 27 3 68
1417 96 E01001437 Enfield 4642 14 2 68
1418 85 E01001438 Enfield 5904 18 2 68
1419 97 E01001439 Enfield 5806 18 2 68
1420 94 E01001440 Enfield 7766 24 3 68
1421 95 E01001441 Enfield 5182 16 2 68
1422 97 E01001442 Enfield 3165 10 1 68
1423 84 E01001444 Enfield 12215 37 4 68
1424 72 E01001445 Enfield 8094 25 3 68
1425 90 E01001446 Enfield 9085 28 3 68
1426 91 E01001447 Enfield 3524 11 2 68
1427 95 E01001448 Enfield 7950 24 3 68
1428 82 E01001449 Enfield 8289 25 3 68
1429 79 E01001450 Enfield 13223 40 5 68
1430 44 E01001451 Enfield 17172 52 6 68
1431 50 E01001452 Enfield 22909 70 7 68
1432 54 E01001453 Enfield 29230 89 9 68
1433 65 E01001454 Enfield 25609 78 8 68
1434 70 E01001455 Enfield 23129 70 8 68
1435 92 E01001456 Enfield 29825 91 10 68
1436 51 E01001457 Enfield 20056 61 7 68
1437 83 E01001458 Enfield 4196 13 2 68
1438 94 E01001459 Enfield 11498 35 4 68
1439 95 E01001460 Enfield 4797 15 2 68
1440 79 E01001461 Enfield 4246 13 2 68
1441 91 E01001462 Enfield 5863 18 2 68
1442 87 E01001463 Enfield 12284 37 4 68
1443 87 E01001464 Enfield 4782 15 2 68
1444 85 E01001465 Enfield 11104 34 4 68
1445 86 E01001466 Enfield 8860 27 3 68
1446 88 E01001467 Enfield 9903 30 4 68
1447 47 E01001468 Enfield 8107 25 3 68
1448 44 E01001469 Enfield 11863 36 4 68
1449 25 E01001470 Enfield 23825 73 8 68
1450 25 E01001471 Enfield 16683 51 6 68
1451 51 E01001472 Enfield 20183 61 7 68
1452 30 E01001473 Enfield 17974 55 6 68
1453 33 E01001474 Enfield 20983 64 7 68
1454 46 E01001475 Enfield 27973 85 9 68
1455 95 E01001476 Enfield 9017 27 3 68
1456 83 E01001477 Enfield 5893 18 2 68
1457 86 E01001478 Enfield 10250 31 4 68
1458 98 E01001479 Enfield 6554 20 2 68
1459 88 E01001480 Enfield 7739 24 3 68
1460 93 E01001481 Enfield 9869 30 4 68
1461 94 E01001482 Enfield 4720 14 2 68
1462 84 E01001483 Enfield 1643 5 1 68
1463 92 E01001484 Enfield 11064 34 4 68
1464 95 E01001485 Enfield 5172 16 2 68
1465 95 E01001486 Enfield 3856 12 2 68
1466 97 E01001487 Enfield 5869 18 2 68
1467 96 E01001488 Enfield 7798 24 3 68
1468 94 E01001489 Enfield 7594 23 3 68
1469 97 E01001491 Enfield 6746 21 3 68
1470 96 E01001492 Enfield 7065 22 3 68
1471 80 E01001493 Enfield 8384 26 3 68
1472 91 E01001494 Enfield 18473 56 6 68
1473 93 E01001495 Enfield 21557 66 7 68
1474 79 E01001496 Enfield 19665 60 6 68
1475 89 E01001497 Enfield 11718 36 4 68
1476 99 E01001498 Enfield 16629 51 6 68
1477 93 E01001499 Enfield 11372 35 4 68
1478 90 E01001500 Enfield 14503 44 5 68
1479 93 E01001501 Enfield 9993 30 4 68
1480 94 E01001502 Enfield 7448 23 3 68
1481 91 E01001503 Enfield 8948 27 3 68
1482 87 E01001504 Enfield 7894 24 3 68
1483 92 E01001505 Enfield 6432 20 2 68
1484 90 E01001506 Enfield 4674 14 2 68
1485 99 E01001507 Enfield 4121 13 2 68
1486 98 E01001508 Enfield 7139 22 3 68
1487 86 E01001509 Enfield 6129 19 2 68
1488 96 E01001510 Enfield 2622 8 1 68
1489 89 E01001511 Enfield 12867 39 4 68
1490 78 E01001512 Enfield 15781 48 5 68
1491 88 E01001513 Enfield 6497 20 2 68
1492 86 E01001514 Enfield 12968 39 4 68
1493 87 E01001515 Enfield 5175 16 2 68
1494 73 E01001516 Enfield 8539 26 3 68
1495 82 E01001517 Enfield 2365 7 1 68
1496 76 E01001518 Enfield 12462 38 4 68
1497 92 E01001519 Enfield 20796 63 7 68
1498 66 E01001520 Enfield 16603 51 6 68
1499 76 E01001521 Enfield 25863 79 8 68
1500 61 E01001522 Enfield 19881 61 7 68
1501 55 E01001523 Enfield 26051 79 8 68
1502 61 E01001524 Enfield 13445 41 5 68
1503 67 E01001525 Enfield 17196 52 6 68
1504 61 E01001526 Enfield 24301 74 8 68
1505 77 E01001527 Enfield 18129 55 6 68
1506 97 E01001528 Enfield 5918 18 2 68
1507 96 E01001529 Enfield 6993 21 3 68
1508 88 E01001530 Enfield 13931 42 5 68
1509 69 E01001531 Enfield 26522 81 9 68
1510 84 E01001532 Enfield 26409 80 9 68
1511 81 E01001533 Enfield 28218 86 9 68
1512 89 E01001534 Enfield 23107 70 8 68
1513 78 E01001535 Enfield 19585 60 6 68
1514 88 E01001536 Enfield 15451 47 5 68
1515 43 E01001537 Enfield 22687 69 7 68
LA_pct LA_decile
1 66 7
2 66 7
3 66 7
4 66 7
5 2 1
6 2 1
7 2 1
8 2 1
9 2 1
10 2 1
11 2 1
12 2 1
13 2 1
14 2 1
15 2 1
16 2 1
17 2 1
18 2 1
19 2 1
20 2 1
21 2 1
22 2 1
23 2 1
24 2 1
25 2 1
26 2 1
27 2 1
28 2 1
29 2 1
30 2 1
31 2 1
32 2 1
33 2 1
34 2 1
35 2 1
36 2 1
37 2 1
38 2 1
39 2 1
40 2 1
41 2 1
42 2 1
43 2 1
44 2 1
45 2 1
46 2 1
47 2 1
48 2 1
49 2 1
50 2 1
51 2 1
52 2 1
53 2 1
54 2 1
55 2 1
56 2 1
57 2 1
58 2 1
59 2 1
60 2 1
61 2 1
62 2 1
63 2 1
64 2 1
65 2 1
66 2 1
67 2 1
68 2 1
69 2 1
70 2 1
71 2 1
72 2 1
73 2 1
74 2 1
75 2 1
76 2 1
77 2 1
78 2 1
79 2 1
80 2 1
81 2 1
82 2 1
83 2 1
84 2 1
85 2 1
86 2 1
87 2 1
88 2 1
89 2 1
90 2 1
91 2 1
92 2 1
93 2 1
94 2 1
95 2 1
96 2 1
97 2 1
98 2 1
99 2 1
100 2 1
101 2 1
102 2 1
103 2 1
104 2 1
105 2 1
106 2 1
107 2 1
108 2 1
109 2 1
110 2 1
111 2 1
112 59 6
113 59 6
114 59 6
115 59 6
116 59 6
117 59 6
118 59 6
119 59 6
120 59 6
121 59 6
122 59 6
123 59 6
124 59 6
125 59 6
126 59 6
127 59 6
128 59 6
129 59 6
130 59 6
131 59 6
132 59 6
133 59 6
134 59 6
135 59 6
136 59 6
137 59 6
138 59 6
139 59 6
140 59 6
141 59 6
142 59 6
143 59 6
144 59 6
145 59 6
146 59 6
147 59 6
148 59 6
149 59 6
150 59 6
151 59 6
152 59 6
153 59 6
154 59 6
155 59 6
156 59 6
157 59 6
158 59 6
159 59 6
160 59 6
161 59 6
162 59 6
163 59 6
164 59 6
165 59 6
166 59 6
167 59 6
168 59 6
169 59 6
170 59 6
171 59 6
172 59 6
173 59 6
174 59 6
175 59 6
176 59 6
177 59 6
178 59 6
179 59 6
180 59 6
181 59 6
182 59 6
183 59 6
184 59 6
185 59 6
186 59 6
187 59 6
188 59 6
189 59 6
190 59 6
191 59 6
192 59 6
193 59 6
194 59 6
195 59 6
196 59 6
197 59 6
198 59 6
199 59 6
200 59 6
201 59 6
202 59 6
203 59 6
204 59 6
205 59 6
206 59 6
207 59 6
208 59 6
209 59 6
210 59 6
211 59 6
212 59 6
213 59 6
214 59 6
215 59 6
216 59 6
217 59 6
218 59 6
219 59 6
220 59 6
221 59 6
222 59 6
223 59 6
224 59 6
225 59 6
226 59 6
227 59 6
228 59 6
229 59 6
230 59 6
231 59 6
232 59 6
233 59 6
234 59 6
235 59 6
236 59 6
237 59 6
238 59 6
239 59 6
240 59 6
241 59 6
242 59 6
243 59 6
244 59 6
245 59 6
246 59 6
247 59 6
248 59 6
249 59 6
250 59 6
251 59 6
252 59 6
253 59 6
254 59 6
255 59 6
256 59 6
257 59 6
258 59 6
259 59 6
260 59 6
261 59 6
262 59 6
263 59 6
264 59 6
265 59 6
266 59 6
267 59 6
268 59 6
269 59 6
270 59 6
271 59 6
272 59 6
273 59 6
274 59 6
275 59 6
276 59 6
277 59 6
278 59 6
279 59 6
280 59 6
281 59 6
282 59 6
283 59 6
284 59 6
285 59 6
286 59 6
287 59 6
288 59 6
289 59 6
290 59 6
291 59 6
292 59 6
293 59 6
294 59 6
295 59 6
296 59 6
297 59 6
298 59 6
299 59 6
300 59 6
301 59 6
302 59 6
303 59 6
304 59 6
305 59 6
306 59 6
307 59 6
308 59 6
309 59 6
310 59 6
311 59 6
312 59 6
313 59 6
314 59 6
315 59 6
316 59 6
317 59 6
318 59 6
319 59 6
320 59 6
321 62 7
322 62 7
323 62 7
324 62 7
325 62 7
326 62 7
327 62 7
328 62 7
329 62 7
330 62 7
331 62 7
332 62 7
333 62 7
334 62 7
335 62 7
336 62 7
337 62 7
338 62 7
339 62 7
340 62 7
341 62 7
342 62 7
343 62 7
344 62 7
345 62 7
346 62 7
347 62 7
348 62 7
349 62 7
350 62 7
351 62 7
352 62 7
353 62 7
354 62 7
355 62 7
356 62 7
357 62 7
358 62 7
359 62 7
360 62 7
361 62 7
362 62 7
363 62 7
364 62 7
365 62 7
366 62 7
367 62 7
368 62 7
369 62 7
370 62 7
371 62 7
372 62 7
373 62 7
374 62 7
375 62 7
376 62 7
377 62 7
378 62 7
379 62 7
380 62 7
381 62 7
382 62 7
383 62 7
384 62 7
385 62 7
386 62 7
387 62 7
388 62 7
389 62 7
390 62 7
391 62 7
392 62 7
393 62 7
394 62 7
395 62 7
396 62 7
397 62 7
398 62 7
399 62 7
400 62 7
401 62 7
402 62 7
403 62 7
404 62 7
405 62 7
406 62 7
407 62 7
408 62 7
409 62 7
410 62 7
411 62 7
412 62 7
413 62 7
414 62 7
415 62 7
416 62 7
417 62 7
418 62 7
419 62 7
420 62 7
421 62 7
422 62 7
423 62 7
424 62 7
425 62 7
426 62 7
427 62 7
428 62 7
429 62 7
430 62 7
431 62 7
432 62 7
433 62 7
434 62 7
435 62 7
436 62 7
437 62 7
438 62 7
439 62 7
440 62 7
441 62 7
442 62 7
443 62 7
444 62 7
445 62 7
446 62 7
447 62 7
448 62 7
449 62 7
450 62 7
451 62 7
452 62 7
453 62 7
454 62 7
455 62 7
456 62 7
457 62 7
458 62 7
459 62 7
460 62 7
461 62 7
462 62 7
463 62 7
464 62 7
465 62 7
466 16 2
467 16 2
468 16 2
469 16 2
470 16 2
471 16 2
472 16 2
473 16 2
474 16 2
475 16 2
476 16 2
477 16 2
478 16 2
479 16 2
480 16 2
481 16 2
482 16 2
483 16 2
484 16 2
485 16 2
486 16 2
487 16 2
488 16 2
489 16 2
490 16 2
491 16 2
492 16 2
493 16 2
494 16 2
495 16 2
496 16 2
497 16 2
498 16 2
499 16 2
500 16 2
501 16 2
502 16 2
503 16 2
504 16 2
505 16 2
506 16 2
507 16 2
508 16 2
509 16 2
510 16 2
511 16 2
512 16 2
513 16 2
514 16 2
515 16 2
516 16 2
517 16 2
518 16 2
519 16 2
520 16 2
521 16 2
522 16 2
523 16 2
524 16 2
525 16 2
526 16 2
527 16 2
528 16 2
529 16 2
530 16 2
531 16 2
532 16 2
533 16 2
534 16 2
535 16 2
536 16 2
537 16 2
538 16 2
539 16 2
540 16 2
541 16 2
542 16 2
543 16 2
544 16 2
545 16 2
546 16 2
547 16 2
548 16 2
549 16 2
550 16 2
551 16 2
552 16 2
553 16 2
554 16 2
555 16 2
556 16 2
557 16 2
558 16 2
559 16 2
560 16 2
561 16 2
562 16 2
563 16 2
564 16 2
565 16 2
566 16 2
567 16 2
568 16 2
569 16 2
570 16 2
571 16 2
572 16 2
573 16 2
574 16 2
575 16 2
576 16 2
577 16 2
578 16 2
579 16 2
580 16 2
581 16 2
582 16 2
583 16 2
584 16 2
585 16 2
586 16 2
587 16 2
588 16 2
589 16 2
590 16 2
591 16 2
592 16 2
593 16 2
594 16 2
595 16 2
596 16 2
597 16 2
598 16 2
599 16 2
600 16 2
601 16 2
602 16 2
603 16 2
604 16 2
605 16 2
606 16 2
607 16 2
608 16 2
609 16 2
610 16 2
611 16 2
612 16 2
613 16 2
614 16 2
615 16 2
616 16 2
617 16 2
618 16 2
619 16 2
620 16 2
621 16 2
622 16 2
623 16 2
624 16 2
625 16 2
626 16 2
627 16 2
628 16 2
629 16 2
630 16 2
631 16 2
632 74 8
633 74 8
634 74 8
635 74 8
636 74 8
637 74 8
638 74 8
639 74 8
640 74 8
641 74 8
642 74 8
643 74 8
644 74 8
645 74 8
646 74 8
647 74 8
648 74 8
649 74 8
650 74 8
651 74 8
652 74 8
653 74 8
654 74 8
655 74 8
656 74 8
657 74 8
658 74 8
659 74 8
660 74 8
661 74 8
662 74 8
663 74 8
664 74 8
665 74 8
666 74 8
667 74 8
668 74 8
669 74 8
670 74 8
671 74 8
672 74 8
673 74 8
674 74 8
675 74 8
676 74 8
677 74 8
678 74 8
679 74 8
680 74 8
681 74 8
682 74 8
683 74 8
684 74 8
685 74 8
686 74 8
687 74 8
688 74 8
689 74 8
690 74 8
691 74 8
692 74 8
693 74 8
694 74 8
695 74 8
696 74 8
697 74 8
698 74 8
699 74 8
700 74 8
701 74 8
702 74 8
703 74 8
704 74 8
705 74 8
706 74 8
707 74 8
708 74 8
709 74 8
710 74 8
711 74 8
712 74 8
713 74 8
714 74 8
715 74 8
716 74 8
717 74 8
718 74 8
719 74 8
720 74 8
721 74 8
722 74 8
723 74 8
724 74 8
725 74 8
726 74 8
727 74 8
728 74 8
729 74 8
730 74 8
731 74 8
732 74 8
733 74 8
734 74 8
735 74 8
736 74 8
737 74 8
738 74 8
739 74 8
740 74 8
741 74 8
742 74 8
743 74 8
744 74 8
745 74 8
746 74 8
747 74 8
748 74 8
749 74 8
750 74 8
751 74 8
752 74 8
753 74 8
754 74 8
755 74 8
756 74 8
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[ reached 'max' / getOption("max.print") -- omitted 40214 rows ]ON is similar to WHERE, it filters things out according to a test condition. We use the table.colname format to tell the SQL manager what column in which table we are referring to. This is an example of a LEFT join.
The following diagram is a visualisation of the different types of joins. In this image, the A table is the primary table (e.g. FROM), and the B table is the table you are joining in.
When joining tables, you can specify the columns you want by using table.colname instead of selecting all the columns using *.
For example:
R
dbGetQuery (cdrcDB, "SELECT imd.LSOA, imd.LANAME, imd.Rank,
ahah.ah3h_rnk, ahah.ah3g_rnk, ahah.ah3e_rnk, ahah.ah3r_rnk
FROM ahah
JOIN imd
ON ahah.lsoa11 = imd.LSOA
")
OUTPUT
LSOA LANAME Rank ah3h_rnk ah3g_rnk ah3e_rnk
1 E01000001 City of London 29199 178 40859 41686
2 E01000002 City of London 30379 3134 41483 41676
3 E01000003 City of London 14915 21 40316 41676
4 E01000005 City of London 8678 925 41406 41607
5 E01000006 Barking and Dagenham 14486 7812 26745 41322
6 E01000007 Barking and Dagenham 7256 237 26634 41422
7 E01000008 Barking and Dagenham 5010 19718 3498 41587
8 E01000009 Barking and Dagenham 6736 2127 32161 41320
9 E01000010 Barking and Dagenham 6900 33 37635 41506
10 E01000011 Barking and Dagenham 7698 5549 16204 41320
11 E01000012 Barking and Dagenham 5990 1013 26676 41422
12 E01000013 Barking and Dagenham 4573 5887 34257 40752
13 E01000014 Barking and Dagenham 5650 9770 26361 40820
14 E01000015 Barking and Dagenham 6405 13571 29267 40823
15 E01000016 Barking and Dagenham 6739 6299 31760 40577
16 E01000017 Barking and Dagenham 4570 5998 31697 40577
17 E01000018 Barking and Dagenham 6504 5828 28715 40823
18 E01000019 Barking and Dagenham 6410 5618 6712 40165
19 E01000020 Barking and Dagenham 5520 4950 17756 40165
20 E01000021 Barking and Dagenham 4611 5095 22247 40165
21 E01000022 Barking and Dagenham 6098 2630 22621 40165
22 E01000023 Barking and Dagenham 5243 14279 15020 40165
23 E01000024 Barking and Dagenham 8333 3309 27490 40165
24 E01000025 Barking and Dagenham 5303 6298 31335 40165
25 E01000027 Barking and Dagenham 5097 8138 24181 36579
26 E01000028 Barking and Dagenham 4240 11555 20205 39120
27 E01000029 Barking and Dagenham 12389 11633 38051 39419
28 E01000030 Barking and Dagenham 4760 11263 18385 39260
29 E01000031 Barking and Dagenham 12267 2425 37266 38874
30 E01000032 Barking and Dagenham 8037 2568 38080 39908
31 E01000033 Barking and Dagenham 4879 16327 23659 40101
32 E01000034 Barking and Dagenham 5575 23926 19838 39173
33 E01000035 Barking and Dagenham 10070 11302 35268 40427
34 E01000036 Barking and Dagenham 15028 9423 34299 40622
35 E01000037 Barking and Dagenham 16128 20796 22561 38196
36 E01000038 Barking and Dagenham 14671 11890 21335 38256
37 E01000039 Barking and Dagenham 12542 29794 9229 39801
38 E01000040 Barking and Dagenham 6028 12716 24114 41548
39 E01000041 Barking and Dagenham 6601 11754 12233 41194
40 E01000042 Barking and Dagenham 3842 13552 3963 41172
41 E01000043 Barking and Dagenham 8992 16277 17185 41142
42 E01000044 Barking and Dagenham 8825 16276 33000 41497
43 E01000045 Barking and Dagenham 5639 12816 15747 40750
44 E01000046 Barking and Dagenham 8138 11958 20714 40541
45 E01000048 Barking and Dagenham 3117 6219 21861 41522
46 E01000049 Barking and Dagenham 3928 5953 23582 41611
47 E01000050 Barking and Dagenham 5994 2324 32370 41547
48 E01000051 Barking and Dagenham 5228 3854 39458 41522
49 E01000052 Barking and Dagenham 6549 12122 26977 41611
50 E01000053 Barking and Dagenham 4249 5168 35898 40603
51 E01000054 Barking and Dagenham 8124 3384 21639 40186
52 E01000055 Barking and Dagenham 7604 8915 24650 40322
53 E01000056 Barking and Dagenham 5571 15153 29965 40186
54 E01000057 Barking and Dagenham 6712 467 17963 40322
55 E01000058 Barking and Dagenham 7176 7040 22747 40837
56 E01000059 Barking and Dagenham 6950 11312 30823 39967
57 E01000060 Barking and Dagenham 5475 8313 21712 39868
58 E01000061 Barking and Dagenham 2802 4548 28653 39170
59 E01000062 Barking and Dagenham 9781 6922 29346 40283
60 E01000063 Barking and Dagenham 6520 1168 25039 40354
61 E01000064 Barking and Dagenham 5791 9438 33372 40283
62 E01000065 Barking and Dagenham 4296 3140 30942 40402
63 E01000066 Barking and Dagenham 10329 16691 5958 41052
64 E01000067 Barking and Dagenham 13573 13068 10032 40900
65 E01000068 Barking and Dagenham 10421 9522 25338 41471
66 E01000069 Barking and Dagenham 17580 7850 13989 41315
67 E01000070 Barking and Dagenham 13531 4903 13137 41434
68 E01000071 Barking and Dagenham 15370 13319 17522 41362
69 E01000072 Barking and Dagenham 3974 7037 9995 40948
70 E01000073 Barking and Dagenham 4645 4792 13809 40781
71 E01000074 Barking and Dagenham 5870 2832 11906 40781
72 E01000075 Barking and Dagenham 5215 7499 3041 40624
73 E01000076 Barking and Dagenham 5451 5881 8980 41194
74 E01000077 Barking and Dagenham 3967 7285 24019 40165
75 E01000078 Barking and Dagenham 5874 7718 29342 40364
76 E01000079 Barking and Dagenham 6057 7793 29493 40658
77 E01000080 Barking and Dagenham 6596 11953 26425 40631
78 E01000081 Barking and Dagenham 7738 11498 31756 40640
79 E01000082 Barking and Dagenham 9100 3296 29970 40482
80 E01000083 Barking and Dagenham 6111 4294 20260 40165
81 E01000084 Barking and Dagenham 4315 4329 24432 40912
82 E01000085 Barking and Dagenham 5838 4038 29800 40953
83 E01000086 Barking and Dagenham 4822 6310 31028 40621
84 E01000087 Barking and Dagenham 6122 9739 25432 40952
85 E01000088 Barking and Dagenham 8574 10383 18845 40953
86 E01000089 Barking and Dagenham 8508 16179 11214 41146
87 E01000090 Barking and Dagenham 8873 14250 21643 40840
88 E01000091 Barking and Dagenham 3669 17455 24203 39440
89 E01000092 Barking and Dagenham 6348 31193 26645 40434
90 E01000093 Barking and Dagenham 2669 2378 21100 40989
91 E01000094 Barking and Dagenham 8930 27218 33618 39440
92 E01000095 Barking and Dagenham 6984 32535 35924 39912
93 E01000096 Barking and Dagenham 3997 31917 39139 39440
94 E01000097 Barking and Dagenham 4866 5253 18232 40024
95 E01000098 Barking and Dagenham 4455 3479 17640 40024
96 E01000099 Barking and Dagenham 8373 7095 28472 40174
97 E01000100 Barking and Dagenham 7152 4756 17927 40300
98 E01000101 Barking and Dagenham 4126 2047 25073 40300
99 E01000102 Barking and Dagenham 3557 5831 22727 40250
100 E01000103 Barking and Dagenham 6708 20562 14548 41009
101 E01000104 Barking and Dagenham 6002 19030 21846 40500
102 E01000105 Barking and Dagenham 3229 5239 33395 41050
103 E01000106 Barking and Dagenham 3355 5002 22790 40845
104 E01000107 Barking and Dagenham 8865 15808 6201 40477
105 E01000108 Barking and Dagenham 8940 10298 18209 40679
106 E01000109 Barking and Dagenham 10373 13607 35660 40262
107 E01000110 Barking and Dagenham 16365 11243 38458 39273
108 E01000111 Barking and Dagenham 8544 12885 35166 39690
109 E01000112 Barking and Dagenham 10925 4906 38875 40038
110 E01000113 Barking and Dagenham 10601 5617 37767 40005
111 E01000114 Barking and Dagenham 11855 6935 34431 39820
112 E01000115 Barnet 29174 8122 24783 34869
113 E01000116 Barnet 27318 11323 30269 36175
114 E01000117 Barnet 24958 13500 32289 35529
115 E01000118 Barnet 24743 15842 34774 35992
116 E01000119 Barnet 22657 6622 25351 36840
117 E01000120 Barnet 29572 7557 32949 36040
118 E01000121 Barnet 5463 24319 31068 36697
119 E01000122 Barnet 24308 19705 16381 38078
120 E01000123 Barnet 23278 22787 23159 37771
121 E01000124 Barnet 11634 12805 37487 36997
122 E01000125 Barnet 9759 8359 39688 36260
123 E01000126 Barnet 6407 18450 36545 36948
124 E01000127 Barnet 9275 3100 31479 36508
125 E01000128 Barnet 9555 7827 29923 36948
126 E01000129 Barnet 7554 4888 38498 36394
127 E01000130 Barnet 7621 6761 34236 37328
128 E01000131 Barnet 13623 9415 36097 36626
129 E01000132 Barnet 10459 3798 38111 37644
130 E01000133 Barnet 7660 7695 35063 37644
131 E01000134 Barnet 10969 8140 34297 36187
132 E01000135 Barnet 21585 5320 34001 38961
133 E01000136 Barnet 25840 7808 16988 38801
134 E01000137 Barnet 8611 1489 34995 38766
135 E01000138 Barnet 9114 10819 37260 38974
136 E01000139 Barnet 21727 2903 32009 38875
137 E01000140 Barnet 17164 807 38007 38766
138 E01000141 Barnet 8601 3536 41077 39058
139 E01000142 Barnet 17305 4219 39129 39058
140 E01000143 Barnet 7380 7315 39150 39083
141 E01000144 Barnet 15833 190 38560 39191
142 E01000145 Barnet 19310 2491 37468 39426
143 E01000146 Barnet 15647 254 40211 39186
144 E01000147 Barnet 21282 1978 35878 36523
145 E01000148 Barnet 9213 4312 39532 36218
146 E01000150 Barnet 18371 6114 33181 36727
147 E01000151 Barnet 4606 21774 37705 37356
148 E01000152 Barnet 6908 26301 40540 37846
149 E01000153 Barnet 3826 26858 39274 38095
150 E01000154 Barnet 6805 13158 41098 37356
151 E01000155 Barnet 13700 8808 40940 36589
152 E01000156 Barnet 26669 3027 28843 37647
153 E01000157 Barnet 21431 6478 25966 37647
154 E01000158 Barnet 14606 14431 37172 37272
155 E01000159 Barnet 17696 13104 18997 37030
156 E01000160 Barnet 22025 19505 35067 37577
157 E01000161 Barnet 19434 6768 37157 37906
158 E01000162 Barnet 15689 2269 38777 38272
159 E01000163 Barnet 8744 13112 21112 38148
160 E01000164 Barnet 10557 7400 26448 38233
161 E01000165 Barnet 20782 11826 33191 37943
162 E01000166 Barnet 19054 18596 5828 32279
163 E01000167 Barnet 8854 12977 2186 31541
164 E01000168 Barnet 28357 15027 20179 32707
165 E01000169 Barnet 20813 9277 9146 32573
166 E01000170 Barnet 14031 2112 20216 32573
167 E01000171 Barnet 11210 1649 31802 32002
168 E01000172 Barnet 26533 9842 15017 34179
169 E01000173 Barnet 24872 5984 25366 34358
170 E01000174 Barnet 17685 6059 27384 33225
171 E01000175 Barnet 27536 12797 21196 33327
172 E01000176 Barnet 7768 11377 33879 39064
173 E01000177 Barnet 26742 2283 36837 38541
174 E01000178 Barnet 27008 2430 37879 38632
175 E01000179 Barnet 26462 9271 38286 39064
176 E01000180 Barnet 19391 7019 32257 37965
177 E01000181 Barnet 26821 256 40621 37965
178 E01000182 Barnet 27057 1525 37461 36741
179 E01000183 Barnet 23760 6823 22976 38510
180 E01000184 Barnet 7110 7458 34936 38780
181 E01000185 Barnet 10299 5426 32701 39064
182 E01000186 Barnet 30326 4036 27569 33423
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1122 E01001140 Croydon 12982 14757 2768 38629
1123 E01001141 Croydon 9313 12152 487 38533
1124 E01001142 Croydon 13217 7003 8946 38533
1125 E01001143 Croydon 7941 7617 12447 38091
1126 E01001144 Croydon 5183 5337 21482 38930
1127 E01001145 Croydon 4281 3544 24909 38440
1128 E01001146 Croydon 14580 9850 32493 39051
1129 E01001147 Croydon 6270 4057 37133 38666
1130 E01001148 Croydon 11948 13212 31241 39051
1131 E01001149 Croydon 17888 12169 22058 39004
1132 E01001150 Croydon 13899 11224 6744 38983
1133 E01001151 Croydon 4019 3109 29434 38666
1134 E01001152 Croydon 5158 1488 37325 39051
1135 E01001153 Croydon 12275 4712 34045 39051
1136 E01001154 Croydon 8530 1305 33917 38983
1137 E01001155 Croydon 3291 1932 38117 39132
1138 E01001156 Croydon 10027 11881 10805 38085
1139 E01001157 Croydon 15973 18508 28667 38171
1140 E01001158 Croydon 13982 7671 7154 38983
1141 E01001159 Croydon 19487 22986 17665 38306
1142 E01001160 Croydon 20215 13218 27629 38051
1143 E01001161 Croydon 3575 9382 19649 37860
1144 E01001162 Croydon 8850 17475 24645 37255
1145 E01001163 Croydon 17644 14674 32485 37772
1146 E01001164 Croydon 13940 4571 37480 36901
1147 E01001165 Croydon 11281 23226 17535 33397
1148 E01001166 Croydon 7025 10837 34812 32744
1149 E01001167 Croydon 12891 9968 13309 31641
1150 E01001168 Croydon 13421 20954 18488 32239
1151 E01001169 Croydon 6795 3748 14449 28128
1152 E01001170 Croydon 9544 6861 22859 30662
1153 E01001171 Croydon 11031 10206 15476 29752
1154 E01001172 Croydon 3467 7564 31014 28044
1155 E01001173 Croydon 14566 25538 25975 27094
1156 E01001174 Croydon 12417 14342 40111 37779
1157 E01001175 Croydon 7742 2624 39985 38581
1158 E01001176 Croydon 12219 6764 40705 37694
1159 E01001177 Croydon 7251 21212 39751 34298
1160 E01001178 Croydon 1096 1806 40611 38920
1161 E01001179 Croydon 13775 3701 40465 37694
1162 E01001180 Croydon 9127 8336 40441 35607
1163 E01001181 Croydon 3607 3422 41128 36596
1164 E01001182 Croydon 13038 3810 38567 37875
1165 E01001183 Croydon 11301 9623 41182 37779
1166 E01001184 Croydon 17067 11738 37450 37779
1167 E01001185 Croydon 14358 7211 31145 37957
1168 E01001186 Croydon 8461 7633 26773 37303
1169 E01001187 Croydon 13847 13684 34038 38354
1170 E01001188 Croydon 8950 7732 32277 38374
1171 E01001189 Croydon 16383 6032 35491 36287
1172 E01001190 Croydon 9331 12421 28348 36384
1173 E01001191 Croydon 5914 4633 33240 37583
1174 E01001192 Croydon 9166 5272 28666 36331
1175 E01001193 Croydon 6123 23693 33355 38293
1176 E01001194 Croydon 15918 4262 33998 36331
1177 E01001195 Ealing 19967 12930 25955 39215
1178 E01001196 Ealing 4857 8776 36923 39275
1179 E01001197 Ealing 12321 9947 30093 38906
1180 E01001198 Ealing 19095 8159 36905 39275
1181 E01001199 Ealing 12563 2404 36696 38901
1182 E01001200 Ealing 17969 727 40152 39396
1183 E01001201 Ealing 16425 1296 38171 39396
1184 E01001202 Ealing 6344 550 41049 38827
1185 E01001203 Ealing 6778 80 40960 39396
1186 E01001204 Ealing 20285 9811 18452 38638
1187 E01001205 Ealing 7545 12952 19405 38036
1188 E01001206 Ealing 3637 17512 13764 38094
1189 E01001207 Ealing 17745 3998 31231 38259
1190 E01001208 Ealing 22354 10455 9529 37913
1191 E01001209 Ealing 28190 3666 4811 38636
1192 E01001210 Ealing 2075 14133 5369 37558
1193 E01001211 Ealing 24028 4988 2745 38862
1194 E01001212 Ealing 20550 10194 8857 38380
1195 E01001213 Ealing 8943 2652 28688 39344
1196 E01001214 Ealing 18010 2588 31417 38836
1197 E01001215 Ealing 7934 1773 36612 39344
1198 E01001216 Ealing 12636 11441 29542 39295
1199 E01001217 Ealing 17865 9846 28838 38151
1200 E01001218 Ealing 5429 14304 16166 38049
1201 E01001219 Ealing 5527 11355 14495 38514
1202 E01001220 Ealing 2523 14508 21219 38359
1203 E01001221 Ealing 11345 1591 39321 38965
1204 E01001222 Ealing 12874 97 39241 38683
1205 E01001223 Ealing 22559 8797 9662 38349
1206 E01001224 Ealing 25604 6504 11765 38537
1207 E01001225 Ealing 12984 525 19684 38787
1208 E01001226 Ealing 20668 10612 8186 38454
1209 E01001227 Ealing 24152 8056 17677 38343
1210 E01001228 Ealing 22860 5752 16779 38626
1211 E01001229 Ealing 7923 7627 29037 39791
1212 E01001230 Ealing 13358 9001 35234 39438
1213 E01001231 Ealing 20102 8330 30486 39625
1214 E01001232 Ealing 11537 15148 33198 39780
1215 E01001233 Ealing 11472 1797 33358 39791
1216 E01001234 Ealing 12109 12673 25214 38578
1217 E01001235 Ealing 19722 3113 26015 38578
1218 E01001236 Ealing 17674 4097 27615 39175
1219 E01001237 Ealing 16963 8810 17111 39780
1220 E01001238 Ealing 11044 4838 36599 39418
1221 E01001239 Ealing 6813 14339 33317 39406
1222 E01001240 Ealing 13977 2540 27611 39910
1223 E01001241 Ealing 12616 10444 39855 39598
1224 E01001242 Ealing 9639 10572 28493 39598
1225 E01001243 Ealing 10522 2905 38853 39628
1226 E01001244 Ealing 8569 3283 36645 39524
1227 E01001245 Ealing 18507 2933 40879 39603
1228 E01001246 Ealing 7075 13259 38240 39511
1229 E01001247 Ealing 13338 13768 41475 39215
1230 E01001248 Ealing 16655 8041 13658 37612
1231 E01001249 Ealing 3848 118 38456 37769
1232 E01001250 Ealing 5176 300 27620 37816
1233 E01001251 Ealing 15489 380 19339 38073
1234 E01001252 Ealing 10397 1189 26044 37919
1235 E01001253 Ealing 18300 4654 20996 37722
1236 E01001254 Ealing 19351 8554 3363 38173
1237 E01001255 Ealing 20547 3839 25330 37787
1238 E01001257 Ealing 4021 8663 18287 37316
1239 E01001258 Ealing 18071 749 8640 37072
1240 E01001259 Ealing 14241 1645 19660 37419
1241 E01001260 Ealing 13738 3298 8783 37404
1242 E01001261 Ealing 12265 1397 17471 37727
1243 E01001262 Ealing 7386 9032 780 37072
1244 E01001263 Ealing 6069 17160 3390 37161
1245 E01001264 Ealing 11124 14810 14386 37280
1246 E01001265 Ealing 13878 26324 25930 37852
1247 E01001266 Ealing 17834 13002 18974 38263
1248 E01001267 Ealing 7140 12293 21168 37392
1249 E01001268 Ealing 15642 15565 12728 37280
1250 E01001269 Ealing 20420 6916 20211 38228
1251 E01001270 Ealing 18289 19828 9918 37958
1252 E01001271 Ealing 17106 14560 22855 38299
1253 E01001272 Ealing 15184 11836 21274 38549
1254 E01001273 Ealing 25179 6176 26774 38918
1255 E01001274 Ealing 26422 10027 21431 38443
1256 E01001275 Ealing 15212 6083 17519 38787
1257 E01001276 Ealing 13885 29031 15591 40069
1258 E01001277 Ealing 16527 19318 31868 39500
1259 E01001278 Ealing 11526 16835 23652 39223
1260 E01001279 Ealing 28128 16024 7549 38812
1261 E01001280 Ealing 20279 19015 7559 38812
1262 E01001281 Ealing 27738 11518 1485 38971
1263 E01001282 Ealing 5881 7659 12142 37372
1264 E01001283 Ealing 4237 3730 8331 37523
1265 E01001284 Ealing 18191 7078 8495 37523
1266 E01001285 Ealing 11937 5853 13640 37372
1267 E01001286 Ealing 11665 13499 15813 37763
1268 E01001287 Ealing 7443 14122 4368 37734
1269 E01001288 Ealing 17925 4260 19779 37763
1270 E01001289 Ealing 18420 8165 24746 37763
1271 E01001290 Ealing 21401 2992 5146 37799
1272 E01001291 Ealing 14947 7262 24236 37679
1273 E01001292 Ealing 20084 4199 22915 37806
1274 E01001293 Ealing 16678 7139 24739 37882
1275 E01001294 Ealing 12398 8305 18021 37728
1276 E01001295 Ealing 16799 6188 25079 37877
1277 E01001296 Ealing 12764 2617 25861 38050
1278 E01001297 Ealing 11800 2348 17831 38752
1279 E01001298 Ealing 9045 1067 25589 38802
1280 E01001299 Ealing 27061 7755 9497 37622
1281 E01001300 Ealing 25967 1598 29039 38733
1282 E01001301 Ealing 14321 321 23745 39415
1283 E01001302 Ealing 22524 2856 23933 38169
1284 E01001303 Ealing 24632 3906 31842 39005
1285 E01001304 Ealing 19885 2131 28545 38422
1286 E01001305 Ealing 27464 2408 17265 37625
1287 E01001306 Ealing 26685 6204 25166 38327
1288 E01001307 Ealing 23210 7082 7262 37990
1289 E01001308 Ealing 22868 12778 26935 37635
1290 E01001309 Ealing 18839 15861 24073 36560
1291 E01001310 Ealing 15589 13091 18734 36743
1292 E01001311 Ealing 8519 19852 29756 36560
1293 E01001312 Ealing 17313 4285 20327 38165
1294 E01001313 Ealing 20272 11398 26173 36633
1295 E01001314 Ealing 23394 11106 6105 37487
1296 E01001315 Ealing 15913 9874 22643 37673
1297 E01001316 Ealing 7159 11329 13156 36946
1298 E01001317 Ealing 9896 4600 16762 36799
1299 E01001318 Ealing 5532 8907 17328 36946
1300 E01001319 Ealing 16095 11677 17005 37116
1301 E01001320 Ealing 3831 19707 16447 36066
1302 E01001321 Ealing 10147 10736 25958 37009
1303 E01001322 Ealing 11458 6117 7017 37631
1304 E01001323 Ealing 12015 2037 12952 36988
1305 E01001324 Ealing 6468 24865 30719 37316
1306 E01001325 Ealing 9812 19496 9548 35795
1307 E01001326 Ealing 6645 26958 29023 36028
1308 E01001327 Ealing 7636 7021 21992 35765
1309 E01001328 Ealing 6406 10757 25441 36558
1310 E01001329 Ealing 11307 7971 15109 35913
1311 E01001330 Ealing 3501 16259 29284 36558
1312 E01001331 Ealing 5126 6601 13546 35711
1313 E01001332 Ealing 4277 9841 8891 37316
1314 E01001333 Ealing 4369 3671 23471 38829
1315 E01001334 Ealing 3919 3243 8776 39473
1316 E01001335 Ealing 13665 12861 4806 39277
1317 E01001336 Ealing 10825 6245 12618 39652
1318 E01001337 Ealing 5627 16120 10734 38048
1319 E01001338 Ealing 9484 15236 37343 38714
1320 E01001339 Ealing 5657 5268 4735 38621
1321 E01001340 Ealing 4859 22906 25522 38221
1322 E01001341 Ealing 21235 8327 25180 38172
1323 E01001342 Ealing 19108 12287 16294 38248
1324 E01001343 Ealing 18564 10653 13063 37864
1325 E01001344 Ealing 15761 16558 8888 37892
1326 E01001345 Ealing 16547 14262 28937 39435
1327 E01001346 Ealing 22171 7360 29992 37488
1328 E01001347 Ealing 15517 14772 21169 38749
1329 E01001348 Ealing 14879 10922 22008 37766
1330 E01001349 Ealing 6422 20785 27848 37637
1331 E01001350 Ealing 17789 12950 35760 38599
1332 E01001351 Ealing 9030 235 41283 39709
1333 E01001352 Ealing 18684 4829 37467 38599
1334 E01001353 Ealing 11787 3246 22829 39515
1335 E01001354 Ealing 12592 1929 39722 39349
1336 E01001355 Ealing 11088 1177 38096 39870
1337 E01001356 Ealing 2863 455 37586 39709
1338 E01001357 Ealing 3722 3754 40360 40151
1339 E01001358 Ealing 2888 6437 41281 40399
1340 E01001359 Ealing 10824 1443 35613 39743
1341 E01001360 Ealing 8447 716 38304 39050
1342 E01001361 Ealing 6178 984 40502 39108
1343 E01001362 Ealing 8413 4580 39867 39510
1344 E01001363 Ealing 10083 5571 32741 39743
1345 E01001364 Ealing 3672 8896 32538 38752
1346 E01001365 Ealing 9026 6923 37171 39779
1347 E01001366 Ealing 8743 12935 33420 40454
1348 E01001367 Ealing 7890 2016 35889 39834
1349 E01001368 Ealing 8520 11462 33475 40109
1350 E01001369 Ealing 10823 1730 15212 39496
1351 E01001370 Ealing 10253 17874 26506 40668
1352 E01001371 Ealing 9509 8674 26770 40159
1353 E01001372 Ealing 7551 8207 18460 39496
1354 E01001373 Ealing 9995 1251 36242 39593
1355 E01001374 Ealing 23089 4407 35293 40253
1356 E01001375 Ealing 29992 1108 33316 39985
1357 E01001376 Ealing 11416 1884 35416 40253
1358 E01001377 Ealing 26779 5065 15559 39990
1359 E01001379 Ealing 28867 2546 36146 39985
1360 E01001380 Ealing 21610 6606 36999 40399
1361 E01001381 Ealing 16099 2155 41672 39751
1362 E01001382 Ealing 26572 3930 26771 38450
1363 E01001383 Ealing 22673 1987 29776 37669
1364 E01001384 Ealing 24713 834 30958 37669
1365 E01001385 Ealing 26344 2920 26724 38327
1366 E01001386 Ealing 24623 7733 30839 39146
1367 E01001387 Ealing 17508 700 15398 38763
1368 E01001388 Ealing 5956 145 34757 38319
1369 E01001389 Ealing 13509 425 31804 37669
1370 E01001390 Enfield 23838 4420 35180 38344
1371 E01001391 Enfield 10400 5757 30133 37949
1372 E01001392 Enfield 23651 6295 33967 38654
1373 E01001393 Enfield 15156 5478 35463 37949
1374 E01001394 Enfield 9612 6940 38546 38596
1375 E01001395 Enfield 5795 17921 27566 38860
1376 E01001396 Enfield 15197 2356 35402 38412
1377 E01001397 Enfield 10992 20629 32802 39122
1378 E01001398 Enfield 25510 5140 9119 37465
1379 E01001399 Enfield 23079 6526 32404 36955
1380 E01001400 Enfield 24050 4389 23382 36370
1381 E01001401 Enfield 21705 4984 31177 37643
1382 E01001402 Enfield 25812 2816 25003 35594
1383 E01001403 Enfield 18070 7866 31233 37911
1384 E01001404 Enfield 15105 18056 30421 39158
1385 E01001405 Enfield 22069 11694 5782 35645
1386 E01001406 Enfield 11086 3980 25592 37614
1387 E01001407 Enfield 15675 21588 8814 33623
1388 E01001408 Enfield 17296 13609 23925 32152
1389 E01001409 Enfield 5926 16329 17795 35699
1390 E01001410 Enfield 2967 21134 13709 35699
1391 E01001411 Enfield 20608 11782 28609 33298
1392 E01001412 Enfield 8853 36900 5320 31391
1393 E01001413 Enfield 27340 21231 3196 32502
1394 E01001414 Enfield 3518 23245 10832 31671
1395 E01001415 Enfield 18476 5302 26526 32465
1396 E01001416 Enfield 27463 23755 16462 34294
1397 E01001417 Enfield 26756 35023 3253 30363
1398 E01001418 Enfield 13494 4412 20984 32956
1399 E01001419 Enfield 18716 10893 19886 33324
1400 E01001420 Enfield 9953 10246 18696 34225
1401 E01001421 Enfield 9728 7456 20483 34647
1402 E01001422 Enfield 27233 32136 4638 29468
1403 E01001423 Enfield 7161 7705 26689 41412
1404 E01001424 Enfield 2918 6968 28849 41412
1405 E01001425 Enfield 2455 7646 15671 41314
1406 E01001426 Enfield 3965 7028 27204 41475
1407 E01001427 Enfield 3582 25212 39790 41181
1408 E01001428 Enfield 4845 11954 7305 41412
1409 E01001429 Enfield 2781 622 39234 41518
1410 E01001430 Enfield 3702 3865 19865 41518
1411 E01001431 Enfield 3388 10875 27269 41428
1412 E01001432 Enfield 4375 6742 33621 41518
1413 E01001433 Enfield 5499 20531 27589 36982
1414 E01001434 Enfield 8928 17582 33219 37076
1415 E01001435 Enfield 10023 8042 32672 36667
1416 E01001436 Enfield 8730 15441 36389 38058
1417 E01001437 Enfield 4642 33417 40091 36981
1418 E01001438 Enfield 5904 26097 28470 37595
1419 E01001439 Enfield 5806 3800 38487 37500
1420 E01001440 Enfield 7766 5009 34534 37398
1421 E01001441 Enfield 5182 2593 36897 36881
1422 E01001442 Enfield 3165 2086 34545 36505
1423 E01001444 Enfield 12215 13850 34909 36071
1424 E01001445 Enfield 8094 31149 12492 37684
1425 E01001446 Enfield 9085 3409 37011 36494
1426 E01001447 Enfield 3524 14234 35127 36872
1427 E01001448 Enfield 7950 10656 39042 36909
1428 E01001449 Enfield 8289 31031 22045 37331
1429 E01001450 Enfield 13223 4235 10543 35645
1430 E01001451 Enfield 17172 11134 1208 34500
1431 E01001452 Enfield 22909 13346 5615 33937
1432 E01001453 Enfield 29230 20633 9173 34747
1433 E01001454 Enfield 25609 14988 13163 33899
1434 E01001455 Enfield 23129 2704 10918 35871
1435 E01001456 Enfield 29825 2411 16544 34757
1436 E01001457 Enfield 20056 8422 7522 32839
1437 E01001458 Enfield 4196 12018 20888 40096
1438 E01001459 Enfield 11498 12301 38345 39074
1439 E01001460 Enfield 4797 2405 34062 40947
1440 E01001461 Enfield 4246 14282 19191 40030
1441 E01001462 Enfield 5863 7273 33522 40458
1442 E01001463 Enfield 12284 8569 28694 40182
1443 E01001464 Enfield 4782 14030 7266 41200
1444 E01001465 Enfield 11104 4994 25269 40342
1445 E01001466 Enfield 8860 9929 12706 41010
1446 E01001467 Enfield 9903 9725 23001 40529
1447 E01001468 Enfield 8107 18125 26755 29897
1448 E01001469 Enfield 11863 20661 17449 32390
1449 E01001470 Enfield 23825 11114 8097 30511
1450 E01001471 Enfield 16683 8296 10138 31556
1451 E01001472 Enfield 20183 5839 8483 32626
1452 E01001473 Enfield 17974 14833 665 33299
1453 E01001474 Enfield 20983 10091 9732 32293
1454 E01001475 Enfield 27973 21459 4833 33715
1455 E01001476 Enfield 9017 3841 37807 39407
1456 E01001477 Enfield 5893 10277 31803 37834
1457 E01001478 Enfield 10250 17377 32474 39152
1458 E01001479 Enfield 6554 682 39546 39928
1459 E01001480 Enfield 7739 16919 34371 38405
1460 E01001481 Enfield 9869 13929 37336 39928
1461 E01001482 Enfield 4720 6978 37709 39928
1462 E01001483 Enfield 1643 17875 24813 39752
1463 E01001484 Enfield 11064 16311 38354 39152
1464 E01001485 Enfield 5172 2186 36132 40833
1465 E01001486 Enfield 3856 10665 30059 41525
1466 E01001487 Enfield 5869 1668 38065 40559
1467 E01001488 Enfield 7798 8322 37441 40833
1468 E01001489 Enfield 7594 12160 35117 40838
1469 E01001491 Enfield 6746 4434 38172 40833
1470 E01001492 Enfield 7065 10874 35356 41525
1471 E01001493 Enfield 8384 8209 20235 39291
1472 E01001494 Enfield 18473 15656 36569 39299
1473 E01001495 Enfield 21557 2574 25621 39125
1474 E01001496 Enfield 19665 10669 20810 39217
1475 E01001497 Enfield 11718 19847 34270 39299
1476 E01001498 Enfield 16629 784 36731 38848
1477 E01001499 Enfield 11372 15697 37108 39116
1478 E01001500 Enfield 14503 8778 30164 38757
1479 E01001501 Enfield 9993 4100 32571 38757
1480 E01001502 Enfield 7448 10131 39001 39322
1481 E01001503 Enfield 8948 13085 37345 38759
1482 E01001504 Enfield 7894 5702 35999 38117
1483 E01001505 Enfield 6432 1423 36944 38253
1484 E01001506 Enfield 4674 12322 38766 37580
1485 E01001507 Enfield 4121 1529 40715 38642
1486 E01001508 Enfield 7139 2589 39946 38495
1487 E01001509 Enfield 6129 6233 32875 39189
1488 E01001510 Enfield 2622 10509 40881 38356
1489 E01001511 Enfield 12867 12126 37557 37324
1490 E01001512 Enfield 15781 10101 23983 36056
1491 E01001513 Enfield 6497 13776 35046 37036
1492 E01001514 Enfield 12968 16576 29871 37359
1493 E01001515 Enfield 5175 11283 33990 37614
1494 E01001516 Enfield 8539 18891 23113 36528
1495 E01001517 Enfield 2365 9855 32265 36611
1496 E01001518 Enfield 12462 9456 21601 36618
1497 E01001519 Enfield 20796 3039 32567 36659
1498 E01001520 Enfield 16603 15966 18833 36069
1499 E01001521 Enfield 25863 10358 4574 37493
1500 E01001522 Enfield 19881 10879 8388 34219
1501 E01001523 Enfield 26051 22345 12454 35657
1502 E01001524 Enfield 13445 18356 21376 35423
1503 E01001525 Enfield 17196 7348 27559 34919
1504 E01001526 Enfield 24301 26249 12775 35669
1505 E01001527 Enfield 18129 8928 17571 38587
1506 E01001528 Enfield 5918 12045 38291 38158
1507 E01001529 Enfield 6993 9132 34875 38078
1508 E01001530 Enfield 13931 4578 36588 38532
1509 E01001531 Enfield 26522 15571 1424 38517
1510 E01001532 Enfield 26409 5251 6935 38587
1511 E01001533 Enfield 28218 11164 14860 38852
1512 E01001534 Enfield 23107 11619 29936 38406
1513 E01001535 Enfield 19585 10281 23223 38695
1514 E01001536 Enfield 15451 1073 12246 34418
1515 E01001537 Enfield 22687 20010 5836 35099
1516 E01001538 Enfield 23188 10352 11401 35585
1517 E01001539 Enfield 18732 10285 20144 35099
1518 E01001540 Enfield 19677 10268 20518 32390
1519 E01001541 Enfield 24871 7925 23820 32501
1520 E01001542 Enfield 15570 5763 19231 35026
1521 E01001543 Enfield 24981 8560 8184 36098
1522 E01001544 Enfield 25045 1313 10715 34635
1523 E01001545 Enfield 2973 23434 19524 35770
1524 E01001546 Enfield 9083 4379 34920 35781
1525 E01001547 Enfield 8436 1790 36158 36179
1526 E01001548 Enfield 7056 11636 22345 35770
1527 E01001549 Enfield 3503 3117 29259 36276
1528 E01001550 Enfield 5526 10840 25765 36448
1529 E01001551 Enfield 3680 29446 20067 35144
1530 E01001552 Enfield 9954 11230 36313 36015
1531 E01001553 Enfield 4794 28826 25143 39572
1532 E01001554 Enfield 3713 3232 21680 40572
1533 E01001555 Enfield 6000 3739 35650 40572
1534 E01001556 Enfield 15029 25473 36208 38746
1535 E01001557 Enfield 7947 11786 35096 40863
1536 E01001558 Enfield 4348 2169 34510 41124
1537 E01001559 Enfield 3951 19676 34034 40476
1538 E01001560 Enfield 6067 25521 34483 38527
1539 E01001562 Enfield 2725 31691 35635 40096
1540 E01001563 Enfield 17402 4049 21912 37366
1541 E01001564 Enfield 24184 4227 10591 37366
1542 E01001565 Enfield 17684 8260 6114 38774
1543 E01001566 Enfield 20017 1421 13732 38762
1544 E01001567 Enfield 29111 10162 12250 35457
1545 E01001568 Enfield 24723 14496 2050 37412
1546 E01001569 Enfield 24037 2786 11496 35594
1547 E01001570 Enfield 16189 4647 23152 37653
1548 E01001571 Greenwich 16175 7661 33702 39633
1549 E01001572 Greenwich 18456 8468 28780 39633
1550 E01001573 Greenwich 18225 7239 36557 39633
1551 E01001574 Greenwich 4479 9074 18445 38777
1552 E01001575 Greenwich 2565 4027 4713 39533
1553 E01001576 Greenwich 4419 7287 7957 39633
1554 E01001577 Greenwich 6440 9264 8833 39633
1555 E01001578 Greenwich 9697 12970 32622 39633
1556 E01001579 Greenwich 4983 13130 14341 39633
1557 E01001580 Greenwich 23584 3438 15795 39080
1558 E01001581 Greenwich 13999 61 31116 40630
1559 E01001582 Greenwich 11864 7175 26339 38373
1560 E01001583 Greenwich 20534 15575 20376 39386
1561 E01001584 Greenwich 26016 16086 16396 38355
1562 E01001585 Greenwich 21113 10730 18825 39970
1563 E01001586 Greenwich 11294 8279 9256 39606
1564 E01001587 Greenwich 22066 13762 11715 39007
1565 E01001588 Greenwich 5533 1611 13574 40335
1566 E01001589 Greenwich 9174 8230 14920 40979
1567 E01001590 Greenwich 15901 13851 30731 40710
1568 E01001591 Greenwich 7189 10846 15370 40839
1569 E01001592 Greenwich 19244 9635 36772 40635
1570 E01001593 Greenwich 22827 3599 38266 40468
1571 E01001594 Greenwich 5415 7269 31359 40635
1572 E01001595 Greenwich 11892 10930 31189 39812
1573 E01001596 Greenwich 25312 12055 38744 33772
1574 E01001597 Greenwich 18757 16502 40740 35283
1575 E01001598 Greenwich 19780 11476 39210 34553
1576 E01001599 Greenwich 16636 12226 37498 34202
1577 E01001600 Greenwich 20482 16557 41125 34633
1578 E01001601 Greenwich 23383 7933 37238 33772
1579 E01001602 Greenwich 6918 3466 38309 33415
1580 E01001603 Greenwich 5305 4546 38869 33181
1581 E01001604 Greenwich 20549 2776 39381 37817
1582 E01001605 Greenwich 28074 22686 39696 37995
1583 E01001606 Greenwich 28995 17137 39470 38612
1584 E01001607 Greenwich 16263 9082 36615 38612
1585 E01001608 Greenwich 19688 8191 35822 36189
1586 E01001609 Greenwich 12789 306 41176 37145
1587 E01001610 Greenwich 21169 15471 33354 38656
1588 E01001611 Greenwich 15294 14768 35983 38674
1589 E01001613 Greenwich 14317 7977 35108 34729
1590 E01001614 Greenwich 26343 19774 23233 35247
1591 E01001615 Greenwich 14143 1674 40905 35003
1592 E01001617 Greenwich 26084 14969 32753 34680
1593 E01001618 Greenwich 11623 11682 30111 34363
1594 E01001619 Greenwich 19186 21220 40099 34737
1595 E01001620 Greenwich 7205 11908 40589 37607
1596 E01001621 Greenwich 7132 6280 38032 37544
1597 E01001623 Greenwich 10924 15963 39293 38382
1598 E01001624 Greenwich 10556 12882 35230 38519
1599 E01001625 Greenwich 4073 14937 40616 38128
1600 E01001629 Greenwich 7852 13516 31735 39165
1601 E01001631 Greenwich 6211 8141 31831 39165
1602 E01001632 Greenwich 15631 4917 38691 38764
1603 E01001633 Greenwich 6202 6011 32499 37904
1604 E01001634 Greenwich 3802 6212 31597 38465
1605 E01001635 Greenwich 11906 7423 37300 38243
1606 E01001636 Greenwich 10378 5599 39023 38243
1607 E01001637 Greenwich 9554 4430 34877 37904
1608 E01001638 Greenwich 8986 9209 24798 38941
1609 E01001640 Greenwich 7763 2835 11965 40048
1610 E01001641 Greenwich 17618 2074 17757 40112
1611 E01001642 Greenwich 22742 6619 3364 39163
1612 E01001644 Greenwich 16768 1589 15175 39595
1613 E01001645 Greenwich 9118 11052 28030 38382
1614 E01001646 Greenwich 10745 15791 38605 38797
1615 E01001647 Greenwich 13052 7337 29204 38341
1616 E01001648 Greenwich 15054 20406 31423 38834
1617 E01001649 Greenwich 5827 20867 39167 38634
1618 E01001650 Greenwich 7097 8754 32456 39812
1619 E01001651 Greenwich 3333 12628 21809 39357
1620 E01001652 Greenwich 16562 6457 31437 39560
1621 E01001653 Greenwich 3995 13816 38063 36354
1622 E01001654 Greenwich 4285 24864 33592 37005
1623 E01001655 Greenwich 3586 14807 34851 35824
1624 E01001656 Greenwich 15898 28586 25557 38358
1625 E01001657 Greenwich 23034 6255 19392 38408
1626 E01001658 Greenwich 15955 13785 29807 38113
1627 E01001659 Greenwich 13757 14228 32910 37562
1628 E01001660 Greenwich 6434 22087 32284 37325
1629 E01001661 Greenwich 5857 19080 33351 36200
1630 E01001662 Greenwich 12724 690 30936 39232
1631 E01001664 Greenwich 13303 2282 20684 39615
1632 E01001665 Greenwich 16860 3783 33175 39879
1633 E01001666 Greenwich 10546 11015 37344 41229
1634 E01001667 Greenwich 3574 16333 34223 40873
1635 E01001668 Greenwich 9655 2159 15436 39817
1636 E01001669 Greenwich 9131 20986 29467 38624
1637 E01001671 Greenwich 12091 8792 37716 38499
1638 E01001672 Greenwich 9511 981 39964 39612
1639 E01001673 Greenwich 5579 1233 39113 39308
1640 E01001674 Greenwich 12679 3120 35885 39436
1641 E01001675 Greenwich 8659 754 38638 38483
1642 E01001676 Greenwich 8863 6642 34560 39343
1643 E01001677 Greenwich 14595 3654 38859 38499
1644 E01001678 Greenwich 19867 9630 37167 37552
1645 E01001679 Greenwich 20502 16225 27866 38490
1646 E01001680 Greenwich 25987 21399 23564 37986
1647 E01001681 Greenwich 15871 9981 29451 37511
1648 E01001682 Greenwich 15940 16229 22396 38126
1649 E01001683 Greenwich 12171 1090 39216 37545
1650 E01001684 Greenwich 10933 10365 30086 37844
1651 E01001685 Greenwich 16704 5633 39785 37545
1652 E01001686 Greenwich 13909 14414 31001 38269
1653 E01001687 Greenwich 5655 10142 7529 39416
1654 E01001688 Greenwich 9824 12198 8074 38814
1655 E01001690 Greenwich 8164 31536 14883 39241
1656 E01001692 Greenwich 8020 7789 21029 39148
1657 E01001693 Greenwich 6383 25559 23874 39241
1658 E01001694 Greenwich 11923 20837 2743 39452
1659 E01001695 Greenwich 5276 6908 27195 38957
1660 E01001696 Greenwich 5270 491 34787 39334
1661 E01001697 Greenwich 6293 7346 31764 38710
1662 E01001698 Greenwich 8235 9526 36695 37873
1663 E01001699 Greenwich 10944 12101 20593 39247
1664 E01001700 Greenwich 7478 5384 35254 38350
1665 E01001701 Greenwich 8286 28686 35991 38597
1666 E01001702 Greenwich 4923 27247 40394 37873
1667 E01001703 Greenwich 7158 5355 30840 37511
1668 E01001704 Greenwich 11676 8063 37073 37511
1669 E01001705 Greenwich 6839 4814 12539 39863
1670 E01001706 Greenwich 4427 11547 19450 40394
1671 E01001708 Greenwich 13833 12175 25087 40685
1672 E01001709 Greenwich 5099 22666 37215 41012
1673 E01001710 Greenwich 6464 9486 13017 40394
1674 E01001711 Greenwich 9120 17491 20077 41197
1675 E01001712 Greenwich 7387 3868 7322 39863
1676 E01001713 Greenwich 5191 11374 17788 40394
1677 E01001714 Hackney 3216 911 6352 40488
1678 E01001715 Hackney 8857 2780 8815 40533
1679 E01001716 Hackney 5179 5622 19672 40461
1680 E01001717 Hackney 9310 3862 15615 40770
1681 E01001718 Hackney 14212 4010 28925 40805
1682 E01001719 Hackney 5629 3683 24850 40732
1683 E01001720 Hackney 14558 2970 26994 40784
1684 E01001722 Hackney 7202 2069 31046 40648
1685 E01001723 Hackney 12151 4471 19903 40268
1686 E01001724 Hackney 10562 3146 36818 40145
1687 E01001725 Hackney 9853 7422 23435 39976
1688 E01001726 Hackney 6738 3171 24641 40050
1689 E01001727 Hackney 12316 5572 20172 40336
1690 E01001728 Hackney 7754 313 23325 40336
1691 E01001729 Hackney 3718 488 36934 41178
1692 E01001730 Hackney 2897 1487 34196 41178
1693 E01001731 Hackney 7474 1481 36600 41316
1694 E01001732 Hackney 4530 572 33385 41294
1695 E01001733 Hackney 6917 2347 28073 41159
1696 E01001734 Hackney 5446 1270 34445 40883
1697 E01001735 Hackney 5831 755 33569 41178
1698 E01001736 Hackney 13149 5139 34634 40779
1699 E01001737 Hackney 11026 1535 32057 41054
1700 E01001738 Hackney 12095 1843 32729 41256
1701 E01001739 Hackney 10312 813 35406 40915
1702 E01001740 Hackney 3274 4048 34869 40974
1703 E01001741 Hackney 16337 2185 32494 40479
1704 E01001742 Hackney 8495 1354 26245 40766
1705 E01001744 Hackney 7078 510 24664 41350
1706 E01001745 Hackney 5257 5357 36712 40619
1707 E01001746 Hackney 5801 11228 31698 40648
1708 E01001747 Hackney 7514 1346 40282 40619
1709 E01001748 Hackney 6737 763 36474 41051
1710 E01001749 Hackney 7497 2192 28873 41350
1711 E01001750 Hackney 5518 2590 12576 41581
1712 E01001751 Hackney 15464 7494 13277 41309
1713 E01001752 Hackney 9681 4974 22650 41564
1714 E01001753 Hackney 5565 4949 15994 41564
1715 E01001754 Hackney 7318 2317 17871 41674
1716 E01001755 Hackney 4241 901 21907 41696
1717 E01001756 Hackney 11738 3825 31496 41309
1718 E01001757 Hackney 7129 1903 34530 40648
1719 E01001758 Hackney 4616 4935 37770 41023
1720 E01001759 Hackney 8528 6945 32160 40648
1721 E01001760 Hackney 4504 1032 39415 41125
1722 E01001761 Hackney 2627 4565 35914 41162
1723 E01001762 Hackney 9543 4752 39560 41023
1724 E01001763 Hackney 12683 3377 27360 41332
1725 E01001764 Hackney 8634 6810 34377 40535
1726 E01001765 Hackney 3374 7522 31924 40547
1727 E01001767 Hackney 6287 4827 15768 40648
1728 E01001768 Hackney 11196 4542 24169 40648
1729 E01001769 Hackney 9723 4007 23903 40466
1730 E01001770 Hackney 6158 4026 29881 40648
1731 E01001772 Hackney 3791 3514 19470 41581
1732 E01001773 Hackney 4810 2600 20946 41696
1733 E01001774 Hackney 8923 4864 31235 41628
1734 E01001775 Hackney 4495 3478 22328 41628
1735 E01001776 Hackney 2862 2758 24601 41696
1736 E01001777 Hackney 6154 1016 34794 41682
1737 E01001779 Hackney 7718 930 18000 41648
1738 E01001780 Hackney 4965 2205 36788 41670
1739 E01001781 Hackney 3123 905 9793 41674
1740 E01001782 Hackney 13505 4564 11896 41648
1741 E01001783 Hackney 4695 1329 7829 41648
1742 E01001784 Hackney 9803 1959 28895 41682
1743 E01001785 Hackney 7676 138 21144 41159
1744 E01001786 Hackney 4889 797 8901 40965
1745 E01001787 Hackney 3371 11251 5427 41013
1746 E01001788 Hackney 3601 5191 3913 41013
1747 E01001789 Hackney 9211 4700 14733 41028
1748 E01001790 Hackney 1876 3982 6163 41289
1749 E01001791 Hackney 6994 2064 21292 41159
1750 E01001792 Hackney 6784 7364 16933 40883
1751 E01001793 Hackney 10841 7483 23775 41028
1752 E01001794 Hackney 9886 1982 31398 40883
1753 E01001795 Hackney 7320 4384 28503 40883
1754 E01001796 Hackney 8807 4881 28458 41028
1755 E01001798 Hackney 2769 3335 15428 40883
1756 E01001799 Hackney 9863 4698 21425 40050
1757 E01001800 Hackney 4523 5711 30604 40145
1758 E01001801 Hackney 7336 8346 12035 40437
1759 E01001802 Hackney 6460 6578 16687 40474
1760 E01001803 Hackney 18241 4945 3560 40732
1761 E01001804 Hackney 9895 6886 3681 40474
1762 E01001805 Hackney 9451 2761 21532 40145
1763 E01001806 Hackney 8025 3082 21109 40479
1764 E01001807 Hackney 8454 7707 15998 40245
1765 E01001808 Hackney 7625 539 30588 40050
1766 E01001809 Hackney 9795 3956 23524 39945
1767 E01001811 Hackney 2394 18807 2348 40015
1768 E01001812 Hackney 8096 2599 9201 40373
1769 E01001813 Hackney 2413 3966 5282 40448
1770 E01001814 Hackney 6783 1706 36303 39911
1771 E01001815 Hackney 5285 6676 19266 41532
1772 E01001816 Hackney 10641 6249 25022 41332
1773 E01001819 Hackney 9108 2596 17344 41529
1774 E01001820 Hackney 3969 8393 23954 41628
1775 E01001821 Hackney 3434 7900 25924 41514
1776 E01001822 Hackney 2917 3025 17245 40336
1777 E01001823 Hackney 8874 20203 18515 39853
1778 E01001824 Hackney 6317 6870 12544 39853
1779 E01001825 Hackney 9633 9507 22206 39898
1780 E01001826 Hackney 6162 7008 19192 39976
1781 E01001827 Hackney 5244 4801 11881 39853
1782 E01001828 Hackney 6187 6144 7158 40302
1783 E01001829 Hackney 17491 2210 33739 40241
1784 E01001830 Hackney 6903 1940 35868 40449
1785 E01001831 Hackney 8414 1300 38712 40241
1786 E01001832 Hackney 8976 2434 36106 40449
1787 E01001833 Hackney 7150 7775 37059 40519
1788 E01001834 Hackney 7666 3639 37553 40601
1789 E01001835 Hackney 13308 2900 39016 40601
1790 E01001836 Hackney 10064 5200 19417 41384
1791 E01001837 Hackney 16914 1701 5702 41481
1792 E01001838 Hackney 2780 638 24036 41316
1793 E01001839 Hackney 4640 129 35470 41445
1794 E01001840 Hackney 4256 1030 21494 41294
1795 E01001841 Hackney 7204 4901 2823 41177
1796 E01001842 Hackney 4411 1200 18830 41462
1797 E01001843 Hackney 7074 870 19370 41384
1798 E01001844 Hackney 9624 890 32254 41294
1799 E01001845 Hackney 2027 1962 28378 40991
1800 E01001846 Hackney 2705 6382 9571 41082
1801 E01001847 Hackney 1315 195 27730 40964
1802 E01001848 Hackney 4298 150 30668 41091
1803 E01001849 Hackney 6227 6012 14798 41082
1804 E01001850 Hackney 3486 1736 29051 40991
1805 E01001851 Hammersmith and Fulham 20771 844 39024 40288
1806 E01001852 Hammersmith and Fulham 17221 1101 40583 40524
1807 E01001853 Hammersmith and Fulham 13706 956 37739 40288
1808 E01001854 Hammersmith and Fulham 15003 1832 39349 40288
1809 E01001855 Hammersmith and Fulham 15740 2541 39554 40524
1810 E01001856 Hammersmith and Fulham 7267 278 35219 40288
1811 E01001857 Hammersmith and Fulham 4267 1600 40824 40288
1812 E01001858 Hammersmith and Fulham 7701 6547 37826 40118
1813 E01001859 Hammersmith and Fulham 14141 5659 38131 39632
1814 E01001860 Hammersmith and Fulham 7131 1400 39402 39895
1815 E01001861 Hammersmith and Fulham 7937 3566 40049 39844
1816 E01001862 Hammersmith and Fulham 6802 5298 35794 40127
1817 E01001863 Hammersmith and Fulham 15265 3352 39782 40127
1818 E01001864 Hammersmith and Fulham 8604 1406 40427 40118
1819 E01001865 Hammersmith and Fulham 20324 4013 40568 39866
1820 E01001866 Hammersmith and Fulham 19847 2850 39028 39993
1821 E01001867 Hammersmith and Fulham 20289 286 26629 39338
1822 E01001868 Hammersmith and Fulham 5585 3288 35766 40088
1823 E01001869 Hammersmith and Fulham 19649 2079 25799 39648
1824 E01001870 Hammersmith and Fulham 17083 4311 38834 40088
1825 E01001871 Hammersmith and Fulham 21856 2731 32655 39881
1826 E01001872 Hammersmith and Fulham 18352 4773 31738 40088
1827 E01001873 Hammersmith and Fulham 12256 3441 36231 39909
1828 E01001874 Hammersmith and Fulham 11438 15377 36560 39761
1829 E01001875 Hammersmith and Fulham 6449 2048 32840 39919
1830 E01001876 Hammersmith and Fulham 5098 26856 38442 39831
1831 E01001877 Hammersmith and Fulham 6532 15007 32376 39714
1832 E01001878 Hammersmith and Fulham 5979 2871 22860 40197
1833 E01001879 Hammersmith and Fulham 12354 1326 36978 39688
1834 E01001880 Hammersmith and Fulham 13446 2049 37960 40210
1835 E01001881 Hammersmith and Fulham 18973 665 40600 39921
1836 E01001882 Hammersmith and Fulham 20454 1652 40410 39921
1837 E01001883 Hammersmith and Fulham 11772 969 40937 40538
1838 E01001884 Hammersmith and Fulham 10214 144 40787 39921
1839 E01001885 Hammersmith and Fulham 2091 2139 35065 39688
1840 E01001886 Hammersmith and Fulham 10269 1378 35051 38696
1841 E01001887 Hammersmith and Fulham 11893 194 21576 38696
1842 E01001888 Hammersmith and Fulham 23550 3744 16132 37472
1843 E01001889 Hammersmith and Fulham 14425 3007 29034 39003
1844 E01001890 Hammersmith and Fulham 20292 2151 27648 38539
1845 E01001891 Hammersmith and Fulham 22811 1209 24582 37885
1846 E01001892 Hammersmith and Fulham 8819 5544 35516 39239
1847 E01001893 Hammersmith and Fulham 6342 2591 25348 38505
1848 E01001894 Hammersmith and Fulham 7814 5802 40597 39012
1849 E01001895 Hammersmith and Fulham 14790 3300 36748 40229
1850 E01001896 Hammersmith and Fulham 12744 53 34513 40229
1851 E01001897 Hammersmith and Fulham 18490 2274 30885 39582
1852 E01001898 Hammersmith and Fulham 12598 202 40173 39432
1853 E01001899 Hammersmith and Fulham 3413 2763 38588 39378
1854 E01001900 Hammersmith and Fulham 5414 998 33374 38213
1855 E01001901 Hammersmith and Fulham 23507 1276 37778 39091
1856 E01001902 Hammersmith and Fulham 18248 959 39937 39091
1857 E01001903 Hammersmith and Fulham 10447 908 37342 38696
1858 E01001904 Hammersmith and Fulham 25162 5967 36598 38249
1859 E01001905 Hammersmith and Fulham 28139 756 31941 38479
1860 E01001906 Hammersmith and Fulham 24988 1864 31119 38425
1861 E01001907 Hammersmith and Fulham 22696 1385 31203 38425
1862 E01001908 Hammersmith and Fulham 16979 2233 40052 40088
1863 E01001909 Hammersmith and Fulham 12383 2722 37419 39978
1864 E01001910 Hammersmith and Fulham 15768 7416 36245 39978
1865 E01001911 Hammersmith and Fulham 6011 734 35621 40285
1866 E01001912 Hammersmith and Fulham 5706 667 38752 40285
1867 E01001913 Hammersmith and Fulham 23554 1415 36422 39978
1868 E01001914 Hammersmith and Fulham 14365 2530 40393 40088
1869 E01001915 Hammersmith and Fulham 21120 6125 3821 37276
1870 E01001916 Hammersmith and Fulham 28505 11346 9659 38027
1871 E01001917 Hammersmith and Fulham 18372 6532 7474 37249
1872 E01001918 Hammersmith and Fulham 23841 7216 19911 37642
1873 E01001919 Hammersmith and Fulham 26263 8201 13177 37249
1874 E01001920 Hammersmith and Fulham 7494 2275 34269 40222
1875 E01001921 Hammersmith and Fulham 15164 1588 29902 39662
1876 E01001922 Hammersmith and Fulham 22079 29 34022 39380
1877 E01001923 Hammersmith and Fulham 16437 2532 26990 39301
1878 E01001924 Hammersmith and Fulham 25569 1138 26164 38535
1879 E01001925 Hammersmith and Fulham 25768 817 29550 38535
1880 E01001926 Hammersmith and Fulham 28809 4159 27350 38469
1881 E01001927 Hammersmith and Fulham 25171 6855 26909 39866
1882 E01001928 Hammersmith and Fulham 13864 7824 33984 39901
1883 E01001929 Hammersmith and Fulham 21853 5378 36574 39901
1884 E01001930 Hammersmith and Fulham 7537 3634 27933 39775
1885 E01001931 Hammersmith and Fulham 15702 1921 36365 39707
1886 E01001932 Hammersmith and Fulham 10242 6301 36861 39724
1887 E01001933 Hammersmith and Fulham 13652 3049 31888 39707
1888 E01001934 Hammersmith and Fulham 11507 10592 12872 38040
1889 E01001935 Hammersmith and Fulham 17011 2503 26587 38858
1890 E01001937 Hammersmith and Fulham 20728 2138 26505 38040
1891 E01001938 Hammersmith and Fulham 9309 5749 31209 38558
1892 E01001939 Hammersmith and Fulham 13510 9084 26126 39512
1893 E01001940 Hammersmith and Fulham 5966 1353 38375 40229
1894 E01001941 Hammersmith and Fulham 7925 451 41564 40043
1895 E01001942 Hammersmith and Fulham 11283 776 39431 40127
1896 E01001943 Hammersmith and Fulham 6650 3531 41561 40006
1897 E01001944 Hammersmith and Fulham 3478 9416 38823 39701
1898 E01001945 Hammersmith and Fulham 10706 1904 39966 39906
1899 E01001946 Hammersmith and Fulham 12811 3229 40010 39906
1900 E01001947 Hammersmith and Fulham 5002 819 35325 39236
1901 E01001948 Hammersmith and Fulham 19353 185 38809 38469
1902 E01001949 Hammersmith and Fulham 27040 1091 35943 39091
1903 E01001950 Hammersmith and Fulham 24876 428 38882 39236
1904 E01001951 Hammersmith and Fulham 16651 2073 31435 38469
1905 E01001952 Hammersmith and Fulham 18223 2654 27217 38425
1906 E01001953 Hammersmith and Fulham 12704 274 40875 39475
1907 E01001954 Hammersmith and Fulham 9370 2218 40977 40161
1908 E01001955 Hammersmith and Fulham 4877 8771 36671 40161
1909 E01001956 Hammersmith and Fulham 9420 3595 37179 39841
1910 E01001957 Hammersmith and Fulham 4637 14974 33144 39884
1911 E01001958 Hammersmith and Fulham 4675 14932 36364 40011
1912 E01001959 Hammersmith and Fulham 4238 6926 30769 39841
1913 E01001960 Hammersmith and Fulham 15773 3231 41151 40161
1914 E01001961 Hammersmith and Fulham 3771 9235 38609 40161
1915 E01001962 Haringey 18441 8679 6464 37921
1916 E01001963 Haringey 26300 3767 14607 37721
1917 E01001964 Haringey 19124 9171 17142 37194
1918 E01001965 Haringey 23030 7387 21550 37198
1919 E01001966 Haringey 20730 6304 7688 37237
1920 E01001967 Haringey 25963 7920 7234 37198
1921 E01001968 Haringey 23140 4648 15609 37198
1922 E01001969 Haringey 9566 5087 28679 37515
1923 E01001970 Haringey 9598 4505 26881 37543
1924 E01001971 Haringey 4922 1872 24410 37333
1925 E01001972 Haringey 9943 10939 20999 37333
1926 E01001973 Haringey 15884 4880 21742 38311
1927 E01001974 Haringey 14821 1244 32667 37979
1928 E01001975 Haringey 13355 2102 35692 37515
1929 E01001976 Haringey 4917 7056 33712 40506
1930 E01001977 Haringey 3940 6985 35709 40491
1931 E01001978 Haringey 4152 4593 30206 40491
1932 E01001979 Haringey 3861 1367 34074 40506
1933 E01001980 Haringey 8788 7230 37150 40258
1934 E01001981 Haringey 8167 3225 37896 40517
1935 E01001982 Haringey 7077 3753 37703 40140
1936 E01001983 Haringey 9236 4025 39017 40140
1937 E01001984 Haringey 14754 5316 7572 38284
1938 E01001985 Haringey 24521 3418 15790 38059
1939 E01001986 Haringey 21667 5652 28661 38914
1940 E01001987 Haringey 25129 19009 10608 37521
1941 E01001988 Haringey 17894 3737 21227 38284
1942 E01001989 Haringey 19138 1023 29065 38278
1943 E01001990 Haringey 18313 336 40135 38278
1944 E01001991 Haringey 18931 304 15980 37198
1945 E01001992 Haringey 27577 6124 17251 37713
1946 E01001993 Haringey 28651 5806 18854 37304
1947 E01001994 Haringey 24362 14763 16287 37058
1948 E01001995 Haringey 10079 16338 19017 38288
1949 E01001996 Haringey 24875 10021 20565 37713
1950 E01001997 Haringey 19221 3065 25795 37198
1951 E01001998 Haringey 16516 3722 32358 39018
1952 E01001999 Haringey 9806 360 38258 39070
1953 E01002000 Haringey 15505 4396 27943 39366
1954 E01002001 Haringey 13735 1947 22894 39366
1955 E01002002 Haringey 4676 2702 23157 40305
1956 E01002003 Haringey 5261 1510 37658 38625
1957 E01002004 Haringey 15817 1252 34620 39070
1958 E01002005 Haringey 17870 9764 34125 37535
1959 E01002006 Haringey 18324 9852 13741 37547
1960 E01002007 Haringey 22397 4835 14609 37521
1961 E01002008 Haringey 25611 9864 5820 37421
1962 E01002009 Haringey 21826 5975 9865 37547
1963 E01002010 Haringey 14235 8218 10871 36827
1964 E01002011 Haringey 13214 3866 10386 37208
1965 E01002013 Haringey 22009 7815 14307 37245
1966 E01002014 Haringey 13122 4923 29123 38143
1967 E01002015 Haringey 9999 8517 24705 37982
1968 E01002016 Haringey 13101 3644 32390 38607
1969 E01002017 Haringey 11671 3305 30293 38143
1970 E01002018 Haringey 9786 13832 4687 37245
1971 E01002019 Haringey 27449 2350 10709 37376
1972 E01002020 Haringey 16855 4645 13441 37198
1973 E01002021 Haringey 24077 5430 8472 37198
1974 E01002022 Haringey 19545 1694 25534 37376
1975 E01002023 Haringey 18466 6656 20210 37198
1976 E01002024 Haringey 16274 79 32389 37785
1977 E01002025 Haringey 27147 12487 27159 37376
1978 E01002026 Haringey 2796 326 41080 38771
1979 E01002027 Haringey 8044 6170 35719 38771
1980 E01002028 Haringey 9520 3080 38109 39358
1981 E01002029 Haringey 5426 462 38761 38055
1982 E01002030 Haringey 12975 1563 35500 38055
1983 E01002031 Haringey 6590 946 39262 38690
1984 E01002032 Haringey 5050 5963 34954 38919
1985 E01002033 Haringey 4748 2995 33201 38771
1986 E01002034 Haringey 1966 3963 40029 39829
1987 E01002036 Haringey 1464 13460 36513 39773
1988 E01002037 Haringey 3076 20618 31448 39883
1989 E01002038 Haringey 2736 7621 33469 40023
1990 E01002039 Haringey 1411 7976 24097 39836
1991 E01002040 Haringey 2791 13711 21008 39915
1992 E01002041 Haringey 4881 11161 34405 40102
1993 E01002042 Haringey 15502 2475 36001 39472
1994 E01002043 Haringey 9360 1071 38211 39535
1995 E01002044 Haringey 11412 12 34793 39332
1996 E01002045 Haringey 8899 1292 34256 39556
1997 E01002046 Haringey 7221 3032 26085 39556
1998 E01002047 Haringey 11874 1192 33491 39332
1999 E01002048 Haringey 10638 1605 38179 39313
2000 E01002049 Haringey 7343 2773 36567 39535
2001 E01002050 Haringey 11791 13467 31449 39832
2002 E01002051 Haringey 5369 7864 31303 39825
2003 E01002052 Haringey 8956 16164 21391 40086
2004 E01002053 Haringey 5534 9105 23968 39945
2005 E01002054 Haringey 5281 4047 15216 39556
2006 E01002055 Haringey 11825 6891 34623 39832
2007 E01002056 Haringey 8479 8489 27054 39972
2008 E01002057 Haringey 12189 16657 38219 39800
2009 E01002058 Haringey 10897 11921 30266 39940
2010 E01002059 Haringey 13380 14711 9024 39143
2011 E01002060 Haringey 22247 10699 19096 39143
2012 E01002061 Haringey 19827 14718 6760 39356
2013 E01002062 Haringey 18183 6648 4036 39355
2014 E01002063 Haringey 12876 5907 1397 39566
2015 E01002064 Haringey 7606 105 12046 39566
2016 E01002065 Haringey 9234 617 11239 40031
2017 E01002066 Haringey 2497 2945 34443 40528
2018 E01002067 Haringey 4260 1954 36148 40140
2019 E01002068 Haringey 7220 3525 35647 40199
2020 E01002069 Haringey 4272 3741 35780 40176
2021 E01002070 Haringey 10051 6042 38098 39849
2022 E01002071 Haringey 1685 4399 34135 40199
2023 E01002072 Haringey 5544 10370 35977 40070
2024 E01002073 Haringey 4466 6013 32392 40176
2025 E01002074 Haringey 4179 9499 30170 40225
2026 E01002075 Haringey 6284 14221 19287 39915
2027 E01002076 Haringey 6556 4933 20448 40001
2028 E01002077 Haringey 4915 168 31975 40344
2029 E01002078 Haringey 6136 24594 39 39950
2030 E01002079 Haringey 9991 1577 27118 40001
2031 E01002080 Haringey 7760 7087 26699 40012
2032 E01002081 Haringey 2971 5784 30316 40522
2033 E01002082 Haringey 546 5573 33120 40406
2034 E01002083 Haringey 16376 3987 38582 39458
2035 E01002084 Haringey 9491 6898 33816 39623
2036 E01002085 Haringey 8908 1846 37208 38690
2037 E01002086 Haringey 6661 6758 32827 40071
2038 E01002087 Haringey 5776 2583 34745 39303
2039 E01002088 Haringey 11266 5150 36825 39458
2040 E01002089 Haringey 2662 14020 33247 40406
2041 E01002090 Haringey 4418 21586 37777 38627
2042 E01002091 Haringey 3886 24052 31763 39048
2043 E01002092 Haringey 5577 20350 31399 39048
2044 E01002093 Haringey 2674 6937 35341 38627
2045 E01002094 Haringey 3922 4191 22653 39740
2046 E01002095 Haringey 2671 3624 34989 40203
2047 E01002096 Haringey 3397 7111 24104 39359
2048 E01002097 Haringey 3670 6582 37444 40315
2049 E01002098 Haringey 12784 535 25279 38098
2050 E01002099 Haringey 4119 8085 28120 39022
2051 E01002100 Haringey 6336 8176 38357 39182
2052 E01002101 Haringey 13136 8326 37112 38412
2053 E01002102 Haringey 8989 3856 35639 38270
2054 E01002103 Haringey 10425 10961 33937 39022
2055 E01002104 Haringey 10478 10136 36570 39182
2056 E01002105 Haringey 9038 939 27145 38098
2057 E01002106 Harrow 23970 15940 36103 34268
2058 E01002107 Harrow 28989 16457 38342 34909
2059 E01002108 Harrow 26452 20751 40244 35435
2060 E01002109 Harrow 25766 26666 17281 33892
2061 E01002110 Harrow 27531 16768 37436 34322
2062 E01002111 Harrow 19020 19228 38433 34290
2063 E01002112 Harrow 29072 25003 9788 31288
2064 E01002113 Harrow 18020 25957 4478 32807
2065 E01002114 Harrow 12948 24382 10663 30384
2066 E01002115 Harrow 21124 24341 21016 32994
2067 E01002116 Harrow 26311 18031 2189 34278
2068 E01002117 Harrow 17612 14382 38225 34416
2069 E01002118 Harrow 15531 6556 22654 35202
2070 E01002119 Harrow 14963 7919 36257 35553
2071 E01002120 Harrow 7228 16117 20289 34982
2072 E01002121 Harrow 22384 14107 39269 35284
2073 E01002122 Harrow 18298 8286 40253 35990
2074 E01002123 Harrow 16942 3558 40895 36340
2075 E01002124 Harrow 19547 4581 39858 35391
2076 E01002125 Harrow 18470 5527 40028 36340
2077 E01002126 Harrow 19272 6196 41625 34423
2078 E01002127 Harrow 20756 5952 40561 34448
2079 E01002128 Harrow 16310 3487 40867 34588
2080 E01002129 Harrow 16216 5614 41606 34494
2081 E01002130 Harrow 11018 6681 41686 34673
2082 E01002131 Harrow 8650 15542 40102 34754
2083 E01002132 Harrow 25446 11673 22995 35135
2084 E01002133 Harrow 6641 9026 28050 35779
2085 E01002134 Harrow 25562 16448 7574 35677
2086 E01002135 Harrow 18752 1698 23946 36322
2087 E01002136 Harrow 21233 3216 36412 34771
2088 E01002137 Harrow 30813 13958 33159 34968
2089 E01002138 Harrow 16583 2507 40274 35012
2090 E01002139 Harrow 7669 17772 8931 29607
2091 E01002140 Harrow 15873 11345 6401 31271
2092 E01002141 Harrow 18818 18175 18720 33489
2093 E01002142 Harrow 19554 10631 12414 31271
2094 E01002143 Harrow 14373 11814 13138 30129
2095 E01002144 Harrow 20101 24020 3340 28465
2096 E01002145 Harrow 18154 17849 11118 31405
2097 E01002146 Harrow 31847 13951 24832 26387
2098 E01002147 Harrow 26037 22120 15013 27182
2099 E01002148 Harrow 24001 13740 15952 29135
2100 E01002149 Harrow 30915 8991 24818 28571
2101 E01002150 Harrow 23608 7094 28644 28619
2102 E01002151 Harrow 6225 19541 20430 29347
2103 E01002152 Harrow 28974 4749 20815 29084
2104 E01002153 Harrow 29775 7270 39761 33554
2105 E01002154 Harrow 21403 14623 30064 29856
2106 E01002155 Harrow 28451 24836 32654 30007
2107 E01002156 Harrow 28427 17109 20418 31074
2108 E01002157 Harrow 23409 5673 39483 32256
2109 E01002158 Harrow 29427 14370 30366 32168
2110 E01002159 Harrow 21098 3238 39537 33142
2111 E01002160 Harrow 20906 1651 41403 34491
2112 E01002161 Harrow 19247 3261 40347 33088
2113 E01002162 Harrow 16353 6585 36282 31145
2114 E01002163 Harrow 23147 12781 31158 32652
2115 E01002164 Harrow 26005 4652 30777 33626
2116 E01002165 Harrow 19339 2333 40815 35139
2117 E01002166 Harrow 20715 5705 40613 34875
2118 E01002167 Harrow 14079 4675 40548 35206
2119 E01002168 Harrow 10183 4246 39620 35206
2120 E01002169 Harrow 16024 9080 40757 35491
2121 E01002170 Harrow 17473 11105 38259 35210
2122 E01002171 Harrow 22823 865 41562 34989
2123 E01002172 Harrow 21241 24997 40236 34784
2124 E01002173 Harrow 20318 14955 41042 35291
2125 E01002174 Harrow 24165 11975 41318 35623
2126 E01002175 Harrow 22661 566 41601 35623
2127 E01002176 Harrow 21152 2401 41323 35291
2128 E01002177 Harrow 20015 14427 40823 35997
2129 E01002178 Harrow 24508 15250 40900 35997
2130 E01002179 Harrow 13474 6710 40494 32321
2131 E01002180 Harrow 9672 9586 40378 34971
2132 E01002181 Harrow 21668 9810 37617 32950
2133 E01002182 Harrow 19260 4871 39371 34010
2134 E01002183 Harrow 15115 7934 38372 34632
2135 E01002184 Harrow 15620 12803 34663 35188
2136 E01002185 Harrow 7721 13268 25457 27443
2137 E01002186 Harrow 15554 12164 25968 27681
2138 E01002187 Harrow 21695 11362 20275 29755
2139 E01002188 Harrow 32125 15295 24648 30001
2140 E01002189 Harrow 29842 8627 36163 30334
2141 E01002190 Harrow 29270 19770 17153 26967
2142 E01002191 Harrow 28891 16491 35875 32717
2143 E01002192 Harrow 28705 13077 18087 30334
2144 E01002193 Harrow 23375 13230 29286 31583
2145 E01002194 Harrow 30112 15486 24295 31583
2146 E01002195 Harrow 29769 15462 37277 33395
2147 E01002196 Harrow 30139 18394 33906 32451
2148 E01002197 Harrow 22180 15665 41026 35672
2149 E01002198 Harrow 20803 7435 40877 35453
2150 E01002199 Harrow 23974 10226 41356 35672
2151 E01002200 Harrow 17997 17354 38725 34923
2152 E01002201 Harrow 24820 10364 41253 35069
2153 E01002202 Harrow 15836 3989 41122 35004
2154 E01002203 Harrow 20984 15470 41144 34774
2155 E01002204 Harrow 19969 9038 40707 34567
2156 E01002206 Harrow 19682 11324 39891 34350
2157 E01002207 Harrow 22350 13450 39570 35130
2158 E01002208 Harrow 30543 14902 34948 33411
2159 E01002209 Harrow 24598 4281 40486 33601
2160 E01002210 Harrow 26446 10409 37987 34280
2161 E01002211 Harrow 9388 11408 35551 35686
2162 E01002212 Harrow 14594 2497 37306 35953
2163 E01002213 Harrow 16121 8657 40791 35794
2164 E01002214 Harrow 15825 15242 36989 36057
2165 E01002215 Harrow 9693 5439 35685 35953
2166 E01002216 Harrow 21924 11774 37382 35402
2167 E01002217 Harrow 6812 15911 40696 34846
2168 E01002218 Harrow 17413 7548 30815 36151
2169 E01002219 Harrow 14033 1048 40512 36129
2170 E01002220 Harrow 19337 14155 25507 36176
2171 E01002221 Harrow 17092 4722 35407 36286
2172 E01002222 Harrow 20887 12864 25323 36699
2173 E01002223 Harrow 19692 17196 39340 36646
2174 E01002224 Harrow 11629 3054 24809 36646
2175 E01002225 Harrow 28358 28432 6076 29030
2176 E01002226 Harrow 20044 13122 14746 31539
2177 E01002227 Harrow 4814 20061 6126 31906
2178 E01002228 Harrow 20166 23214 6900 32122
2179 E01002229 Harrow 14052 21065 16851 32882
2180 E01002230 Harrow 23954 25093 16385 32931
2181 E01002231 Harrow 12439 19854 29262 34268
2182 E01002232 Harrow 14624 2642 27516 31564
2183 E01002233 Harrow 10857 3188 35959 33085
2184 E01002234 Harrow 15352 7252 33289 30580
2185 E01002235 Harrow 9047 11916 30712 33085
2186 E01002236 Harrow 16117 4376 38174 31954
2187 E01002237 Harrow 14308 3979 39863 34491
2188 E01002238 Harrow 23160 4362 40869 34092
2189 E01002239 Harrow 25612 6102 38471 33969
2190 E01002240 Harrow 14190 6785 37132 34491
2191 E01002241 Harrow 12828 15705 38810 34846
2192 E01002242 Harrow 26617 6405 39860 33719
2193 E01002243 Havering 7880 6994 36021 37879
2194 E01002244 Havering 15215 14137 27020 37565
2195 E01002245 Havering 16221 11502 35642 37565
2196 E01002246 Havering 19248 12660 40136 37576
2197 E01002247 Havering 14389 10745 39927 37999
2198 E01002248 Havering 13331 7937 31357 37914
2199 E01002249 Havering 13869 9174 37452 37915
2200 E01002250 Havering 13105 30653 35877 38685
2201 E01002251 Havering 11069 16043 4585 39170
2202 E01002252 Havering 24057 26089 27947 32747
2203 E01002253 Havering 32507 19722 7461 32819
2204 E01002254 Havering 32025 12546 16979 32784
2205 E01002255 Havering 26637 26384 10905 34105
2206 E01002256 Havering 28938 22583 30651 32336
2207 E01002257 Havering 31282 13481 2677 33200
2208 E01002258 Havering 19021 11372 24262 32437
2209 E01002259 Havering 27753 19288 14792 33371
2210 E01002260 Havering 22086 9657 8468 39939
2211 E01002261 Havering 20263 6436 13648 39715
2212 E01002262 Havering 17924 11802 26709 40221
2213 E01002263 Havering 27243 30430 31713 39706
2214 E01002264 Havering 7061 9109 21944 39971
2215 E01002265 Havering 22582 35404 30023 39476
2216 E01002266 Havering 18799 15894 28440 40209
2217 E01002267 Havering 10117 16180 31989 40257
2218 E01002268 Havering 22617 24504 13990 33933
2219 E01002269 Havering 26160 33526 18133 33690
2220 E01002270 Havering 28801 26011 13010 34903
2221 E01002271 Havering 27175 30762 14184 34185
2222 E01002272 Havering 25437 11716 32396 37027
2223 E01002273 Havering 23998 29844 13020 33905
2224 E01002274 Havering 27628 15245 26610 34929
2225 E01002275 Havering 26667 23206 10417 34400
2226 E01002276 Havering 8185 31797 16327 31730
2227 E01002277 Havering 6499 17168 27234 34184
2228 E01002278 Havering 6660 28621 21228 32631
2229 E01002279 Havering 10596 18314 24936 33013
2230 E01002280 Havering 2185 25059 31767 31992
2231 E01002281 Havering 6352 7047 19851 33883
2232 E01002282 Havering 4217 12906 36942 33388
2233 E01002283 Havering 7779 8367 33907 34617
2234 E01002284 Havering 8184 14368 33126 33388
2235 E01002285 Havering 28150 30860 16444 36317
2236 E01002286 Havering 30183 22301 31514 38389
2237 E01002287 Havering 25723 10427 27913 39302
2238 E01002288 Havering 28877 32611 22792 37978
2239 E01002289 Havering 25405 17818 16020 34460
2240 E01002290 Havering 27373 17725 14864 36317
2241 E01002291 Havering 24957 12642 21439 36639
2242 E01002292 Havering 15963 23151 13817 35177
2243 E01002293 Havering 16740 16396 37109 33982
2244 E01002294 Havering 25787 2501 11357 33549
2245 E01002295 Havering 17761 22537 31795 33931
2246 E01002296 Havering 20805 31619 33842 33156
2247 E01002297 Havering 4699 20404 25088 34035
2248 E01002298 Havering 22608 27521 35227 34392
2249 E01002299 Havering 14348 15888 29419 34218
2250 E01002300 Havering 23899 6836 24449 34233
2251 E01002301 Havering 22015 12570 33912 36289
2252 E01002302 Havering 15819 7736 37425 36289
2253 E01002303 Havering 7536 21431 24875 36325
2254 E01002304 Havering 12535 33093 17876 32544
2255 E01002305 Havering 16007 27299 38181 33925
2256 E01002306 Havering 7421 22187 32334 35382
2257 E01002307 Havering 14231 22797 38661 35269
2258 E01002308 Havering 11054 25149 36623 34485
2259 E01002309 Havering 12175 23317 35917 34950
2260 E01002310 Havering 4401 18717 38803 33609
2261 E01002311 Havering 10025 26876 34542 34946
2262 E01002312 Havering 9194 33228 18493 31182
2263 E01002313 Havering 10387 28395 34064 33237
2264 E01002314 Havering 4287 20393 38946 32836
2265 E01002315 Havering 12112 24376 39504 34327
2266 E01002316 Havering 4045 17693 41163 33643
2267 E01002317 Havering 30042 10843 6714 36469
2268 E01002318 Havering 26458 9484 6253 35554
2269 E01002319 Havering 17177 9011 20085 37135
2270 E01002320 Havering 25875 8796 16791 36694
2271 E01002321 Havering 25096 6481 13374 36395
2272 E01002322 Havering 27418 17652 11347 37621
2273 E01002323 Havering 22290 13949 9836 37394
2274 E01002324 Havering 12735 19385 6720 36798
2275 E01002325 Havering 9804 18892 33953 37150
2276 E01002326 Havering 14732 4594 38365 36954
2277 E01002327 Havering 18495 15570 25211 37587
2278 E01002328 Havering 24496 10080 33808 37587
2279 E01002329 Havering 18401 22198 36252 37586
2280 E01002330 Havering 15284 24879 35286 37962
2281 E01002331 Havering 18514 20737 35253 35598
2282 E01002332 Havering 19097 12276 26423 36751
2283 E01002333 Havering 26426 23346 19933 36913
2284 E01002334 Havering 22951 28713 1884 36987
2285 E01002335 Havering 17529 15231 26778 37587
2286 E01002336 Havering 21056 21456 26468 37507
2287 E01002337 Havering 20266 17970 869 36801
2288 E01002338 Havering 22621 8473 31160 37531
2289 E01002339 Havering 29691 17834 4883 37585
2290 E01002340 Havering 26207 7293 16155 37878
2291 E01002341 Havering 23558 27418 26680 36702
2292 E01002342 Havering 14597 11882 26858 40303
2293 E01002343 Havering 20839 25910 11877 40160
2294 E01002344 Havering 14484 27854 20586 39423
2295 E01002345 Havering 7882 12498 26592 40642
2296 E01002346 Havering 10436 8331 15872 40661
2297 E01002347 Havering 19605 20039 8065 39886
2298 E01002348 Havering 24372 29925 11988 38748
2299 E01002349 Havering 20045 25859 4370 39076
2300 E01002350 Havering 9974 11794 38276 37823
2301 E01002351 Havering 22391 10876 35177 37826
2302 E01002352 Havering 16177 12170 28446 38671
2303 E01002353 Havering 18644 6838 24152 38110
2304 E01002354 Havering 30485 15614 5014 37699
2305 E01002355 Havering 28979 19685 13875 37926
2306 E01002356 Havering 6369 2414 40507 38167
2307 E01002358 Havering 17520 6508 37625 38671
2308 E01002359 Havering 28300 3973 22873 34702
2309 E01002360 Havering 20161 7375 14685 34644
2310 E01002361 Havering 14950 3894 28055 34959
2311 E01002362 Havering 28491 9316 18878 34292
2312 E01002363 Havering 15822 14775 2328 36309
2313 E01002364 Havering 28386 11287 13200 35253
2314 E01002365 Havering 20464 2493 6311 39060
2315 E01002366 Havering 23269 13517 15389 38317
2316 E01002367 Havering 24902 2036 15743 34750
2317 E01002368 Havering 4538 28391 23795 40934
2318 E01002369 Havering 13245 22825 18562 41095
2319 E01002370 Havering 8228 22353 16551 40457
2320 E01002371 Havering 17717 14668 19331 40780
2321 E01002372 Havering 23525 19988 32649 40495
2322 E01002373 Havering 20103 8499 17854 40677
2323 E01002374 Havering 17267 17069 23197 40565
2324 E01002375 Havering 8523 16643 21480 40730
2325 E01002376 Havering 28536 23062 8078 36115
2326 E01002377 Havering 21172 17350 33585 34626
2327 E01002378 Havering 27059 14156 21383 35390
2328 E01002379 Havering 28821 19417 12698 36812
2329 E01002380 Havering 17013 27201 26515 35682
2330 E01002381 Havering 20683 24961 14516 35682
2331 E01002382 Havering 26841 10405 16199 38199
2332 E01002383 Havering 26684 26632 27235 35029
2333 E01002384 Havering 28313 7725 25275 33023
2334 E01002385 Havering 20191 34827 3597 36231
2335 E01002386 Havering 27280 1981 26203 33575
2336 E01002387 Havering 30996 7432 7362 33755
2337 E01002388 Havering 32563 8732 3378 34321
2338 E01002389 Havering 31077 17368 3665 35330
2339 E01002390 Havering 32137 5591 10251 35325
2340 E01002391 Havering 23815 26123 12352 34450
2341 E01002392 Hillingdon 5845 21000 2790 36914
2342 E01002393 Hillingdon 12206 9866 5632 37156
2343 E01002394 Hillingdon 15258 12009 7742 37034
2344 E01002395 Hillingdon 13140 12898 11697 37156
2345 E01002396 Hillingdon 8694 11863 16693 38952
2346 E01002397 Hillingdon 9958 10334 32444 37731
2347 E01002398 Hillingdon 13411 5795 19748 37731
2348 E01002399 Hillingdon 14662 11286 19018 38015
2349 E01002400 Hillingdon 9745 17143 30607 37370
2350 E01002401 Hillingdon 9807 19328 30615 36980
2351 E01002402 Hillingdon 11133 20944 31090 36466
2352 E01002403 Hillingdon 9823 16688 33241 36864
2353 E01002404 Hillingdon 8171 11567 23109 37581
2354 E01002405 Hillingdon 11728 20131 17444 38146
2355 E01002406 Hillingdon 10781 13564 35622 38849
2356 E01002407 Hillingdon 11705 9597 34816 40747
2357 E01002408 Hillingdon 7544 23844 34232 36649
2358 E01002409 Hillingdon 12495 17428 33883 36550
2359 E01002410 Hillingdon 18114 23337 37182 36256
2360 E01002411 Hillingdon 11386 27906 4169 37262
2361 E01002412 Hillingdon 20749 23574 34047 36756
2362 E01002413 Hillingdon 7705 25883 7149 38180
2363 E01002414 Hillingdon 26080 28398 23463 37037
2364 E01002415 Hillingdon 28382 8057 30032 33624
2365 E01002416 Hillingdon 28002 8328 35528 34309
2366 E01002417 Hillingdon 28823 7463 29890 31662
2367 E01002418 Hillingdon 22256 23981 32178 33042
2368 E01002419 Hillingdon 30025 11100 33051 32507
2369 E01002420 Hillingdon 20174 13145 25370 32287
2370 E01002421 Hillingdon 25809 11053 29400 33042
2371 E01002422 Hillingdon 18115 15044 23036 35922
2372 E01002423 Hillingdon 20224 18962 38571 36479
2373 E01002424 Hillingdon 20546 9167 13357 36255
2374 E01002425 Hillingdon 11402 18329 20452 35790
2375 E01002426 Hillingdon 16368 6815 24089 36914
2376 E01002427 Hillingdon 20845 16444 27019 36479
2377 E01002428 Hillingdon 21987 18733 7916 35757
2378 E01002429 Hillingdon 7970 30459 11066 35977
2379 E01002430 Hillingdon 29334 14604 9773 28999
2380 E01002431 Hillingdon 30573 8259 26756 31949
2381 E01002432 Hillingdon 28738 2749 33920 31692
2382 E01002433 Hillingdon 17059 20609 21019 31591
2383 E01002434 Hillingdon 30000 9608 7470 27598
2384 E01002435 Hillingdon 31339 9887 22322 31025
2385 E01002436 Hillingdon 23393 16256 13049 29373
2386 E01002437 Hillingdon 29735 21314 16591 29933
2387 E01002438 Hillingdon 21531 36373 185 26942
2388 E01002439 Hillingdon 16990 19955 19301 25650
2389 E01002440 Hillingdon 14167 25447 25648 22884
2390 E01002441 Hillingdon 11576 32041 5772 27411
2391 E01002442 Hillingdon 11533 37564 214 27747
2392 E01002443 Hillingdon 14430 31454 39615 41596
2393 E01002444 Hillingdon 12349 35775 41092 41453
2394 E01002445 Hillingdon 7835 18828 22464 39885
2395 E01002446 Hillingdon 12848 28364 15241 41498
2396 E01002447 Hillingdon 11245 30394 29103 41624
2397 E01002448 Hillingdon 15919 9971 32238 41561
2398 E01002449 Hillingdon 13247 24000 38553 41692
2399 E01002450 Hillingdon 27513 18784 19219 34865
2400 E01002451 Hillingdon 28166 6956 19976 35583
2401 E01002452 Hillingdon 25275 2789 20400 34920
2402 E01002453 Hillingdon 23046 11018 20670 35668
2403 E01002454 Hillingdon 14666 19587 15528 34849
2404 E01002455 Hillingdon 14192 17274 36968 36075
2405 E01002456 Hillingdon 15086 15025 23060 36520
2406 E01002457 Hillingdon 9683 22454 33091 36386
2407 E01002458 Hillingdon 28217 23296 4133 33107
2408 E01002459 Hillingdon 31719 15544 12660 32605
2409 E01002460 Hillingdon 28811 6380 5154 35246
2410 E01002461 Hillingdon 24176 32636 3054 34355
2411 E01002462 Hillingdon 28397 30358 1452 35548
2412 E01002463 Hillingdon 27916 23418 3185 35548
2413 E01002464 Hillingdon 29027 15318 4814 34789
2414 E01002465 Hillingdon 23956 10624 12119 32833
2415 E01002466 Hillingdon 27551 12344 17348 32754
2416 E01002467 Hillingdon 29710 12989 21618 32432
2417 E01002468 Hillingdon 28529 11409 26311 31534
2418 E01002469 Hillingdon 27093 8707 26185 31267
2419 E01002470 Hillingdon 23632 3366 35975 31267
2420 E01002471 Hillingdon 27928 3901 31806 31438
2421 E01002472 Hillingdon 26768 6158 18902 24004
2422 E01002473 Hillingdon 17981 29765 9160 22971
2423 E01002474 Hillingdon 23911 7803 21591 24399
2424 E01002475 Hillingdon 16423 20337 18758 23252
2425 E01002476 Hillingdon 30955 26491 15724 24846
2426 E01002477 Hillingdon 24561 15138 14628 26129
2427 E01002478 Hillingdon 27666 5483 25055 24231
2428 E01002479 Hillingdon 14690 15770 5639 27169
2429 E01002480 Hillingdon 31432 22072 11892 28172
2430 E01002481 Hillingdon 15178 14472 7790 28158
2431 E01002482 Hillingdon 32164 15274 15761 25785
2432 E01002483 Hillingdon 25352 6008 30778 25142
2433 E01002484 Hillingdon 13323 4156 26429 25080
2434 E01002485 Hillingdon 18663 6900 18529 25099
2435 E01002486 Hillingdon 10820 25861 18135 40568
2436 E01002487 Hillingdon 11335 18975 29625 40026
2437 E01002488 Hillingdon 15580 10934 33516 40916
2438 E01002489 Hillingdon 17959 7865 33683 40769
2439 E01002490 Hillingdon 12914 12338 37447 40916
2440 E01002491 Hillingdon 10125 22538 30538 41055
2441 E01002492 Hillingdon 13506 16904 26096 41055
2442 E01002493 Hillingdon 7115 17955 30892 41210
2443 E01002494 Hillingdon 23112 20312 4114 33612
2444 E01002495 Hillingdon 24471 13793 20613 33304
2445 E01002496 Hillingdon 17182 23957 38217 35676
2446 E01002497 Hillingdon 18915 17571 27352 34396
2447 E01002498 Hillingdon 26697 10345 29368 35251
2448 E01002499 Hillingdon 21340 21701 8750 34342
2449 E01002501 Hillingdon 13368 4393 22581 39263
2450 E01002502 Hillingdon 8401 6669 21743 38857
2451 E01002503 Hillingdon 7561 3589 31670 39337
2452 E01002504 Hillingdon 10595 16386 22079 38615
2453 E01002505 Hillingdon 5524 19659 24508 39145
2454 E01002506 Hillingdon 6678 2035 39208 39605
2455 E01002507 Hillingdon 13549 24285 27380 39924
2456 E01002508 Hillingdon 6038 8309 15919 38593
2457 E01002509 Hillingdon 26850 28853 17638 36585
2458 E01002511 Hillingdon 11647 17537 18245 36432
2459 E01002512 Hillingdon 29384 18757 3209 36434
2460 E01002513 Hillingdon 21967 14268 9350 35648
2461 E01002514 Hillingdon 21785 7716 11035 37292
2462 E01002515 Hillingdon 12892 5192 32384 36979
2463 E01002516 Hillingdon 27668 15878 7467 36140
2464 E01002518 Hillingdon 24260 17126 5805 37862
2465 E01002519 Hillingdon 8067 22487 1291 37257
2466 E01002520 Hillingdon 14591 22174 13882 36687
2467 E01002521 Hillingdon 8385 1980 15397 36878
2468 E01002523 Hillingdon 16868 14553 16931 38206
2469 E01002525 Hillingdon 15013 13021 4335 40467
2470 E01002526 Hillingdon 8626 19098 16751 37994
2471 E01002527 Hillingdon 9202 24147 2403 40111
2472 E01002528 Hillingdon 5861 18287 17352 39755
2473 E01002529 Hillingdon 13991 12386 12598 39679
2474 E01002530 Hillingdon 5774 24828 6590 40298
2475 E01002531 Hillingdon 16512 21967 1290 39974
2476 E01002532 Hillingdon 8763 27612 16208 38859
2477 E01002533 Hillingdon 16920 26493 12056 24738
2478 E01002534 Hillingdon 24926 6236 13945 27979
2479 E01002535 Hillingdon 26634 2822 33786 30393
2480 E01002536 Hillingdon 25715 12449 22582 30341
2481 E01002537 Hillingdon 28136 19964 29979 32605
2482 E01002538 Hillingdon 21973 20129 5904 25858
2483 E01002539 Hillingdon 28177 11552 11659 27031
2484 E01002540 Hillingdon 9149 15806 15461 37416
2485 E01002541 Hillingdon 19169 11910 21039 37416
2486 E01002542 Hillingdon 8115 7895 9813 37268
2487 E01002543 Hillingdon 7704 17149 7227 37416
2488 E01002544 Hillingdon 19620 23973 17407 38511
2489 E01002545 Hillingdon 3488 28178 16133 38850
2490 E01002546 Hillingdon 14713 30927 23068 39243
2491 E01002547 Hillingdon 10730 22632 17611 38999
2492 E01002548 Hillingdon 7083 20477 14120 37884
2493 E01002549 Hillingdon 13435 21265 24529 37520
2494 E01002550 Hillingdon 8239 27776 15947 37497
2495 E01002551 Hillingdon 12906 24731 31329 37244
2496 E01002552 Hillingdon 8365 11841 9937 38236
2497 E01002553 Hillingdon 5488 21596 23357 37437
2498 E01002554 Hillingdon 9125 13414 23341 38353
2499 E01002555 Hounslow 19332 23767 15371 41452
2500 E01002556 Hounslow 17019 12269 6560 40943
2501 E01002557 Hounslow 10494 24345 12205 41033
2502 E01002558 Hounslow 11490 9640 13482 40985
2503 E01002559 Hounslow 10334 27513 14015 38878
2504 E01002560 Hounslow 8721 9653 13972 35792
2505 E01002561 Hounslow 5999 6818 14735 35773
2506 E01002562 Hounslow 6744 13774 13271 40343
2507 E01002563 Hounslow 18140 15986 10014 37863
2508 E01002564 Hounslow 6163 2759 17345 39017
2509 E01002565 Hounslow 15965 9849 30270 37961
2510 E01002566 Hounslow 6165 12738 9128 38463
2511 E01002567 Hounslow 13287 4776 15390 37032
2512 E01002568 Hounslow 7180 7075 15169 37897
2513 E01002569 Hounslow 25541 11317 25047 38776
2514 E01002570 Hounslow 20610 2176 25514 39664
2515 E01002571 Hounslow 30161 27519 27344 39210
2516 E01002572 Hounslow 7879 29390 7479 38260
2517 E01002573 Hounslow 22030 5080 13825 39653
2518 E01002574 Hounslow 23534 4931 24754 39653
2519 E01002575 Hounslow 27891 1941 20966 39169
2520 E01002576 Hounslow 12986 11558 8983 39200
2521 E01002577 Hounslow 21840 18007 14087 38338
2522 E01002578 Hounslow 23903 21885 10015 38348
2523 E01002579 Hounslow 24691 23680 1498 38057
2524 E01002580 Hounslow 10987 5657 18692 39162
2525 E01002581 Hounslow 22834 7882 7809 38463
2526 E01002582 Hounslow 22012 14346 9867 38796
2527 E01002583 Hounslow 11602 21735 24852 41521
2528 E01002584 Hounslow 15419 8480 20773 41625
2529 E01002585 Hounslow 8782 31407 23186 41563
2530 E01002586 Hounslow 17327 30540 33093 41631
2531 E01002587 Hounslow 11297 12251 36019 41461
2532 E01002588 Hounslow 4946 12235 18355 41489
2533 E01002589 Hounslow 11917 29513 21437 41282
2534 E01002590 Hounslow 15491 16074 24788 40374
2535 E01002591 Hounslow 12963 19660 2130 38687
2536 E01002592 Hounslow 11100 22178 14808 41341
2537 E01002593 Hounslow 11534 11265 20651 38675
2538 E01002594 Hounslow 12881 13870 8896 38972
2539 E01002595 Hounslow 9557 12600 2598 40882
2540 E01002596 Hounslow 11229 27034 19539 35671
2541 E01002598 Hounslow 10352 8889 28674 36024
2542 E01002599 Hounslow 9854 22377 25194 35823
2543 E01002600 Hounslow 9513 16732 30986 36102
2544 E01002601 Hounslow 17139 25372 5015 35811
2545 E01002602 Hounslow 18387 28265 7546 37592
2546 E01002603 Hounslow 9819 21663 23091 35531
2547 E01002604 Hounslow 5805 17706 3189 36766
2548 E01002605 Hounslow 7338 16210 13132 35807
2549 E01002606 Hounslow 4811 20951 21663 36126
2550 E01002607 Hounslow 13493 4786 14072 36968
2551 E01002608 Hounslow 7837 20041 20469 36126
2552 E01002609 Hounslow 17978 24014 21818 35805
2553 E01002610 Hounslow 9741 25673 7651 35715
2554 E01002611 Hounslow 13547 8989 27094 36887
2555 E01002612 Hounslow 9664 3860 30625 36335
2556 E01002613 Hounslow 15529 4734 12238 37096
2557 E01002614 Hounslow 19316 14920 32948 37023
2558 E01002615 Hounslow 5539 21083 34098 36670
2559 E01002616 Hounslow 16858 12388 23275 36830
2560 E01002617 Hounslow 20968 32942 20398 36960
2561 E01002618 Hounslow 17916 14820 36582 39684
2562 E01002619 Hounslow 15394 20883 40058 40626
2563 E01002620 Hounslow 10260 19838 35586 39684
2564 E01002621 Hounslow 14294 15764 34205 38655
2565 E01002622 Hounslow 12136 8148 36634 40711
2566 E01002623 Hounslow 8903 13166 38714 39486
2567 E01002624 Hounslow 13021 8922 36987 39063
2568 E01002625 Hounslow 17517 15956 16739 40279
2569 E01002626 Hounslow 15569 7274 27768 40076
2570 E01002627 Hounslow 8506 12542 10789 39695
2571 E01002628 Hounslow 16819 13222 33928 39762
2572 E01002629 Hounslow 11979 18796 32994 38966
2573 E01002630 Hounslow 16936 20013 31360 38592
2574 E01002631 Hounslow 11568 18496 9370 40527
2575 E01002632 Hounslow 14926 25709 37664 40986
2576 E01002633 Hounslow 4802 33568 37544 41369
2577 E01002634 Hounslow 6742 34405 40213 41288
2578 E01002635 Hounslow 14005 21272 37251 41510
2579 E01002636 Hounslow 17423 26266 40008 40872
2580 E01002637 Hounslow 7357 17039 22248 40632
2581 E01002638 Hounslow 7635 23543 8346 40807
2582 E01002639 Hounslow 19136 13962 32431 39043
2583 E01002640 Hounslow 15615 13365 34157 38077
2584 E01002641 Hounslow 10104 611 41160 38107
2585 E01002642 Hounslow 13415 2484 41269 38052
2586 E01002643 Hounslow 12090 5576 35682 37972
2587 E01002645 Hounslow 10526 7429 38055 36768
2588 E01002646 Hounslow 8074 2339 37500 37130
2589 E01002647 Hounslow 11448 12413 34265 37934
2590 E01002648 Hounslow 14256 4777 40311 36299
2591 E01002649 Hounslow 9818 3391 38252 36299
2592 E01002650 Hounslow 11539 22025 32661 38005
2593 E01002651 Hounslow 15066 10500 38999 36656
2594 E01002652 Hounslow 15782 11712 35833 36841
2595 E01002653 Hounslow 19227 16579 40344 36871
2596 E01002654 Hounslow 19284 15578 37688 37065
2597 E01002655 Hounslow 21413 6793 36002 36503
2598 E01002656 Hounslow 18955 14006 26364 36938
2599 E01002657 Hounslow 26151 5413 36734 36242
2600 E01002658 Hounslow 24569 13176 17851 37652
2601 E01002659 Hounslow 19183 29664 37100 37196
2602 E01002660 Hounslow 15408 11025 37328 40435
2603 E01002661 Hounslow 17440 2941 39461 40435
2604 E01002662 Hounslow 16786 843 40408 38604
2605 E01002663 Hounslow 12810 6466 39492 38437
2606 E01002664 Hounslow 8869 740 40277 37401
2607 E01002665 Hounslow 11944 13153 37413 39387
2608 E01002666 Hounslow 16317 21552 34271 39444
2609 E01002667 Hounslow 13586 3457 5839 37850
2610 E01002668 Hounslow 18494 3613 19528 37626
2611 E01002669 Hounslow 4666 26747 30991 37866
2612 E01002670 Hounslow 18118 3144 4954 37444
2613 E01002671 Hounslow 16369 10148 1764 37563
2614 E01002672 Hounslow 9767 19643 32905 37741
2615 E01002673 Hounslow 2294 22458 23429 37741
2616 E01002674 Hounslow 19371 14960 18492 38261
2617 E01002675 Hounslow 20123 16580 25823 38331
2618 E01002676 Hounslow 18291 29111 10662 38809
2619 E01002677 Hounslow 14763 2129 33678 38523
2620 E01002678 Hounslow 22847 30100 15138 38428
2621 E01002679 Hounslow 20674 26334 28710 38182
2622 E01002680 Hounslow 17764 13653 19960 38261
2623 E01002681 Hounslow 9916 8933 19001 38053
2624 E01002682 Hounslow 15987 14062 8722 38301
2625 E01002683 Hounslow 22060 5789 29906 37859
2626 E01002684 Hounslow 11286 5765 14028 38045
2627 E01002686 Hounslow 4940 13267 9405 37768
2628 E01002687 Hounslow 22842 1875 19016 39726
2629 E01002689 Hounslow 15036 2543 24101 39583
2630 E01002690 Hounslow 24196 5655 23927 39214
2631 E01002691 Hounslow 23626 11652 27504 40440
2632 E01002692 Hounslow 17842 7076 13715 40399
2633 E01002693 Hounslow 18443 128 27327 39997
2634 E01002694 Islington 3487 4406 7433 41671
2635 E01002695 Islington 12467 5822 31149 41671
2636 E01002696 Islington 14178 5445 29784 41648
2637 E01002697 Islington 7142 2376 12880 41671
2638 E01002698 Islington 16593 4318 28692 41404
2639 E01002699 Islington 14586 6316 22256 41584
2640 E01002700 Islington 20562 4064 8906 41592
2641 E01002701 Islington 9154 100 37301 41648
2642 E01002702 Islington 8242 1453 31867 41709
2643 E01002703 Islington 9396 2172 28905 41709
2644 E01002704 Islington 12549 1879 41192 41687
2645 E01002706 Islington 10815 2078 36593 41648
2646 E01002707 Islington 10377 861 27820 41695
2647 E01002708 Islington 8035 6331 32584 41597
2648 E01002709 Islington 5835 1043 19422 41693
2649 E01002710 Islington 7574 1590 11468 41693
2650 E01002711 Islington 12915 736 27667 41707
2651 E01002712 Islington 9562 717 25830 41404
2652 E01002713 Islington 3166 3549 34712 41367
2653 E01002714 Islington 19913 990 14447 41597
2654 E01002715 Islington 4721 1022 17943 41597
2655 E01002716 Islington 6033 3260 25453 41256
2656 E01002717 Islington 12461 10523 8143 41256
2657 E01002718 Islington 14929 4662 12900 41256
2658 E01002719 Islington 17270 4342 7044 41361
2659 E01002720 Islington 4250 3931 28422 41256
2660 E01002721 Islington 8938 3033 11789 41556
2661 E01002722 Islington 5269 2661 16192 41556
2662 E01002723 Islington 8750 2469 23849 41728
2663 E01002724 Islington 19372 669 41348 41715
2664 E01002725 Islington 8458 3184 30049 41728
2665 E01002726 Islington 11070 742 35432 41725
2666 E01002727 Islington 10165 1579 17906 41709
2667 E01002728 Islington 9446 1614 27713 41706
2668 E01002729 Islington 7539 3723 27233 41725
2669 E01002730 Islington 7841 666 36073 40530
2670 E01002731 Islington 11066 1267 39430 40486
2671 E01002732 Islington 2650 1075 29810 40794
2672 E01002733 Islington 15654 876 31140 40413
2673 E01002734 Islington 4096 221 30325 40515
2674 E01002735 Islington 6465 758 24566 40122
2675 E01002736 Islington 3060 1562 15265 40515
2676 E01002737 Islington 5609 6837 24042 40413
2677 E01002738 Islington 10960 6379 22013 41284
2678 E01002739 Islington 16660 4298 37407 41150
2679 E01002740 Islington 17843 6126 33215 41334
2680 E01002741 Islington 5946 2300 3664 40976
2681 E01002742 Islington 18132 991 29107 40999
2682 E01002743 Islington 15181 2409 8808 40976
2683 E01002744 Islington 16228 554 19530 41183
2684 E01002745 Islington 18128 3914 31373 41150
2685 E01002747 Islington 20714 3201 32955 40805
2686 E01002748 Islington 4293 709 26965 40968
2687 E01002749 Islington 12160 1974 31625 40968
2688 E01002751 Islington 4870 1973 29029 40731
2689 E01002752 Islington 12440 2072 23396 41150
2690 E01002753 Islington 8283 6007 35362 39154
2691 E01002754 Islington 17536 7388 23502 38589
2692 E01002755 Islington 4303 654 20683 38290
2693 E01002756 Islington 9162 651 16811 38914
2694 E01002757 Islington 11321 9756 18478 37547
2695 E01002758 Islington 3231 3460 15845 38290
2696 E01002759 Islington 13811 7553 31598 37547
2697 E01002760 Islington 4631 9568 32467 38290
2698 E01002762 Islington 13764 2812 21896 40608
2699 E01002763 Islington 6622 4358 34449 40486
2700 E01002764 Islington 7581 6248 21937 40773
2701 E01002765 Islington 8909 3367 37471 41066
2702 E01002766 Islington 7264 1842 35480 40773
2703 E01002767 Islington 5275 1096 32897 40608
2704 E01002768 Islington 8350 1465 26022 39578
2705 E01002769 Islington 14242 3610 34666 39713
2706 E01002770 Islington 8029 2001 36416 38280
2707 E01002771 Islington 9390 1441 29417 39434
2708 E01002772 Islington 8637 593 36091 38589
2709 E01002773 Islington 2164 1602 25495 38547
2710 E01002774 Islington 7608 903 27622 39952
2711 E01002775 Islington 12620 11911 10048 41319
2712 E01002776 Islington 7029 4558 25203 41308
2713 E01002777 Islington 9255 3912 21999 41130
2714 E01002778 Islington 4551 3699 30209 41060
2715 E01002779 Islington 15584 1700 23094 41256
2716 E01002780 Islington 9965 3077 25015 41256
2717 E01002781 Islington 8526 9022 6245 41256
2718 E01002782 Islington 5157 4163 23389 40974
2719 E01002783 Islington 2766 3935 15011 40453
2720 E01002784 Islington 6145 2892 18264 40281
2721 E01002785 Islington 15334 301 34287 39931
2722 E01002786 Islington 5495 2075 37408 40328
2723 E01002787 Islington 7051 7430 30389 40281
2724 E01002788 Islington 17004 7863 26996 40113
2725 E01002789 Islington 20257 703 24359 39891
2726 E01002790 Islington 3653 2025 33629 41436
2727 E01002791 Islington 20072 1431 16733 41436
2728 E01002792 Islington 17852 2907 31326 41584
2729 E01002793 Islington 5450 2109 28654 41560
2730 E01002794 Islington 12607 1366 32907 41584
2731 E01002795 Islington 10755 673 33941 41334
2732 E01002796 Islington 11641 446 26040 41404
2733 E01002797 Islington 7039 866 18425 41613
2734 E01002798 Islington 13193 2649 26427 41648
2735 E01002799 Islington 6972 1909 25294 41613
2736 E01002800 Islington 4590 3625 28743 41648
2737 E01002801 Islington 17133 848 17263 41648
2738 E01002802 Islington 10255 2349 13717 41648
2739 E01002803 Islington 11531 873 11122 41688
2740 E01002804 Islington 5087 2062 27766 38914
2741 E01002805 Islington 12161 1852 19543 39848
2742 E01002806 Islington 9620 2899 22540 39656
2743 E01002807 Islington 7258 2474 36255 39604
2744 E01002808 Islington 10985 2730 33434 39656
2745 E01002809 Islington 7327 2942 34642 39952
2746 E01002810 Islington 6536 1859 34680 39952
2747 E01002811 Islington 4691 3405 12684 38914
2748 E01002812 Kensington and Chelsea 22698 685 33676 40696
2749 E01002813 Kensington and Chelsea 24398 240 33748 40696
2750 E01002814 Kensington and Chelsea 10748 3583 38400 40532
2751 E01002815 Kensington and Chelsea 15885 1151 36241 40696
2752 E01002816 Kensington and Chelsea 22718 523 39440 40696
2753 E01002817 Kensington and Chelsea 24015 317 35710 40589
2754 E01002818 Kensington and Chelsea 21429 2963 40790 41250
2755 E01002819 Kensington and Chelsea 23245 5070 37743 41323
2756 E01002820 Kensington and Chelsea 25054 1902 41326 40955
2757 E01002821 Kensington and Chelsea 23418 1861 40240 41189
2758 E01002822 Kensington and Chelsea 21201 1546 35468 41131
2759 E01002823 Kensington and Chelsea 8812 910 33523 41131
2760 E01002824 Kensington and Chelsea 24462 2294 24656 40793
2761 E01002825 Kensington and Chelsea 24885 4457 18314 40728
2762 E01002826 Kensington and Chelsea 23594 387 32061 40910
2763 E01002827 Kensington and Chelsea 22084 3450 37270 40849
2764 E01002828 Kensington and Chelsea 17715 3971 38642 40736
2765 E01002829 Kensington and Chelsea 6055 419 28017 40812
2766 E01002830 Kensington and Chelsea 5764 92 25008 40864
2767 E01002831 Kensington and Chelsea 5299 134 34259 40864
2768 E01002832 Kensington and Chelsea 7367 157 31958 40811
2769 E01002833 Kensington and Chelsea 15083 295 34886 40785
2770 E01002834 Kensington and Chelsea 18346 101 34502 40696
2771 E01002835 Kensington and Chelsea 23929 2932 38324 40760
2772 E01002836 Kensington and Chelsea 23221 3372 36843 40760
2773 E01002837 Kensington and Chelsea 20942 2496 37588 40843
2774 E01002838 Kensington and Chelsea 23203 2516 32306 40843
2775 E01002839 Kensington and Chelsea 10320 585 39969 40760
2776 E01002840 Kensington and Chelsea 4981 24 7222 40536
2777 E01002841 Kensington and Chelsea 9898 3543 21042 39693
2778 E01002842 Kensington and Chelsea 2593 1603 7141 40232
2779 E01002843 Kensington and Chelsea 3564 846 19076 40232
2780 E01002844 Kensington and Chelsea 16966 3778 20485 40929
2781 E01002845 Kensington and Chelsea 13544 553 18371 40536
2782 E01002846 Kensington and Chelsea 7626 792 36535 40696
2783 E01002847 Kensington and Chelsea 12666 372 37621 40696
2784 E01002848 Kensington and Chelsea 8243 431 34484 40429
2785 E01002849 Kensington and Chelsea 16808 99 36836 40696
2786 E01002850 Kensington and Chelsea 11573 392 40845 40696
2787 E01002851 Kensington and Chelsea 4330 281 40544 40696
2788 E01002852 Kensington and Chelsea 3797 1501 30949 39802
2789 E01002853 Kensington and Chelsea 1212 989 32149 40508
2790 E01002854 Kensington and Chelsea 3030 156 21310 40508
2791 E01002855 Kensington and Chelsea 2975 477 23431 40864
2792 E01002856 Kensington and Chelsea 4928 186 30001 40864
2793 E01002857 Kensington and Chelsea 1012 66 2623 40508
2794 E01002858 Kensington and Chelsea 11753 1680 34086 41417
2795 E01002859 Kensington and Chelsea 24280 1246 39957 41286
2796 E01002860 Kensington and Chelsea 22839 3031 40133 41377
2797 E01002861 Kensington and Chelsea 18886 284 35571 41417
2798 E01002862 Kensington and Chelsea 10169 591 33977 41417
2799 E01002863 Kensington and Chelsea 24615 3591 39454 41244
2800 E01002864 Kensington and Chelsea 25115 2735 23207 40696
2801 E01002865 Kensington and Chelsea 27993 1240 31839 40696
2802 E01002866 Kensington and Chelsea 13786 5281 33059 40524
2803 E01002867 Kensington and Chelsea 12519 4550 34848 40429
2804 E01002868 Kensington and Chelsea 25448 6777 29895 40721
2805 E01002869 Kensington and Chelsea 14640 2223 33999 40588
2806 E01002870 Kensington and Chelsea 3890 5271 35278 40324
2807 E01002871 Kensington and Chelsea 22944 5148 36051 40691
2808 E01002872 Kensington and Chelsea 4605 5966 36832 40324
2809 E01002873 Kensington and Chelsea 14480 2615 37082 40433
2810 E01002874 Kensington and Chelsea 14325 407 23785 40785
2811 E01002875 Kensington and Chelsea 18986 6723 18693 40691
2812 E01002876 Kensington and Chelsea 14225 1213 29354 39793
2813 E01002877 Kensington and Chelsea 3925 5678 35493 39691
2814 E01002878 Kensington and Chelsea 6319 2055 23885 40345
2815 E01002879 Kensington and Chelsea 3808 171 31263 40355
2816 E01002880 Kensington and Chelsea 3215 2864 34397 39691
2817 E01002881 Kensington and Chelsea 4113 3588 35655 40324
2818 E01002882 Kensington and Chelsea 16904 520 32294 40736
2819 E01002883 Kensington and Chelsea 22472 3275 31100 40736
2820 E01002884 Kensington and Chelsea 13100 2137 32040 40736
2821 E01002885 Kensington and Chelsea 14695 4424 29914 40849
2822 E01002886 Kensington and Chelsea 19099 521 30232 40818
2823 E01002887 Kensington and Chelsea 21530 1919 38615 40955
2824 E01002888 Kensington and Chelsea 23449 937 37166 40862
2825 E01002889 Kensington and Chelsea 26867 835 31913 41016
2826 E01002890 Kensington and Chelsea 25832 4779 25577 41016
2827 E01002891 Kensington and Chelsea 25103 6914 11566 41285
2828 E01002892 Kensington and Chelsea 26365 5199 40407 40955
2829 E01002893 Kensington and Chelsea 12935 646 32343 40456
2830 E01002894 Kensington and Chelsea 14414 60 37188 40538
2831 E01002895 Kensington and Chelsea 23084 361 28383 40574
2832 E01002896 Kensington and Chelsea 24135 374 30078 40551
2833 E01002897 Kensington and Chelsea 18277 750 30491 40222
2834 E01002898 Kensington and Chelsea 25185 856 21517 40760
2835 E01002899 Kensington and Chelsea 13213 692 23454 41122
2836 E01002900 Kensington and Chelsea 26730 4145 9522 40946
2837 E01002901 Kensington and Chelsea 17464 4905 10637 40959
2838 E01002902 Kensington and Chelsea 23591 3403 34941 41242
2839 E01002903 Kensington and Chelsea 27528 1743 28041 41122
2840 E01002904 Kensington and Chelsea 3043 4637 33152 39600
2841 E01002905 Kensington and Chelsea 3154 1063 23832 40156
2842 E01002906 Kensington and Chelsea 6647 90 20254 39600
2843 E01002907 Kensington and Chelsea 1794 4716 23808 39600
2844 E01002908 Kensington and Chelsea 9637 2586 25962 39793
2845 E01002909 Kensington and Chelsea 8155 1690 18903 40345
2846 E01002910 Kensington and Chelsea 17632 3791 23921 40905
2847 E01002911 Kensington and Chelsea 21556 405 25994 40574
2848 E01002912 Kensington and Chelsea 20040 320 28085 40574
2849 E01002913 Kensington and Chelsea 16091 239 22168 40222
2850 E01002914 Kensington and Chelsea 25957 602 36226 41131
2851 E01002915 Kingston upon Thames 26998 21036 10868 35832
2852 E01002916 Kingston upon Thames 26782 10393 12479 35379
2853 E01002917 Kingston upon Thames 31433 13956 8038 35521
2854 E01002918 Kingston upon Thames 21946 16385 14006 34916
2855 E01002919 Kingston upon Thames 18341 14118 32153 34505
2856 E01002920 Kingston upon Thames 30459 17789 272 35521
2857 E01002921 Kingston upon Thames 18698 1788 11796 34600
2858 E01002922 Kingston upon Thames 25712 11435 6790 34761
2859 E01002923 Kingston upon Thames 7999 2910 26158 34797
2860 E01002924 Kingston upon Thames 32012 11275 5000 34918
2861 E01002925 Kingston upon Thames 22790 2817 18480 34830
2862 E01002926 Kingston upon Thames 27879 22005 275 34935
2863 E01002927 Kingston upon Thames 21448 12423 35636 34949
2864 E01002928 Kingston upon Thames 17328 3580 34969 35072
2865 E01002929 Kingston upon Thames 26011 5915 24911 36217
2866 E01002930 Kingston upon Thames 23273 2157 40385 34515
2867 E01002931 Kingston upon Thames 22804 5480 37422 36016
2868 E01002932 Kingston upon Thames 9799 9407 37268 34820
2869 E01002933 Kingston upon Thames 18511 5266 29694 35150
2870 E01002934 Kingston upon Thames 31781 4963 25019 34657
2871 E01002935 Kingston upon Thames 26771 1106 32074 35334
2872 E01002937 Kingston upon Thames 30452 3045 28025 35150
2873 E01002938 Kingston upon Thames 30727 9184 28585 35401
2874 E01002939 Kingston upon Thames 21310 9441 35686 31903
2875 E01002940 Kingston upon Thames 16076 10421 34982 30069
2876 E01002941 Kingston upon Thames 25233 19738 37855 30163
2877 E01002942 Kingston upon Thames 23570 6317 39074 30069
2878 E01002943 Kingston upon Thames 17230 27545 30873 29999
2879 E01002944 Kingston upon Thames 20667 11091 38950 29552
2880 E01002945 Kingston upon Thames 25677 23132 36343 28352
2881 E01002946 Kingston upon Thames 26145 28854 33188 26486
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3321 E01003394 Merton 17864 15101 39524 39014
3322 E01003395 Merton 22275 21082 39551 38609
3323 E01003396 Merton 21834 6413 39938 39390
3324 E01003397 Merton 19838 9203 39648 39149
3325 E01003398 Merton 18705 9374 39111 39103
3326 E01003399 Merton 25722 6430 24574 36327
3327 E01003400 Merton 28565 2811 30931 36486
3328 E01003401 Merton 31444 2149 21204 35579
3329 E01003402 Merton 30815 534 32978 35579
3330 E01003403 Merton 29724 4999 18368 36908
3331 E01003404 Merton 25994 4165 24084 36327
3332 E01003405 Merton 10386 6812 33347 37483
3333 E01003406 Merton 12088 22586 37134 38711
3334 E01003407 Merton 22329 9364 30749 37432
3335 E01003408 Merton 22311 7418 24828 37455
3336 E01003409 Merton 11085 9023 32016 38711
3337 E01003410 Merton 13118 7770 29005 37432
3338 E01003411 Merton 17900 14399 37180 36996
3339 E01003412 Merton 12249 25756 37027 38497
3340 E01003413 Merton 18563 11260 39183 36937
3341 E01003414 Merton 20261 10357 36738 36416
3342 E01003415 Merton 14583 15757 36851 35384
3343 E01003416 Merton 19804 15325 24630 36747
3344 E01003417 Merton 25536 9759 33014 34468
3345 E01003418 Merton 28652 12613 39632 34384
3346 E01003419 Merton 22958 20701 40652 34838
3347 E01003420 Merton 25563 11730 40188 34398
3348 E01003421 Merton 24701 11898 31013 34389
3349 E01003422 Merton 25586 16993 36922 34406
3350 E01003423 Merton 29630 701 28494 33729
3351 E01003424 Merton 31683 10570 3120 34590
3352 E01003425 Merton 31463 9455 6786 34153
3353 E01003426 Merton 24238 4730 9200 36138
3354 E01003427 Merton 19865 3869 27787 33934
3355 E01003428 Merton 25298 2002 7175 34563
3356 E01003429 Merton 19712 6767 33559 35268
3357 E01003430 Merton 7614 12381 36931 36877
3358 E01003431 Merton 8324 8616 34596 36772
3359 E01003432 Merton 4161 9671 22988 35713
3360 E01003433 Merton 16455 2213 34219 35937
3361 E01003434 Merton 21055 10598 27846 34748
3362 E01003435 Merton 16472 19911 7029 36117
3363 E01003436 Merton 10411 10915 6966 37346
3364 E01003437 Merton 17944 16753 2299 37346
3365 E01003438 Merton 9642 7938 18864 37346
3366 E01003439 Merton 9363 6410 3805 36364
3367 E01003440 Merton 11998 17170 329 37448
3368 E01003441 Merton 12131 19528 5655 37427
3369 E01003442 Merton 30296 12941 17501 36692
3370 E01003443 Merton 30966 1839 30943 36696
3371 E01003444 Merton 30129 3498 21898 36211
3372 E01003445 Merton 25201 11831 25647 36582
3373 E01003446 Merton 24364 660 39003 37016
3374 E01003447 Merton 11113 15753 36718 36805
3375 E01003448 Merton 11020 3192 9843 36454
3376 E01003449 Merton 15717 9835 15164 34141
3377 E01003450 Merton 8982 5616 24264 36273
3378 E01003451 Merton 21481 20631 18139 34753
3379 E01003452 Merton 9580 9944 16999 34870
3380 E01003453 Merton 11146 2107 12531 35904
3381 E01003454 Merton 29968 13079 17656 37564
3382 E01003455 Merton 23343 9621 29211 38448
3383 E01003456 Merton 21283 694 36178 37441
3384 E01003457 Merton 29971 6694 29521 37306
3385 E01003458 Merton 29454 3943 31392 38159
3386 E01003459 Merton 17877 1514 30578 38676
3387 E01003460 Merton 25790 9644 6421 33781
3388 E01003461 Merton 31737 5185 11213 34867
3389 E01003462 Merton 28468 16219 10539 35883
3390 E01003463 Merton 31211 21645 19332 35270
3391 E01003464 Merton 29339 18144 2500 32367
3392 E01003465 Merton 30822 12799 2242 31938
3393 E01003466 Merton 30901 7027 38192 36303
3394 E01003467 Merton 28169 14224 31535 35905
3395 E01003468 Merton 31001 4533 36684 36012
3396 E01003469 Merton 17934 15813 40788 36614
3397 E01003470 Merton 25091 13598 40761 36614
3398 E01003471 Merton 27014 9212 34594 37054
3399 E01003472 Merton 31671 816 10888 33513
3400 E01003473 Merton 30253 1306 16908 34957
3401 E01003474 Merton 30969 7469 4586 34510
3402 E01003475 Merton 16682 14619 19638 36858
3403 E01003476 Merton 22492 5307 23243 36486
3404 E01003477 Merton 26305 18379 7620 37678
3405 E01003478 Merton 28880 1999 14684 35819
3406 E01003479 Newham 7984 24676 21315 40393
3407 E01003480 Newham 11375 19907 23096 40939
3408 E01003481 Newham 8693 18767 26009 40680
3409 E01003482 Newham 9464 27486 31540 41167
3410 E01003483 Newham 5149 14910 18497 41129
3411 E01003484 Newham 12241 4865 23985 41387
3412 E01003485 Newham 11327 10794 14566 41264
3413 E01003486 Newham 2519 3249 26597 40855
3414 E01003487 Newham 3338 16731 32780 40441
3415 E01003488 Newham 4059 947 35569 41327
3416 E01003489 Newham 6119 2150 40797 41365
3417 E01003490 Newham 7543 2955 37819 41421
3418 E01003491 Newham 8256 2458 41216 41365
3419 E01003492 Newham 10800 2870 39217 41338
3420 E01003493 Newham 9393 907 39579 41431
3421 E01003494 Newham 13284 8780 40263 41338
3422 E01003495 Newham 16134 8043 37683 41446
3423 E01003496 Newham 8737 18937 28003 41410
3424 E01003497 Newham 6552 3178 32471 41486
3425 E01003498 Newham 6586 6876 29909 41429
3426 E01003499 Newham 4081 1642 34165 41426
3427 E01003500 Newham 6133 15704 33269 41460
3428 E01003501 Newham 5437 3179 35260 41491
3429 E01003502 Newham 5384 1692 34119 41496
3430 E01003503 Newham 4459 4495 27745 41530
3431 E01003506 Newham 3005 6038 27997 41173
3432 E01003507 Newham 6282 1540 38315 41454
3433 E01003508 Newham 5231 6965 35673 41454
3434 E01003509 Newham 5736 5231 39650 41454
3435 E01003511 Newham 5790 8304 27789 41466
3436 E01003512 Newham 5783 9545 30006 41117
3437 E01003513 Newham 12640 15807 10146 40408
3438 E01003514 Newham 5315 14845 26682 40416
3439 E01003515 Newham 2533 12244 31108 40889
3440 E01003516 Newham 4284 10389 29755 40821
3441 E01003517 Newham 2706 4747 30500 41117
3442 E01003518 Newham 12298 11990 12730 40997
3443 E01003519 Newham 8298 15291 37050 40821
3444 E01003520 Newham 9784 2359 39283 41391
3445 E01003521 Newham 8772 934 40397 41449
3446 E01003522 Newham 7371 5223 39312 41449
3447 E01003523 Newham 7292 499 35366 41512
3448 E01003524 Newham 8734 1625 39050 41467
3449 E01003525 Newham 7708 1152 39724 41543
3450 E01003526 Newham 7996 9 36454 41543
3451 E01003527 Newham 14394 5814 35447 41512
3452 E01003528 Newham 7853 10107 18402 41297
3453 E01003529 Newham 11784 3365 32794 41272
3454 E01003530 Newham 12818 10697 29834 41272
3455 E01003531 Newham 8410 108 35277 41272
3456 E01003532 Newham 10613 3446 35601 41272
3457 E01003533 Newham 9258 899 39764 41272
3458 E01003534 Newham 10661 2488 30992 41134
3459 E01003535 Newham 3580 17533 21615 41594
3460 E01003536 Newham 8245 15796 37912 41553
3461 E01003537 Newham 10573 6907 37796 41393
3462 E01003538 Newham 7064 14301 36460 41553
3463 E01003539 Newham 9378 13619 40080 41393
3464 E01003540 Newham 4673 16453 27776 41553
3465 E01003541 Newham 9496 24112 37250 41393
3466 E01003542 Newham 6748 13291 22705 41567
3467 E01003543 Newham 11912 7858 38088 41058
3468 E01003544 Newham 8651 8617 39142 41102
3469 E01003545 Newham 9504 14165 36171 41102
3470 E01003546 Newham 6455 6033 39523 41102
3471 E01003547 Newham 15291 15792 27112 40907
3472 E01003548 Newham 12546 7297 39416 41038
3473 E01003549 Newham 10418 11218 39310 41184
3474 E01003550 Newham 9615 9503 39258 41049
3475 E01003551 Newham 5894 9434 39429 41207
3476 E01003552 Newham 8113 4147 38427 41207
3477 E01003553 Newham 5596 10461 38285 41184
3478 E01003554 Newham 12839 8199 37810 41312
3479 E01003555 Newham 10282 7178 29942 41058
3480 E01003556 Newham 3646 1702 37693 41168
3481 E01003557 Newham 5271 5920 33976 41149
3482 E01003558 Newham 4804 4062 41589 41140
3483 E01003559 Newham 13767 3419 40543 41184
3484 E01003560 Newham 9022 2814 37887 41134
3485 E01003561 Newham 11544 2734 39096 41134
3486 E01003562 Newham 10266 994 40399 41272
3487 E01003563 Newham 9532 2887 37915 41272
3488 E01003564 Newham 9354 285 41081 41272
3489 E01003565 Newham 10503 396 40425 41327
3490 E01003566 Newham 7833 527 41328 41327
3491 E01003567 Newham 7033 2154 39793 41126
3492 E01003568 Newham 11361 4440 39813 41182
3493 E01003569 Newham 9189 234 41433 41196
3494 E01003570 Newham 7384 2375 41234 41140
3495 E01003571 Newham 9039 1547 41416 41201
3496 E01003572 Newham 9158 252 41497 41157
3497 E01003573 Newham 9549 1349 41350 41201
3498 E01003574 Newham 8339 1149 40363 41119
3499 E01003575 Newham 8100 2325 26247 41396
3500 E01003576 Newham 4849 3849 17105 40930
3501 E01003577 Newham 4012 5499 6226 41326
3502 E01003578 Newham 10059 1593 36173 40446
3503 E01003579 Newham 8778 2444 30468 41003
3504 E01003580 Newham 6741 13890 8806 41549
3505 E01003581 Newham 9714 4625 31462 41003
3506 E01003582 Newham 7600 12343 12010 41447
3507 E01003583 Newham 8779 5235 22186 41447
3508 E01003584 Newham 8266 10763 22627 40689
3509 E01003585 Newham 9049 193 34128 41003
3510 E01003586 Newham 8043 5564 33197 41134
3511 E01003587 Newham 9006 4650 28774 41098
3512 E01003588 Newham 8411 3827 38394 41134
3513 E01003589 Newham 9696 4015 38161 41272
3514 E01003590 Newham 4780 8972 18202 40681
3515 E01003591 Newham 6209 2577 35839 41003
3516 E01003592 Newham 6110 7854 37744 41107
3517 E01003593 Newham 6804 3852 37864 41336
3518 E01003594 Newham 8396 1416 38568 41221
3519 E01003595 Newham 8140 798 39780 41221
3520 E01003596 Newham 10626 1671 37926 41119
3521 E01003597 Newham 10384 5929 39174 41107
3522 E01003598 Newham 7435 3899 38549 41107
3523 E01003599 Newham 7477 7054 35735 41188
3524 E01003600 Newham 6130 2230 37698 41085
3525 E01003601 Newham 5153 3182 33360 41114
3526 E01003602 Newham 10115 822 35905 41426
3527 E01003603 Newham 12180 6706 39915 41293
3528 E01003604 Newham 5642 4291 29959 41211
3529 E01003605 Newham 8278 1337 39833 41338
3530 E01003606 Newham 8735 2429 39482 41271
3531 E01003607 Newham 7786 868 37925 41221
3532 E01003608 Newham 11406 4973 38866 41378
3533 E01003609 Newham 12030 21799 18156 40504
3534 E01003611 Newham 7348 9439 5076 40272
3535 E01003615 Newham 9394 2826 34918 41092
3536 E01003616 Newham 8296 6199 36421 41199
3537 E01003617 Newham 8005 3611 40250 41245
3538 E01003618 Newham 9706 2058 38944 41312
3539 E01003619 Newham 5784 4334 39286 41234
3540 E01003621 Newham 12000 1081 32932 41590
3541 E01003622 Newham 6357 2042 27672 41551
3542 E01003623 Newham 7356 9047 31904 41639
3543 E01003624 Newham 7229 4115 32038 41590
3544 E01003625 Newham 8697 14417 25636 41388
3545 E01003626 Newham 11413 8758 35398 41388
3546 E01003627 Newham 8805 6467 34749 41457
3547 E01003628 Newham 13234 7687 29016 41501
3548 E01003629 Newham 9618 2448 36546 41449
3549 E01003630 Newham 8101 1813 32200 41085
3550 E01003631 Newham 9440 11000 30271 41410
3551 E01003632 Newham 13571 3936 30288 41026
3552 E01003633 Newham 4440 1896 23875 41026
3553 E01003634 Newham 7499 2984 22418 41192
3554 E01003635 Newham 10995 8535 36160 41174
3555 E01003636 Newham 6945 5651 31146 41187
3556 E01003637 Newham 12791 6751 32963 41085
3557 E01003638 Redbridge 16400 14792 38163 39185
3558 E01003639 Redbridge 14102 15415 36625 38735
3559 E01003640 Redbridge 16305 26848 4909 36396
3560 E01003641 Redbridge 19658 21100 24899 39249
3561 E01003642 Redbridge 17430 19435 29094 39249
3562 E01003643 Redbridge 22934 7147 37917 39123
3563 E01003644 Redbridge 21466 7177 37043 40044
3564 E01003645 Redbridge 14895 2005 39045 39466
3565 E01003646 Redbridge 21747 9056 32697 39658
3566 E01003647 Redbridge 20532 5771 36449 40044
3567 E01003648 Redbridge 27567 5106 30594 39033
3568 E01003649 Redbridge 25780 2424 34116 40363
3569 E01003650 Redbridge 17738 2111 35107 39571
3570 E01003651 Redbridge 22972 10583 31041 40027
3571 E01003652 Redbridge 26981 4685 32077 39983
3572 E01003653 Redbridge 19591 2752 39291 39983
3573 E01003654 Redbridge 15907 18517 10813 39587
3574 E01003655 Redbridge 24380 19401 27011 38947
3575 E01003656 Redbridge 9053 16725 6690 39233
3576 E01003657 Redbridge 21818 25819 12901 40280
3577 E01003658 Redbridge 12182 20819 21419 39044
3578 E01003659 Redbridge 23697 28150 7280 40673
3579 E01003660 Redbridge 28631 26025 8392 37672
3580 E01003661 Redbridge 16106 1675 35363 39838
3581 E01003662 Redbridge 16077 2757 38948 39838
3582 E01003663 Redbridge 18844 15780 29443 39411
3583 E01003664 Redbridge 18219 17070 35161 39516
3584 E01003665 Redbridge 22292 6816 34833 39838
3585 E01003666 Redbridge 14098 8197 35156 39702
3586 E01003668 Redbridge 25877 4375 21721 39104
3587 E01003669 Redbridge 29252 2656 33062 40419
3588 E01003670 Redbridge 25058 5435 17910 39961
3589 E01003671 Redbridge 31809 12142 24504 38911
3590 E01003672 Redbridge 16827 1158 30708 40057
3591 E01003673 Redbridge 23653 5766 32322 39759
3592 E01003674 Redbridge 25801 4553 34170 39759
3593 E01003675 Redbridge 19264 5683 13986 39413
3594 E01003676 Redbridge 24174 6171 21208 39413
3595 E01003677 Redbridge 25226 13939 14631 40350
3596 E01003678 Redbridge 24850 11202 31689 41076
3597 E01003679 Redbridge 25777 9309 34457 40321
3598 E01003680 Redbridge 27414 4403 36393 39616
3599 E01003681 Redbridge 18092 11306 20541 40240
3600 E01003682 Redbridge 26704 12495 21769 40332
3601 E01003683 Redbridge 14189 7145 27592 41615
3602 E01003684 Redbridge 15771 10671 25561 41632
3603 E01003685 Redbridge 13604 1798 31153 41545
3604 E01003686 Redbridge 9947 3435 25429 41579
3605 E01003688 Redbridge 10610 288 27914 41359
3606 E01003689 Redbridge 7418 472 34331 41545
3607 E01003690 Redbridge 15629 6703 30217 40208
3608 E01003691 Redbridge 20419 13995 14619 40133
3609 E01003692 Redbridge 19306 4506 20623 39837
3610 E01003693 Redbridge 19697 22249 8145 39575
3611 E01003694 Redbridge 17773 13629 16760 39318
3612 E01003695 Redbridge 12102 11689 21440 40041
3613 E01003696 Redbridge 22750 12061 23987 39658
3614 E01003697 Redbridge 16185 18389 9559 39575
3615 E01003698 Redbridge 19482 6511 35791 37937
3616 E01003699 Redbridge 20047 22789 33577 36802
3617 E01003700 Redbridge 16080 7802 34318 38000
3618 E01003701 Redbridge 17540 1137 40821 38361
3619 E01003702 Redbridge 17235 17532 38719 37214
3620 E01003703 Redbridge 19424 22956 24404 39336
3621 E01003704 Redbridge 15466 6016 37725 37604
3622 E01003705 Redbridge 19660 4704 37775 38276
3623 E01003706 Redbridge 17640 8999 36577 38054
3624 E01003707 Redbridge 18419 16746 33048 40248
3625 E01003708 Redbridge 8492 18701 23507 40206
3626 E01003709 Redbridge 24915 12499 38449 40248
3627 E01003710 Redbridge 23433 16681 25519 40958
3628 E01003711 Redbridge 17087 10844 39185 38540
3629 E01003712 Redbridge 4305 16109 37524 38704
3630 E01003713 Redbridge 16721 3483 25071 40339
3631 E01003714 Redbridge 15160 1629 29413 40715
3632 E01003715 Redbridge 14846 955 29697 40715
3633 E01003716 Redbridge 12597 3518 9155 39958
3634 E01003718 Redbridge 15521 2167 19875 39532
3635 E01003719 Redbridge 11868 615 22497 40056
3636 E01003720 Redbridge 7685 3607 31308 35925
3637 E01003721 Redbridge 14768 19809 39789 37561
3638 E01003722 Redbridge 11062 26729 22130 33833
3639 E01003723 Redbridge 8981 14316 17008 33821
3640 E01003724 Redbridge 15922 19437 19682 36227
3641 E01003725 Redbridge 10042 10902 35371 37169
3642 E01003726 Redbridge 7199 33950 20271 33832
3643 E01003727 Redbridge 8070 1997 25205 36169
3644 E01003728 Redbridge 8420 3093 15717 40920
3645 E01003729 Redbridge 8275 724 28489 41488
3646 E01003730 Redbridge 11709 1990 28840 41604
3647 E01003731 Redbridge 9924 2946 22066 41604
3648 E01003732 Redbridge 6300 8635 3866 41549
3649 E01003733 Redbridge 10523 1175 24431 41604
3650 E01003734 Redbridge 12747 759 25458 41578
3651 E01003735 Redbridge 6134 5561 2470 41536
3652 E01003736 Redbridge 10763 5259 19242 41566
3653 E01003737 Redbridge 19340 8763 15629 40615
3654 E01003738 Redbridge 19783 18707 16264 40501
3655 E01003739 Redbridge 14512 10919 15238 41476
3656 E01003740 Redbridge 15804 11428 829 41476
3657 E01003741 Redbridge 17671 11755 12887 41147
3658 E01003742 Redbridge 18836 2553 13782 40983
3659 E01003743 Redbridge 13901 10533 19199 41476
3660 E01003744 Redbridge 26576 26481 11756 37525
3661 E01003745 Redbridge 29754 18223 9500 36975
3662 E01003746 Redbridge 31386 22056 13165 37933
3663 E01003747 Redbridge 29547 12513 9832 38508
3664 E01003748 Redbridge 30568 8280 17676 38508
3665 E01003749 Redbridge 26609 13940 24991 38741
3666 E01003750 Redbridge 21971 13656 20812 39461
3667 E01003751 Redbridge 17637 15300 33263 39296
3668 E01003752 Redbridge 21341 11666 32607 40366
3669 E01003753 Redbridge 20656 7792 32581 40099
3670 E01003754 Redbridge 21046 5774 34048 40099
3671 E01003755 Redbridge 19173 10904 39489 40263
3672 E01003756 Redbridge 17117 14554 33499 40540
3673 E01003757 Redbridge 14062 7830 28312 41018
3674 E01003758 Redbridge 13455 10798 28922 41018
3675 E01003759 Redbridge 30489 17602 16476 40079
3676 E01003760 Redbridge 18912 21684 9098 39737
3677 E01003761 Redbridge 4343 21364 7013 40666
3678 E01003762 Redbridge 19879 26488 13402 39462
3679 E01003763 Redbridge 22891 15629 14126 40937
3680 E01003764 Redbridge 19839 19947 29757 39959
3681 E01003765 Redbridge 26421 22713 29184 39959
3682 E01003766 Redbridge 14798 6234 37287 39932
3683 E01003767 Redbridge 12449 3923 36144 39932
3684 E01003768 Redbridge 8376 1530 32324 40386
3685 E01003769 Redbridge 10920 1534 38199 39932
3686 E01003770 Redbridge 17295 9633 26997 39554
3687 E01003771 Redbridge 17062 3668 31720 39799
3688 E01003772 Redbridge 16747 6264 35039 39772
3689 E01003773 Redbridge 18922 3650 31901 39621
3690 E01003774 Redbridge 25937 7833 7204 40629
3691 E01003775 Redbridge 27588 12682 2063 39860
3692 E01003776 Redbridge 11451 12721 1153 40788
3693 E01003777 Redbridge 27288 1219 17177 40462
3694 E01003778 Redbridge 24959 1425 13432 41480
3695 E01003779 Redbridge 19836 2886 22012 41301
3696 E01003780 Redbridge 29644 12564 15877 40117
3697 E01003781 Redbridge 16875 1088 24471 40607
3698 E01003782 Redbridge 12806 1912 34911 40935
3699 E01003783 Redbridge 6193 366 34081 41015
3700 E01003784 Redbridge 15774 6121 7372 40376
3701 E01003785 Redbridge 10363 3274 10200 40496
3702 E01003786 Redbridge 21062 11496 27904 40594
3703 E01003787 Redbridge 18548 4993 28183 40594
3704 E01003788 Redbridge 10819 6208 14638 40376
3705 E01003789 Redbridge 24187 11855 11313 41071
3706 E01003790 Redbridge 17735 17922 350 40152
3707 E01003791 Redbridge 18271 15412 3863 41096
3708 E01003792 Redbridge 22984 14734 740 40725
3709 E01003793 Redbridge 10782 8316 2557 40483
3710 E01003794 Redbridge 27130 10648 21161 40548
3711 E01003795 Redbridge 26624 17101 5021 40452
3712 E01003796 Redbridge 25148 12880 8679 40599
3713 E01003797 Richmond upon Thames 29529 9489 3229 38112
3714 E01003798 Richmond upon Thames 26405 2178 5816 37939
3715 E01003799 Richmond upon Thames 28093 1095 15592 37633
3716 E01003800 Richmond upon Thames 20893 7696 1717 37960
3717 E01003801 Richmond upon Thames 31478 5137 16405 38576
3718 E01003802 Richmond upon Thames 30831 14800 2782 37602
3719 E01003803 Richmond upon Thames 11485 5844 3569 38723
3720 E01003804 Richmond upon Thames 29734 4891 19917 35818
3721 E01003805 Richmond upon Thames 31751 10827 10957 33361
3722 E01003806 Richmond upon Thames 27043 13439 3230 31323
3723 E01003807 Richmond upon Thames 27275 2220 32917 35227
3724 E01003808 Richmond upon Thames 29480 2323 26114 33923
3725 E01003809 Richmond upon Thames 29373 6169 5951 32078
3726 E01003810 Richmond upon Thames 27730 2713 16588 32496
3727 E01003811 Richmond upon Thames 30014 1638 23563 32496
3728 E01003812 Richmond upon Thames 27315 1009 27837 34021
3729 E01003813 Richmond upon Thames 30765 6307 1247 33739
3730 E01003814 Richmond upon Thames 25837 2745 11341 32496
3731 E01003815 Richmond upon Thames 25903 971 15825 33242
3732 E01003816 Richmond upon Thames 21996 23053 2345 33325
3733 E01003817 Richmond upon Thames 23338 7592 3820 33863
3734 E01003818 Richmond upon Thames 28188 10052 1298 35828
3735 E01003819 Richmond upon Thames 8640 10668 2346 36191
3736 E01003820 Richmond upon Thames 22800 7150 8367 35582
3737 E01003821 Richmond upon Thames 30378 7665 4058 34548
3738 E01003822 Richmond upon Thames 32237 12879 2786 33631
3739 E01003823 Richmond upon Thames 28018 18630 2039 33159
3740 E01003824 Richmond upon Thames 30910 1398 8685 33118
3741 E01003825 Richmond upon Thames 32070 10050 14796 33119
3742 E01003826 Richmond upon Thames 12129 7528 14258 32611
3743 E01003827 Richmond upon Thames 26433 8947 16336 33499
3744 E01003828 Richmond upon Thames 29370 10093 6554 33691
3745 E01003829 Richmond upon Thames 9764 20411 1199 34101
3746 E01003830 Richmond upon Thames 25199 14340 2396 33504
3747 E01003831 Richmond upon Thames 24306 23387 18629 33691
3748 E01003832 Richmond upon Thames 5206 31537 14349 33375
3749 E01003833 Richmond upon Thames 17419 27173 19873 33263
3750 E01003834 Richmond upon Thames 27946 3203 5669 31113
3751 E01003835 Richmond upon Thames 31040 12555 2807 33873
3752 E01003836 Richmond upon Thames 21069 8615 5850 33434
3753 E01003837 Richmond upon Thames 27266 15400 347 33275
3754 E01003838 Richmond upon Thames 27892 7051 5780 31515
3755 E01003839 Richmond upon Thames 20899 2851 1295 31925
3756 E01003840 Richmond upon Thames 19113 19247 24020 37476
3757 E01003841 Richmond upon Thames 10173 15482 8129 37476
3758 E01003842 Richmond upon Thames 14040 10633 19048 37664
3759 E01003843 Richmond upon Thames 18212 11936 10820 37735
3760 E01003844 Richmond upon Thames 25517 5428 21741 36959
3761 E01003845 Richmond upon Thames 25364 8184 1378 37460
3762 E01003846 Richmond upon Thames 31335 12591 4407 37903
3763 E01003847 Richmond upon Thames 28640 9257 926 36800
3764 E01003848 Richmond upon Thames 22916 14084 12667 37326
3765 E01003849 Richmond upon Thames 26496 6993 3716 36874
3766 E01003851 Richmond upon Thames 29595 9930 3503 35981
3767 E01003852 Richmond upon Thames 20334 12755 6696 34489
3768 E01003853 Richmond upon Thames 22779 4255 4390 35569
3769 E01003854 Richmond upon Thames 27287 2245 7746 35468
3770 E01003855 Richmond upon Thames 15099 11173 20653 37770
3771 E01003856 Richmond upon Thames 29104 11461 21397 36320
3772 E01003857 Richmond upon Thames 29987 9744 20865 35468
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4217 E01004325 Tower Hamlets 11050 386 41145 41634
4218 E01004326 Tower Hamlets 10008 631 37026 41539
4219 E01004327 Waltham Forest 7992 2145 40771 41381
4220 E01004328 Waltham Forest 11954 3009 41120 41143
4221 E01004329 Waltham Forest 11575 4676 39169 41053
4222 E01004330 Waltham Forest 17056 3157 41113 41143
4223 E01004331 Waltham Forest 12158 8767 39448 41090
4224 E01004332 Waltham Forest 8927 6415 38351 41038
4225 E01004333 Waltham Forest 9066 7283 38437 41381
4226 E01004334 Waltham Forest 3119 3896 39339 41381
4227 E01004335 Waltham Forest 4362 647 38072 41074
4228 E01004336 Waltham Forest 11164 1130 35393 41047
4229 E01004337 Waltham Forest 10118 1656 31101 41092
4230 E01004338 Waltham Forest 14941 1161 34721 41047
4231 E01004339 Waltham Forest 11057 9563 38942 41379
4232 E01004340 Waltham Forest 3432 2683 36690 41121
4233 E01004341 Waltham Forest 7036 6705 39907 41078
4234 E01004342 Waltham Forest 12475 2998 32076 40714
4235 E01004343 Waltham Forest 18190 12272 31302 40808
4236 E01004344 Waltham Forest 7780 13233 30072 40808
4237 E01004345 Waltham Forest 13646 2194 35428 40521
4238 E01004346 Waltham Forest 15972 8553 13134 40340
4239 E01004347 Waltham Forest 18452 7354 28478 40340
4240 E01004348 Waltham Forest 15993 962 39613 40817
4241 E01004349 Waltham Forest 8091 24908 830 37137
4242 E01004350 Waltham Forest 8698 13137 3631 36911
4243 E01004351 Waltham Forest 18892 19943 6043 37008
4244 E01004352 Waltham Forest 23995 14447 21153 36564
4245 E01004353 Waltham Forest 17875 24622 15274 37228
4246 E01004354 Waltham Forest 20330 10073 38368 38192
4247 E01004355 Waltham Forest 10657 14259 9797 39830
4248 E01004356 Waltham Forest 10256 10382 3297 39000
4249 E01004357 Waltham Forest 16459 10717 3916 38619
4250 E01004358 Waltham Forest 12717 9902 16816 38754
4251 E01004359 Waltham Forest 21404 9474 24692 38506
4252 E01004360 Waltham Forest 20890 11610 15246 39127
4253 E01004361 Waltham Forest 18552 12177 8157 40554
4254 E01004362 Waltham Forest 11856 18546 24856 41022
4255 E01004363 Waltham Forest 14952 8237 20035 41148
4256 E01004364 Waltham Forest 7069 1223 33209 40719
4257 E01004365 Waltham Forest 8358 279 40710 40908
4258 E01004366 Waltham Forest 14761 8059 33633 40951
4259 E01004367 Waltham Forest 9423 785 36834 40906
4260 E01004368 Waltham Forest 12888 5286 32820 40748
4261 E01004369 Waltham Forest 18122 1828 38822 40682
4262 E01004370 Waltham Forest 19459 4247 39740 40748
4263 E01004371 Waltham Forest 13836 3340 38845 40993
4264 E01004372 Waltham Forest 22386 3455 39109 40895
4265 E01004373 Waltham Forest 10432 164 39034 40682
4266 E01004374 Waltham Forest 16899 2966 39479 40994
4267 E01004375 Waltham Forest 13709 388 37197 40994
4268 E01004376 Waltham Forest 12644 1494 39073 40994
4269 E01004377 Waltham Forest 14476 13666 30886 40853
4270 E01004378 Waltham Forest 12064 11119 33795 40353
4271 E01004379 Waltham Forest 22382 5509 34113 40512
4272 E01004380 Waltham Forest 12272 11165 4668 40768
4273 E01004381 Waltham Forest 18539 5948 25273 40674
4274 E01004382 Waltham Forest 4663 14983 32351 41225
4275 E01004383 Waltham Forest 18959 7603 20330 41075
4276 E01004384 Waltham Forest 7043 11800 15785 39062
4277 E01004385 Waltham Forest 6481 3332 4001 39340
4278 E01004386 Waltham Forest 25868 14072 11240 39030
4279 E01004387 Waltham Forest 28095 14811 7020 40196
4280 E01004388 Waltham Forest 14955 9851 6162 40503
4281 E01004389 Waltham Forest 7533 17870 16474 38192
4282 E01004390 Waltham Forest 5903 15539 13114 38631
4283 E01004391 Waltham Forest 13300 7183 10755 39857
4284 E01004392 Waltham Forest 10024 4437 23609 40053
4285 E01004393 Waltham Forest 12894 10287 11099 39769
4286 E01004394 Waltham Forest 5529 2985 17383 40053
4287 E01004395 Waltham Forest 16750 12532 3452 39888
4288 E01004396 Waltham Forest 14422 2894 25481 39008
4289 E01004397 Waltham Forest 9666 6269 39611 40534
4290 E01004398 Waltham Forest 4902 12382 2487 39889
4291 E01004399 Waltham Forest 2576 11807 4101 39966
4292 E01004400 Waltham Forest 8395 13294 18304 39925
4293 E01004401 Waltham Forest 12638 13255 23350 39770
4294 E01004402 Waltham Forest 6798 9163 18971 39428
4295 E01004403 Waltham Forest 7659 9079 13239 40431
4296 E01004404 Waltham Forest 8644 10855 25411 39460
4297 E01004405 Waltham Forest 8814 2964 33773 40908
4298 E01004406 Waltham Forest 12412 1437 36618 40751
4299 E01004407 Waltham Forest 3915 6162 14785 41041
4300 E01004408 Waltham Forest 11853 1342 36234 41041
4301 E01004409 Waltham Forest 9342 3985 37615 40903
4302 E01004410 Waltham Forest 6167 3616 19699 40938
4303 E01004411 Waltham Forest 9899 3504 37420 40903
4304 E01004412 Waltham Forest 15738 1938 29639 40931
4305 E01004413 Waltham Forest 6997 10144 26818 39642
4306 E01004414 Waltham Forest 13165 4177 27558 40455
4307 E01004415 Waltham Forest 9922 4916 24549 39843
4308 E01004416 Waltham Forest 12086 14071 18921 40518
4309 E01004417 Waltham Forest 12004 3582 28042 40256
4310 E01004418 Waltham Forest 14916 5240 30843 40765
4311 E01004419 Waltham Forest 13460 12127 32873 41225
4312 E01004420 Waltham Forest 3684 612 37890 40616
4313 E01004421 Waltham Forest 10740 232 33749 40605
4314 E01004422 Waltham Forest 9657 17261 20590 40520
4315 E01004423 Waltham Forest 5540 1776 34578 40349
4316 E01004424 Waltham Forest 5128 1418 35007 40623
4317 E01004425 Waltham Forest 10288 2504 28012 40688
4318 E01004426 Waltham Forest 10530 4514 32183 40469
4319 E01004427 Waltham Forest 13096 7000 23776 40776
4320 E01004428 Waltham Forest 4387 8787 33314 40469
4321 E01004429 Waltham Forest 11880 2187 38388 40960
4322 E01004430 Waltham Forest 11129 1518 39225 41040
4323 E01004432 Waltham Forest 9936 6073 36050 40555
4324 E01004434 Waltham Forest 9155 10506 33309 40581
4325 E01004435 Waltham Forest 8481 1083 34817 40469
4326 E01004436 Waltham Forest 9833 13490 32988 41215
4327 E01004437 Waltham Forest 10395 8500 29778 41232
4328 E01004438 Waltham Forest 13609 371 37315 41068
4329 E01004439 Waltham Forest 15233 4557 37303 41232
4330 E01004440 Waltham Forest 10223 6774 39071 41231
4331 E01004441 Waltham Forest 15444 2605 30436 41204
4332 E01004442 Waltham Forest 20152 15298 25961 41215
4333 E01004443 Waltham Forest 7369 1719 39747 40777
4334 E01004444 Waltham Forest 6152 505 31040 40802
4335 E01004445 Waltham Forest 8617 3900 36756 40777
4336 E01004446 Waltham Forest 11752 478 19826 40802
4337 E01004447 Waltham Forest 17154 2737 35222 40558
4338 E01004448 Waltham Forest 9772 2558 21710 40191
4339 E01004449 Waltham Forest 2803 6309 35026 40657
4340 E01004450 Waltham Forest 18040 12478 8406 40498
4341 E01004451 Waltham Forest 17874 9450 9682 40498
4342 E01004452 Waltham Forest 10862 1255 24134 40481
4343 E01004453 Waltham Forest 10327 9679 12411 40367
4344 E01004454 Waltham Forest 11139 2431 19462 40639
4345 E01004455 Waltham Forest 8328 2740 29614 40490
4346 E01004456 Waltham Forest 3536 6343 31266 40351
4347 E01004457 Waltham Forest 13953 3086 33284 40155
4348 E01004458 Waltham Forest 10047 1778 32468 39008
4349 E01004459 Waltham Forest 3379 5265 17203 39428
4350 E01004460 Waltham Forest 8097 469 37321 40881
4351 E01004461 Waltham Forest 18694 14671 29675 39297
4352 E01004462 Waltham Forest 11471 5383 33444 40277
4353 E01004463 Waltham Forest 18935 3830 17516 40318
4354 E01004464 Waltham Forest 5047 12327 38157 41062
4355 E01004465 Waltham Forest 16047 3164 30896 41062
4356 E01004466 Waltham Forest 19125 4338 30094 40949
4357 E01004467 Waltham Forest 8188 5886 26301 41062
4358 E01004468 Waltham Forest 16258 17715 7550 40627
4359 E01004469 Waltham Forest 4431 8416 22203 40695
4360 E01004470 Waltham Forest 6157 1369 35890 41041
4361 E01004471 Waltham Forest 6772 2038 23383 41041
4362 E01004472 Wandsworth 24666 5502 29987 37908
4363 E01004473 Wandsworth 22310 2928 36891 38410
4364 E01004474 Wandsworth 16534 632 39686 38153
4365 E01004475 Wandsworth 17970 1482 35106 38617
4366 E01004476 Wandsworth 20382 4844 31940 37908
4367 E01004477 Wandsworth 30427 5362 23616 37749
4368 E01004478 Wandsworth 31143 6999 32357 37749
4369 E01004479 Wandsworth 24219 1950 12001 37967
4370 E01004480 Wandsworth 28021 6709 39275 38351
4371 E01004481 Wandsworth 18761 207 39795 39069
4372 E01004482 Wandsworth 18803 5130 34429 39311
4373 E01004483 Wandsworth 19926 22365 36244 39213
4374 E01004484 Wandsworth 15837 1663 28924 38815
4375 E01004485 Wandsworth 17817 314 34961 38793
4376 E01004486 Wandsworth 16426 3609 30345 39196
4377 E01004487 Wandsworth 13248 2845 34186 39326
4378 E01004488 Wandsworth 19364 1670 33642 39326
4379 E01004489 Wandsworth 9627 7848 30676 39311
4380 E01004490 Wandsworth 28015 3511 21378 37338
4381 E01004491 Wandsworth 19740 16683 22227 37928
4382 E01004492 Wandsworth 18414 6729 21343 36858
4383 E01004493 Wandsworth 20364 1420 31840 36607
4384 E01004494 Wandsworth 15151 34 38175 36390
4385 E01004495 Wandsworth 11697 3687 23573 36607
4386 E01004496 Wandsworth 22187 2345 25038 36294
4387 E01004497 Wandsworth 17512 5057 16442 37710
4388 E01004498 Wandsworth 26162 86 10644 35916
4389 E01004499 Wandsworth 20104 578 26817 35934
4390 E01004500 Wandsworth 23432 4707 13000 35560
4391 E01004501 Wandsworth 16374 4179 7324 35116
4392 E01004502 Wandsworth 25288 3123 27712 35934
4393 E01004503 Wandsworth 15634 7677 8616 35983
4394 E01004504 Wandsworth 24721 8481 13833 35727
4395 E01004505 Wandsworth 27364 10180 13478 34790
4396 E01004506 Wandsworth 25152 496 19495 36232
4397 E01004507 Wandsworth 26239 995 15050 35983
4398 E01004508 Wandsworth 23599 735 30230 38867
4399 E01004509 Wandsworth 18176 2130 38130 37893
4400 E01004510 Wandsworth 26091 588 33965 38908
4401 E01004511 Wandsworth 26969 1186 24952 36735
4402 E01004512 Wandsworth 21622 5648 32876 37080
4403 E01004513 Wandsworth 15875 4843 30116 37080
4404 E01004514 Wandsworth 25454 2940 35846 37977
4405 E01004515 Wandsworth 19074 656 32849 38908
4406 E01004516 Wandsworth 21815 4157 38213 39229
4407 E01004517 Wandsworth 18989 332 41302 39485
4408 E01004518 Wandsworth 20999 2057 41162 39427
4409 E01004519 Wandsworth 17332 6374 37630 39229
4410 E01004520 Wandsworth 17433 5631 38468 39229
4411 E01004521 Wandsworth 17534 4169 41360 39903
4412 E01004522 Wandsworth 15866 1154 41261 39519
4413 E01004523 Wandsworth 15182 4150 16956 39298
4414 E01004524 Wandsworth 5868 577 21242 39251
4415 E01004525 Wandsworth 13131 515 41171 39394
4416 E01004526 Wandsworth 12185 603 39644 39506
4417 E01004527 Wandsworth 18676 2925 39499 39361
4418 E01004528 Wandsworth 8673 6920 36324 39368
4419 E01004529 Wandsworth 20554 1620 40372 39368
4420 E01004530 Wandsworth 18736 1237 37230 39506
4421 E01004531 Wandsworth 10579 2183 38635 39361
4422 E01004532 Wandsworth 17810 9398 38909 39317
4423 E01004533 Wandsworth 9564 7462 39394 39361
4424 E01004534 Wandsworth 20468 28 22931 39819
4425 E01004535 Wandsworth 4970 3226 6347 39482
4426 E01004536 Wandsworth 11674 915 12084 39450
4427 E01004537 Wandsworth 6489 1745 15173 39482
4428 E01004538 Wandsworth 10702 1142 13498 39517
4429 E01004539 Wandsworth 6208 4695 7923 39981
4430 E01004540 Wandsworth 9942 433 10066 39346
4431 E01004541 Wandsworth 4700 166 21703 39374
4432 E01004542 Wandsworth 28352 5274 16998 38129
4433 E01004543 Wandsworth 27182 2843 16664 38237
4434 E01004544 Wandsworth 22063 2829 29338 38153
4435 E01004545 Wandsworth 23829 458 35444 38793
4436 E01004546 Wandsworth 28753 699 31151 38542
4437 E01004547 Wandsworth 14054 1723 26784 38650
4438 E01004548 Wandsworth 16560 354 33791 38677
4439 E01004549 Wandsworth 14976 2495 33656 38420
4440 E01004550 Wandsworth 20846 4365 14762 38002
4441 E01004551 Wandsworth 16564 120 39437 39482
4442 E01004552 Wandsworth 23714 205 39329 38820
4443 E01004553 Wandsworth 23022 713 32625 38618
4444 E01004554 Wandsworth 28864 1972 34164 38705
4445 E01004555 Wandsworth 30653 7020 31627 38414
4446 E01004556 Wandsworth 30796 2011 35380 37901
4447 E01004557 Wandsworth 26658 3881 27349 37901
4448 E01004558 Wandsworth 29652 3407 27894 37880
4449 E01004559 Wandsworth 27575 4615 6470 38014
4450 E01004560 Wandsworth 16606 1682 17059 40361
4451 E01004562 Wandsworth 8087 22069 40416 40264
4452 E01004563 Wandsworth 7775 4357 7662 40513
4453 E01004564 Wandsworth 15699 968 36029 40278
4454 E01004565 Wandsworth 15043 2232 35836 40013
4455 E01004566 Wandsworth 22476 4618 10890 40443
4456 E01004567 Wandsworth 7246 10381 35843 40066
4457 E01004568 Wandsworth 11579 2342 6573 30349
4458 E01004569 Wandsworth 10975 1318 7837 30349
4459 E01004570 Wandsworth 6433 5604 6912 30710
4460 E01004571 Wandsworth 11003 5792 7219 30710
4461 E01004572 Wandsworth 12072 19767 1026 32210
4462 E01004573 Wandsworth 9403 24814 17991 32032
4463 E01004574 Wandsworth 5928 4364 1213 30248
4464 E01004575 Wandsworth 8305 11151 7629 31748
4465 E01004576 Wandsworth 9829 12687 791 30725
4466 E01004577 Wandsworth 19652 1949 11178 39346
4467 E01004579 Wandsworth 15348 241 21056 39218
4468 E01004580 Wandsworth 15480 806 23501 39218
4469 E01004581 Wandsworth 18520 3993 21353 39218
4470 E01004582 Wandsworth 25733 6279 10163 40267
4471 E01004583 Wandsworth 21872 5455 11994 39963
4472 E01004584 Wandsworth 7042 2494 4978 39346
4473 E01004585 Wandsworth 24327 1284 30782 39731
4474 E01004586 Wandsworth 24309 1594 36637 39445
4475 E01004587 Wandsworth 26459 3276 37839 39408
4476 E01004588 Wandsworth 21164 196 37288 39525
4477 E01004589 Wandsworth 27504 2454 38460 39445
4478 E01004590 Wandsworth 10520 5126 33361 39731
4479 E01004591 Wandsworth 15550 583 36864 39408
4480 E01004592 Wandsworth 10399 4922 25316 39731
4481 E01004593 Wandsworth 26376 3053 36799 35481
4482 E01004594 Wandsworth 30272 1734 30214 35481
4483 E01004595 Wandsworth 26770 1634 32478 35481
4484 E01004596 Wandsworth 29297 2262 27512 34508
4485 E01004597 Wandsworth 22210 718 23361 34403
4486 E01004598 Wandsworth 26755 5153 21514 34403
4487 E01004599 Wandsworth 31858 2314 19123 33981
4488 E01004600 Wandsworth 9097 437 40210 35887
4489 E01004601 Wandsworth 14917 4466 25922 35392
4490 E01004602 Wandsworth 25029 2203 15085 36762
4491 E01004604 Wandsworth 27298 4656 15693 36089
4492 E01004605 Wandsworth 21436 5449 7009 36643
4493 E01004606 Wandsworth 29425 1695 14489 36458
4494 E01004607 Wandsworth 28435 1394 14580 35968
4495 E01004608 Wandsworth 18238 963 16082 36778
4496 E01004609 Wandsworth 23061 415 30774 36522
4497 E01004610 Wandsworth 14415 1644 37426 38366
4498 E01004611 Wandsworth 18072 2565 38789 39128
4499 E01004612 Wandsworth 13529 2808 38945 38943
4500 E01004613 Wandsworth 6866 616 40120 38943
4501 E01004614 Wandsworth 16536 1291 34332 38808
4502 E01004615 Wandsworth 5177 4401 13713 37659
4503 E01004616 Wandsworth 17793 181 39186 39394
4504 E01004617 Wandsworth 12245 878 38218 39257
4505 E01004618 Wandsworth 20722 4634 37253 38420
4506 E01004619 Wandsworth 20376 12108 2064 38074
4507 E01004620 Wandsworth 20379 6024 34956 36837
4508 E01004621 Wandsworth 17769 10741 6414 38061
4509 E01004622 Wandsworth 13491 10496 10391 38074
4510 E01004623 Wandsworth 25996 4475 31775 38122
4511 E01004624 Wandsworth 14815 11733 15873 37973
4512 E01004625 Wandsworth 27625 12129 13457 38013
4513 E01004626 Wandsworth 19942 3038 27109 37973
4514 E01004627 Wandsworth 24322 2783 30745 38155
4515 E01004628 Wandsworth 11763 6754 21432 34669
4516 E01004629 Wandsworth 26152 3507 10121 35983
4517 E01004630 Wandsworth 8066 3215 6902 33989
4518 E01004631 Wandsworth 13693 4034 5630 33989
4519 E01004632 Wandsworth 26566 7580 617 34602
4520 E01004633 Wandsworth 10006 2161 3009 35983
4521 E01004634 Wandsworth 21202 7002 4127 31201
4522 E01004635 Wandsworth 20830 5099 1658 33051
4523 E01004636 Wandsworth 18240 5557 3320 33051
4524 E01004637 Wandsworth 19001 12185 849 32017
4525 E01004638 Wandsworth 28633 5135 10958 34118
4526 E01004639 Wandsworth 24017 6403 10804 33757
4527 E01004640 Wandsworth 30360 5636 25092 35034
4528 E01004641 Wandsworth 14652 12845 13144 32386
4529 E01004642 Wandsworth 12645 16817 19916 32386
4530 E01004643 Wandsworth 12940 6461 12612 35116
4531 E01004644 Wandsworth 15979 12640 11049 30710
4532 E01004645 Wandsworth 8654 3656 5445 33214
4533 E01004646 Westminster 19570 3904 18667 40410
4534 E01004647 Westminster 17624 2862 9330 40848
4535 E01004648 Westminster 23935 3717 22292 40919
4536 E01004649 Westminster 29012 1086 28086 40330
4537 E01004650 Westminster 29514 4241 26558 40664
4538 E01004651 Westminster 25503 2651 31939 40664
4539 E01004652 Westminster 18062 1505 38430 41110
4540 E01004653 Westminster 23503 676 31715 40812
4541 E01004654 Westminster 21266 836 34873 40869
4542 E01004656 Westminster 11625 3001 29637 41110
4543 E01004657 Westminster 22741 2383 41238 41472
4544 E01004658 Westminster 18296 1281 41095 41346
4545 E01004659 Westminster 27574 483 32721 41616
4546 E01004660 Westminster 26318 424 38576 41616
4547 E01004661 Westminster 14144 94 35763 41616
4548 E01004662 Westminster 22170 263 38806 41616
4549 E01004663 Westminster 16131 280 35235 41616
4550 E01004665 Westminster 5376 1801 3104 40740
4551 E01004666 Westminster 10123 1112 32510 41000
4552 E01004667 Westminster 7987 3579 35088 41000
4553 E01004668 Westminster 15757 3081 33625 40667
4554 E01004669 Westminster 7591 2533 5754 40505
4555 E01004670 Westminster 2488 4981 25939 41492
4556 E01004674 Westminster 6143 2215 15156 40797
4557 E01004675 Westminster 6646 3306 20766 40797
4558 E01004676 Westminster 13382 3620 21588 41458
4559 E01004677 Westminster 12092 3697 31722 40613
4560 E01004678 Westminster 10961 1561 22235 40797
4561 E01004679 Westminster 7034 8 7043 40508
4562 E01004680 Westminster 23309 1475 30602 41346
4563 E01004681 Westminster 22113 5349 34200 41153
4564 E01004682 Westminster 19698 1236 30499 41153
4565 E01004683 Westminster 26341 5590 28229 41248
4566 E01004684 Westminster 13307 330 27129 41533
4567 E01004686 Westminster 11469 859 26851 41616
4568 E01004687 Westminster 28371 1476 38296 41069
4569 E01004688 Westminster 30198 9551 32529 41057
4570 E01004689 Westminster 17986 3718 33555 41067
4571 E01004690 Westminster 30073 3217 36240 41069
4572 E01004691 Westminster 23381 6808 40057 41094
4573 E01004692 Westminster 28779 7723 18353 41265
4574 E01004693 Westminster 21478 2728 31553 40849
4575 E01004694 Westminster 26491 2380 23896 41153
4576 E01004695 Westminster 21342 191 33245 40868
4577 E01004696 Westminster 6924 4120 3095 41110
4578 E01004697 Westminster 17722 3467 35536 41011
4579 E01004698 Westminster 14384 1010 18944 40978
4580 E01004699 Westminster 19200 339 38339 40869
4581 E01004700 Westminster 22989 2608 25306 41153
4582 E01004701 Westminster 25245 1833 23771 41370
4583 E01004702 Westminster 3687 63 19205 41487
4584 E01004703 Westminster 23871 2330 12042 41139
4585 E01004705 Westminster 30175 928 29074 41217
4586 E01004706 Westminster 27823 4073 16316 41458
4587 E01004707 Westminster 31583 5079 10934 41370
4588 E01004708 Westminster 12143 5797 22326 41099
4589 E01004709 Westminster 14236 987 22533 41370
4590 E01004710 Westminster 7483 808 25388 41099
4591 E01004711 Westminster 11199 3817 18533 41116
4592 E01004712 Westminster 23263 345 40043 41593
4593 E01004713 Westminster 27672 65 41535 41568
4594 E01004714 Westminster 24181 154 41462 41633
4595 E01004715 Westminster 18090 88 41556 41647
4596 E01004716 Westminster 27864 655 39756 41568
4597 E01004717 Westminster 22125 106 40239 41568
4598 E01004718 Westminster 8120 1679 14136 40215
4599 E01004719 Westminster 8731 23 18671 40215
4600 E01004720 Westminster 7066 3388 20047 39871
4601 E01004721 Westminster 4722 1913 627 39871
4602 E01004722 Westminster 5553 46 18208 40215
4603 E01004723 Westminster 8354 123 24631 40178
4604 E01004724 Westminster 23490 151 26396 41240
4605 E01004725 Westminster 9498 2338 27647 41241
4606 E01004726 Westminster 25261 3013 22841 40892
4607 E01004727 Westminster 24363 3095 22890 41495
4608 E01004728 Westminster 19059 312 24563 41217
4609 E01004729 Westminster 10420 5812 27631 41217
4610 E01004730 Westminster 28806 2688 9393 41435
4611 E01004731 Westminster 24520 84 35883 41145
4612 E01004732 Westminster 3324 30 37648 41193
4613 E01004733 Westminster 15991 163 24689 41318
4614 E01004734 Westminster 7933 261 41251 41663
4615 E01004735 Westminster 5794 795 39361 41690
4616 E01004736 Westminster 24862 2876 40635 41390
4617 E01004737 Westminster 14145 7151 10572 40662
4618 E01004738 Westminster 25164 3667 6972 40662
4619 E01004739 Westminster 25205 4503 18104 40592
4620 E01004740 Westminster 6426 160 18956 40921
4621 E01004741 Westminster 13839 291 8243 40921
4622 E01004742 Westminster 23098 141 25394 40921
4623 E01004743 Westminster 13668 82 31957 40878
4624 E01004744 Westminster 10482 55 37057 41020
4625 E01004745 Westminster 17777 725 28732 40878
4626 E01004746 Westminster 9216 230 23772 40921
4627 E01004747 Westminster 12655 362 31164 40921
4628 E01004748 Westminster 26006 25 38538 41020
4629 E01004749 Westminster 20814 401 36543 40980
4630 E01004750 Westminster 15320 1566 39710 41065
4631 E01004751 Westminster 24060 4948 37115 40980
4632 E01004752 Westminster 12381 824 30375 40921
4633 E01004753 Westminster 17568 2578 30313 40980
4634 E01004754 Westminster 2865 1243 12893 41088
4635 E01004755 Westminster 8689 112 22765 40810
4636 E01004756 Westminster 12183 9161 23930 41088
4637 E01004757 Westminster 4110 2800 10855 41110
4638 E01004760 Westminster 10773 1254 8177 40812
4639 E01004761 Westminster 26464 7164 41664 41249
4640 E01004762 Westminster 23921 2302 41471 41403
4641 E01004763 Westminster 11768 111 41573 41640
4642 E01004765 Westminster 15472 16 41711 41691
4643 E01004766 Bolton 7694 12516 33707 26979
4644 E01004767 Bolton 10776 11481 27407 31743
4645 E01004768 Bolton 28288 21987 11899 19226
4646 E01004769 Bolton 24505 17195 7824 28322
4647 E01004770 Bolton 22815 20726 3614 31592
4648 E01004771 Bolton 29639 12788 12504 27614
4649 E01004772 Bolton 6242 13869 10979 25003
4650 E01004773 Bolton 20211 3353 29524 31262
4651 E01004774 Bolton 7377 4604 25985 26724
4652 E01004775 Bolton 21251 31224 16289 21905
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5551 E01005711 Salford 14334 24996 6287 32438
5552 E01005712 Salford 7661 4016 19924 31952
5553 E01005713 Salford 25771 17521 29557 30383
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5555 E01005715 Salford 20639 19035 14807 32023
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5562 E01005722 Salford 2012 11049 17826 39757
5563 E01005723 Salford 2117 11825 33333 36880
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5565 E01005725 Salford 1537 16343 3946 37170
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5568 E01005728 Salford 12998 15367 24917 36420
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5571 E01005731 Salford 3223 30264 11495 32702
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6469 E01006643 Liverpool 811 9867 40743 35590
6470 E01006644 Liverpool 1898 13834 36632 33958
6471 E01006645 Liverpool 471 8372 37669 34537
6472 E01006646 Liverpool 521 8075 30210 37518
6473 E01006647 Liverpool 121 11236 37481 38267
6474 E01006648 Liverpool 2388 16914 37340 36965
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6489 E01006665 Liverpool 14894 30163 33174 30833
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6499 E01006675 Liverpool 1625 9789 4786 29879
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6501 E01006677 Liverpool 143 8799 35240 34462
6502 E01006678 Liverpool 1278 6424 23290 30718
6503 E01006679 Liverpool 511 8491 28573 33834
6504 E01006680 Liverpool 23378 16299 25526 28501
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6507 E01006683 Liverpool 22111 22694 26502 29016
6508 E01006684 Liverpool 25216 25404 4409 21622
6509 E01006685 Liverpool 17486 18023 12245 21662
6510 E01006686 Liverpool 21518 13400 22211 29277
6511 E01006687 Liverpool 14413 28407 1642 24110
6512 E01006688 Liverpool 11454 13422 22010 24924
6513 E01006689 Liverpool 21926 8001 28187 26955
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6515 E01006691 Liverpool 299 3540 41133 36113
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6518 E01006694 Liverpool 785 3308 39886 37217
6519 E01006695 Liverpool 105 5586 36874 36713
6520 E01006696 Liverpool 1390 10150 38421 36521
6521 E01006697 Liverpool 710 1232 40906 36732
6522 E01006698 Liverpool 1017 3284 37970 38214
6523 E01006699 Liverpool 325 3695 24704 39261
6524 E01006700 Liverpool 276 6637 31301 38214
6525 E01006701 Liverpool 1276 6432 24356 38807
6526 E01006702 Liverpool 158 11764 32901 39548
6527 E01006703 Liverpool 165 6799 24602 38214
6528 E01006705 Liverpool 676 3107 39936 38214
6529 E01006706 Liverpool 343 22796 40345 28271
6530 E01006707 Liverpool 860 16834 38544 29951
6531 E01006708 Liverpool 2573 13007 37229 29173
6532 E01006709 Liverpool 2753 6665 33923 28515
6533 E01006710 Liverpool 4472 30601 39812 30698
6534 E01006711 Liverpool 901 8064 38828 37389
6535 E01006712 Liverpool 4172 1898 41191 37532
6536 E01006713 Liverpool 4884 3570 41368 37532
6537 E01006716 Liverpool 2338 13044 40820 38205
6538 E01006717 Liverpool 7831 13584 32012 37123
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6540 E01006719 Liverpool 7677 3747 40420 36640
6541 E01006720 Liverpool 764 4894 40171 35114
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6543 E01006722 Liverpool 5768 2901 41058 34039
6544 E01006723 Liverpool 4164 2423 40666 31685
6545 E01006724 Liverpool 13760 8115 40245 30879
6546 E01006725 Liverpool 3938 4041 39240 35728
6547 E01006726 Liverpool 2881 8578 41089 33398
6548 E01006727 Liverpool 5608 4972 41242 32589
6549 E01006728 Liverpool 460 7844 41013 33398
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6551 E01006730 Liverpool 1204 12257 35909 36173
6552 E01006731 Liverpool 798 13299 34722 36180
6553 E01006732 Liverpool 469 10784 36418 36776
6554 E01006734 Liverpool 809 19029 34485 35766
6555 E01006735 Liverpool 301 18186 40581 36510
6556 E01006736 Liverpool 2419 22403 35716 35627
6557 E01006737 Liverpool 1599 16544 37078 36563
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6560 E01006740 Liverpool 1359 12313 25720 24920
6561 E01006741 Liverpool 1506 17594 30050 31042
6562 E01006742 Liverpool 3553 15174 27780 29258
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6564 E01006744 Liverpool 5324 11281 36277 29266
6565 E01006745 Liverpool 2874 19 39921 31530
6566 E01006746 Liverpool 1527 9236 39450 36725
6567 E01006747 Liverpool 11477 5829 41555 37506
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6569 E01006751 Liverpool 4262 12740 35289 34886
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6571 E01006753 Liverpool 852 14722 18745 32511
6572 E01006754 Liverpool 802 16965 7948 33817
6573 E01006755 Liverpool 559 6414 15663 32904
6574 E01006756 Liverpool 923 14446 15158 34170
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6576 E01006758 Liverpool 1099 16121 20015 34095
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6578 E01006760 Liverpool 34 17310 22364 37403
6579 E01006761 Liverpool 763 1958 23149 37502
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6585 E01006767 Liverpool 617 15196 33627 38309
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6591 E01006773 Liverpool 16445 12116 37536 32901
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6594 E01006776 Liverpool 2641 15213 30238 37098
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6596 E01006779 Liverpool 173 9356 24540 35868
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6600 E01006783 Liverpool 3981 1851 41260 37598
6601 E01006784 Liverpool 5617 201 40986 38521
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6620 E01006804 St. Helens 14163 18915 30024 20364
6621 E01006805 St. Helens 9172 29856 33110 29817
6622 E01006806 St. Helens 27591 14588 22351 20052
6623 E01006807 St. Helens 27038 24567 11662 20244
6624 E01006808 St. Helens 22335 28809 37371 28174
6625 E01006809 St. Helens 23669 25942 34481 23427
6626 E01006810 St. Helens 22219 18273 14856 30761
6627 E01006811 St. Helens 6263 21946 13793 30948
6628 E01006812 St. Helens 1910 20619 13319 32240
6629 E01006813 St. Helens 6074 13221 29447 29863
6630 E01006814 St. Helens 20981 24750 22782 33285
6631 E01006815 St. Helens 7749 16373 11935 30391
6632 E01006816 St. Helens 924 26886 20914 28029
6633 E01006817 St. Helens 119 16813 30043 30437
6634 E01006818 St. Helens 16992 22026 31092 30276
6635 E01006819 St. Helens 6294 24086 30199 30045
6636 E01006820 St. Helens 1093 21986 27663 30311
6637 E01006821 St. Helens 281 18109 33657 30860
6638 E01006822 St. Helens 25053 13329 1992 22163
6639 E01006823 St. Helens 27845 15605 18584 21123
6640 E01006824 St. Helens 25964 14601 12199 22163
6641 E01006825 St. Helens 29500 24233 4595 23538
6642 E01006826 St. Helens 3537 23121 274 22348
6643 E01006827 St. Helens 23600 24255 7398 30821
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6647 E01006831 St. Helens 7413 3617 19868 28885
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6649 E01006833 St. Helens 13086 11118 11033 23071
6650 E01006834 St. Helens 1310 4202 16360 27414
6651 E01006835 St. Helens 8632 5124 5177 24964
6652 E01006836 St. Helens 6655 18151 38160 28662
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6655 E01006839 St. Helens 9537 8072 39117 25686
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6658 E01006842 St. Helens 4478 5912 38868 26314
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6660 E01006844 St. Helens 1100 1998 19454 30136
6661 E01006845 St. Helens 5205 13526 26831 30143
6662 E01006846 St. Helens 11403 12929 16844 29959
6663 E01006847 St. Helens 1371 18842 3161 29212
6664 E01006848 St. Helens 10942 22209 22040 29959
6665 E01006849 St. Helens 1434 22263 10643 24488
6666 E01006850 St. Helens 2460 22834 1282 24740
6667 E01006851 St. Helens 11232 21814 12175 23398
6668 E01006852 St. Helens 21421 24357 5742 30761
6669 E01006853 St. Helens 12727 25981 21720 29361
6670 E01006854 St. Helens 9516 27349 13397 31283
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6675 E01006859 St. Helens 26237 21931 1410 28489
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6688 E01006872 St. Helens 516 461 40130 32650
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7836 E01008042 Sheffield 14767 4320 36415 20269
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7844 E01008050 Sheffield 27631 8727 38243 17690
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8030 E01008243 Gateshead 19805 22975 9537 18200
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8032 E01008245 Gateshead 25867 21659 12185 4240
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8034 E01008247 Gateshead 9332 19454 8762 5153
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8036 E01008249 Gateshead 22421 19582 6709 5337
8037 E01008250 Gateshead 16978 15825 5266 5013
8038 E01008251 Gateshead 7707 7365 41205 20711
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8044 E01008257 Gateshead 742 9260 16131 27418
8045 E01008258 Gateshead 6990 26842 6251 25684
8046 E01008259 Gateshead 2156 21342 38863 16724
8047 E01008260 Gateshead 27129 16376 24298 13859
8048 E01008261 Gateshead 3665 13245 15537 10395
8049 E01008262 Gateshead 7898 17597 22693 9690
8050 E01008263 Gateshead 6492 6501 13243 9741
8051 E01008264 Gateshead 30610 9728 14422 10062
8052 E01008265 Gateshead 9479 7740 12829 9958
8053 E01008266 Gateshead 24480 17280 14212 5814
8054 E01008267 Gateshead 12176 6109 14026 8014
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8056 E01008269 Gateshead 29931 21980 30801 4835
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8059 E01008272 Gateshead 27421 13667 21548 5775
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8062 E01008275 Gateshead 29115 29612 28222 4744
8063 E01008276 Gateshead 14295 25463 14332 5351
8064 E01008277 Gateshead 11410 14420 21788 5522
8065 E01008278 Gateshead 24141 32710 18454 4588
8066 E01008279 Gateshead 21250 16808 26408 5032
8067 E01008280 Gateshead 3539 6988 23865 5522
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8069 E01008282 Gateshead 4803 12415 28808 14181
8070 E01008283 Gateshead 22965 34278 32570 15755
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8072 E01008285 Gateshead 2541 29146 27690 15284
8073 E01008286 Gateshead 8540 33129 31604 15602
8074 E01008287 Gateshead 24459 32065 35378 15447
8075 E01008288 Newcastle upon Tyne 9092 15036 32085 17484
8076 E01008289 Newcastle upon Tyne 1985 11277 21501 16485
8077 E01008290 Newcastle upon Tyne 1567 8306 28920 16156
8078 E01008291 Newcastle upon Tyne 137 11089 12669 16622
8079 E01008292 Newcastle upon Tyne 26799 15493 31003 17743
8080 E01008293 Newcastle upon Tyne 15011 28817 35598 12598
8081 E01008294 Newcastle upon Tyne 26280 10709 34770 12033
8082 E01008295 Newcastle upon Tyne 1238 22004 38832 13650
8083 E01008296 Newcastle upon Tyne 5591 32353 37768 15077
8084 E01008297 Newcastle upon Tyne 858 16663 39649 16151
8085 E01008298 Newcastle upon Tyne 6036 24590 40221 15137
8086 E01008299 Newcastle upon Tyne 2458 19305 39881 16970
8087 E01008300 Newcastle upon Tyne 2869 12065 40662 15754
8088 E01008301 Newcastle upon Tyne 3162 20846 8997 20522
8089 E01008302 Newcastle upon Tyne 235 9854 13706 20548
8090 E01008303 Newcastle upon Tyne 218 444 33353 21190
8091 E01008304 Newcastle upon Tyne 76 4215 17803 21293
8092 E01008305 Newcastle upon Tyne 403 13417 12518 20537
8093 E01008306 Newcastle upon Tyne 11569 36356 37092 7065
8094 E01008307 Newcastle upon Tyne 4767 13551 22568 6972
8095 E01008308 Newcastle upon Tyne 16434 36813 37570 10822
8096 E01008309 Newcastle upon Tyne 32714 10106 17655 15644
8097 E01008311 Newcastle upon Tyne 30331 36125 20624 9719
8098 E01008312 Newcastle upon Tyne 26094 29161 28725 9957
8099 E01008313 Newcastle upon Tyne 23384 30870 23400 11993
8100 E01008314 Newcastle upon Tyne 18556 20491 39257 18585
8101 E01008315 Newcastle upon Tyne 19028 20089 33184 18821
8102 E01008316 Newcastle upon Tyne 27064 22389 40381 19531
8103 E01008317 Newcastle upon Tyne 32456 22724 39089 18446
8104 E01008318 Newcastle upon Tyne 7112 14182 33100 18814
8105 E01008319 Newcastle upon Tyne 30539 31603 32532 18927
8106 E01008320 Newcastle upon Tyne 19716 1497 36768 16768
8107 E01008321 Newcastle upon Tyne 29827 22129 20337 14218
8108 E01008322 Newcastle upon Tyne 29437 22997 40727 14793
8109 E01008323 Newcastle upon Tyne 23163 24366 40632 17546
8110 E01008324 Newcastle upon Tyne 4219 4413 37131 13145
8111 E01008325 Newcastle upon Tyne 2198 13780 22771 11041
8112 E01008326 Newcastle upon Tyne 23526 20292 38042 10758
8113 E01008327 Newcastle upon Tyne 622 29545 26893 13325
8114 E01008328 Newcastle upon Tyne 24916 13154 36605 8139
8115 E01008329 Newcastle upon Tyne 12595 18369 32891 10758
8116 E01008330 Newcastle upon Tyne 2733 21653 34491 10758
8117 E01008331 Newcastle upon Tyne 1631 4534 34434 15021
8118 E01008332 Newcastle upon Tyne 553 4851 38573 16065
8119 E01008333 Newcastle upon Tyne 681 6198 34203 15021
8120 E01008334 Newcastle upon Tyne 4286 6516 39729 15511
8121 E01008335 Newcastle upon Tyne 5278 7234 34162 15348
8122 E01008336 Newcastle upon Tyne 3960 15119 32397 16397
8123 E01008337 Newcastle upon Tyne 4124 16539 37504 16178
8124 E01008338 Newcastle upon Tyne 5878 9829 34248 13583
8125 E01008339 Newcastle upon Tyne 4708 7890 38888 15124
8126 E01008340 Newcastle upon Tyne 843 10565 37380 16907
8127 E01008341 Newcastle upon Tyne 5084 9139 40174 16907
8128 E01008342 Newcastle upon Tyne 17195 30020 38236 15563
8129 E01008343 Newcastle upon Tyne 16224 16292 32099 16434
8130 E01008344 Newcastle upon Tyne 5756 19704 24644 16101
8131 E01008345 Newcastle upon Tyne 2327 9735 23288 14147
8132 E01008346 Newcastle upon Tyne 14340 11744 28162 13229
8133 E01008347 Newcastle upon Tyne 15129 11061 38951 15088
8134 E01008348 Newcastle upon Tyne 2870 15010 26738 14397
8135 E01008349 Newcastle upon Tyne 7781 12926 38269 14397
8136 E01008350 Newcastle upon Tyne 7910 24658 37905 16879
8137 E01008351 Newcastle upon Tyne 21702 19673 10305 14015
8138 E01008352 Newcastle upon Tyne 15317 15499 30208 15683
8139 E01008353 Newcastle upon Tyne 8463 6282 37323 16907
8140 E01008354 Newcastle upon Tyne 16335 6002 32360 13472
8141 E01008355 Newcastle upon Tyne 30486 334 39227 15436
8142 E01008356 Newcastle upon Tyne 10927 12366 31707 14551
8143 E01008357 Newcastle upon Tyne 32112 20227 13451 16230
8144 E01008358 Newcastle upon Tyne 19411 11084 33140 15950
8145 E01008359 Newcastle upon Tyne 13459 4754 40932 21838
8146 E01008360 Newcastle upon Tyne 21835 3918 40785 19854
8147 E01008361 Newcastle upon Tyne 12393 5475 41112 19854
8148 E01008362 Newcastle upon Tyne 13212 8741 40831 21838
8149 E01008363 Newcastle upon Tyne 24663 13353 40609 21978
8150 E01008364 Newcastle upon Tyne 21239 508 41437 20823
8151 E01008365 Newcastle upon Tyne 28028 2148 38903 21309
8152 E01008366 Newcastle upon Tyne 29906 8350 39022 24031
8153 E01008367 Newcastle upon Tyne 27068 4501 35844 24031
8154 E01008368 Newcastle upon Tyne 26450 6830 37964 24393
8155 E01008369 Newcastle upon Tyne 26386 2701 33521 19251
8156 E01008370 Newcastle upon Tyne 26002 5897 34320 20948
8157 E01008371 Newcastle upon Tyne 31953 6306 16617 16993
8158 E01008372 Newcastle upon Tyne 23204 992 40405 22485
8159 E01008373 Newcastle upon Tyne 25191 840 40928 18202
8160 E01008374 Newcastle upon Tyne 20236 9230 38246 15100
8161 E01008375 Newcastle upon Tyne 6623 9133 36747 14546
8162 E01008376 Newcastle upon Tyne 28964 4259 40953 15346
8163 E01008377 Newcastle upon Tyne 3644 19542 39300 14917
8164 E01008378 Newcastle upon Tyne 27779 12852 32219 12882
8165 E01008379 Newcastle upon Tyne 8301 11643 32713 12833
8166 E01008380 Newcastle upon Tyne 179 8611 38680 14413
8167 E01008381 Newcastle upon Tyne 18087 32002 15601 8322
8168 E01008382 Newcastle upon Tyne 780 25373 2839 11183
8169 E01008383 Newcastle upon Tyne 3286 27396 6292 8821
8170 E01008384 Newcastle upon Tyne 12825 27355 9655 10488
8171 E01008385 Newcastle upon Tyne 3138 17410 13643 9645
8172 E01008386 Newcastle upon Tyne 14193 25407 23319 11183
8173 E01008387 Newcastle upon Tyne 18038 28599 4852 9333
8174 E01008388 Newcastle upon Tyne 709 8541 17015 18979
8175 E01008389 Newcastle upon Tyne 957 9063 8821 19170
8176 E01008390 Newcastle upon Tyne 532 11656 3505 18946
8177 E01008391 Newcastle upon Tyne 446 11926 17478 19074
8178 E01008392 Newcastle upon Tyne 1171 13463 35954 20068
8179 E01008394 Newcastle upon Tyne 22680 20015 28864 17211
8180 E01008395 Newcastle upon Tyne 7728 7180 31847 15416
8181 E01008396 Newcastle upon Tyne 6752 11452 40059 17017
8182 E01008397 Newcastle upon Tyne 18149 2438 39255 20915
8183 E01008398 Newcastle upon Tyne 672 416 34818 14051
8184 E01008399 Newcastle upon Tyne 1314 10815 31137 14051
8185 E01008400 Newcastle upon Tyne 2507 22749 8126 4735
8186 E01008401 Newcastle upon Tyne 5471 21657 10026 5254
8187 E01008402 Newcastle upon Tyne 10486 31701 12361 6911
8188 E01008403 Newcastle upon Tyne 17917 23294 19595 4820
8189 E01008404 Newcastle upon Tyne 10676 19681 4497 6251
8190 E01008405 Newcastle upon Tyne 6438 24409 29999 5793
8191 E01008406 Newcastle upon Tyne 10578 5403 25155 24169
8192 E01008407 Newcastle upon Tyne 16184 7312 34427 25865
8193 E01008409 Newcastle upon Tyne 21587 16970 27364 24481
8194 E01008410 Newcastle upon Tyne 16658 14412 33008 23791
8195 E01008411 Newcastle upon Tyne 19559 11138 36902 25264
8196 E01008412 Newcastle upon Tyne 22504 6577 35784 22544
8197 E01008413 Newcastle upon Tyne 9210 7308 37576 21669
8198 E01008415 Newcastle upon Tyne 1602 18009 22680 12930
8199 E01008416 Newcastle upon Tyne 14353 5318 32926 14468
8200 E01008418 Newcastle upon Tyne 30892 8263 24329 13472
8201 E01008419 Newcastle upon Tyne 30906 762 40419 13961
8202 E01008420 Newcastle upon Tyne 31917 2896 33637 12439
8203 E01008421 Newcastle upon Tyne 31549 6428 40374 12610
8204 E01008422 Newcastle upon Tyne 31752 7831 34386 13029
8205 E01008423 Newcastle upon Tyne 31360 8914 25511 12740
8206 E01008424 Newcastle upon Tyne 22505 14841 33905 13844
8207 E01008425 Newcastle upon Tyne 380 22942 14817 18701
8208 E01008426 Newcastle upon Tyne 293 8905 23813 18492
8209 E01008427 Newcastle upon Tyne 32 15472 4297 18667
8210 E01008428 Newcastle upon Tyne 3991 20840 18428 18656
8211 E01008429 Newcastle upon Tyne 673 6714 31675 17334
8212 E01008430 Newcastle upon Tyne 4503 8577 32211 17321
8213 E01008431 Newcastle upon Tyne 10542 8414 32848 17334
8214 E01008432 Newcastle upon Tyne 4852 12371 23902 17346
8215 E01008433 Newcastle upon Tyne 15621 10553 31402 21173
8216 E01008434 Newcastle upon Tyne 16608 17784 32502 19406
8217 E01008435 Newcastle upon Tyne 4463 16632 31485 17334
8218 E01008436 Newcastle upon Tyne 1805 20620 16383 18794
8219 E01008437 Newcastle upon Tyne 315 18136 21386 16561
8220 E01008438 Newcastle upon Tyne 393 20511 29366 23233
8221 E01008439 Newcastle upon Tyne 208 12618 23637 18630
8222 E01008441 Newcastle upon Tyne 5826 12903 38122 12429
8223 E01008442 Newcastle upon Tyne 26679 22098 39801 9315
8224 E01008443 Newcastle upon Tyne 27269 36156 35899 7568
8225 E01008444 Newcastle upon Tyne 23236 23019 40020 9576
8226 E01008445 Newcastle upon Tyne 10428 1986 40846 12296
8227 E01008446 Newcastle upon Tyne 24467 22118 40640 10816
8228 E01008447 Newcastle upon Tyne 24860 8595 38759 8756
8229 E01008448 Newcastle upon Tyne 27379 30770 36322 8383
8230 E01008449 Newcastle upon Tyne 6526 3521 41265 13795
8231 E01008450 Newcastle upon Tyne 3114 5361 35502 14587
8232 E01008451 Newcastle upon Tyne 7784 9750 40014 16126
8233 E01008452 Newcastle upon Tyne 21951 18876 39705 13587
8234 E01008453 Newcastle upon Tyne 18198 14853 39822 14492
8235 E01008455 Newcastle upon Tyne 9467 9596 40775 13686
8236 E01008456 Newcastle upon Tyne 3494 25268 40887 11365
8237 E01008457 Newcastle upon Tyne 2267 19960 40677 10608
8238 E01008458 Newcastle upon Tyne 20406 35025 38343 7946
8239 E01008459 Newcastle upon Tyne 478 11605 40260 10546
8240 E01008460 Newcastle upon Tyne 3406 26187 41065 9310
8241 E01008461 North Tyneside 7613 22128 30644 18537
8242 E01008462 North Tyneside 8517 23023 37583 18523
8243 E01008463 North Tyneside 8154 27453 34664 18537
8244 E01008464 North Tyneside 19746 25494 40141 18041
8245 E01008465 North Tyneside 20061 22864 38409 18511
8246 E01008466 North Tyneside 29577 27136 32634 17208
8247 E01008467 North Tyneside 20356 22851 30173 18411
8248 E01008468 North Tyneside 7952 21140 28147 17944
8249 E01008469 North Tyneside 21260 6553 31619 16728
8250 E01008470 North Tyneside 12287 10115 35335 14451
8251 E01008471 North Tyneside 11742 17767 24537 16223
8252 E01008472 North Tyneside 29316 19884 24514 17103
8253 E01008473 North Tyneside 20508 14449 27854 16658
8254 E01008474 North Tyneside 4580 13507 24106 16223
8255 E01008475 North Tyneside 28187 30820 28385 11510
8256 E01008476 North Tyneside 8710 29662 31624 10311
8257 E01008477 North Tyneside 5882 31364 16198 10588
8258 E01008478 North Tyneside 6680 27938 18512 10605
8259 E01008479 North Tyneside 30017 25045 6110 11883
8260 E01008480 North Tyneside 5013 31880 34281 10606
8261 E01008481 North Tyneside 5995 20317 38604 19451
8262 E01008482 North Tyneside 2392 13380 32496 20521
8263 E01008483 North Tyneside 10000 1044 34066 20299
8264 E01008484 North Tyneside 2439 11740 38237 20557
8265 E01008485 North Tyneside 286 15829 28731 20448
8266 E01008486 North Tyneside 7055 7828 31533 21285
8267 E01008487 North Tyneside 5412 11971 31568 21571
8268 E01008488 North Tyneside 6981 23244 39697 19727
8269 E01008489 North Tyneside 5416 23655 35903 22243
8270 E01008490 North Tyneside 12134 25707 31962 22061
8271 E01008491 North Tyneside 4959 27771 38617 19530
8272 E01008492 North Tyneside 4998 11320 31382 21453
8273 E01008493 North Tyneside 26991 18381 23467 16573
8274 E01008494 North Tyneside 11748 18098 23513 16946
8275 E01008495 North Tyneside 31117 9449 22657 16150
8276 E01008496 North Tyneside 11506 8867 17137 16189
8277 E01008497 North Tyneside 32185 6242 14035 15883
8278 E01008498 North Tyneside 28638 14000 23151 16380
8279 E01008499 North Tyneside 15140 29129 21470 14212
8280 E01008500 North Tyneside 21019 22500 30074 13916
8281 E01008501 North Tyneside 25440 34001 34897 15983
8282 E01008502 North Tyneside 10540 21159 30591 14713
8283 E01008503 North Tyneside 8431 30189 23738 13963
8284 E01008504 North Tyneside 30636 19367 24414 11754
8285 E01008505 North Tyneside 21175 25147 11398 12861
8286 E01008506 North Tyneside 10653 23861 12466 13377
8287 E01008507 North Tyneside 24980 30240 12873 13199
8288 E01008508 North Tyneside 8191 11602 18178 17633
8289 E01008509 North Tyneside 4957 15638 9415 17635
8290 E01008510 North Tyneside 9284 6250 20312 17405
8291 E01008511 North Tyneside 7381 9894 7425 17737
8292 E01008512 North Tyneside 3306 17726 17492 17635
8293 E01008513 North Tyneside 10967 16189 15302 14361
8294 E01008514 North Tyneside 11391 13155 26089 13449
8295 E01008516 North Tyneside 26989 34086 16345 10144
8296 E01008517 North Tyneside 29976 10914 31444 13214
8297 E01008518 North Tyneside 20395 18826 36852 13948
8298 E01008519 North Tyneside 19964 20582 25345 13852
8299 E01008520 North Tyneside 28248 4643 26251 14080
8300 E01008521 North Tyneside 26330 8168 37565 13504
8301 E01008522 North Tyneside 31800 4658 37147 14123
8302 E01008523 North Tyneside 31830 10071 17090 13264
8303 E01008524 North Tyneside 2404 426 35288 20163
8304 E01008525 North Tyneside 24069 15726 35657 18229
8305 E01008526 North Tyneside 28586 16812 33697 21079
8306 E01008527 North Tyneside 24137 6627 35940 18003
8307 E01008528 North Tyneside 22679 1840 33727 19625
8308 E01008529 North Tyneside 21395 1506 32354 18880
8309 E01008530 North Tyneside 17941 4279 31349 20058
8310 E01008531 North Tyneside 24518 31602 30832 16254
8311 E01008532 North Tyneside 9629 26044 30759 16932
8312 E01008533 North Tyneside 6883 25060 27099 16411
8313 E01008534 North Tyneside 21442 32071 27119 19450
8314 E01008535 North Tyneside 13384 17046 23730 19034
8315 E01008536 North Tyneside 7627 5242 39478 18150
8316 E01008537 North Tyneside 5502 7359 36335 17809
8317 E01008538 North Tyneside 24012 30176 39503 15796
8318 E01008539 North Tyneside 16394 17293 6405 22350
8319 E01008540 North Tyneside 762 24509 29014 20593
8320 E01008541 North Tyneside 2470 22780 12896 21800
8321 E01008542 North Tyneside 2214 10090 15213 19494
8322 E01008543 North Tyneside 6543 12329 9047 19233
8323 E01008544 North Tyneside 864 6047 21724 20278
8324 E01008545 North Tyneside 491 16125 11828 20519
8325 E01008546 North Tyneside 32596 14183 17412 12587
8326 E01008547 North Tyneside 29993 29445 17370 12772
8327 E01008548 North Tyneside 30276 30659 30278 11657
8328 E01008549 North Tyneside 32200 17734 20971 10828
8329 E01008550 North Tyneside 31517 4069 23375 12587
8330 E01008551 North Tyneside 29450 26930 13376 8728
8331 E01008552 North Tyneside 22676 7402 33885 19065
8332 E01008553 North Tyneside 26021 3727 36044 14926
8333 E01008554 North Tyneside 11708 6091 19523 15078
8334 E01008555 North Tyneside 11644 14473 15689 16368
8335 E01008556 North Tyneside 29306 27180 34638 18911
8336 E01008557 North Tyneside 30571 31533 38183 19749
8337 E01008558 North Tyneside 23292 23194 20820 17055
8338 E01008559 North Tyneside 19315 10788 34626 17848
8339 E01008560 North Tyneside 24104 21430 17663 16608
8340 E01008561 North Tyneside 6912 10451 31027 18335
8341 E01008562 North Tyneside 27330 26780 26257 16260
8342 E01008563 North Tyneside 32782 25459 21020 16289
8343 E01008564 North Tyneside 29791 33981 31497 12476
8344 E01008565 North Tyneside 14346 34847 32942 12195
8345 E01008567 North Tyneside 7049 19082 40673 15252
8346 E01008568 North Tyneside 8955 12046 40208 19297
8347 E01008569 North Tyneside 6893 11889 32116 17852
8348 E01008570 North Tyneside 21743 22253 40836 16021
8349 E01008571 North Tyneside 4717 19131 5307 18380
8350 E01008572 North Tyneside 2715 6899 32406 18568
8351 E01008573 North Tyneside 2064 506 38317 18874
8352 E01008574 North Tyneside 18512 7314 18303 18503
8353 E01008575 North Tyneside 2281 6649 27683 18151
8354 E01008576 North Tyneside 6765 26208 13303 18621
8355 E01008577 North Tyneside 16890 28320 17129 9388
8356 E01008578 North Tyneside 12345 25251 20592 8722
8357 E01008579 North Tyneside 31031 18563 26019 8457
8358 E01008580 North Tyneside 28197 29180 26374 8746
8359 E01008581 North Tyneside 26979 28671 31007 11081
8360 E01008582 North Tyneside 13897 28846 8080 8226
8361 E01008583 North Tyneside 10674 22572 16002 8710
8362 E01008584 North Tyneside 3961 1550 36715 14266
8363 E01008585 North Tyneside 22455 402 31608 14505
8364 E01008586 North Tyneside 24678 158 29713 13716
8365 E01008587 North Tyneside 16309 1848 22336 13468
8366 E01008588 North Tyneside 13924 253 31098 13468
8367 E01008589 North Tyneside 31013 5451 11500 14718
8368 E01008590 South Tyneside 2677 4131 37821 22281
8369 E01008591 South Tyneside 2513 2452 41366 21343
8370 E01008592 South Tyneside 7196 11172 41603 18258
8371 E01008593 South Tyneside 971 18000 31258 20440
8372 E01008594 South Tyneside 6933 21221 33638 18088
8373 E01008595 South Tyneside 7819 6260 40312 19847
8374 E01008596 South Tyneside 1281 3263 36142 21591
8375 E01008597 South Tyneside 11268 7636 34290 18477
8376 E01008598 South Tyneside 7615 4669 34067 21440
8377 E01008599 South Tyneside 3542 9840 13522 20430
8378 E01008600 South Tyneside 1089 11849 16478 19550
8379 E01008601 South Tyneside 3642 35402 28166 20256
8380 E01008602 South Tyneside 3483 30354 29150 17498
8381 E01008603 South Tyneside 2212 29670 28612 17569
8382 E01008604 South Tyneside 2052 3712 17069 20460
8383 E01008605 South Tyneside 9344 33897 39043 16420
8384 E01008606 South Tyneside 2774 30586 36848 14667
8385 E01008607 South Tyneside 1603 31823 35352 14916
8386 E01008608 South Tyneside 2487 29054 29207 17665
8387 E01008609 South Tyneside 3242 27924 37219 14254
8388 E01008610 South Tyneside 1836 17048 19056 16175
8389 E01008611 South Tyneside 29023 25529 24558 17799
8390 E01008612 South Tyneside 23066 29123 24846 16840
8391 E01008613 South Tyneside 3895 10880 33471 17275
8392 E01008614 South Tyneside 13080 26501 28278 13713
8393 E01008615 South Tyneside 14891 31216 14209 17186
8394 E01008616 South Tyneside 28879 18272 39573 13524
8395 E01008617 South Tyneside 28176 28421 30123 14856
8396 E01008618 South Tyneside 28072 32843 32871 13146
8397 E01008619 South Tyneside 31929 27686 33634 12394
8398 E01008620 South Tyneside 29296 19370 38862 13727
8399 E01008621 South Tyneside 29205 32384 40318 14286
8400 E01008622 South Tyneside 15864 29420 38025 13316
8401 E01008624 South Tyneside 12060 17936 25488 12620
8402 E01008625 South Tyneside 3679 12123 25918 13416
8403 E01008627 South Tyneside 24572 35908 31262 17641
8404 E01008628 South Tyneside 3841 28308 19745 19082
8405 E01008629 South Tyneside 13772 34830 25395 16428
8406 E01008630 South Tyneside 4892 32336 23490 17391
8407 E01008631 South Tyneside 9093 33381 26239 17459
8408 E01008632 South Tyneside 5825 34928 31036 18674
8409 E01008633 South Tyneside 4505 13121 33504 12210
8410 E01008634 South Tyneside 3681 7962 35543 15336
8411 E01008635 South Tyneside 13277 13663 36842 15928
8412 E01008636 South Tyneside 7527 12744 31196 13863
8413 E01008637 South Tyneside 9865 16764 30028 13363
8414 E01008638 South Tyneside 19796 17301 5814 17828
8415 E01008639 South Tyneside 9055 19278 14546 17825
8416 E01008640 South Tyneside 11594 12500 25872 17749
8417 E01008641 South Tyneside 4244 3214 32747 17998
8418 E01008642 South Tyneside 22819 14490 26583 18862
8419 E01008643 South Tyneside 14249 20827 18048 18548
8420 E01008644 South Tyneside 5717 29143 24765 18548
8421 E01008645 South Tyneside 4633 30205 26604 19015
8422 E01008646 South Tyneside 11000 18119 15855 19061
8423 E01008647 South Tyneside 26138 15881 29728 15978
8424 E01008648 South Tyneside 13527 18177 30973 16795
8425 E01008649 South Tyneside 6793 14227 24528 15054
8426 E01008650 South Tyneside 22110 14491 31005 16005
8427 E01008651 South Tyneside 1677 6998 22372 14539
8428 E01008652 South Tyneside 2699 10872 20467 17612
8429 E01008653 South Tyneside 4388 12550 18534 16839
8430 E01008654 South Tyneside 8459 1792 35133 17685
8431 E01008655 South Tyneside 2864 4414 24701 17426
8432 E01008656 South Tyneside 7257 23176 20641 18500
8433 E01008657 South Tyneside 24288 13756 32890 19018
8434 E01008658 South Tyneside 2131 35350 28090 19730
8435 E01008659 South Tyneside 9350 32389 28931 19044
8436 E01008660 South Tyneside 9649 1907 33301 18313
8437 E01008661 South Tyneside 4069 7331 19518 18684
8438 E01008662 South Tyneside 5583 29568 23187 18478
8439 E01008663 South Tyneside 5390 21832 13409 18531
8440 E01008664 South Tyneside 2427 9178 39380 20105
8441 E01008665 South Tyneside 2611 21809 29076 22644
8442 E01008666 South Tyneside 305 10038 30698 22880
8443 E01008667 South Tyneside 1844 6429 30693 22388
8444 E01008668 South Tyneside 3638 1597 39446 19048
8445 E01008669 South Tyneside 870 28916 30724 19606
8446 E01008670 South Tyneside 3471 26783 20602 20086
8447 E01008671 South Tyneside 1820 26013 33274 23365
8448 E01008672 South Tyneside 8108 27798 31215 21034
8449 E01008673 South Tyneside 26235 6223 40703 18276
8450 E01008674 South Tyneside 29436 18047 32865 16294
8451 E01008675 South Tyneside 13107 12869 41141 16834
8452 E01008676 South Tyneside 10251 7015 40980 18541
8453 E01008677 South Tyneside 25159 10748 28702 17284
8454 E01008678 South Tyneside 9447 557 41010 18741
8455 E01008679 South Tyneside 13063 7476 39817 18916
8456 E01008680 South Tyneside 26648 19926 37972 18611
8457 E01008681 South Tyneside 28138 12270 35457 17959
8458 E01008682 South Tyneside 1690 27956 39999 18265
8459 E01008683 South Tyneside 10094 1993 41155 20117
8460 E01008684 South Tyneside 7610 24037 17205 12344
8461 E01008685 South Tyneside 16637 28746 16704 10240
8462 E01008686 South Tyneside 13327 23168 25846 12977
8463 E01008687 South Tyneside 16700 10667 14994 9238
8464 E01008688 South Tyneside 3191 30296 40679 15293
8465 E01008689 South Tyneside 2459 29911 41047 13319
8466 E01008690 South Tyneside 3538 29507 41275 13319
8467 E01008691 South Tyneside 22284 34542 41324 14319
8468 E01008692 South Tyneside 5943 27947 40092 13120
8469 E01008693 Sunderland 4769 9834 26674 18082
8470 E01008694 Sunderland 6702 16648 23452 21704
8471 E01008695 Sunderland 4370 19450 28059 18089
8472 E01008696 Sunderland 17500 22406 21961 20122
8473 E01008697 Sunderland 6017 14187 19312 18816
8474 E01008698 Sunderland 4630 15175 39984 19880
8475 E01008699 Sunderland 3754 19389 32103 19880
8476 E01008700 Sunderland 6817 14130 34456 19063
8477 E01008701 Sunderland 5661 4075 41018 16347
8478 E01008702 Sunderland 399 8585 10471 15718
8479 E01008703 Sunderland 3277 398 36609 16084
8480 E01008704 Sunderland 7201 5457 41575 17751
8481 E01008705 Sunderland 4994 9310 37296 18060
8482 E01008706 Sunderland 6315 10329 40971 19039
8483 E01008707 Sunderland 10584 6300 41539 14879
8484 E01008708 Sunderland 7512 13521 26531 18623
8485 E01008709 Sunderland 745 10193 21243 20907
8486 E01008711 Sunderland 10358 8015 37996 18956
8487 E01008712 Sunderland 2402 19966 28627 16246
8488 E01008713 Sunderland 28783 13786 32824 14047
8489 E01008714 Sunderland 1920 20345 33447 12630
8490 E01008715 Sunderland 10081 19415 32473 12504
8491 E01008716 Sunderland 24415 25349 24321 9960
8492 E01008717 Sunderland 7972 18661 23780 10100
8493 E01008718 Sunderland 8648 17146 31799 8731
8494 E01008719 Sunderland 3380 1905 31312 8420
8495 E01008720 Sunderland 7225 20205 39862 10922
8496 E01008721 Sunderland 24220 22235 37604 10918
8497 E01008722 Sunderland 28685 2128 33133 13900
8498 E01008723 Sunderland 29311 23966 22309 13889
8499 E01008724 Sunderland 31678 22434 32989 13816
8500 E01008725 Sunderland 25585 6161 32331 15812
8501 E01008726 Sunderland 22448 452 35789 15170
8502 E01008727 Sunderland 16388 618 38073 15812
8503 E01008728 Sunderland 23826 7134 36195 17680
8504 E01008729 Sunderland 2090 12166 32870 19961
8505 E01008730 Sunderland 1430 25667 30725 16589
8506 E01008731 Sunderland 1440 12782 30314 19260
8507 E01008732 Sunderland 11231 10159 35015 16883
8508 E01008733 Sunderland 2665 12835 29327 16580
8509 E01008734 Sunderland 22270 21574 37155 13934
8510 E01008735 Sunderland 2008 9045 28305 12840
8511 E01008736 Sunderland 167 4816 36121 13173
8512 E01008737 Sunderland 810 5147 39555 12512
8513 E01008738 Sunderland 795 8028 39025 12511
8514 E01008739 Sunderland 5751 3686 13185 12878
8515 E01008740 Sunderland 16173 13685 14902 12960
8516 E01008741 Sunderland 14056 10292 28203 13268
8517 E01008742 Sunderland 7931 8533 40180 8482
8518 E01008743 Sunderland 1264 28272 28303 7001
8519 E01008744 Sunderland 3836 17050 40716 8288
8520 E01008745 Sunderland 18251 19299 39090 7785
8521 E01008746 Sunderland 1580 23875 40056 7766
8522 E01008747 Sunderland 12762 33370 17823 9897
8523 E01008748 Sunderland 6931 25295 21108 7635
8524 E01008749 Sunderland 22506 9192 23131 11118
8525 E01008750 Sunderland 16579 14199 18375 11347
8526 E01008751 Sunderland 8771 19244 39453 11498
8527 E01008752 Sunderland 5147 20214 30656 11700
8528 E01008753 Sunderland 6580 11700 33759 11426
8529 E01008754 Sunderland 5325 1456 26910 11930
8530 E01008755 Sunderland 4212 14965 22649 12064
8531 E01008756 Sunderland 3392 14141 20028 16247
8532 E01008757 Sunderland 5051 3185 40557 16347
8533 E01008758 Sunderland 15359 12775 37374 16413
8534 E01008759 Sunderland 13357 2655 40032 15746
8535 E01008760 Sunderland 23330 6044 41197 14858
8536 E01008761 Sunderland 22301 10772 35388 15746
8537 E01008762 Sunderland 1429 12563 29288 16730
8538 E01008763 Sunderland 7535 20422 30721 12025
8539 E01008764 Sunderland 9900 23343 25728 11042
8540 E01008765 Sunderland 20528 34967 36330 10000
8541 E01008766 Sunderland 14150 20813 35478 11445
8542 E01008767 Sunderland 11870 30141 37137 11933
8543 E01008768 Sunderland 9913 9247 26237 11203
8544 E01008769 Sunderland 5184 2523 32783 10783
8545 E01008770 Sunderland 18729 31286 38762 10384
8546 E01008771 Sunderland 14320 33258 39156 10332
8547 E01008772 Sunderland 24612 32473 24435 13768
8548 E01008773 Sunderland 2199 25260 28828 12896
8549 E01008774 Sunderland 15420 31198 34399 13388
8550 E01008775 Sunderland 27813 33909 30704 10298
8551 E01008776 Sunderland 3855 27394 14098 14360
8552 E01008777 Sunderland 1436 30244 7676 13730
8553 E01008778 Sunderland 10402 26628 29735 15024
8554 E01008779 Sunderland 10221 8190 20804 12530
8555 E01008780 Sunderland 6349 16986 31480 12752
8556 E01008781 Sunderland 20581 19057 31431 12741
8557 E01008782 Sunderland 26943 28240 23075 14135
8558 E01008783 Sunderland 25827 19987 35430 13195
8559 E01008784 Sunderland 29155 15601 35823 13117
8560 E01008785 Sunderland 23589 30825 31276 13383
8561 E01008786 Sunderland 22453 12059 27321 17726
8562 E01008787 Sunderland 14557 8655 38891 19645
8563 E01008788 Sunderland 15393 10807 38279 17739
8564 E01008789 Sunderland 20418 15257 12290 17651
8565 E01008790 Sunderland 13390 11350 28919 17741
8566 E01008791 Sunderland 4705 1854 26556 19298
8567 E01008792 Sunderland 18780 15532 14879 17548
8568 E01008793 Sunderland 1476 11815 31256 11680
8569 E01008795 Sunderland 15603 19117 29285 10500
8570 E01008796 Sunderland 12257 10703 37692 11364
8571 E01008797 Sunderland 22701 31531 35830 11579
8572 E01008799 Sunderland 24472 34761 9517 11156
8573 E01008800 Sunderland 2335 15930 20384 12061
8574 E01008801 Sunderland 25314 20165 33755 11973
8575 E01008802 Sunderland 17001 28319 27462 12265
8576 E01008803 Sunderland 6048 17703 35990 12688
8577 E01008804 Sunderland 6787 25719 35285 11600
8578 E01008805 Sunderland 8325 13265 40631 12022
8579 E01008808 Sunderland 25528 28673 30580 10192
8580 E01008809 Sunderland 9815 26619 24211 12651
8581 E01008810 Sunderland 4318 17852 27524 17615
8582 E01008811 Sunderland 13209 8913 10440 16394
8583 E01008812 Sunderland 3331 15438 30635 16012
8584 E01008813 Sunderland 3778 11400 35111 17847
8585 E01008814 Sunderland 11188 9991 4673 16217
8586 E01008817 Sunderland 415 15711 21891 16648
8587 E01008819 Sunderland 6272 18819 37462 16181
8588 E01008820 Sunderland 4651 13539 38659 19262
8589 E01008821 Sunderland 539 22362 33396 14651
8590 E01008822 Sunderland 3440 17267 38630 15896
8591 E01008823 Sunderland 2636 27615 26681 16121
8592 E01008824 Sunderland 2047 27472 29907 14889
8593 E01008825 Sunderland 3849 3474 26567 15916
8594 E01008826 Sunderland 5731 24717 22236 13987
8595 E01008827 Sunderland 2312 9043 15234 14136
8596 E01008828 Sunderland 2479 23233 12444 14711
8597 E01008829 Sunderland 1092 11576 20872 15907
8598 E01008830 Sunderland 11824 7662 40558 13904
8599 E01008831 Sunderland 8279 5851 38426 14370
8600 E01008832 Sunderland 11344 5803 41607 14879
8601 E01008833 Sunderland 9512 5393 41653 14542
8602 E01008834 Sunderland 6070 5855 24074 12957
8603 E01008835 Sunderland 12961 11454 35394 13538
8604 E01008836 Sunderland 259 761 34370 13194
8605 E01008837 Sunderland 2318 26522 39561 21208
8606 E01008838 Sunderland 3099 22643 41126 19127
8607 E01008839 Sunderland 417 26768 39852 18968
8608 E01008840 Sunderland 5366 25840 40596 19127
8609 E01008841 Sunderland 347 22440 33296 19131
8610 E01008842 Sunderland 9229 27060 38531 18188
8611 E01008843 Sunderland 23300 22065 21486 17273
8612 E01008844 Sunderland 12669 28361 24907 19568
8613 E01008845 Sunderland 21188 25390 9271 15631
8614 E01008846 Sunderland 1915 24487 15700 14363
8615 E01008847 Sunderland 3112 29379 9833 14363
8616 E01008848 Sunderland 17790 12971 24442 21227
8617 E01008849 Sunderland 2495 6230 37975 18560
8618 E01008850 Sunderland 24400 34338 17585 15304
8619 E01008851 Sunderland 7642 21573 10130 16118
8620 E01008852 Sunderland 22057 24227 12257 16628
8621 E01008853 Sunderland 2584 3711 33164 20268
8622 E01008854 Sunderland 2222 17604 27156 20649
8623 E01008855 Sunderland 12300 27384 22228 18619
8624 E01008856 Sunderland 19409 26607 32053 21229
8625 E01008857 Sunderland 8000 20968 24309 26799
8626 E01008858 Sunderland 2022 2777 28201 23672
8627 E01008859 Sunderland 2702 22619 28498 18510
8628 E01008860 Sunderland 4481 7706 35215 26799
8629 E01008861 Sunderland 13353 36480 7674 13278
8630 E01008862 Sunderland 25574 36984 2107 14530
8631 E01008863 Sunderland 26706 31343 10776 16941
8632 E01008864 Sunderland 22072 31993 10919 19668
8633 E01008865 Sunderland 9621 22006 18950 18723
8634 E01008866 Sunderland 10167 28248 16848 21725
8635 E01008867 Sunderland 2614 25329 22283 22822
8636 E01008868 Sunderland 25948 32737 26294 23647
8637 E01008869 Sunderland 16092 30381 26112 23713
8638 E01008870 Sunderland 23282 33368 22552 23324
8639 E01008871 Sunderland 9231 23933 32565 22157
8640 E01008872 Sunderland 19479 34558 22516 23195
8641 E01008873 Sunderland 21112 32787 19768 22022
8642 E01008874 Sunderland 5707 30972 29324 24252
8643 E01008875 Sunderland 12859 29906 25913 24570
8644 E01008876 Sunderland 22708 30126 28019 20357
8645 E01008877 Sunderland 20205 31433 26002 17215
8646 E01008878 Sunderland 10030 24494 26256 26799
8647 E01008879 Sunderland 14866 22039 19743 26520
8648 E01008880 Sunderland 11428 29878 31420 24252
8649 E01008881 Birmingham 3924 12273 22700 38706
8650 E01008882 Birmingham 939 28358 20351 39850
8651 E01008883 Birmingham 4684 12873 19915 39321
8652 E01008884 Birmingham 3204 25546 29389 39142
8653 E01008885 Birmingham 12110 7142 25890 38097
8654 E01008886 Birmingham 4415 3958 29440 38362
8655 E01008887 Birmingham 2764 10407 7738 38761
8656 E01008888 Birmingham 12246 12106 21746 37282
8657 E01008889 Birmingham 3516 15676 30545 37890
8658 E01008890 Birmingham 7389 17555 5698 38365
8659 E01008891 Birmingham 11247 24449 8340 37141
8660 E01008892 Birmingham 3845 18715 7345 38266
8661 E01008893 Birmingham 7809 13322 1896 37100
8662 E01008894 Birmingham 5173 3714 5519 36472
8663 E01008895 Birmingham 8344 21394 6530 34809
8664 E01008896 Birmingham 1558 24164 21186 38768
8665 E01008897 Birmingham 5500 19850 19268 38289
8666 E01008898 Birmingham 2526 27722 17089 39274
8667 E01008899 Birmingham 530 18859 35870 40877
8668 E01008901 Birmingham 827 8383 28070 40729
8669 E01008905 Birmingham 1606 132 34991 39208
8670 E01008906 Birmingham 1532 1435 34903 39425
8671 E01008907 Birmingham 351 3207 23796 38645
8672 E01008909 Birmingham 2990 6184 33205 39944
8673 E01008910 Birmingham 2153 6069 32062 40783
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9617 E01009914 Dudley 29485 26299 33895 18287
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9619 E01009916 Dudley 15476 9077 29046 23126
9620 E01009917 Dudley 25055 22207 36127 18407
9621 E01009918 Dudley 7751 24974 23570 23334
9622 E01009919 Dudley 25511 22946 34155 17511
9623 E01009920 Dudley 23889 17956 33147 26786
9624 E01009921 Sandwell 10721 1054 40247 36008
9625 E01009922 Sandwell 9488 10330 27731 36253
9626 E01009923 Sandwell 13564 16664 24643 36369
9627 E01009924 Sandwell 16905 3664 38949 34749
9628 E01009925 Sandwell 16714 18296 31844 35035
9629 E01009926 Sandwell 17042 1689 40293 36253
9630 E01009927 Sandwell 10435 353 41277 34413
9631 E01009928 Sandwell 8946 2967 35901 36201
9632 E01009929 Sandwell 3476 12392 25779 35610
9633 E01009930 Sandwell 5557 26495 26168 37085
9634 E01009931 Sandwell 18249 13372 16315 35980
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9636 E01009933 Sandwell 6327 12221 11443 34526
9637 E01009934 Sandwell 4450 13324 14257 38026
9638 E01009935 Sandwell 2520 13373 15187 37514
9639 E01009936 Sandwell 15407 23511 25270 37425
9640 E01009937 Sandwell 5110 13628 29879 36580
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9642 E01009939 Sandwell 15625 17745 23999 36478
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9647 E01009944 Sandwell 4992 10379 23644 36489
9648 E01009946 Sandwell 13574 20140 32808 40493
9649 E01009947 Sandwell 9144 11157 30707 40432
9650 E01009948 Sandwell 15499 24683 5673 39538
9651 E01009949 Sandwell 21397 34259 7616 39089
9652 E01009950 Sandwell 7542 7759 26388 40108
9653 E01009951 Sandwell 1776 15618 8045 39626
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9660 E01009958 Sandwell 22788 22482 11409 32055
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9664 E01009962 Sandwell 1225 6528 32996 39649
9665 E01009963 Sandwell 1619 3150 30902 40183
9666 E01009964 Sandwell 1166 17412 22934 40198
9667 E01009965 Sandwell 1018 7261 28984 39439
9668 E01009966 Sandwell 5689 18954 16448 40125
9669 E01009967 Sandwell 9600 23159 33997 40358
9670 E01009968 Sandwell 17408 34680 18108 39949
9671 E01009969 Sandwell 6099 19881 10695 40451
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9675 E01009973 Sandwell 15008 23929 27889 40387
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9677 E01009975 Sandwell 18632 23760 31019 39996
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9679 E01009977 Sandwell 8855 13345 17456 38368
9680 E01009978 Sandwell 2430 13351 25315 38063
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9682 E01009980 Sandwell 5224 7125 18230 38821
9683 E01009981 Sandwell 3346 19816 25630 39720
9684 E01009982 Sandwell 4423 21263 12831 38010
9685 E01009983 Sandwell 3053 22076 19423 38312
9686 E01009985 Sandwell 2550 13395 15040 40712
9687 E01009986 Sandwell 5331 536 26696 40950
9688 E01009987 Sandwell 1082 4614 26234 40712
9689 E01009988 Sandwell 3541 2050 34782 40941
9690 E01009989 Sandwell 6261 16045 25523 40693
9691 E01009991 Sandwell 5501 19871 25000 40753
9692 E01009992 Sandwell 5899 10711 30650 40758
9693 E01009993 Sandwell 2054 13489 25651 40617
9694 E01009994 Sandwell 3484 10476 27493 40077
9695 E01009995 Sandwell 6221 28103 10671 40549
9696 E01009996 Sandwell 1973 6446 23225 40077
9697 E01009997 Sandwell 5386 24619 23560 40514
9698 E01009998 Sandwell 5700 23188 15544 40753
9699 E01009999 Sandwell 6396 18568 35932 36651
9700 E01010000 Sandwell 12120 18320 12208 36363
9701 E01010001 Sandwell 4433 17487 20726 36740
9702 E01010002 Sandwell 11509 22844 13759 38377
9703 E01010003 Sandwell 2017 13567 22304 38308
9704 E01010004 Sandwell 3704 24939 24158 38156
9705 E01010005 Sandwell 8351 9670 26474 38060
9706 E01010006 Sandwell 11729 12466 23786 36869
9707 E01010007 Sandwell 8558 26811 6262 36779
9708 E01010008 Sandwell 11726 25203 5985 36834
9709 E01010009 Sandwell 10639 16425 8262 37959
9710 E01010010 Sandwell 6052 26297 11984 36405
9711 E01010011 Sandwell 19563 18420 22151 38357
9712 E01010012 Sandwell 16727 26686 19705 38775
9713 E01010013 Sandwell 19178 25808 10996 38501
9714 E01010014 Sandwell 13844 26726 11480 37683
9715 E01010015 Sandwell 11310 24130 21047 39046
9716 E01010016 Sandwell 6035 15305 8674 37819
9717 E01010017 Sandwell 3245 4947 29649 40087
9718 E01010018 Sandwell 9289 27849 17284 39711
9719 E01010019 Sandwell 3617 12944 33239 39613
9720 E01010020 Sandwell 7563 4663 10861 37541
9721 E01010021 Sandwell 3878 3064 22038 38637
9722 E01010022 Sandwell 15998 10936 36433 32480
9723 E01010023 Sandwell 13492 16163 36499 32862
9724 E01010024 Sandwell 19370 21916 39004 33783
9725 E01010025 Sandwell 4443 17685 31578 35196
9726 E01010026 Sandwell 12799 19869 29824 35808
9727 E01010027 Sandwell 19262 23661 35271 34821
9728 E01010028 Sandwell 6137 7135 36458 33141
9729 E01010029 Sandwell 268 1315 26552 37573
9730 E01010030 Sandwell 875 16091 30978 37900
9731 E01010031 Sandwell 913 5972 29408 37751
9732 E01010032 Sandwell 146 16417 32339 37553
9733 E01010033 Sandwell 1892 2667 25956 37910
9734 E01010034 Sandwell 22440 25811 11159 37410
9735 E01010035 Sandwell 17396 22916 18411 37616
9736 E01010036 Sandwell 6037 17795 32572 37789
9737 E01010037 Sandwell 2262 10095 21542 37733
9738 E01010038 Sandwell 5692 20079 9154 36780
9739 E01010039 Sandwell 3500 22854 5620 36437
9740 E01010040 Sandwell 8625 17812 8663 36149
9741 E01010041 Sandwell 3839 25118 27246 36209
9742 E01010042 Sandwell 6692 6122 24300 35474
9743 E01010043 Sandwell 17326 28234 19706 37504
9744 E01010044 Sandwell 5891 28322 6542 37063
9745 E01010045 Sandwell 5644 28208 30559 36301
9746 E01010046 Sandwell 4078 12359 17327 40019
9747 E01010047 Sandwell 5063 6611 19553 40485
9748 E01010048 Sandwell 7329 4601 32060 40019
9749 E01010049 Sandwell 6128 6797 31661 37715
9750 E01010050 Sandwell 7126 10813 26766 38219
9751 E01010051 Sandwell 6259 16838 10276 37390
9752 E01010052 Sandwell 3408 17471 33658 40973
9753 E01010053 Sandwell 2633 14480 24625 40304
9754 E01010054 Sandwell 829 5040 22091 37383
9755 E01010055 Sandwell 8497 2742 31097 37336
9756 E01010056 Sandwell 4234 14398 14600 37270
9757 E01010057 Sandwell 4446 3897 29780 37211
9758 E01010058 Sandwell 2810 10504 20699 36524
9759 E01010059 Sandwell 4865 4001 35451 36720
9760 E01010060 Sandwell 3012 3567 35799 37084
9761 E01010061 Sandwell 3910 297 37823 36720
9762 E01010062 Sandwell 1394 10619 24312 39331
9763 E01010063 Sandwell 882 10710 20208 38402
9764 E01010064 Sandwell 4438 1202 29828 37307
9765 E01010065 Sandwell 7488 4110 28261 37238
9766 E01010066 Sandwell 1886 10532 5701 38518
9767 E01010067 Sandwell 1145 6270 10723 38750
9768 E01010068 Sandwell 6821 6971 3580 37041
9769 E01010069 Sandwell 13487 24385 11640 39124
9770 E01010070 Sandwell 6732 14172 11396 37970
9771 E01010071 Sandwell 5907 11023 10370 38385
9772 E01010072 Sandwell 10156 11523 9718 38385
9773 E01010073 Sandwell 6332 25444 13696 38399
9774 E01010074 Sandwell 5597 22665 23876 37111
9775 E01010075 Sandwell 17274 14970 3225 38466
9776 E01010076 Sandwell 2426 14685 20076 38163
9777 E01010077 Sandwell 4205 33963 17380 36833
9778 E01010078 Sandwell 18830 29657 30017 37690
9779 E01010079 Sandwell 18503 33431 32225 36723
9780 E01010080 Sandwell 3316 21366 20630 38224
9781 E01010081 Sandwell 18918 24807 21368 37942
9782 E01010082 Sandwell 16153 29371 27919 37220
9783 E01010083 Sandwell 8456 25677 30687 36876
9784 E01010084 Sandwell 4669 25514 17222 37530
9785 E01010085 Sandwell 7107 15273 25747 39905
9786 E01010086 Sandwell 5866 15442 26148 39875
9787 E01010087 Sandwell 5025 20655 28108 40000
9788 E01010088 Sandwell 5387 10220 28543 40028
9789 E01010089 Sandwell 6104 9324 27984 39875
9790 E01010090 Sandwell 4410 5645 33783 39129
9791 E01010091 Sandwell 4903 1033 18816 40357
9792 E01010092 Sandwell 6568 5730 25790 40356
9793 E01010093 Sandwell 3660 15751 30286 40405
9794 E01010094 Sandwell 8809 10216 30073 40897
9795 E01010095 Sandwell 2785 22240 32206 39660
9796 E01010096 Sandwell 3712 2771 31461 40423
9797 E01010097 Sandwell 6409 25797 18705 39181
9798 E01010098 Sandwell 2696 25646 2842 40549
9799 E01010099 Sandwell 7484 25974 14770 40962
9800 E01010100 Sandwell 9976 15650 20230 40684
9801 E01010101 Sandwell 3985 14493 35405 40744
9802 E01010102 Sandwell 2982 4842 38402 41084
9803 E01010103 Sandwell 3466 6731 32403 40826
9804 E01010104 Sandwell 5359 11637 27435 40767
9805 E01010105 Sandwell 8470 16593 34821 40852
9806 E01010106 Sandwell 3343 3043 37563 40963
9807 E01010107 Sandwell 366 1762 40238 40990
9808 E01010108 Solihull 29660 34767 4272 23703
9809 E01010109 Solihull 15613 36711 37961 34621
9810 E01010110 Solihull 14509 18204 22436 36263
9811 E01010111 Solihull 1845 7904 23182 33271
9812 E01010112 Solihull 9008 9691 29957 36112
9813 E01010113 Solihull 9401 9980 25443 36055
9814 E01010114 Solihull 18184 13252 27017 38489
9815 E01010115 Solihull 16306 35717 4431 27845
9816 E01010116 Solihull 27090 29158 5296 30003
9817 E01010117 Solihull 26583 14039 12849 35909
9818 E01010118 Solihull 16194 15429 19103 36105
9819 E01010119 Solihull 26034 9431 27989 35909
9820 E01010120 Solihull 10097 5605 2404 35991
9821 E01010121 Solihull 21688 17400 15336 35404
9822 E01010122 Solihull 23399 24804 20086 36767
9823 E01010123 Solihull 19490 5780 28074 35647
9824 E01010124 Solihull 22920 8364 25361 35542
9825 E01010125 Solihull 1115 8934 19414 33188
9826 E01010126 Solihull 2194 28519 8846 36001
9827 E01010127 Solihull 6648 15433 14876 33020
9828 E01010128 Solihull 3521 12932 27665 36619
9829 E01010129 Solihull 1627 4017 25347 32984
9830 E01010130 Solihull 1369 4799 26289 33569
9831 E01010131 Solihull 1651 15948 30438 36482
9832 E01010132 Solihull 18496 12881 4432 35641
9833 E01010133 Solihull 18569 9742 14316 39655
9834 E01010134 Solihull 24105 15458 12221 41473
9835 E01010135 Solihull 15310 26067 5211 31558
9836 E01010136 Solihull 22154 19865 4440 32409
9837 E01010137 Solihull 7682 19954 6125 32060
9838 E01010138 Solihull 20682 27368 18186 36813
9839 E01010139 Solihull 7404 21296 13398 33525
9840 E01010140 Solihull 2504 20581 13417 33648
9841 E01010141 Solihull 1905 20248 622 33160
9842 E01010142 Solihull 564 18930 21254 33648
9843 E01010143 Solihull 1988 12003 29559 33479
9844 E01010144 Solihull 9242 2417 33700 33605
9845 E01010145 Solihull 11089 13717 10547 33805
9846 E01010146 Solihull 4429 7275 11149 34365
9847 E01010147 Solihull 1581 19687 717 33818
9848 E01010148 Solihull 2195 15604 8170 33795
9849 E01010149 Solihull 9466 28496 11070 33828
9850 E01010150 Solihull 32804 31907 20276 27790
9851 E01010151 Solihull 23769 13826 5810 20148
9852 E01010152 Solihull 32417 29607 18666 22546
9853 E01010153 Solihull 30583 25935 10959 17770
9854 E01010154 Solihull 29372 30458 1974 26881
9855 E01010155 Solihull 32690 25235 13726 23381
9856 E01010156 Solihull 32404 29746 16654 24848
9857 E01010157 Solihull 18207 23922 18785 34443
9858 E01010158 Solihull 4137 5418 5847 39184
9859 E01010159 Solihull 12518 12897 27405 40942
9860 E01010160 Solihull 14828 8343 2047 37124
9861 E01010161 Solihull 23180 19653 4336 37124
9862 E01010162 Solihull 19995 15681 22482 38416
9863 E01010163 Solihull 22789 13185 18682 38012
9864 E01010164 Solihull 23186 38900 12131 17462
9865 E01010165 Solihull 17405 36247 8427 20310
9866 E01010166 Solihull 30687 35056 18838 15975
9867 E01010167 Solihull 13548 37901 1756 15000
9868 E01010168 Solihull 28065 34786 8632 17255
9869 E01010169 Solihull 32334 25159 22706 15782
9870 E01010170 Solihull 32677 29229 20890 14418
9871 E01010171 Solihull 27115 33573 12656 13684
9872 E01010172 Solihull 31819 17871 3626 32060
9873 E01010173 Solihull 32435 13860 5201 30528
9874 E01010174 Solihull 18471 16821 28315 31568
9875 E01010175 Solihull 28953 22157 4211 31562
9876 E01010176 Solihull 31232 22618 7157 30586
9877 E01010177 Solihull 18625 20221 10746 33614
9878 E01010178 Solihull 7210 8704 14952 31937
9879 E01010179 Solihull 25161 13388 2701 32060
9880 E01010180 Solihull 29493 31350 11537 19989
9881 E01010181 Solihull 31674 34908 10361 19498
9882 E01010183 Solihull 27106 37037 15384 23445
9883 E01010184 Solihull 18992 29618 22783 25088
9884 E01010185 Solihull 32411 17638 19979 18817
9885 E01010186 Solihull 31842 25120 22054 20801
9886 E01010187 Solihull 32282 29978 22374 23556
9887 E01010188 Solihull 32626 13109 12858 17485
9888 E01010189 Solihull 31506 29982 6004 22990
9889 E01010190 Solihull 31223 32181 17158 28836
9890 E01010191 Solihull 30597 16739 13415 27986
9891 E01010192 Solihull 26307 8619 39058 28770
9892 E01010193 Solihull 32218 33181 27001 28492
9893 E01010194 Solihull 31222 30890 20990 29616
9894 E01010195 Solihull 31535 14791 4752 29343
9895 E01010196 Solihull 31877 20682 9360 30397
9896 E01010197 Solihull 31577 18774 15597 29313
9897 E01010198 Solihull 31990 14816 17088 28368
9898 E01010199 Solihull 31563 17790 22378 28033
9899 E01010200 Solihull 17736 7199 29705 27552
9900 E01010201 Solihull 26707 9475 32593 27536
9901 E01010202 Solihull 31299 9291 20704 26847
9902 E01010203 Solihull 24003 9452 29336 24675
9903 E01010204 Solihull 4597 20451 18508 30990
9904 E01010205 Solihull 32361 27185 21441 30517
9905 E01010206 Solihull 25471 17838 25369 30958
9906 E01010207 Solihull 30730 28166 21154 26748
9907 E01010208 Solihull 25713 7534 28888 23075
9908 E01010209 Solihull 21231 11919 28600 24274
9909 E01010210 Solihull 29365 17973 21529 21939
9910 E01010211 Solihull 13324 18149 30152 23033
9911 E01010212 Solihull 32487 14363 10400 29493
9912 E01010213 Solihull 13832 20693 24178 22688
9913 E01010214 Solihull 32528 28339 7004 25133
9914 E01010215 Solihull 28415 26502 8945 22943
9915 E01010216 Solihull 30898 23845 13328 26378
9916 E01010217 Solihull 31068 28036 22970 21772
9917 E01010218 Solihull 9348 9155 8699 24638
9918 E01010219 Solihull 18593 26197 8018 24793
9919 E01010220 Solihull 26438 15832 21420 26603
9920 E01010221 Solihull 16847 29894 13734 23051
9921 E01010222 Solihull 25961 24882 8660 25562
9922 E01010223 Solihull 15217 12151 20323 26162
9923 E01010225 Solihull 26038 16037 10812 27627
9924 E01010226 Solihull 24570 11591 7711 29305
9925 E01010227 Solihull 29489 23130 1067 29997
9926 E01010228 Solihull 20698 25848 14935 30757
9927 E01010229 Solihull 31592 14706 2425 30372
9928 E01010230 Solihull 15234 6517 16694 30104
9929 E01010231 Solihull 31638 12731 11539 30344
9930 E01010232 Solihull 17268 20969 12307 30051
9931 E01010233 Solihull 17678 8464 9369 29253
9932 E01010234 Solihull 1635 8391 31894 35172
9933 E01010235 Solihull 2403 7390 34820 35649
9934 E01010236 Solihull 3609 12804 30480 35853
9935 E01010237 Solihull 7805 15308 26560 34686
9936 E01010238 Solihull 1711 20364 17568 33829
9937 E01010239 Solihull 3185 23161 34195 35914
9938 E01010240 Solihull 3577 22450 26882 35842
9939 E01010241 Walsall 26693 12224 21270 35867
9940 E01010242 Walsall 6056 19173 19925 39586
9941 E01010243 Walsall 22884 7611 13681 37881
9942 E01010244 Walsall 5155 14108 11079 33726
9943 E01010245 Walsall 28144 9837 17258 31392
9944 E01010246 Walsall 21411 26517 10390 34151
9945 E01010247 Walsall 19112 13807 13997 33280
9946 E01010248 Walsall 28403 25599 11486 32257
9947 E01010249 Walsall 8270 6189 13665 34052
9948 E01010250 Walsall 13605 19155 9573 31492
9949 E01010251 Walsall 28975 13049 14660 36414
9950 E01010252 Walsall 12212 15557 11043 33432
9951 E01010253 Walsall 9269 9304 23648 38102
9952 E01010254 Walsall 10149 1824 17414 37619
9953 E01010255 Walsall 24613 23862 27509 36491
9954 E01010256 Walsall 14204 10657 20831 37619
9955 E01010257 Walsall 29154 22387 23534 39403
9956 E01010258 Walsall 4559 20738 29854 39865
9957 E01010259 Walsall 10500 17121 30007 39190
9958 E01010260 Walsall 4261 15365 30140 40080
9959 E01010261 Walsall 3630 23215 20600 40094
9960 E01010262 Walsall 7355 13794 18641 38782
9961 E01010263 Walsall 4291 621 32117 39447
9962 E01010264 Walsall 3594 4961 20883 39514
9963 E01010265 Walsall 4142 17250 24782 40158
9964 E01010266 Walsall 3178 24781 26206 39776
9965 E01010267 Walsall 15089 18899 26018 39847
9966 E01010268 Walsall 3740 5513 23420 40390
9967 E01010269 Walsall 2024 5204 25669 40854
9968 E01010270 Walsall 4534 16968 25822 40745
9969 E01010271 Walsall 2002 16948 10119 38989
9970 E01010272 Walsall 1546 13482 22419 39155
9971 E01010273 Walsall 1565 13028 5335 38337
9972 E01010274 Walsall 1392 5884 15140 39238
9973 E01010275 Walsall 2263 6856 8175 40184
9974 E01010277 Walsall 2939 11225 8096 38717
9975 E01010279 Walsall 3675 14686 9068 39683
9976 E01010282 Walsall 1244 4840 19062 39155
9977 E01010283 Walsall 1949 2134 20864 37382
9978 E01010284 Walsall 4001 17560 7001 34660
9979 E01010285 Walsall 15138 17581 12807 36141
9980 E01010286 Walsall 1756 12149 14720 34660
9981 E01010287 Walsall 5423 7113 28362 37391
9982 E01010288 Walsall 2204 8746 23470 36714
9983 E01010289 Walsall 654 5179 24258 36154
9984 E01010290 Walsall 7513 9213 8345 33971
9985 E01010291 Walsall 1664 14947 3381 37572
9986 E01010292 Walsall 2727 7383 25146 37364
9987 E01010293 Walsall 4439 10516 11432 37756
9988 E01010294 Walsall 2333 15815 7993 38108
9989 E01010295 Walsall 1263 7584 21499 38989
9990 E01010296 Walsall 29054 31776 6638 36724
9991 E01010297 Walsall 29876 23533 10814 35848
9992 E01010298 Walsall 8565 18412 20610 37756
9993 E01010299 Walsall 3133 16810 15189 38548
9994 E01010300 Walsall 2220 5069 10281 37828
9995 E01010301 Walsall 4758 32159 21476 29705
9996 E01010302 Walsall 5515 24431 7820 31281
9997 E01010303 Walsall 12348 25114 23680 28092
9998 E01010304 Walsall 12613 31923 29177 30052
9999 E01010305 Walsall 5330 20817 20463 29401
10000 E01010306 Walsall 15009 10355 7732 28544
10001 E01010307 Walsall 24816 29328 8834 29812
10002 E01010308 Walsall 2311 13088 8845 29416
10003 E01010309 Walsall 4652 4517 25923 38482
10004 E01010310 Walsall 3916 17403 8736 37888
10005 E01010311 Walsall 2410 8145 32846 39201
10006 E01010312 Walsall 4680 11797 11447 38451
10007 E01010313 Walsall 5634 18594 21176 38023
10008 E01010314 Walsall 4136 9389 10917 37594
10009 E01010315 Walsall 5920 20181 11894 37216
10010 E01010316 Walsall 1304 8091 7415 38451
10011 E01010317 Walsall 20253 28087 3496 37183
10012 E01010318 Walsall 2583 5980 3593 40008
10013 E01010319 Walsall 27691 17542 6368 34093
10014 E01010320 Walsall 6867 26215 7953 36426
10015 E01010321 Walsall 6360 8385 11256 34733
10016 E01010322 Walsall 9222 14764 10907 36750
10017 E01010323 Walsall 9377 20088 6703 35854
10018 E01010324 Walsall 8838 15024 7596 36603
10019 E01010325 Walsall 11750 17569 2589 39523
10020 E01010326 Walsall 16719 9469 6940 39474
10021 E01010327 Walsall 7487 5297 25622 40352
10022 E01010328 Walsall 28287 25246 13996 38976
10023 E01010329 Walsall 24498 30313 11278 35726
10024 E01010330 Walsall 9727 6181 11044 40544
10025 E01010331 Walsall 27961 23304 25893 37227
10026 E01010332 Walsall 27237 28603 8194 39754
10027 E01010333 Walsall 23670 26658 11802 37639
10028 E01010334 Walsall 27073 30177 5040 39031
10029 E01010335 Walsall 3599 12436 17046 40874
10030 E01010336 Walsall 6566 16983 20041 40606
10031 E01010337 Walsall 12426 13398 8781 40591
10032 E01010338 Walsall 6486 6384 9933 40880
10033 E01010339 Walsall 15191 12320 8636 40874
10034 E01010340 Walsall 2773 5810 34671 40936
10035 E01010341 Walsall 5636 4409 34806 40484
10036 E01010342 Walsall 2308 5441 34014 40896
10037 E01010343 Walsall 3544 7030 29033 40676
10038 E01010344 Walsall 3959 6769 22128 40564
10039 E01010345 Walsall 21645 12284 13453 29014
10040 E01010346 Walsall 26153 18543 9133 29511
10041 E01010347 Walsall 5548 14653 8088 30493
10042 E01010348 Walsall 15452 12490 14060 33240
10043 E01010349 Walsall 9305 3255 12693 31274
10044 E01010350 Walsall 19134 27548 12328 31376
10045 E01010351 Walsall 15032 24473 21726 34545
10046 E01010352 Walsall 22632 23582 18387 33676
10047 E01010353 Walsall 10134 18604 15773 33668
10048 E01010354 Walsall 13207 16234 18389 33672
10049 E01010355 Walsall 20630 7433 35076 37569
10050 E01010356 Walsall 21789 17891 22365 37737
10051 E01010357 Walsall 25910 21488 31668 39529
10052 E01010358 Walsall 16910 1584 35865 38352
10053 E01010359 Walsall 17526 2351 34471 40010
10054 E01010360 Walsall 20708 13533 34605 39968
10055 E01010361 Walsall 9291 15414 27377 40391
10056 E01010362 Walsall 3606 9999 26455 40720
10057 E01010363 Walsall 2740 7411 33118 40832
10058 E01010364 Walsall 1573 3307 30263 40804
10059 E01010365 Walsall 2652 8840 32971 40391
10060 E01010366 Walsall 2240 10198 18795 40686
10061 E01010367 Walsall 2277 19808 19650 40584
10062 E01010368 Walsall 820 2168 38480 40444
10063 E01010369 Walsall 1774 3062 12545 40082
10064 E01010370 Walsall 3062 1684 27800 40489
10065 E01010371 Walsall 1053 1922 35232 40842
10066 E01010372 Walsall 3042 2712 32838 40911
10067 E01010373 Walsall 21616 14026 8335 40846
10068 E01010374 Walsall 2390 15344 19042 40029
10069 E01010375 Walsall 2663 5962 29352 40307
10070 E01010376 Walsall 16918 19619 29187 37413
10071 E01010377 Walsall 10003 20226 19024 37057
10072 E01010378 Walsall 15292 22190 25569 39015
10073 E01010379 Walsall 19936 16055 8490 37696
10074 E01010380 Walsall 14663 22313 7720 36788
10075 E01010381 Walsall 5698 18030 12469 36788
10076 E01010382 Walsall 8016 22292 7463 37983
10077 E01010383 Walsall 3095 22212 14363 37889
10078 E01010384 Walsall 29122 27046 38457 32841
10079 E01010385 Walsall 31710 19762 14984 31143
10080 E01010386 Walsall 31030 12813 30452 32246
10081 E01010387 Walsall 29586 16340 34191 32759
10082 E01010388 Walsall 31543 29551 14176 31860
10083 E01010389 Walsall 22845 24969 18537 35220
10084 E01010390 Walsall 29077 25664 35043 33246
10085 E01010391 Walsall 29290 29078 34495 34274
10086 E01010392 Walsall 29594 25134 22713 30553
10087 E01010393 Walsall 11785 15397 12358 36346
10088 E01010394 Walsall 18542 13101 21555 36346
10089 E01010395 Walsall 25954 15449 17604 35979
10090 E01010396 Walsall 6780 11924 12000 37294
10091 E01010397 Walsall 4018 11478 9605 35436
10092 E01010398 Walsall 26186 7546 25228 35534
10093 E01010399 Walsall 14854 14769 20460 35534
10094 E01010400 Walsall 2749 18983 12607 36922
10095 E01010401 Walsall 3054 23413 33318 36818
10096 E01010402 Walsall 11278 18916 30372 39316
10097 E01010403 Walsall 4974 11322 37062 38494
10098 E01010404 Walsall 3237 3678 35595 38245
10099 E01010405 Walsall 5318 11395 29448 39151
10100 E01010406 Walsall 4067 3034 38382 38447
10101 E01010407 Walsall 5972 19554 31325 37624
10102 E01010408 Walsall 2816 20281 34355 38109
10103 E01010409 Walsall 6084 21506 29106 38854
10104 E01010410 Wolverhampton 3038 16578 14267 37099
10105 E01010411 Wolverhampton 9209 22432 13926 37354
10106 E01010412 Wolverhampton 5297 16628 14583 37320
10107 E01010413 Wolverhampton 2207 15603 12994 37354
10108 E01010414 Wolverhampton 1121 9305 32147 37405
10109 E01010415 Wolverhampton 3251 27899 31542 38545
10110 E01010416 Wolverhampton 581 12358 31006 38737
10111 E01010417 Wolverhampton 3656 16647 35619 37829
10112 E01010418 Wolverhampton 14390 20139 36887 38324
10113 E01010419 Wolverhampton 6045 7443 24619 36792
10114 E01010420 Wolverhampton 4391 19552 36299 35488
10115 E01010421 Wolverhampton 1999 21939 31908 38737
10116 E01010422 Wolverhampton 7137 4610 23441 37847
10117 E01010423 Wolverhampton 1931 11111 39108 37636
10118 E01010424 Wolverhampton 10390 15092 38542 38152
10119 E01010425 Wolverhampton 6975 27647 39584 37693
10120 E01010426 Wolverhampton 9876 6741 41043 29994
10121 E01010427 Wolverhampton 10738 10555 29749 26462
10122 E01010428 Wolverhampton 4856 3356 41009 29554
10123 E01010429 Wolverhampton 5494 10320 40523 29002
10124 E01010430 Wolverhampton 3409 5447 35802 29634
10125 E01010431 Wolverhampton 17142 21787 33189 26658
10126 E01010432 Wolverhampton 13850 16535 24653 27406
10127 E01010433 Wolverhampton 2833 3592 40384 29554
10128 E01010434 Wolverhampton 9441 21999 29982 34507
10129 E01010435 Wolverhampton 2007 29862 39221 34002
10130 E01010436 Wolverhampton 21011 30487 13772 34466
10131 E01010437 Wolverhampton 26125 31409 15080 36703
10132 E01010438 Wolverhampton 18096 26221 12985 34201
10133 E01010439 Wolverhampton 4801 26996 14595 34258
10134 E01010440 Wolverhampton 2910 20387 21101 34434
10135 E01010441 Wolverhampton 3775 20169 24539 34454
10136 E01010442 Wolverhampton 3505 25975 39545 36081
10137 E01010443 Wolverhampton 1525 19094 39702 35843
10138 E01010444 Wolverhampton 7121 22774 39180 37660
10139 E01010445 Wolverhampton 1109 17384 37711 38688
10140 E01010446 Wolverhampton 4942 26017 39533 37381
10141 E01010447 Wolverhampton 5293 11028 38319 37440
10142 E01010448 Wolverhampton 3332 13146 38773 36488
10143 E01010449 Wolverhampton 5726 15946 25725 30682
10144 E01010450 Wolverhampton 1422 19176 32886 34969
10145 E01010451 Wolverhampton 8476 24735 30809 35195
10146 E01010452 Wolverhampton 4604 22082 28756 32429
10147 E01010453 Wolverhampton 4027 16907 36319 33165
10148 E01010454 Wolverhampton 4913 8229 37379 32228
10149 E01010455 Wolverhampton 3151 22847 30807 34165
10150 E01010456 Wolverhampton 340 6851 14070 35348
10151 E01010457 Wolverhampton 11943 11608 15084 35264
10152 E01010458 Wolverhampton 6602 11353 18007 37179
10153 E01010459 Wolverhampton 10350 801 22408 35411
10154 E01010460 Wolverhampton 13935 6789 23379 38187
10155 E01010461 Wolverhampton 22394 8096 15726 38187
10156 E01010462 Wolverhampton 2179 13757 7649 34573
10157 E01010463 Wolverhampton 2515 1543 27314 32294
10158 E01010464 Wolverhampton 1257 3679 19474 32492
10159 E01010465 Wolverhampton 5211 7526 33930 28361
10160 E01010466 Wolverhampton 2280 529 37401 31148
10161 E01010467 Wolverhampton 12651 6794 20043 26688
10162 E01010468 Wolverhampton 12274 16118 24893 27376
10163 E01010469 Wolverhampton 16835 22395 33652 24849
10164 E01010470 Wolverhampton 3730 11009 25261 29469
10165 E01010471 Wolverhampton 2719 18945 35171 39539
10166 E01010472 Wolverhampton 4900 20407 38883 39176
10167 E01010473 Wolverhampton 2589 15718 35097 39097
10168 E01010474 Wolverhampton 5040 7552 4686 38318
10169 E01010475 Wolverhampton 14782 13144 18348 38183
10170 E01010476 Wolverhampton 4283 5954 22553 38745
10171 E01010477 Wolverhampton 5298 20882 37257 39539
10172 E01010478 Wolverhampton 1971 16588 37736 38973
10173 E01010479 Wolverhampton 5537 4398 25788 38478
10174 E01010480 Wolverhampton 10398 12266 32883 39607
10175 E01010481 Wolverhampton 3401 8127 16648 35348
10176 E01010482 Wolverhampton 3143 16262 22478 35175
10177 E01010483 Wolverhampton 1027 14116 27330 34716
10178 E01010484 Wolverhampton 2176 5389 27727 38729
10179 E01010485 Wolverhampton 2159 9529 34759 36609
10180 E01010486 Wolverhampton 1724 7634 31217 37361
10181 E01010487 Wolverhampton 24754 20578 25608 20109
10182 E01010488 Wolverhampton 12541 20359 33437 21228
10183 E01010489 Wolverhampton 10415 22336 24994 16764
10184 E01010490 Wolverhampton 1854 13630 30800 17206
10185 E01010491 Wolverhampton 9164 19609 34401 17623
10186 E01010492 Wolverhampton 25106 32054 31191 18127
10187 E01010493 Wolverhampton 22605 22701 13673 23805
10188 E01010494 Wolverhampton 27320 25127 16820 16647
10189 E01010495 Wolverhampton 8084 18040 15772 30560
10190 E01010496 Wolverhampton 7084 25626 8308 24663
10191 E01010497 Wolverhampton 27710 18520 6409 26443
10192 E01010498 Wolverhampton 21564 24670 8938 25205
10193 E01010499 Wolverhampton 13587 16534 18276 31154
10194 E01010500 Wolverhampton 4046 22366 25043 31594
10195 E01010501 Wolverhampton 9035 23951 1024 27877
10196 E01010502 Wolverhampton 18229 29468 18263 31428
10197 E01010503 Wolverhampton 3879 31972 24764 31450
10198 E01010504 Wolverhampton 23519 22905 5855 25620
10199 E01010505 Wolverhampton 22550 25946 7456 27793
10200 E01010506 Wolverhampton 4216 4959 13332 29928
10201 E01010507 Wolverhampton 23002 21514 8075 23283
10202 E01010508 Wolverhampton 3581 5094 7901 32382
10203 E01010509 Wolverhampton 8093 25269 14181 19095
10204 E01010510 Wolverhampton 10234 2524 6500 24982
10205 E01010511 Wolverhampton 3685 5569 7248 30540
10206 E01010512 Wolverhampton 8627 3978 5245 29935
10207 E01010513 Wolverhampton 16172 29614 27324 23657
10208 E01010514 Wolverhampton 23833 33021 30864 21410
10209 E01010515 Wolverhampton 26085 23791 35354 24821
10210 E01010516 Wolverhampton 23696 21356 28437 21101
10211 E01010517 Wolverhampton 12454 24854 34093 21410
10212 E01010518 Wolverhampton 20622 13376 25106 24860
10213 E01010519 Wolverhampton 14431 13763 29507 24892
10214 E01010520 Wolverhampton 25117 19969 33299 24989
10215 E01010521 Wolverhampton 6373 1372 40799 37067
10216 E01010522 Wolverhampton 3468 18809 23339 31101
10217 E01010523 Wolverhampton 7867 7886 10567 28997
10218 E01010524 Wolverhampton 3068 16520 11760 29233
10219 E01010525 Wolverhampton 4111 8128 25265 29941
10220 E01010526 Wolverhampton 5103 11208 19315 32459
10221 E01010527 Wolverhampton 2339 8827 13827 29941
10222 E01010528 Wolverhampton 7638 15370 22176 33307
10223 E01010529 Wolverhampton 3502 11264 9960 33379
10224 E01010530 Wolverhampton 2880 10475 40551 34253
10225 E01010531 Wolverhampton 5761 11868 14777 35332
10226 E01010532 Wolverhampton 3097 10755 21139 32049
10227 E01010533 Wolverhampton 6698 23925 23227 29517
10228 E01010534 Wolverhampton 17399 19624 8655 33470
10229 E01010535 Wolverhampton 4908 25325 12543 30653
10230 E01010536 Wolverhampton 19423 20255 21652 28580
10231 E01010537 Wolverhampton 22191 14834 23472 28719
10232 E01010538 Wolverhampton 8786 15198 17555 31389
10233 E01010539 Wolverhampton 16259 17042 6682 28138
10234 E01010540 Wolverhampton 23843 13980 2671 24320
10235 E01010541 Wolverhampton 2797 35122 1562 23448
10236 E01010542 Wolverhampton 16865 33624 14246 25904
10237 E01010543 Wolverhampton 3517 35150 10172 23448
10238 E01010544 Wolverhampton 22644 33834 10162 20875
10239 E01010545 Wolverhampton 20643 31608 20858 28343
10240 E01010546 Wolverhampton 22236 27802 6440 18064
10241 E01010547 Wolverhampton 26646 4310 1808 24866
10242 E01010548 Wolverhampton 13653 14684 6141 21134
10243 E01010549 Wolverhampton 17162 14855 6803 20516
10244 E01010550 Wolverhampton 29582 25754 1165 17422
10245 E01010551 Wolverhampton 22002 13718 2483 20516
10246 E01010552 Wolverhampton 15737 22127 9175 17167
10247 E01010553 Wolverhampton 21804 20579 7368 20303
10248 E01010554 Wolverhampton 14259 23203 16941 36588
10249 E01010555 Wolverhampton 3457 14324 14215 36367
10250 E01010556 Wolverhampton 9949 21352 16468 35635
10251 E01010557 Wolverhampton 19233 10168 12458 36828
10252 E01010558 Wolverhampton 13108 15327 11478 37092
10253 E01010559 Wolverhampton 4925 27552 26639 34367
10254 E01010560 Wolverhampton 5616 24395 15463 35741
10255 E01010561 Wolverhampton 22879 23953 12277 36587
10256 E01010562 Wolverhampton 4569 17362 13557 37790
10257 E01010563 Wolverhampton 5308 19919 12942 36711
10258 E01010564 Wolverhampton 4864 13170 35348 37833
10259 E01010565 Wolverhampton 24617 21388 23763 36689
10260 E01010566 Wolverhampton 9933 16561 8823 38174
10261 E01010567 Wolverhampton 4977 21557 3921 37110
10262 E01010568 Bradford 23447 27473 7967 24583
10263 E01010569 Bradford 5775 27066 4719 20295
10264 E01010570 Bradford 29423 34415 25120 16660
10265 E01010571 Bradford 6829 21699 3641 24528
10266 E01010572 Bradford 22844 20565 21968 24061
10267 E01010573 Bradford 23097 30765 24682 16078
10268 E01010574 Bradford 25037 21476 8795 16756
10269 E01010575 Bradford 23641 15566 31054 13749
10270 E01010576 Bradford 27392 27629 3271 21938
10271 E01010577 Bradford 25950 14771 18717 16594
10272 E01010578 Bradford 13956 13647 8240 10337
10273 E01010579 Bradford 30816 18749 2735 12252
10274 E01010580 Bradford 31226 24598 16290 14305
10275 E01010581 Bradford 14152 12523 11204 14754
10276 E01010582 Bradford 17435 6828 21960 12964
10277 E01010583 Bradford 3202 30613 2591 17031
10278 E01010584 Bradford 7752 3645 12626 12423
10279 E01010585 Bradford 13558 5879 21701 11927
10280 E01010586 Bradford 30409 29692 3165 9995
10281 E01010587 Bradford 20073 31136 12200 12539
10282 E01010588 Bradford 18565 11847 11549 12679
10283 E01010589 Bradford 27895 27878 34581 10525
10284 E01010590 Bradford 20493 34374 5509 9302
10285 E01010591 Bradford 9619 11388 20244 12698
10286 E01010592 Bradford 18143 33497 9476 10197
10287 E01010593 Bradford 20193 16781 31072 10526
10288 E01010594 Bradford 17252 35682 9065 8240
10289 E01010595 Bradford 9536 34161 23105 8671
10290 E01010596 Bradford 21671 22645 4628 13417
10291 E01010597 Bradford 8251 25831 32100 32665
10292 E01010598 Bradford 12863 14401 38115 34470
10293 E01010599 Bradford 6717 30466 28027 33556
10294 E01010600 Bradford 7663 28927 35867 33556
10295 E01010601 Bradford 9489 8794 40601 35166
10296 E01010602 Bradford 9538 22544 32426 34232
10297 E01010603 Bradford 11724 15528 38684 30802
10298 E01010604 Bradford 14727 16856 35757 28950
10299 E01010605 Bradford 3184 11729 30653 32665
10300 E01010606 Bradford 595 8857 41712 36886
10301 E01010607 Bradford 1781 11359 41641 36844
10302 E01010608 Bradford 1815 11234 41648 37540
10303 E01010609 Bradford 1740 19214 41690 37380
10304 E01010610 Bradford 659 26756 41505 35115
10305 E01010611 Bradford 2893 16231 41663 35621
10306 E01010612 Bradford 81 25600 36396 34471
10307 E01010613 Bradford 1043 17141 41710 37508
10308 E01010614 Bradford 1704 24975 41718 35537
10309 E01010615 Bradford 5255 10911 41600 35928
10310 E01010616 Bradford 2739 25779 37873 37209
10311 E01010617 Bradford 240 3500 41036 35539
10312 E01010618 Bradford 1653 12192 41707 36676
10313 E01010619 Bradford 5265 3227 41708 36676
10314 E01010620 Bradford 1227 7455 41716 37396
10315 E01010621 Bradford 3652 3085 41705 36844
10316 E01010622 Bradford 1753 3882 41679 36781
10317 E01010623 Bradford 442 15012 41700 35737
10318 E01010624 Bradford 1515 7945 41684 37538
10319 E01010625 Bradford 1481 13318 40471 36577
10320 E01010626 Bradford 1846 13702 41351 37140
10321 E01010627 Bradford 2045 10927 41706 36221
10322 E01010628 Bradford 5042 26982 13605 22826
10323 E01010629 Bradford 6935 28189 11367 22978
10324 E01010630 Bradford 5481 17592 21885 24796
10325 E01010631 Bradford 1614 24858 19161 18196
10326 E01010632 Bradford 1098 24090 12258 18598
10327 E01010633 Bradford 11771 24148 19440 23107
10328 E01010634 Bradford 16550 19425 15791 18937
10329 E01010635 Bradford 498 21715 14199 23120
10330 E01010636 Bradford 16884 16243 21415 21457
10331 E01010637 Bradford 9989 10681 18137 21177
10332 E01010638 Bradford 19901 18137 8174 4819
10333 E01010639 Bradford 19142 3345 9940 8225
10334 E01010640 Bradford 15247 1340 18647 7618
10335 E01010641 Bradford 20172 7888 6036 9322
10336 E01010642 Bradford 27932 20949 12441 5889
10337 E01010643 Bradford 19334 13657 20859 5426
10338 E01010644 Bradford 18379 24365 19093 7569
10339 E01010645 Bradford 26197 18388 16700 7706
10340 E01010646 Bradford 29901 28222 3484 4202
10341 E01010647 Bradford 22949 17320 16071 4684
10342 E01010648 Bradford 30451 25795 19800 4146
10343 E01010649 Bradford 4608 17113 36014 32561
10344 E01010650 Bradford 1951 26974 22699 32561
10345 E01010651 Bradford 13389 11334 38297 35101
10346 E01010652 Bradford 9628 8149 37248 34126
10347 E01010653 Bradford 1518 10666 17131 30656
10348 E01010654 Bradford 1052 18453 14951 31129
10349 E01010655 Bradford 1156 13734 21882 31151
10350 E01010656 Bradford 10667 5926 37541 33650
10351 E01010657 Bradford 8453 2022 35825 34126
10352 E01010658 Bradford 4493 23385 38644 29286
10353 E01010659 Bradford 741 21959 13954 25696
10354 E01010662 Bradford 8069 25297 25549 24044
10355 E01010663 Bradford 679 2104 39477 30504
10356 E01010664 Bradford 9930 20809 22606 23531
10357 E01010665 Bradford 6496 14245 28355 28892
10358 E01010666 Bradford 151 4341 35438 33801
10359 E01010667 Bradford 3028 5632 32094 29780
10360 E01010668 Bradford 15976 18026 30985 26588
10361 E01010669 Bradford 7022 22175 33035 15992
10362 E01010670 Bradford 7526 14344 9456 26294
10363 E01010671 Bradford 9153 17252 26345 24641
10364 E01010672 Bradford 20973 31331 11018 12693
10365 E01010673 Bradford 3566 10102 12253 28761
10366 E01010674 Bradford 3035 22772 28987 16094
10367 E01010675 Bradford 8500 12441 19710 23158
10368 E01010676 Bradford 2066 6037 28990 32258
10369 E01010677 Bradford 3305 21678 21090 20986
10370 E01010678 Bradford 12642 34293 9837 12796
10371 E01010679 Bradford 228 639 30847 32258
10372 E01010680 Bradford 1393 9070 12449 30884
10373 E01010681 Bradford 29385 22064 32295 28249
10374 E01010682 Bradford 3292 10526 10444 32781
10375 E01010683 Bradford 23940 13865 8641 26757
10376 E01010684 Bradford 18316 19360 25357 27642
10377 E01010685 Bradford 13944 20667 6808 21014
10378 E01010686 Bradford 19542 27781 10452 27344
10379 E01010687 Bradford 27716 24899 15394 26331
10380 E01010688 Bradford 12121 8894 30374 27839
10381 E01010689 Bradford 13622 4369 18061 32213
10382 E01010690 Bradford 17051 10996 28927 29129
10383 E01010691 Bradford 31769 15418 7330 5618
10384 E01010692 Bradford 28120 10979 7669 5455
10385 E01010693 Bradford 31946 20588 10025 4660
10386 E01010694 Bradford 30606 32087 4025 5482
10387 E01010695 Bradford 25647 800 18236 5349
10388 E01010696 Bradford 30401 25806 4372 6519
10389 E01010697 Bradford 31942 8582 7542 4866
10390 E01010698 Bradford 24118 7143 16013 5481
10391 E01010699 Bradford 14424 19612 2912 6285
10392 E01010700 Bradford 2306 11427 36743 22161
10393 E01010701 Bradford 1472 7597 35505 24103
10394 E01010702 Bradford 2598 4125 40154 24103
10395 E01010703 Bradford 6914 24452 16947 16816
10396 E01010704 Bradford 8547 22023 24516 13369
10397 E01010705 Bradford 17236 16855 25321 11775
10398 E01010706 Bradford 26741 36623 2161 8158
10399 E01010707 Bradford 24599 32270 1641 11377
10400 E01010708 Bradford 11897 23006 10473 17672
10401 E01010709 Bradford 23189 33978 2546 14709
10402 E01010710 Bradford 125 864 40412 14854
10403 E01010711 Bradford 85 1802 36398 12054
10404 E01010712 Bradford 2808 874 30426 12097
10405 E01010713 Bradford 1174 27543 29050 11349
10406 E01010714 Bradford 4952 4063 32075 10442
10407 E01010715 Bradford 4201 12735 13171 8812
10408 E01010716 Bradford 3987 20998 19489 10244
10409 E01010717 Bradford 5085 6730 28495 8812
10410 E01010718 Bradford 1790 26793 11146 8726
10411 E01010719 Bradford 2858 3202 33939 12097
10412 E01010720 Bradford 1531 17984 14014 11562
10413 E01010721 Bradford 758 30238 6511 8823
10414 E01010722 Bradford 2233 33717 6564 5448
10415 E01010723 Bradford 1324 4240 39758 12097
10416 E01010724 Bradford 3161 8107 3768 10519
10417 E01010725 Bradford 6500 2486 20981 10335
10418 E01010726 Bradford 22296 12232 10740 7128
10419 E01010727 Bradford 9813 29382 11400 9244
10420 E01010728 Bradford 3650 10639 26535 16416
10421 E01010729 Bradford 14379 25123 11270 8558
10422 E01010730 Bradford 75 12544 41695 38333
10423 E01010731 Bradford 2208 3951 41407 37231
10424 E01010732 Bradford 1728 10418 41504 37707
10425 E01010733 Bradford 647 3742 41568 37314
10426 E01010734 Bradford 2021 18133 41692 38333
10427 E01010735 Bradford 302 6332 38423 35544
10428 E01010736 Bradford 2289 15009 41567 38333
10429 E01010737 Bradford 328 15149 41673 36442
10430 E01010738 Bradford 3872 6335 41636 36210
10431 E01010739 Bradford 418 10626 38763 35317
10432 E01010740 Bradford 5083 10910 41335 35865
10433 E01010741 Bradford 9746 14274 7392 26408
10434 E01010742 Bradford 1730 16274 41511 37209
10435 E01010743 Bradford 1193 6824 41571 36534
10436 E01010744 Bradford 1507 12378 41644 35865
10437 E01010745 Bradford 2508 15171 41110 36208
10438 E01010746 Bradford 12605 28140 34069 34972
10439 E01010747 Bradford 6375 8789 37638 35530
10440 E01010748 Bradford 1545 11798 16254 32126
10441 E01010749 Bradford 3799 4784 31498 31552
10442 E01010750 Bradford 11599 24742 27391 31340
10443 E01010751 Bradford 7722 21652 7583 29843
10444 E01010752 Bradford 6179 7200 34947 20056
10445 E01010753 Bradford 20132 10331 39465 17106
10446 E01010754 Bradford 15713 13136 38009 16543
10447 E01010755 Bradford 1871 14749 14648 21987
10448 E01010756 Bradford 11597 12134 29472 19686
10449 E01010758 Bradford 25004 22896 39069 17285
10450 E01010759 Bradford 5854 7917 38348 19249
10451 E01010760 Bradford 21506 22430 38912 18678
10452 E01010761 Bradford 7891 10024 11015 22258
10453 E01010762 Bradford 7634 16104 21875 22598
10454 E01010763 Bradford 7743 13923 16145 20957
10455 E01010764 Bradford 27838 35817 10555 10225
10456 E01010765 Bradford 18003 26924 4578 11584
10457 E01010766 Bradford 32445 29556 30748 14305
10458 E01010767 Bradford 22388 28881 12292 7591
10459 E01010768 Bradford 32103 30229 15054 6942
10460 E01010769 Bradford 26788 26532 20571 8346
10461 E01010770 Bradford 30751 35371 9310 6938
10462 E01010771 Bradford 31937 32489 10363 8852
10463 E01010772 Bradford 30998 26989 17003 8794
10464 E01010773 Bradford 30840 14372 32412 10773
10465 E01010774 Bradford 29347 26245 30419 7859
10466 E01010775 Bradford 20451 28820 40336 28717
10467 E01010776 Bradford 4506 20481 11032 29977
10468 E01010777 Bradford 363 9716 11817 24011
10469 E01010778 Bradford 4807 23225 22146 31733
10470 E01010779 Bradford 4351 12823 12252 26921
10471 E01010781 Bradford 7398 22661 11244 26125
10472 E01010782 Bradford 1647 7361 21847 25026
10473 E01010783 Bradford 11376 31418 38707 27322
10474 E01010784 Bradford 8175 1722 6156 17902
10475 E01010785 Bradford 19785 2500 15670 21936
10476 E01010786 Bradford 17258 16994 6835 19062
10477 E01010787 Bradford 18864 2482 22398 23692
10478 E01010788 Bradford 14992 490 24928 20943
10479 E01010789 Bradford 6934 260 32568 23385
10480 E01010790 Bradford 23912 24502 9949 18552
10481 E01010791 Bradford 8078 7215 19621 26202
10482 E01010792 Bradford 3908 12385 26478 28978
10483 E01010793 Bradford 6952 12078 16029 28978
10484 E01010794 Bradford 7713 29029 10435 17404
10485 E01010795 Bradford 11166 25245 20836 11540
10486 E01010796 Bradford 5816 22097 12805 15205
10487 E01010797 Bradford 18284 32758 10752 12660
10488 E01010798 Bradford 9927 10621 31306 13594
10489 E01010799 Bradford 5697 29648 20170 14300
10490 E01010800 Bradford 314 18573 6483 17029
10491 E01010801 Bradford 8207 18164 9688 17029
10492 E01010802 Bradford 2637 26343 14596 14368
10493 E01010803 Bradford 1465 918 38295 28423
10494 E01010804 Bradford 5489 2095 30747 28477
10495 E01010805 Bradford 6337 24175 9402 22911
10496 E01010806 Bradford 4339 12601 24921 28194
10497 E01010807 Bradford 2400 4927 34866 28761
10498 E01010808 Bradford 2721 7576 38558 28851
10499 E01010809 Bradford 2328 3843 39760 28947
10500 E01010810 Bradford 7215 7767 31296 27981
10501 E01010811 Bradford 2752 2146 39140 28725
10502 E01010812 Bradford 1307 3688 36780 28851
10503 E01010813 Bradford 1186 799 39892 28423
10504 E01010814 Bradford 2956 16786 41699 30017
10505 E01010815 Bradford 5105 20049 41592 32831
10506 E01010816 Bradford 16635 32156 40843 28792
10507 E01010817 Bradford 3055 23066 40463 34682
10508 E01010818 Bradford 15685 32089 39607 34055
10509 E01010819 Bradford 83 21840 37809 33586
10510 E01010820 Bradford 171 22169 35399 32602
10511 E01010821 Bradford 1340 27516 37530 32602
10512 E01010822 Bradford 350 22094 37610 33498
10513 E01010824 Bradford 768 19817 20316 34276
10514 E01010825 Bradford 9028 18538 40124 36170
10515 E01010826 Bradford 805 30918 36197 34925
10516 E01010827 Bradford 6642 14212 40217 36170
10517 E01010828 Bradford 2952 5237 40804 35586
10518 E01010829 Bradford 2499 9198 40101 34880
10519 E01010830 Bradford 1716 8737 39418 35042
10520 E01010831 Bradford 2069 10898 41035 35687
10521 E01010832 Bradford 2728 12904 40902 36453
10522 E01010833 Bradford 1729 10590 41357 32686
10523 E01010834 Bradford 7117 5592 41674 36308
10524 E01010835 Bradford 7079 2026 41588 35189
10525 E01010836 Bradford 5985 3629 41604 35189
10526 E01010837 Bradford 3336 15724 41344 34354
10527 E01010838 Bradford 1650 5116 41314 34894
10528 E01010839 Bradford 1495 2723 41123 35213
10529 E01010840 Bradford 726 480 32055 32587
10530 E01010841 Bradford 878 733 34033 35002
10531 E01010842 Bradford 643 5857 39487 34506
10532 E01010843 Bradford 738 4673 37433 32054
10533 E01010845 Bradford 1088 18112 15656 24189
10534 E01010846 Bradford 7793 15784 22677 25653
10535 E01010847 Bradford 8624 5404 37278 30423
10536 E01010848 Bradford 9366 6313 34051 25932
10537 E01010849 Bradford 12024 10228 20350 26391
10538 E01010850 Bradford 357 16324 20263 22870
10539 E01010851 Bradford 9787 13696 23807 24469
10540 E01010852 Bradford 4806 13968 38024 34205
10541 E01010853 Bradford 12093 16468 34862 32868
10542 E01010854 Bradford 12588 26782 27245 8633
10543 E01010855 Bradford 13036 37719 1782 4455
10544 E01010856 Bradford 9677 22989 28380 5564
10545 E01010857 Bradford 15021 30108 4071 5530
10546 E01010858 Bradford 20896 13062 9640 5634
10547 E01010859 Bradford 22736 20614 27117 7135
10548 E01010860 Bradford 22022 25308 3856 5088
10549 E01010861 Bradford 24344 32613 21389 8974
10550 E01010862 Bradford 23732 30185 22199 5805
10551 E01010863 Bradford 25369 25179 7320 7047
10552 E01010864 Bradford 4756 18415 7168 22421
10553 E01010865 Bradford 11215 33214 36505 32578
10554 E01010866 Bradford 11551 23980 33962 25811
10555 E01010867 Bradford 8448 22226 3630 22855
10556 E01010868 Bradford 1391 20890 20868 23279
10557 E01010869 Bradford 5476 9794 30062 24091
10558 E01010870 Bradford 16340 16989 22003 27280
10559 E01010871 Bradford 5356 7714 32675 26079
10560 E01010872 Bradford 1533 16754 13381 26910
10561 E01010873 Bradford 16321 13777 25674 25537
10562 E01010874 Bradford 2337 20084 13544 22358
10563 E01010875 Calderdale 29263 27419 20650 32679
10564 E01010876 Calderdale 22283 14859 10940 32516
10565 E01010877 Calderdale 9102 14243 11393 35146
10566 E01010878 Calderdale 9946 4623 13851 32655
10567 E01010879 Calderdale 20304 28160 11491 33008
10568 E01010880 Calderdale 2811 24093 9705 32906
10569 E01010881 Calderdale 19934 25889 4349 8509
10570 E01010882 Calderdale 16396 31987 1220 7397
10571 E01010883 Calderdale 17979 37492 8923 6615
10572 E01010884 Calderdale 10349 29626 673 8632
10573 E01010885 Calderdale 17892 35871 3566 7229
10574 E01010886 Calderdale 11907 37782 338 7911
10575 E01010887 Calderdale 20477 37135 6194 5260
10576 E01010888 Calderdale 14403 4229 6998 7539
10577 E01010889 Calderdale 4089 3424 15738 23691
10578 E01010890 Calderdale 11126 19899 25777 30207
10579 E01010891 Calderdale 4601 17093 10304 36759
10580 E01010892 Calderdale 22541 28624 23519 34965
10581 E01010893 Calderdale 9901 4345 22917 21146
10582 E01010894 Calderdale 3768 2548 32229 28507
10583 E01010895 Calderdale 6587 13742 12138 37838
10584 E01010896 Calderdale 22643 36226 6117 17753
10585 E01010897 Calderdale 20055 34838 3262 14469
10586 E01010898 Calderdale 11216 4021 23621 18858
10587 E01010899 Calderdale 22163 25233 27949 15554
10588 E01010900 Calderdale 28998 24672 20065 14852
10589 E01010901 Calderdale 20663 29121 31341 22209
10590 E01010902 Calderdale 10575 28732 18069 15676
10591 E01010903 Calderdale 16225 27222 24748 18336
10592 E01010904 Calderdale 26081 30785 29021 28720
10593 E01010905 Calderdale 22413 30370 3107 28485
10594 E01010906 Calderdale 30314 18419 12089 27950
10595 E01010907 Calderdale 23118 19539 12169 24704
10596 E01010908 Calderdale 18619 8213 11641 30229
10597 E01010909 Calderdale 18262 14450 22981 28074
10598 E01010910 Calderdale 5813 22063 13159 32187
10599 E01010911 Calderdale 18524 29636 10344 9090
10600 E01010912 Calderdale 6079 13215 28820 13616
10601 E01010913 Calderdale 23135 25210 34802 15006
10602 E01010914 Calderdale 8827 10690 25339 12440
10603 E01010915 Calderdale 18947 25481 32142 15392
10604 E01010916 Calderdale 3337 13909 25738 14173
10605 E01010917 Calderdale 20190 27030 4810 9442
10606 E01010918 Calderdale 19301 36833 1074 7313
10607 E01010919 Calderdale 9457 20273 4568 10094
10608 E01010920 Calderdale 18342 37376 1578 9004
10609 E01010921 Calderdale 12319 34577 8810 10323
10610 E01010922 Calderdale 16896 33647 1117 10964
10611 E01010923 Calderdale 12584 3492 2382 6880
10612 E01010924 Calderdale 1284 21519 8172 13500
10613 E01010925 Calderdale 2112 25999 3066 9591
10614 E01010926 Calderdale 494 33047 8376 11171
10615 E01010927 Calderdale 16996 33253 11850 12572
10616 E01010928 Calderdale 2321 15521 7111 12843
10617 E01010929 Calderdale 4571 11137 15776 18412
10618 E01010930 Calderdale 4010 5744 6240 17227
10619 E01010931 Calderdale 20572 26946 28153 21648
10620 E01010932 Calderdale 19002 10019 22384 21736
10621 E01010933 Calderdale 17184 29269 28719 22234
10622 E01010934 Calderdale 13457 27631 29848 27295
10623 E01010935 Calderdale 24681 34977 37981 24394
10624 E01010936 Calderdale 29948 35308 23904 22275
10625 E01010937 Calderdale 23397 34544 24441 27894
10626 E01010938 Calderdale 1039 21855 28954 24400
10627 E01010939 Calderdale 16387 19623 14829 18652
10628 E01010940 Calderdale 4725 15590 39211 20201
10629 E01010941 Calderdale 1467 12866 25983 15047
10630 E01010942 Calderdale 3504 1741 39011 18672
10631 E01010943 Calderdale 977 14423 29706 21498
10632 E01010944 Calderdale 1078 10616 23731 17577
10633 E01010945 Calderdale 15081 9774 11243 33551
10634 E01010946 Calderdale 32486 19928 9743 29906
10635 E01010947 Calderdale 30601 26226 16394 32163
10636 E01010948 Calderdale 15643 15673 28845 30631
10637 E01010949 Calderdale 7439 6378 15874 32930
10638 E01010950 Calderdale 6614 13052 13856 33314
10639 E01010951 Calderdale 12858 11098 16792 33477
10640 E01010952 Calderdale 19816 15147 311 8827
10641 E01010953 Calderdale 27945 36642 2304 12875
10642 E01010954 Calderdale 27381 31936 1392 10476
10643 E01010955 Calderdale 19324 37635 2498 11031
10644 E01010956 Calderdale 17395 35568 2041 8548
10645 E01010957 Calderdale 17422 31111 1502 11614
10646 E01010958 Calderdale 2586 31173 12810 9608
10647 E01010959 Calderdale 8106 21929 7405 10293
10648 E01010960 Calderdale 1095 14917 36827 29492
10649 E01010961 Calderdale 3514 26353 38508 27460
10650 E01010964 Calderdale 212 11781 35149 27529
10651 E01010965 Calderdale 550 3433 39691 32663
10652 E01010966 Calderdale 1425 4953 38215 28025
10653 E01010967 Calderdale 1623 9765 39072 25683
10654 E01010968 Calderdale 21244 10832 26460 23280
10655 E01010969 Calderdale 18647 9115 34823 23280
10656 E01010970 Calderdale 14330 15352 15860 21196
10657 E01010971 Calderdale 24186 15405 15939 17331
10658 E01010972 Calderdale 20348 16915 23136 18395
10659 E01010973 Calderdale 24438 23241 1981 15488
10660 E01010974 Calderdale 5329 1383 37580 28547
10661 E01010975 Calderdale 18131 25055 11456 17286
10662 E01010976 Calderdale 20701 21310 9057 15651
10663 E01010977 Calderdale 22656 25357 15425 16423
10664 E01010978 Calderdale 11174 16789 16156 13470
10665 E01010979 Calderdale 5666 4429 13969 12832
10666 E01010980 Calderdale 7825 13626 20511 16088
10667 E01010981 Calderdale 7776 12418 3624 15361
10668 E01010982 Calderdale 10598 14271 7464 11677
10669 E01010983 Calderdale 5312 4616 31589 11099
10670 E01010984 Calderdale 9682 13078 27385 11658
10671 E01010985 Calderdale 10308 32464 4505 7425
10672 E01010986 Calderdale 6582 38310 30662 6207
10673 E01010987 Calderdale 9176 34011 24256 8308
10674 E01010988 Calderdale 4269 30389 10234 7668
10675 E01010989 Calderdale 11007 12867 36263 28344
10676 E01010990 Calderdale 14164 32529 33441 31767
10677 E01010991 Calderdale 15794 31035 23685 30699
10678 E01010992 Calderdale 12751 20992 28340 23278
10679 E01010993 Calderdale 5454 20068 7406 21033
10680 E01010994 Calderdale 1974 440 41615 33856
10681 E01010995 Calderdale 1094 5946 38554 32663
10682 E01010996 Calderdale 3080 6772 38750 28547
10683 E01010997 Calderdale 22629 29986 6317 13812
10684 E01010998 Calderdale 7420 12893 25208 19372
10685 E01010999 Calderdale 19208 17957 22266 15016
10686 E01011000 Calderdale 5049 6289 31245 22315
10687 E01011001 Calderdale 2359 10489 38865 22315
10688 E01011002 Calderdale 5309 8566 35652 23537
10689 E01011003 Calderdale 1414 11894 40000 28547
10690 E01011004 Kirklees 1757 21038 4792 20131
10691 E01011005 Kirklees 19194 23736 5324 16388
10692 E01011006 Kirklees 14114 13518 23205 19827
10693 E01011007 Kirklees 15682 13608 23224 19920
10694 E01011008 Kirklees 10954 6156 37671 20792
10695 E01011009 Kirklees 14881 23451 11294 14994
10696 E01011010 Kirklees 4447 21144 16964 18695
10697 E01011011 Kirklees 28258 28267 9041 14317
10698 E01011012 Kirklees 16888 8872 30557 22905
10699 E01011013 Kirklees 20042 32891 38232 31112
10700 E01011014 Kirklees 6471 3386 39195 34312
10701 E01011015 Kirklees 3300 5193 41423 34083
10702 E01011016 Kirklees 5497 6820 35494 34246
10703 E01011017 Kirklees 4899 4135 41029 33896
10704 E01011018 Kirklees 6508 8407 33101 33857
10705 E01011019 Kirklees 12774 10081 39475 35110
10706 E01011020 Kirklees 5771 10117 21598 33857
10707 E01011021 Kirklees 22501 26590 37241 33115
10708 E01011022 Kirklees 15266 26228 33588 35110
10709 E01011023 Kirklees 7873 5167 38637 33264
10710 E01011024 Kirklees 5523 13836 31754 33454
10711 E01011025 Kirklees 2316 16612 20558 30716
10712 E01011026 Kirklees 13179 11039 35429 31420
10713 E01011027 Kirklees 6205 21928 40365 32812
10714 E01011028 Kirklees 6030 19258 40550 33250
10715 E01011029 Kirklees 1146 2838 38358 33517
10716 E01011030 Kirklees 3258 22597 40313 33054
10717 E01011031 Kirklees 12765 18221 40298 33508
10718 E01011032 Kirklees 2617 15516 38158 34003
10719 E01011033 Kirklees 9227 21792 40117 34245
10720 E01011034 Kirklees 3803 12231 39464 33496
10721 E01011035 Kirklees 7280 12537 34375 33329
10722 E01011036 Kirklees 2661 15929 30250 34422
10723 E01011037 Kirklees 7997 19657 39713 31595
10724 E01011038 Kirklees 1091 9243 20828 33412
10725 E01011039 Kirklees 9130 15671 17453 28042
10726 E01011040 Kirklees 6109 4921 32670 29112
10727 E01011041 Kirklees 4005 9481 19510 32508
10728 E01011042 Kirklees 19500 11599 21722 27532
10729 E01011043 Kirklees 5947 8030 35907 31705
10730 E01011044 Kirklees 11700 5939 33805 28106
10731 E01011045 Kirklees 1926 1066 34237 34191
10732 E01011046 Kirklees 26951 31674 19938 27359
10733 E01011047 Kirklees 24752 30678 18829 29270
10734 E01011048 Kirklees 7275 3167 41694 28820
10735 E01011049 Kirklees 9379 15301 38741 31566
10736 E01011050 Kirklees 22624 21374 41570 31412
10737 E01011051 Kirklees 22924 31658 40789 31174
10738 E01011052 Kirklees 10294 25758 41202 32082
10739 E01011053 Kirklees 19462 10970 41498 31135
10740 E01011054 Kirklees 22864 23164 39334 31066
10741 E01011055 Kirklees 21568 32690 37892 31075
10742 E01011056 Kirklees 25255 26998 40079 32107
10743 E01011057 Kirklees 18920 26515 36362 32297
10744 E01011058 Kirklees 15268 28403 40884 32627
10745 E01011059 Kirklees 1720 23575 40377 30767
10746 E01011060 Kirklees 6283 15901 38047 32975
10747 E01011061 Kirklees 4528 1910 41158 33571
10748 E01011062 Kirklees 17666 31248 36301 31303
10749 E01011063 Kirklees 14676 1395 41627 31756
10750 E01011064 Kirklees 6696 31278 30824 29587
10751 E01011065 Kirklees 13276 13974 41088 31555
10752 E01011066 Kirklees 26112 10446 40547 31296
10753 E01011067 Kirklees 19803 27148 35856 31156
10754 E01011068 Kirklees 19366 32672 34225 32455
10755 E01011069 Kirklees 19870 26718 33017 28636
10756 E01011070 Kirklees 18464 23848 90 11738
10757 E01011071 Kirklees 17762 32975 3194 11832
10758 E01011072 Kirklees 20007 30923 6726 13607
10759 E01011073 Kirklees 10245 11991 5431 13182
10760 E01011074 Kirklees 17393 34178 5821 11125
10761 E01011075 Kirklees 11667 35091 1219 10883
10762 E01011076 Kirklees 17105 35348 1349 10991
10763 E01011077 Kirklees 12793 27188 3398 15575
10764 E01011078 Kirklees 15691 14367 13484 13344
10765 E01011079 Kirklees 3970 5775 16954 18462
10766 E01011080 Kirklees 3006 10116 18763 20991
10767 E01011081 Kirklees 1917 2514 14430 18269
10768 E01011082 Kirklees 2953 979 23859 29563
10769 E01011083 Kirklees 16748 29802 22342 16170
10770 E01011084 Kirklees 2319 15518 9818 18269
10771 E01011085 Kirklees 7391 27808 10816 15886
10772 E01011086 Kirklees 27084 30707 12890 13600
10773 E01011087 Kirklees 9645 14284 8887 13475
10774 E01011088 Kirklees 30789 17523 5833 14284
10775 E01011089 Kirklees 14688 35941 23424 27054
10776 E01011090 Kirklees 9014 21960 19214 31078
10777 E01011091 Kirklees 25308 35688 23242 27639
10778 E01011092 Kirklees 26289 34483 18627 24761
10779 E01011093 Kirklees 1717 20246 7681 34961
10780 E01011094 Kirklees 1210 20346 13347 35503
10781 E01011095 Kirklees 15762 9566 24984 27493
10782 E01011096 Kirklees 13525 9975 34241 30399
10783 E01011097 Kirklees 7956 8362 29130 30399
10784 E01011098 Kirklees 9283 3532 35353 30519
10785 E01011099 Kirklees 13229 7513 24270 28981
10786 E01011100 Kirklees 7279 23656 3490 32115
10787 E01011101 Kirklees 2062 20978 9888 34195
10788 E01011102 Kirklees 21724 28458 16594 31533
10789 E01011103 Kirklees 5034 25310 3159 33401
10790 E01011104 Kirklees 4891 18660 5451 33103
10791 E01011105 Kirklees 6758 16596 33762 30287
10792 E01011106 Kirklees 910 30086 17583 33798
10793 E01011107 Kirklees 2928 1479 39640 32526
10794 E01011108 Kirklees 16094 27320 7566 32398
10795 E01011109 Kirklees 26106 29478 33007 13744
10796 E01011110 Kirklees 18858 22831 20374 11342
10797 E01011111 Kirklees 23142 30842 31559 12542
10798 E01011112 Kirklees 22402 30921 24111 11900
10799 E01011113 Kirklees 29963 12480 39422 13302
10800 E01011114 Kirklees 12339 19569 33108 13361
10801 E01011115 Kirklees 24964 35887 23628 9923
10802 E01011116 Kirklees 27969 31567 27230 12509
10803 E01011117 Kirklees 27360 36331 28014 10551
10804 E01011118 Kirklees 27503 35270 14487 11767
10805 E01011119 Kirklees 21716 38700 28665 16339
10806 E01011120 Kirklees 31556 33871 12814 11638
10807 E01011121 Kirklees 4489 27655 27895 26995
10808 E01011122 Kirklees 1523 27863 28363 27197
10809 E01011123 Kirklees 5937 18870 14751 33146
10810 E01011124 Kirklees 15769 33752 8725 27021
10811 E01011125 Kirklees 7281 28093 26464 31396
10812 E01011126 Kirklees 3368 28213 37769 31160
10813 E01011127 Kirklees 17502 26576 37574 33353
10814 E01011128 Kirklees 5941 8224 31397 33802
10815 E01011129 Kirklees 12591 20768 27869 32292
10816 E01011130 Kirklees 1438 1263 37174 32593
10817 E01011132 Kirklees 31594 22342 4649 22409
10818 E01011133 Kirklees 3222 17178 7073 24390
10819 E01011134 Kirklees 2358 14044 21053 26023
10820 E01011136 Kirklees 5262 19896 26029 30432
10821 E01011137 Kirklees 5477 21728 22832 29909
10822 E01011138 Kirklees 914 7609 13745 29635
10823 E01011139 Kirklees 5942 24826 16775 26628
10824 E01011140 Kirklees 661 24744 9245 28937
10825 E01011141 Kirklees 5865 20410 15886 30068
10826 E01011142 Kirklees 19185 26585 14568 25707
10827 E01011143 Kirklees 2962 17128 22505 26023
10828 E01011144 Kirklees 2154 14237 32283 24970
10829 E01011145 Kirklees 21077 19356 17848 17474
10830 E01011146 Kirklees 26412 15207 25266 17595
10831 E01011147 Kirklees 14180 20748 7281 19829
10832 E01011148 Kirklees 1366 18648 3671 20535
10833 E01011149 Kirklees 4243 7090 20087 21944
10834 E01011150 Kirklees 12403 22009 11635 24838
10835 E01011151 Kirklees 25902 36195 4018 17024
10836 E01011152 Kirklees 19864 26862 5200 15587
10837 E01011153 Kirklees 9762 10912 14753 20693
10838 E01011154 Kirklees 9774 27141 12426 16060
10839 E01011155 Kirklees 19476 26505 12652 20508
10840 E01011156 Kirklees 17159 28327 30833 28936
10841 E01011157 Kirklees 6516 19584 40438 33918
10842 E01011158 Kirklees 12533 11012 41394 30108
10843 E01011159 Kirklees 22184 35663 20537 30687
10844 E01011160 Kirklees 26725 30293 34354 28449
10845 E01011161 Kirklees 15263 20439 36413 30421
10846 E01011162 Kirklees 21007 34163 35574 26634
10847 E01011163 Kirklees 3102 16490 36880 34772
10848 E01011164 Kirklees 15309 20113 39749 32581
10849 E01011165 Kirklees 10170 16239 40591 34310
10850 E01011166 Kirklees 5588 5999 41037 33490
10851 E01011167 Kirklees 3354 9231 40783 33988
10852 E01011168 Kirklees 27056 22966 18561 8257
10853 E01011169 Kirklees 25267 27006 5376 12795
10854 E01011170 Kirklees 25724 19753 9565 11519
10855 E01011171 Kirklees 24736 6868 8362 12205
10856 E01011172 Kirklees 9139 9911 20584 11143
10857 E01011173 Kirklees 30278 20770 19051 11678
10858 E01011174 Kirklees 24967 32591 7083 8773
10859 E01011175 Kirklees 7955 24209 14134 11006
10860 E01011176 Kirklees 22765 33764 4314 13135
10861 E01011177 Kirklees 26876 28725 2569 10401
10862 E01011178 Kirklees 15869 12380 27030 10678
10863 E01011179 Kirklees 29565 36130 15933 8547
10864 E01011180 Kirklees 27915 30728 3981 7804
10865 E01011181 Kirklees 23827 11763 11739 8654
10866 E01011182 Kirklees 17049 35940 1128 7040
10867 E01011183 Kirklees 24700 36250 4538 6751
10868 E01011184 Kirklees 12946 27211 9386 12046
10869 E01011185 Kirklees 24399 28940 18681 12466
10870 E01011186 Kirklees 26563 23010 6666 11477
10871 E01011187 Kirklees 23025 25888 7437 14227
10872 E01011188 Kirklees 19850 19464 5407 9514
10873 E01011189 Kirklees 28681 30522 7623 10544
10874 E01011190 Kirklees 29905 30940 1595 13098
10875 E01011191 Kirklees 24759 13999 19899 15898
10876 E01011192 Kirklees 12230 30031 9885 18326
10877 E01011193 Kirklees 22931 38430 30923 15249
10878 E01011194 Kirklees 28853 20396 11637 15798
10879 E01011195 Kirklees 24335 37400 17564 12366
10880 E01011196 Kirklees 31288 29282 16783 12002
10881 E01011197 Kirklees 14029 32184 7855 13244
10882 E01011198 Kirklees 30498 28078 16060 11296
10883 E01011199 Kirklees 27366 13473 28084 10933
10884 E01011200 Kirklees 24391 26071 11207 22248
10885 E01011201 Kirklees 12926 6284 38595 28433
10886 E01011202 Kirklees 13855 9872 27122 22477
10887 E01011203 Kirklees 25976 20441 37818 24758
10888 E01011204 Kirklees 26102 9817 18794 28432
10889 E01011205 Kirklees 26242 34257 22402 18977
10890 E01011206 Kirklees 11508 19271 34768 28433
10891 E01011207 Kirklees 24616 23216 25634 23557
10892 E01011208 Kirklees 12159 5172 40197 28433
10893 E01011209 Kirklees 25320 26227 36371 24477
10894 E01011210 Kirklees 24157 18150 31851 27862
10895 E01011211 Kirklees 24133 12387 32909 23981
10896 E01011212 Kirklees 7938 7993 10984 20997
10897 E01011213 Kirklees 30977 17485 9352 21685
10898 E01011214 Kirklees 17983 35637 11170 21697
10899 E01011215 Kirklees 16403 14468 9147 20286
10900 E01011216 Kirklees 24655 29615 6780 26250
10901 E01011217 Kirklees 25831 27488 35886 27037
10902 E01011218 Kirklees 12430 21286 22319 24319
10903 E01011219 Kirklees 25385 20909 8457 24152
10904 E01011220 Kirklees 3770 22483 14370 24944
10905 E01011221 Kirklees 28216 18418 25222 23350
10906 E01011222 Kirklees 4990 26978 2400 15952
10907 E01011223 Kirklees 4405 23396 8841 16332
10908 E01011224 Kirklees 3920 22626 3682 19225
10909 E01011225 Kirklees 7305 24232 2981 16636
10910 E01011226 Kirklees 14889 27555 4228 15665
10911 E01011227 Kirklees 2282 24230 4576 16796
10912 E01011228 Kirklees 13295 30278 5489 15086
10913 E01011229 Kirklees 9558 8523 21502 24766
10914 E01011230 Kirklees 5287 3014 16303 26714
10915 E01011231 Kirklees 11570 68 29471 29800
10916 E01011232 Kirklees 3596 4014 18390 30026
10917 E01011233 Kirklees 12680 5873 19785 28728
10918 E01011234 Kirklees 5567 24811 15909 26551
10919 E01011235 Kirklees 3074 4651 16253 26759
10920 E01011236 Kirklees 4175 376 34890 32888
10921 E01011237 Kirklees 3433 12587 17552 26464
10922 E01011238 Kirklees 9906 6529 17435 31162
10923 E01011239 Kirklees 14042 674 32400 31107
10924 E01011240 Kirklees 8085 5310 33323 27028
10925 E01011241 Kirklees 27152 27983 33525 30386
10926 E01011242 Kirklees 8102 24765 32605 33098
10927 E01011243 Kirklees 22858 17183 40747 30840
10928 E01011244 Kirklees 24339 24758 41079 32929
10929 E01011245 Kirklees 7932 24349 36216 31779
10930 E01011246 Kirklees 4634 18049 29611 33490
10931 E01011247 Kirklees 20223 28544 35307 30198
10932 E01011248 Kirklees 14599 22355 37786 30027
10933 E01011249 Kirklees 7089 34821 35018 30925
10934 E01011250 Kirklees 4039 19527 41250 33229
10935 E01011251 Kirklees 3593 35077 31890 31886
10936 E01011252 Kirklees 22749 36799 11825 18077
10937 E01011253 Kirklees 3846 20005 19572 16999
10938 E01011254 Kirklees 24189 21120 17912 20034
10939 E01011255 Kirklees 2303 24056 19390 19424
10940 E01011256 Kirklees 6389 26964 17074 19197
10941 E01011257 Kirklees 7720 4305 20793 27778
10942 E01011258 Kirklees 9433 4253 18908 26285
10943 E01011259 Kirklees 4220 16772 10614 26337
10944 E01011260 Kirklees 7145 30483 20032 25465
10945 E01011261 Kirklees 6863 13106 11210 26285
10946 E01011262 Kirklees 4354 15452 4215 26337
10947 E01011263 Kirklees 11351 20788 2889 22757
10948 E01011264 Leeds 13915 8408 5887 20931
10949 E01011265 Leeds 20368 3551 39054 16168
10950 E01011266 Leeds 29666 29719 33158 11778
10951 E01011267 Leeds 9111 11613 19615 16917
10952 E01011268 Leeds 6082 13583 13298 16917
10953 E01011269 Leeds 13768 5019 15809 23135
10954 E01011270 Leeds 31787 28422 8998 10040
10955 E01011271 Leeds 29068 5279 30310 15720
10956 E01011272 Leeds 29185 17229 30157 15406
10957 E01011273 Leeds 19375 5641 26147 17421
10958 E01011274 Leeds 5701 997 17717 22050
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11439 E01011791 Wakefield 2772 28206 18050 18532
11440 E01011792 Wakefield 230 22612 6202 20818
11441 E01011793 Wakefield 14068 31199 34390 25948
11442 E01011794 Wakefield 9955 28909 30691 24225
11443 E01011795 Wakefield 11204 25097 33822 25948
11444 E01011796 Wakefield 23765 28095 28762 19813
11445 E01011797 Wakefield 31200 15440 19157 25890
11446 E01011798 Wakefield 15167 2644 25735 18622
11447 E01011799 Wakefield 13125 7604 17108 22871
11448 E01011800 Wakefield 23138 25745 5070 19585
11449 E01011801 Wakefield 12710 17389 12825 21727
11450 E01011802 Wakefield 17370 1127 18697 19198
11451 E01011803 Wakefield 1468 28891 27100 31494
11452 E01011804 Wakefield 9611 34723 17266 29650
11453 E01011805 Wakefield 3853 19806 1752 33452
11454 E01011806 Wakefield 8833 25897 17033 31603
11455 E01011807 Wakefield 5749 14951 6742 34243
11456 E01011808 Wakefield 11678 15055 9403 33545
11457 E01011809 Wakefield 6390 22633 8605 33545
11458 E01011810 Wakefield 10356 34055 20939 32308
11459 E01011811 Wakefield 692 22239 16194 34143
11460 E01011812 Wakefield 29285 33363 36915 20877
11461 E01011813 Wakefield 3473 28137 33622 21432
11462 E01011814 Wakefield 4226 10829 29478 22303
11463 E01011815 Wakefield 3862 36316 17239 22525
11464 E01011816 Wakefield 2726 29515 33719 22282
11465 E01011817 Wakefield 7696 24946 8536 20118
11466 E01011818 Wakefield 15022 27905 5704 17369
11467 E01011819 Wakefield 13857 2805 40505 23889
11468 E01011820 Wakefield 14644 10611 39763 24082
11469 E01011821 Wakefield 13789 13829 35412 23597
11470 E01011822 Wakefield 8959 12661 39372 21981
11471 E01011823 Wakefield 13089 31778 38298 29866
11472 E01011824 Wakefield 6759 27585 37845 29098
11473 E01011825 Wakefield 22259 19126 39904 29393
11474 E01011826 Wakefield 24232 21072 37411 26113
11475 E01011827 Wakefield 19617 24040 35596 30643
11476 E01011828 Wakefield 19711 8824 39438 26397
11477 E01011829 Wakefield 21909 23262 29857 21443
11478 E01011830 Wakefield 15541 8687 36669 22799
11479 E01011831 Wakefield 12059 10416 35409 25057
11480 E01011832 Wakefield 10572 20256 30606 21425
11481 E01011833 Wakefield 18749 19163 26442 25184
11482 E01011834 Wakefield 10986 24146 29549 26472
11483 E01011835 Wakefield 19087 29341 36710 27231
11484 E01011836 Wakefield 14783 22649 36907 27111
11485 E01011837 Wakefield 6231 2472 41121 24899
11486 E01011838 Wakefield 2100 573 30031 25624
11487 E01011839 Wakefield 10898 29160 39179 26689
11488 E01011840 Wakefield 5460 8506 32720 24899
11489 E01011841 Wakefield 9646 14885 31537 25590
11490 E01011842 Wakefield 1063 16213 30239 24040
11491 E01011843 Wakefield 8746 32317 36881 29326
11492 E01011844 Wakefield 28765 32579 35146 27514
11493 E01011845 Wakefield 31061 29686 36472 22935
11494 E01011846 Wakefield 18228 18698 29399 23223
11495 E01011847 Wakefield 26996 22021 33898 23749
11496 E01011848 Wakefield 24161 25362 29738 22575
11497 E01011849 Wakefield 21151 38853 30083 24300
11498 E01011850 Wakefield 1884 13735 29316 22959
11499 E01011851 Wakefield 6310 12650 30362 23915
11500 E01011852 Wakefield 3378 34807 37140 22368
11501 E01011853 Wakefield 6102 16841 33566 22419
11502 E01011854 Wakefield 5465 37398 37766 23679
11503 E01011855 Wakefield 15595 35841 35778 22239
11504 E01011856 Wakefield 6029 37504 36705 24600
11505 E01011857 Wakefield 25944 38407 32617 20407
11506 E01011858 Wakefield 11479 36044 37475 22936
11507 E01011859 Wakefield 4147 16169 35541 21416
11508 E01011860 Wakefield 15716 13966 34525 22531
11509 E01011861 Wakefield 17380 10233 32626 20606
11510 E01011862 Wakefield 4599 13224 30903 20518
11511 E01011863 Wakefield 868 5452 32115 20970
11512 E01011864 Wakefield 2078 32765 15802 21437
11513 E01011865 Wakefield 2932 10247 28260 22643
11514 E01011866 Wakefield 3039 29761 22053 20300
11515 E01011867 Wakefield 4449 5529 24033 22601
11516 E01011868 Wakefield 6509 17332 15176 20794
11517 E01011869 Wakefield 2737 4635 37022 21476
11518 E01011870 Wakefield 12379 21251 27198 22193
11519 E01011871 Wakefield 8402 12390 9811 21180
11520 E01011872 Wakefield 4694 25469 25477 20296
11521 E01011873 Wakefield 24767 26351 32301 31307
11522 E01011874 Wakefield 27442 37655 23150 24423
11523 E01011875 Wakefield 7241 33115 15401 27896
11524 E01011876 Wakefield 10243 29447 13284 23372
11525 E01011877 Wakefield 13858 19046 17681 26128
11526 E01011878 Wakefield 22387 16600 19305 25953
11527 E01011879 Wakefield 19299 11446 37919 23313
11528 E01011880 Wakefield 26993 31312 13697 25342
11529 E01011881 Wakefield 17973 6613 31418 27251
11530 E01011882 Wakefield 24346 31046 27878 23308
11531 E01011883 Wakefield 17095 37959 30236 26002
11532 E01011884 Wakefield 24316 23408 30258 26645
11533 E01011885 Wakefield 18320 33316 38521 30770
11534 E01011886 Wakefield 25062 26880 40876 26170
11535 E01011887 Wakefield 26407 26158 40350 27400
11536 E01011888 Wakefield 30603 13691 40433 26170
11537 E01011889 Wakefield 22859 31795 38917 32770
11538 E01011890 Wakefield 20438 25804 38796 30306
11539 E01011891 Wakefield 12023 17986 36716 28417
11540 E01011892 Wakefield 13356 32102 37284 30306
11541 E01011893 Wakefield 23064 18960 28796 31602
11542 E01011894 Wakefield 29802 23103 19391 27058
11543 E01011895 Wakefield 20601 18552 13818 27565
11544 E01011896 Wakefield 13112 13846 31127 27836
11545 E01011897 Wakefield 7136 5380 22551 28076
11546 E01011898 Wakefield 10102 16319 5026 25766
11547 E01011899 Wakefield 1637 24596 26199 30546
11548 E01011900 Wakefield 4151 12638 31236 30170
11549 E01011901 Wakefield 2341 13425 21456 30582
11550 E01011902 Wakefield 13512 24214 19087 27563
11551 E01011903 Wakefield 8408 26952 31699 27090
11552 E01011904 Wakefield 2384 17641 27396 31000
11553 E01011905 Wakefield 26748 25293 26512 28319
11554 E01011906 Wakefield 1419 21748 1751 25130
11555 E01011907 Wakefield 6437 11139 38054 29039
11556 E01011908 Wakefield 9352 19760 11507 27342
11557 E01011909 Wakefield 10589 26167 24620 24568
11558 E01011910 Wakefield 1020 11357 7333 26659
11559 E01011911 Wakefield 2549 14870 3537 25567
11560 E01011912 Wakefield 3384 4154 35625 28760
11561 E01011913 Wakefield 4939 3449 34201 27645
11562 E01011914 Wakefield 4395 10899 5129 26005
11563 E01011915 Wakefield 6583 1134 10857 27645
11564 E01011916 Wakefield 1714 929 38881 28376
11565 E01011917 Wakefield 1267 29096 11036 27703
11566 E01011918 Wakefield 4145 23473 29805 31269
11567 E01011919 Wakefield 6477 6349 32624 29005
11568 E01011920 Wakefield 7274 1053 40691 28865
11569 E01011921 Wakefield 10521 21640 29772 30564
11570 E01011922 Wakefield 2498 26809 30462 30872
11571 E01011923 Wakefield 26587 10654 34962 28089
11572 E01011924 Wakefield 12988 22827 35401 28362
11573 E01011925 Wakefield 5770 14100 30935 29336
11574 E01011926 Wakefield 4129 8618 35426 28939
11575 E01011927 Wakefield 6444 24249 33666 31019
11576 E01011928 Wakefield 14218 26605 24886 16789
11577 E01011929 Wakefield 25644 32895 25128 22930
11578 E01011930 Wakefield 25820 33415 19091 21747
11579 E01011931 Wakefield 25101 22909 29064 16245
11580 E01011932 Wakefield 29729 25818 11882 17357
11581 E01011933 Wakefield 9967 36196 25712 20444
11582 E01011934 Wakefield 23279 33596 17573 20728
11583 E01011935 Wakefield 27479 38018 10186 17387
11584 E01011936 Wakefield 7843 36129 29599 19670
11585 E01011937 Wakefield 26907 35391 19758 26698
11586 E01011938 Wakefield 21332 28899 14790 16344
11587 E01011939 Wakefield 29389 35095 18037 23650
11588 E01011940 Wakefield 7091 11479 13320 25680
11589 E01011941 Wakefield 17701 37299 8976 15995
11590 E01011942 Wakefield 21018 37237 13540 17233
11591 E01011943 Wakefield 5554 27933 20059 26071
11592 E01011944 Wakefield 7908 28006 13995 20006
11593 E01011945 Wakefield 24421 22478 11728 19652
11594 E01011946 Wakefield 28593 36932 13592 17603
11595 E01011947 Wakefield 30170 33919 19500 18071
11596 E01011948 Wakefield 30393 34397 12840 19715
11597 E01011949 Hartlepool 4731 19599 37928 14217
11598 E01011950 Hartlepool 527 3416 41392 14500
11599 E01011951 Hartlepool 1663 4044 40421 13742
11600 E01011952 Hartlepool 3469 12367 31035 14273
11601 E01011953 Hartlepool 911 15093 31320 12119
11602 E01011954 Hartlepool 5729 23369 28806 11849
11603 E01011955 Hartlepool 848 8730 34617 13993
11604 E01011957 Hartlepool 4716 12072 39157 13418
11605 E01011959 Hartlepool 22123 39542 16103 11992
11606 E01011960 Hartlepool 23195 24560 41174 16640
11607 E01011961 Hartlepool 6362 17104 39330 16905
11608 E01011962 Hartlepool 2937 16254 41064 15774
11609 E01011963 Hartlepool 20655 5932 40359 18790
11610 E01011964 Hartlepool 5370 1749 40270 11746
11611 E01011965 Hartlepool 25734 20128 36576 12775
11612 E01011966 Hartlepool 9822 17516 39384 12311
11613 E01011967 Hartlepool 16405 8363 38683 12775
11614 E01011968 Hartlepool 14530 37886 13473 18247
11615 E01011969 Hartlepool 19743 20720 26310 10357
11616 E01011970 Hartlepool 25000 23468 32756 9657
11617 E01011971 Hartlepool 27780 28862 34309 10931
11618 E01011973 Hartlepool 155 1659 39765 13340
11619 E01011974 Hartlepool 3148 4238 40464 21613
11620 E01011975 Hartlepool 5988 10860 41241 12605
11621 E01011976 Hartlepool 831 6447 39188 12605
11622 E01011977 Hartlepool 1232 17334 38697 15509
11623 E01011978 Hartlepool 194 15743 39224 15495
11624 E01011979 Hartlepool 2486 17798 40702 15262
11625 E01011980 Hartlepool 1412 21501 41094 13803
11626 E01011981 Hartlepool 2437 22985 40330 13803
11627 E01011982 Hartlepool 28897 33894 31691 11405
11628 E01011983 Hartlepool 27613 27752 16535 11130
11629 E01011984 Hartlepool 19135 23780 38059 15239
11630 E01011985 Hartlepool 16014 15424 34055 15902
11631 E01011986 Hartlepool 8692 11005 37465 15069
11632 E01011987 Hartlepool 5780 2695 41131 15902
11633 E01011988 Hartlepool 8711 25344 37091 17499
11634 E01011989 Hartlepool 1451 28530 31148 20895
11635 E01011990 Hartlepool 10616 19456 36024 18790
11636 E01011991 Hartlepool 8618 20142 13468 16583
11637 E01011992 Hartlepool 571 16744 24381 17469
11638 E01011993 Hartlepool 2890 25048 12681 17316
11639 E01011994 Hartlepool 111 28561 11353 18868
11640 E01011995 Hartlepool 20642 11447 19762 27237
11641 E01011996 Hartlepool 15686 17916 14919 24637
11642 E01011997 Hartlepool 25228 23251 22753 24714
11643 E01011998 Hartlepool 19739 23295 24003 27129
11644 E01011999 Hartlepool 430 1283 41164 23366
11645 E01012000 Hartlepool 209 6530 32134 28528
11646 E01012001 Hartlepool 2395 3011 39451 24416
11647 E01012002 Hartlepool 10001 25783 38106 13418
11648 E01012003 Hartlepool 27990 30911 30430 10003
11649 E01012005 Hartlepool 30400 26109 11218 10769
11650 E01012007 Middlesbrough 20769 32852 36838 18168
11651 E01012008 Middlesbrough 22573 29939 32271 18581
11652 E01012009 Middlesbrough 24662 14587 31112 21391
11653 E01012010 Middlesbrough 25764 16115 25859 19380
11654 E01012011 Middlesbrough 869 7968 11716 25066
11655 E01012012 Middlesbrough 15306 14471 9541 21272
11656 E01012013 Middlesbrough 2568 13097 26748 26266
11657 E01012014 Middlesbrough 3285 20623 30869 28294
11658 E01012015 Middlesbrough 752 10230 40172 20011
11659 E01012016 Middlesbrough 598 18909 40660 20811
11660 E01012017 Middlesbrough 5788 7102 40406 20011
11661 E01012018 Middlesbrough 1659 9381 17814 21261
11662 E01012019 Middlesbrough 127 18897 24110 18332
11663 E01012020 Middlesbrough 2463 11020 29520 20066
11664 E01012021 Middlesbrough 888 19724 29574 18837
11665 E01012022 Middlesbrough 19123 33327 38302 20475
11666 E01012023 Middlesbrough 23575 19366 39520 16158
11667 E01012024 Middlesbrough 22602 19105 38675 19690
11668 E01012025 Middlesbrough 23859 22233 38178 18465
11669 E01012026 Middlesbrough 8503 17630 27567 25101
11670 E01012027 Middlesbrough 670 20471 16031 24868
11671 E01012030 Middlesbrough 23239 29711 35938 13088
11672 E01012031 Middlesbrough 4591 31610 19498 16215
11673 E01012032 Middlesbrough 23342 29262 39759 11116
11674 E01012033 Middlesbrough 931 22236 31078 12167
11675 E01012034 Middlesbrough 8473 35649 36797 11923
11676 E01012035 Middlesbrough 6921 24555 33283 15127
11677 E01012036 Middlesbrough 1022 3757 39343 27669
11678 E01012037 Middlesbrough 195 8061 39991 29625
11679 E01012038 Middlesbrough 1130 7583 40706 29625
11680 E01012039 Middlesbrough 1630 1825 38685 27669
11681 E01012040 Middlesbrough 502 4627 40687 29625
11682 E01012041 Middlesbrough 51 5263 33868 28791
11683 E01012042 Middlesbrough 4537 29868 1404 16614
11684 E01012043 Middlesbrough 12573 21515 17322 16487
11685 E01012044 Middlesbrough 376 32772 9589 14600
11686 E01012045 Middlesbrough 307 33198 12295 15193
11687 E01012046 Middlesbrough 15731 26612 38797 17784
11688 E01012047 Middlesbrough 22518 21738 19359 21861
11689 E01012048 Middlesbrough 26607 17519 31895 21724
11690 E01012049 Middlesbrough 18743 27311 37849 17861
11691 E01012050 Middlesbrough 2945 21230 34898 18721
11692 E01012051 Middlesbrough 3742 18467 36709 18933
11693 E01012052 Middlesbrough 13132 24301 35435 18134
11694 E01012053 Middlesbrough 21026 11397 26162 24506
11695 E01012054 Middlesbrough 15874 7820 22048 25815
11696 E01012055 Middlesbrough 18537 26075 26527 23201
11697 E01012056 Middlesbrough 10168 5506 32957 29462
11698 E01012057 Middlesbrough 8811 12174 26306 29398
11699 E01012058 Middlesbrough 47 10858 41321 24995
11700 E01012059 Middlesbrough 138 5446 40578 27199
11701 E01012060 Middlesbrough 220 18343 35811 25869
11702 E01012061 Middlesbrough 930 24702 32592 27317
11703 E01012062 Middlesbrough 20673 36648 36542 16705
11704 E01012063 Middlesbrough 27031 24218 36456 16473
11705 E01012064 Middlesbrough 20760 30988 36228 18181
11706 E01012065 Middlesbrough 26274 26256 32998 15317
11707 E01012066 Middlesbrough 27274 34224 20989 12070
11708 E01012067 Middlesbrough 24960 20875 37392 15300
11709 E01012068 Middlesbrough 2348 1403 40751 28511
11710 E01012071 Middlesbrough 31644 35192 19715 16014
11711 E01012073 Middlesbrough 26471 34360 30671 15506
11712 E01012074 Middlesbrough 2249 6845 35747 24284
11713 E01012075 Middlesbrough 329 8910 33536 22523
11714 E01012076 Middlesbrough 123 19195 27735 24903
11715 E01012077 Middlesbrough 856 21650 29348 24620
11716 E01012078 Middlesbrough 1292 69 38082 27506
11717 E01012079 Middlesbrough 9810 11491 24455 27395
11718 E01012080 Middlesbrough 5259 10993 10225 25434
11719 E01012081 Middlesbrough 4658 7596 33542 27395
11720 E01012082 Middlesbrough 1583 21226 38749 18639
11721 E01012083 Middlesbrough 733 14664 37102 22346
11722 E01012084 Middlesbrough 292 13453 37857 20876
11723 E01012085 Middlesbrough 412 20239 38540 18116
11724 E01012088 Middlesbrough 963 13149 29501 24872
11725 E01012089 Middlesbrough 109 5979 34090 23295
11726 E01012090 Middlesbrough 46 23522 35105 25093
11727 E01012091 Middlesbrough 149 20152 34096 21875
11728 E01012092 Middlesbrough 2051 1387 32110 25685
11729 E01012093 Middlesbrough 1594 2281 24968 25327
11730 E01012094 Middlesbrough 2979 6683 30927 24877
11731 E01012095 Redcar and Cleveland 23318 30495 21637 7317
11732 E01012096 Redcar and Cleveland 2127 29993 20997 6852
11733 E01012097 Redcar and Cleveland 13024 33725 38305 8502
11734 E01012098 Redcar and Cleveland 17054 22650 26533 7158
11735 E01012099 Redcar and Cleveland 1936 30714 32912 7892
11736 E01012100 Redcar and Cleveland 248 769 35094 22717
11737 E01012101 Redcar and Cleveland 4702 2895 21212 29886
11738 E01012102 Redcar and Cleveland 3056 2849 37741 24258
11739 E01012105 Redcar and Cleveland 12148 13512 16567 29498
11740 E01012106 Redcar and Cleveland 11896 21211 19709 33686
11741 E01012107 Redcar and Cleveland 2934 30181 25473 32629
11742 E01012108 Redcar and Cleveland 3932 19489 31852 19230
11743 E01012109 Redcar and Cleveland 8182 36167 4853 18983
11744 E01012110 Redcar and Cleveland 13903 5987 35640 16797
11745 E01012111 Redcar and Cleveland 3198 8968 31973 16904
11746 E01012112 Redcar and Cleveland 197 17013 34011 16300
11747 E01012113 Redcar and Cleveland 406 19553 35339 21717
11748 E01012114 Redcar and Cleveland 62 26650 37727 23152
11749 E01012117 Redcar and Cleveland 7460 940 38401 11141
11750 E01012118 Redcar and Cleveland 11687 2465 38870 11003
11751 E01012119 Redcar and Cleveland 8080 16541 28224 12822
11752 E01012120 Redcar and Cleveland 19741 8070 22543 11452
11753 E01012121 Redcar and Cleveland 2132 10974 35054 10797
11754 E01012124 Redcar and Cleveland 27205 34810 20880 8567
11755 E01012127 Redcar and Cleveland 258 15271 37513 32220
11756 E01012128 Redcar and Cleveland 558 20995 37878 32531
11757 E01012129 Redcar and Cleveland 13152 20196 34688 32220
11758 E01012130 Redcar and Cleveland 13273 23932 32718 32531
11759 E01012131 Redcar and Cleveland 492 12070 28290 32220
11760 E01012132 Redcar and Cleveland 4933 36577 8534 4924
11761 E01012134 Redcar and Cleveland 5505 35851 8477 5596
11762 E01012136 Redcar and Cleveland 5408 6407 26622 5451
11763 E01012137 Redcar and Cleveland 7703 28102 6728 4203
11764 E01012138 Redcar and Cleveland 26165 35921 35817 15434
11765 E01012139 Redcar and Cleveland 27524 35420 27012 12887
11766 E01012140 Redcar and Cleveland 13734 32542 34737 12418
11767 E01012141 Redcar and Cleveland 22767 26902 29606 16539
11768 E01012142 Redcar and Cleveland 11036 16430 23161 28773
11769 E01012143 Redcar and Cleveland 867 13612 30403 28773
11770 E01012144 Redcar and Cleveland 13070 7776 22344 25852
11771 E01012145 Redcar and Cleveland 10566 7875 38420 17677
11772 E01012146 Redcar and Cleveland 22445 19224 35079 19990
11773 E01012147 Redcar and Cleveland 25645 24506 39973 16459
11774 E01012148 Redcar and Cleveland 1549 21169 38717 18924
11775 E01012149 Redcar and Cleveland 21718 31317 39509 16933
11776 E01012150 Redcar and Cleveland 1772 17656 37035 18315
11777 E01012151 Redcar and Cleveland 16548 27618 39198 18333
11778 E01012152 Redcar and Cleveland 18307 33256 39387 16214
11779 E01012154 Redcar and Cleveland 24523 29400 31937 13224
11780 E01012155 Redcar and Cleveland 7334 20236 21523 12092
11781 E01012156 Redcar and Cleveland 25136 26094 20553 13913
11782 E01012157 Redcar and Cleveland 12050 14551 15353 14331
11783 E01012158 Redcar and Cleveland 27904 14033 7502 10054
11784 E01012159 Redcar and Cleveland 4229 2212 33293 10092
11785 E01012160 Redcar and Cleveland 12118 14286 16773 11408
11786 E01012161 Redcar and Cleveland 16059 2528 14383 8622
11787 E01012162 Redcar and Cleveland 8338 35463 24217 7377
11788 E01012163 Redcar and Cleveland 23181 29923 29654 8716
11789 E01012164 Redcar and Cleveland 13590 29141 4763 8371
11790 E01012165 Redcar and Cleveland 3381 24135 20389 7939
11791 E01012167 Redcar and Cleveland 10029 16785 35984 23405
11792 E01012168 Redcar and Cleveland 4871 14563 35835 21924
11793 E01012170 Redcar and Cleveland 160 12398 31887 23844
11794 E01012171 Redcar and Cleveland 5056 14770 32913 19230
11795 E01012172 Redcar and Cleveland 15078 11873 38223 19977
11796 E01012173 Redcar and Cleveland 16004 12345 38162 20099
11797 E01012174 Redcar and Cleveland 21473 12998 39815 21471
11798 E01012175 Redcar and Cleveland 1034 9662 36298 20978
11799 E01012176 Redcar and Cleveland 23270 23412 22622 24807
11800 E01012177 Redcar and Cleveland 25010 31650 32209 16596
11801 E01012178 Redcar and Cleveland 18013 12585 14399 26213
11802 E01012179 Redcar and Cleveland 26866 25680 31022 25282
11803 E01012180 Redcar and Cleveland 29308 33310 36349 23046
11804 E01012181 Redcar and Cleveland 7813 36705 16592 5678
11805 E01012182 Redcar and Cleveland 31245 19143 28846 5549
11806 E01012183 Redcar and Cleveland 31578 26992 37724 6701
11807 E01012184 Redcar and Cleveland 8027 1068 9939 21404
11808 E01012185 Redcar and Cleveland 12373 29522 14158 19963
11809 E01012186 Redcar and Cleveland 18345 20603 15260 19831
11810 E01012187 Stockton-on-Tees 15752 27720 41211 10786
11811 E01012188 Stockton-on-Tees 25487 30813 40651 11247
11812 E01012189 Stockton-on-Tees 21878 19500 41460 14739
11813 E01012190 Stockton-on-Tees 21644 29353 40482 12228
11814 E01012191 Stockton-on-Tees 12896 20007 39609 16921
11815 E01012192 Stockton-on-Tees 10993 21132 30726 16159
11816 E01012193 Stockton-on-Tees 4894 20671 35328 16967
11817 E01012194 Stockton-on-Tees 5773 14736 32826 18481
11818 E01012195 Stockton-on-Tees 505 21291 33874 17277
11819 E01012196 Stockton-on-Tees 7788 11422 23906 33276
11820 E01012197 Stockton-on-Tees 9074 8354 28252 28503
11821 E01012198 Stockton-on-Tees 2363 34540 12966 33427
11822 E01012199 Stockton-on-Tees 27359 11209 19934 15260
11823 E01012200 Stockton-on-Tees 28161 17327 17430 11383
11824 E01012201 Stockton-on-Tees 31459 24701 29375 14491
11825 E01012202 Stockton-on-Tees 21031 13719 22647 19423
11826 E01012203 Stockton-on-Tees 29242 31174 35832 16427
11827 E01012204 Stockton-on-Tees 22593 29930 32896 15463
11828 E01012205 Stockton-on-Tees 16245 31637 40227 14739
11829 E01012206 Stockton-on-Tees 7915 34012 39463 14683
11830 E01012207 Stockton-on-Tees 20832 32550 30875 15403
11831 E01012208 Stockton-on-Tees 27070 35084 35906 16061
11832 E01012209 Stockton-on-Tees 20753 35220 25217 19454
11833 E01012210 Stockton-on-Tees 27174 29681 33617 16865
11834 E01012211 Stockton-on-Tees 27847 23208 31636 14653
11835 E01012212 Stockton-on-Tees 22997 22655 36424 15596
11836 E01012213 Stockton-on-Tees 17379 22758 38328 15053
11837 E01012214 Stockton-on-Tees 8112 13289 30038 33009
11838 E01012215 Stockton-on-Tees 1731 7836 25182 33203
11839 E01012216 Stockton-on-Tees 5543 22990 25258 27518
11840 E01012217 Stockton-on-Tees 1645 10511 27575 19333
11841 E01012218 Stockton-on-Tees 11828 25845 11086 19208
11842 E01012219 Stockton-on-Tees 15237 27150 20767 17573
11843 E01012223 Stockton-on-Tees 30660 35341 16531 20928
11844 E01012224 Stockton-on-Tees 28571 34062 37170 16591
11845 E01012225 Stockton-on-Tees 23477 34400 37528 12548
11846 E01012226 Stockton-on-Tees 24410 30500 40676 13690
11847 E01012227 Stockton-on-Tees 26221 32450 38493 10938
11848 E01012228 Stockton-on-Tees 26071 30836 33550 14742
11849 E01012230 Stockton-on-Tees 25158 34165 34267 11356
11850 E01012231 Stockton-on-Tees 27614 33951 36957 10396
11851 E01012232 Stockton-on-Tees 26903 35992 34717 10415
11852 E01012233 Stockton-on-Tees 27437 37685 13638 10297
11853 E01012234 Stockton-on-Tees 29746 36345 29221 10396
11854 E01012235 Stockton-on-Tees 21703 35639 25152 7500
11855 E01012236 Stockton-on-Tees 25758 21062 25613 16403
11856 E01012237 Stockton-on-Tees 28243 31116 32359 14243
11857 E01012238 Stockton-on-Tees 2456 14913 23529 17640
11858 E01012239 Stockton-on-Tees 9186 17217 31674 19322
11859 E01012240 Stockton-on-Tees 10018 20912 18358 20427
11860 E01012241 Stockton-on-Tees 20965 11495 31319 20345
11861 E01012242 Stockton-on-Tees 17251 25455 35767 23234
11862 E01012243 Stockton-on-Tees 23219 27138 36475 18416
11863 E01012244 Stockton-on-Tees 24844 27284 38170 16665
11864 E01012245 Stockton-on-Tees 1466 27819 35077 26159
11865 E01012246 Stockton-on-Tees 28842 30790 37920 16438
11866 E01012247 Stockton-on-Tees 3946 10907 38511 15709
11867 E01012248 Stockton-on-Tees 5033 23319 38416 16093
11868 E01012249 Stockton-on-Tees 2850 10895 39594 13246
11869 E01012250 Stockton-on-Tees 1768 15226 41168 10487
11870 E01012251 Stockton-on-Tees 2734 15375 38738 17664
11871 E01012252 Stockton-on-Tees 269 24050 28951 17706
11872 E01012253 Stockton-on-Tees 6881 26993 25354 16208
11873 E01012254 Stockton-on-Tees 386 7658 34416 18562
11874 E01012255 Stockton-on-Tees 28012 28343 38784 16044
11875 E01012256 Stockton-on-Tees 24082 27509 34231 15199
11876 E01012257 Stockton-on-Tees 29076 21273 39912 15199
11877 E01012258 Stockton-on-Tees 2585 18728 37782 22513
11878 E01012259 Stockton-on-Tees 13397 12443 36816 19762
11879 E01012260 Stockton-on-Tees 18887 17691 22999 18101
11880 E01012261 Stockton-on-Tees 16755 15953 30523 18101
11881 E01012262 Stockton-on-Tees 1940 6383 28976 22479
11882 E01012264 Stockton-on-Tees 12021 28307 36200 22962
11883 E01012266 Stockton-on-Tees 115 18611 30765 22321
11884 E01012267 Stockton-on-Tees 229 926 34489 20311
11885 E01012268 Stockton-on-Tees 1363 14291 37645 19429
11886 E01012269 Stockton-on-Tees 25943 40288 13935 9628
11887 E01012270 Stockton-on-Tees 20070 25659 28631 22673
11888 E01012271 Stockton-on-Tees 1739 21566 36504 16607
11889 E01012272 Stockton-on-Tees 16785 22891 39639 15988
11890 E01012273 Stockton-on-Tees 1418 14300 39086 15811
11891 E01012274 Stockton-on-Tees 3651 16458 37394 14800
11892 E01012275 Stockton-on-Tees 6385 4790 27372 30097
11893 E01012276 Stockton-on-Tees 4707 1257 35842 27629
11894 E01012277 Stockton-on-Tees 8700 4220 28320 26754
11895 E01012278 Stockton-on-Tees 8232 29168 9990 30915
11896 E01012279 Stockton-on-Tees 17922 23395 20862 33296
11897 E01012280 Stockton-on-Tees 13639 18053 24999 25618
11898 E01012281 Stockton-on-Tees 3320 23432 17931 29145
11899 E01012282 Stockton-on-Tees 7035 24901 34363 15233
11900 E01012283 Stockton-on-Tees 2686 15487 36110 17127
11901 E01012284 Stockton-on-Tees 837 7253 36876 19781
11902 E01012285 Stockton-on-Tees 10726 28558 8304 15970
11903 E01012286 Stockton-on-Tees 696 7588 35210 21966
11904 E01012287 Stockton-on-Tees 8196 15421 20386 21674
11905 E01012288 Stockton-on-Tees 2028 2754 30856 16872
11906 E01012289 Stockton-on-Tees 7358 13769 26710 22953
11907 E01012290 Stockton-on-Tees 15971 24293 12102 16298
11908 E01012291 Stockton-on-Tees 5482 18257 14429 15943
11909 E01012292 Stockton-on-Tees 9327 9302 23558 18870
11910 E01012294 Stockton-on-Tees 24473 39898 23183 7992
11911 E01012295 Stockton-on-Tees 14536 40191 6376 6712
11912 E01012296 Stockton-on-Tees 16241 27874 34409 22446
11913 E01012297 Stockton-on-Tees 29043 32416 33904 17936
11914 E01012298 Stockton-on-Tees 32205 28145 9613 10159
11915 E01012299 Stockton-on-Tees 30284 3682 18719 11207
11916 E01012300 Stockton-on-Tees 13033 24263 10296 10116
11917 E01012301 Stockton-on-Tees 31316 30871 15459 10142
11918 E01012302 Stockton-on-Tees 31976 23764 12396 10936
11919 E01012303 Stockton-on-Tees 31004 29836 20255 7950
11920 E01012304 Darlington 303 4769 31740 15544
11921 E01012305 Darlington 4294 2357 38790 9846
11922 E01012306 Darlington 7828 11256 27386 11266
11923 E01012307 Darlington 5026 25914 35576 14747
11924 E01012309 Darlington 24336 20732 28395 8861
11925 E01012310 Darlington 17058 25184 31284 8283
11926 E01012311 Darlington 11275 19751 26572 8267
11927 E01012312 Darlington 1011 32720 31978 9792
11928 E01012313 Darlington 6301 27817 26103 8711
11929 E01012314 Darlington 2940 34418 32631 8076
11930 E01012315 Darlington 30258 11937 16431 7122
11931 E01012316 Darlington 26689 4583 17462 8350
11932 E01012317 Darlington 15743 24617 32071 6144
11933 E01012318 Darlington 2843 25558 32943 6090
11934 E01012319 Darlington 10936 17858 35310 9453
11935 E01012323 Darlington 14148 20208 20762 11902
11936 E01012324 Darlington 20496 16820 22495 13300
11937 E01012325 Darlington 13907 33029 1740 12939
11938 E01012326 Darlington 6941 32360 5512 12939
11939 E01012327 Darlington 476 29028 672 14853
11940 E01012328 Darlington 6756 26549 12686 12506
11941 E01012329 Darlington 24424 32788 15506 12044
11942 E01012330 Darlington 28448 31408 14200 13254
11943 E01012331 Darlington 18088 32385 17490 13254
11944 E01012332 Darlington 4727 32403 10753 13187
11945 E01012333 Darlington 11163 34084 5953 14107
11946 E01012334 Darlington 18804 39052 17184 5162
11947 E01012335 Darlington 28648 39131 38938 5092
11948 E01012336 Darlington 28409 27742 11109 7200
11949 E01012337 Darlington 30612 23178 9859 7270
11950 E01012338 Darlington 16670 37752 2540 5637
11951 E01012339 Darlington 31114 35373 15714 5289
11952 E01012340 Darlington 8316 12658 27371 7385
11953 E01012341 Darlington 1699 25993 30384 7385
11954 E01012342 Darlington 5180 25704 28821 14247
11955 E01012343 Darlington 16777 17599 39276 14912
11956 E01012344 Darlington 21402 34342 18760 5946
11957 E01012345 Darlington 22190 38274 24775 6570
11958 E01012346 Darlington 29090 36406 25172 7574
11959 E01012347 Darlington 30873 19650 21612 7502
11960 E01012348 Darlington 31720 27569 26125 7877
11961 E01012349 Darlington 552 4196 39677 12800
11962 E01012350 Darlington 5976 7146 32362 13431
11963 E01012351 Darlington 22896 14827 20353 13721
11964 E01012352 Darlington 1858 16264 34504 12237
11965 E01012353 Darlington 5268 6333 38359 10680
11966 E01012354 Darlington 991 3046 37391 12558
11967 E01012355 Darlington 8334 460 37083 9581
11968 E01012356 Darlington 8984 3358 6693 9627
11969 E01012357 Darlington 5090 5037 24993 9979
11970 E01012358 Darlington 8821 20106 3443 6605
11971 E01012359 Darlington 470 29601 6288 6605
11972 E01012360 Darlington 22508 12664 5531 8290
11973 E01012361 Darlington 30081 23389 2868 7399
11974 E01012362 Darlington 5150 14831 40138 10680
11975 E01012363 Darlington 13268 12197 38962 8809
11976 E01012364 Darlington 12581 5723 37156 8809
11977 E01012365 Darlington 20993 9487 36004 7013
11978 E01012366 Darlington 18125 39833 19282 7994
11979 E01012367 Halton 1051 1739 38622 36769
11980 E01012368 Halton 7725 1194 37263 35171
11981 E01012369 Halton 7063 4705 24239 34836
11982 E01012370 Halton 3694 91 39687 36527
11983 E01012371 Halton 19389 34309 21285 33991
11984 E01012372 Halton 21642 36474 17243 31612
11985 E01012373 Halton 23479 36520 32930 32919
11986 E01012374 Halton 29112 27115 36219 32137
11987 E01012375 Halton 29348 23250 33573 32922
11988 E01012376 Halton 28490 27087 36955 32699
11989 E01012377 Halton 5549 25420 22896 31943
11990 E01012378 Halton 18867 7127 33308 33335
11991 E01012379 Halton 4696 17522 32726 34156
11992 E01012380 Halton 2036 17932 24955 34054
11993 E01012381 Halton 373 22167 3438 36077
11994 E01012382 Halton 536 28285 5179 35911
11995 E01012383 Halton 4734 24125 6679 34501
11996 E01012384 Halton 3958 22840 7983 35083
11997 E01012385 Halton 24244 35899 4600 28958
11998 E01012386 Halton 23861 36377 7014 32554
11999 E01012387 Halton 26008 37853 1474 28873
12000 E01012388 Halton 4326 13485 24473 35563
12001 E01012389 Halton 24127 31270 27715 34997
12002 E01012390 Halton 7104 18092 17549 33728
12003 E01012391 Halton 5968 34376 18301 31621
12004 E01012392 Halton 27533 32486 38419 35633
12005 E01012393 Halton 30140 25112 35140 31898
12006 E01012394 Halton 11572 6052 37005 34688
12007 E01012395 Halton 25516 20621 36594 32672
12008 E01012396 Halton 713 12827 23995 33555
12009 E01012397 Halton 1797 2934 20433 35287
12010 E01012398 Halton 13689 11708 17684 35287
12011 E01012399 Halton 2840 5900 26189 34425
12012 E01012400 Halton 15012 12604 24386 35788
12013 E01012401 Halton 19132 29156 7799 27692
12014 E01012402 Halton 3327 26736 15763 34181
12015 E01012403 Halton 1741 22875 20027 34330
12016 E01012404 Halton 10844 31592 7977 35124
12017 E01012405 Halton 11915 19879 8202 34740
12018 E01012406 Halton 5733 15935 26012 34222
12019 E01012407 Halton 1035 5405 22367 34175
12020 E01012408 Halton 461 8264 27651 32697
12021 E01012409 Halton 2795 18358 24272 34175
12022 E01012410 Halton 23402 27582 26300 37609
12023 E01012411 Halton 13829 21600 32985 37800
12024 E01012412 Halton 4400 11543 26155 35874
12025 E01012413 Halton 3654 7448 26377 35920
12026 E01012414 Halton 16458 10219 31488 38305
12027 E01012415 Halton 22003 31239 32925 34129
12028 E01012416 Halton 19216 29079 13590 32111
12029 E01012417 Halton 6244 35846 6461 27874
12030 E01012418 Halton 23505 30718 27534 33792
12031 E01012419 Halton 2143 26020 36822 31802
12032 E01012420 Halton 596 6766 33695 32069
12033 E01012421 Halton 23303 26305 36909 30589
12034 E01012422 Halton 2449 29015 34598 31943
12035 E01012423 Halton 18245 15453 37784 31618
12036 E01012424 Halton 690 12190 33087 36278
12037 E01012425 Halton 4221 14512 32845 35689
12038 E01012426 Halton 17167 13911 29905 34075
12039 E01012427 Halton 7426 18540 27840 35495
12040 E01012428 Halton 10623 14375 24503 30117
12041 E01012429 Halton 7765 24210 6629 26390
12042 E01012430 Halton 2107 680 6572 33827
12043 E01012431 Halton 5296 6970 18011 34642
12044 E01012432 Halton 9552 28667 3608 32420
12045 E01012433 Halton 3201 21460 1023 32420
12046 E01012434 Halton 21820 29724 519 30247
12047 E01012435 Halton 24677 32318 3791 33596
12048 E01012436 Halton 2286 20270 7432 32494
12049 E01012437 Halton 1986 27164 22886 33621
12050 E01012438 Halton 1084 10627 4623 32494
12051 E01012439 Halton 3262 23486 16659 33963
12052 E01012440 Halton 14211 28946 25406 34007
12053 E01012441 Halton 921 9778 29156 35316
12054 E01012442 Halton 2684 21864 27583 34815
12055 E01012443 Halton 10057 27790 30520 32790
12056 E01012444 Halton 523 30446 1489 32731
12057 E01012445 Halton 549 23371 303 34399
12058 E01012446 Warrington 30091 29418 12023 23333
12059 E01012447 Warrington 31482 29890 17913 24192
12060 E01012448 Warrington 29139 29707 35573 24665
12061 E01012449 Warrington 31648 19568 14814 23501
12062 E01012450 Warrington 26677 16461 2618 25235
12063 E01012451 Warrington 16662 17226 3836 27209
12064 E01012452 Warrington 30893 25788 3792 24407
12065 E01012453 Warrington 2326 9288 13603 34477
12066 E01012454 Warrington 10624 10053 24261 35039
12067 E01012455 Warrington 2009 10977 6132 35017
12068 E01012457 Warrington 5581 3026 14216 35589
12069 E01012458 Warrington 8639 26740 3962 31774
12070 E01012459 Warrington 4511 23669 33620 34666
12071 E01012460 Warrington 9846 30959 25876 34739
12072 E01012461 Warrington 30364 36304 31421 31207
12073 E01012462 Warrington 24183 35415 33111 33553
12074 E01012463 Warrington 28548 34226 24209 34914
12075 E01012464 Warrington 11898 31695 28509 35180
12076 E01012465 Warrington 17090 32042 32469 33191
12077 E01012466 Warrington 3066 30043 30306 34603
12078 E01012467 Warrington 20669 35761 33524 30159
12079 E01012468 Warrington 12575 35254 15179 32320
12080 E01012469 Warrington 10704 35107 14334 29153
12081 E01012470 Warrington 9465 34879 25293 29091
12082 E01012471 Warrington 23541 29261 7548 33244
12083 E01012472 Warrington 23250 36954 16362 31915
12084 E01012473 Warrington 26220 18672 12895 26291
12085 E01012474 Warrington 14110 15326 9916 29206
12086 E01012475 Warrington 19767 25519 8528 32768
12087 E01012476 Warrington 21083 35018 3479 25298
12088 E01012477 Warrington 31857 26240 14624 24937
12089 E01012478 Warrington 13658 5977 14051 35640
12090 E01012479 Warrington 3543 4242 31870 35526
12091 E01012480 Warrington 3867 10008 17404 34755
12092 E01012481 Warrington 11330 2441 29206 35473
12093 E01012482 Warrington 4823 7141 32587 35204
12094 E01012483 Warrington 1334 7186 36651 34952
12095 E01012485 Warrington 24888 25221 4197 26211
12096 E01012486 Warrington 30985 6045 7845 26424
12097 E01012487 Warrington 30048 13226 10434 25240
12098 E01012488 Warrington 28824 33346 596 25807
12099 E01012489 Warrington 31883 22998 1432 24515
12100 E01012490 Warrington 31083 30798 5055 24630
12101 E01012491 Warrington 16769 24859 32482 31963
12102 E01012492 Warrington 26282 28851 31505 32780
12103 E01012493 Warrington 28088 24847 32293 31249
12104 E01012494 Warrington 28971 30635 32793 30640
12105 E01012495 Warrington 26210 28836 1092 27805
12106 E01012496 Warrington 24718 27344 13900 30376
12107 E01012497 Warrington 9122 30519 1924 34328
12108 E01012498 Warrington 11211 24339 13275 32375
12109 E01012499 Warrington 24446 31804 33254 32375
12110 E01012500 Warrington 28024 15073 21347 32254
12111 E01012501 Warrington 18800 31068 4487 29658
12112 E01012502 Warrington 28275 26360 333 25887
12113 E01012503 Warrington 29995 30892 23721 24543
12114 E01012504 Warrington 10900 15551 7414 29946
12115 E01012505 Warrington 8019 20006 1833 30339
12116 E01012506 Warrington 4043 13945 5495 33289
12117 E01012507 Warrington 7245 2202 14428 29830
12118 E01012508 Warrington 2273 10649 9158 31020
12119 E01012509 Warrington 20430 17210 10431 26293
12120 E01012510 Warrington 9875 11622 9417 31123
12121 E01012511 Warrington 9384 24352 16242 34533
12122 E01012512 Warrington 21432 9418 4547 30445
12123 E01012513 Warrington 31885 24971 1181 29294
12124 E01012514 Warrington 28836 33233 4608 23517
12125 E01012515 Warrington 19855 33128 2275 29122
12126 E01012516 Warrington 28482 18472 398 27553
12127 E01012517 Warrington 30859 31382 6946 25569
12128 E01012518 Warrington 29341 36370 2558 22950
12129 E01012519 Warrington 28613 34138 3594 28321
12130 E01012520 Warrington 1746 6967 24978 35303
12131 E01012521 Warrington 10604 15331 35874 35131
12132 E01012522 Warrington 6083 11993 29297 35697
12133 E01012523 Warrington 7897 2575 31793 35159
12134 E01012524 Warrington 19519 12278 29662 35446
12135 E01012525 Warrington 5292 2852 35919 34828
12136 E01012526 Warrington 2646 3122 26130 35666
12137 E01012527 Warrington 19744 16888 10412 30110
12138 E01012528 Warrington 22794 23650 12606 28131
12139 E01012529 Warrington 25789 13695 26559 30812
12140 E01012530 Warrington 25720 32846 15803 31909
12141 E01012531 Warrington 26499 9501 29687 31184
12142 E01012532 Warrington 25858 8431 21553 30110
12143 E01012533 Warrington 1083 27217 33615 35089
12144 E01012534 Warrington 3748 21823 32934 34858
12145 E01012535 Warrington 5198 12130 34799 35329
12146 E01012536 Warrington 4409 16660 24635 35301
12147 E01012537 Warrington 3081 2913 24338 35574
12148 E01012538 Warrington 25706 33217 26152 34851
12149 E01012539 Warrington 6673 18781 23108 34579
12150 E01012540 Warrington 21038 21401 35638 34535
12151 E01012541 Warrington 15055 34466 25620 34939
12152 E01012542 Warrington 15196 33821 20912 34802
12153 E01012543 Warrington 25322 25973 38299 34631
12154 E01012544 Warrington 14090 32519 22170 34121
12155 E01012545 Warrington 3735 18325 32688 34535
12156 E01012546 Warrington 2485 24290 23768 35446
12157 E01012547 Warrington 23359 16472 18046 34136
12158 E01012548 Warrington 25412 21087 18126 33284
12159 E01012549 Warrington 27914 22282 20142 33102
12160 E01012550 Warrington 24945 17761 12379 34250
12161 E01012551 Warrington 26115 27681 10111 31014
12162 E01012552 Warrington 17531 8225 9992 27367
12163 E01012553 Warrington 30279 22688 8012 28199
12164 E01012554 Warrington 20932 37007 935 30240
12165 E01012555 Warrington 27900 6693 19497 29964
12166 E01012556 Warrington 26529 5583 19182 30100
12167 E01012557 Warrington 23874 83 12193 27209
12168 E01012558 Warrington 31350 2784 10122 26035
12169 E01012559 Warrington 30857 15340 632 28584
12170 E01012560 Warrington 20005 12026 419 27209
12171 E01012561 Warrington 21935 28123 3615 33094
12172 E01012562 Warrington 27846 22848 30804 31241
12173 E01012563 Warrington 29113 22495 16785 32245
12174 E01012564 Warrington 17965 30969 1537 34079
12175 E01012565 Warrington 23405 23021 22014 33787
12176 E01012566 Warrington 28925 24226 19308 32586
12177 E01012567 Warrington 31041 34328 40499 32477
12178 E01012568 Warrington 30262 28148 34801 32360
12179 E01012569 Warrington 26621 27680 22748 31610
12180 E01012570 Warrington 6311 26063 4192 34402
12181 E01012571 Blackburn with Darwen 2666 6610 12313 24036
12182 E01012572 Blackburn with Darwen 1102 8654 6979 23979
12183 E01012573 Blackburn with Darwen 5088 2492 27953 24036
12184 E01012574 Blackburn with Darwen 2421 8961 8323 25716
12185 E01012575 Blackburn with Darwen 1236 4394 14180 24624
12186 E01012576 Blackburn with Darwen 3369 619 12734 23925
12187 E01012577 Blackburn with Darwen 2951 5991 32342 24429
12188 E01012578 Blackburn with Darwen 1939 2098 30846 25153
12189 E01012579 Blackburn with Darwen 3664 9255 16566 24556
12190 E01012580 Blackburn with Darwen 4071 1104 35920 24556
12191 E01012581 Blackburn with Darwen 21806 25328 35510 12295
12192 E01012582 Blackburn with Darwen 22362 20707 14977 9648
12193 E01012583 Blackburn with Darwen 25178 25298 33049 11969
12194 E01012584 Blackburn with Darwen 22756 21302 8785 12191
12195 E01012585 Blackburn with Darwen 7223 1917 21495 16947
12196 E01012586 Blackburn with Darwen 1692 1360 39094 13412
12197 E01012587 Blackburn with Darwen 7810 7172 33489 13198
12198 E01012588 Blackburn with Darwen 7087 1857 40835 13412
12199 E01012589 Blackburn with Darwen 1987 5351 21807 17921
12200 E01012590 Blackburn with Darwen 5637 11865 23219 21120
12201 E01012591 Blackburn with Darwen 3390 18203 3838 12783
12202 E01012592 Blackburn with Darwen 20949 34756 1733 15550
12203 E01012593 Blackburn with Darwen 10382 10672 13366 18872
12204 E01012594 Blackburn with Darwen 2200 16487 8765 16503
12205 E01012595 Blackburn with Darwen 1923 8956 7356 19336
12206 E01012596 Blackburn with Darwen 2250 3222 32427 17300
12207 E01012597 Blackburn with Darwen 22612 32647 13058 23956
12208 E01012598 Blackburn with Darwen 28858 26024 10188 16798
12209 E01012599 Blackburn with Darwen 13930 26816 1233 21408
12210 E01012600 Blackburn with Darwen 2618 7859 5603 19426
12211 E01012601 Blackburn with Darwen 411 9973 4644 19982
12212 E01012602 Blackburn with Darwen 22890 31294 14672 24149
12213 E01012603 Blackburn with Darwen 1667 16642 7773 21071
12214 E01012604 Blackburn with Darwen 12198 19908 6533 18114
12215 E01012605 Blackburn with Darwen 4385 5832 35287 25447
12216 E01012606 Blackburn with Darwen 6475 10801 29190 24518
12217 E01012607 Blackburn with Darwen 10394 32164 24080 19806
12218 E01012608 Blackburn with Darwen 3763 15199 15190 22448
12219 E01012609 Blackburn with Darwen 28004 29666 14806 15467
12220 E01012610 Blackburn with Darwen 18927 27302 1510 16975
12221 E01012611 Blackburn with Darwen 20111 35884 290 12131
12222 E01012612 Blackburn with Darwen 24207 18083 11438 18945
12223 E01012613 Blackburn with Darwen 25958 21945 16855 17276
12224 E01012614 Blackburn with Darwen 22176 27517 30961 17993
12225 E01012615 Blackburn with Darwen 6195 14211 33732 18197
12226 E01012616 Blackburn with Darwen 15189 29653 35933 11587
12227 E01012617 Blackburn with Darwen 6693 13178 37894 18197
12228 E01012618 Blackburn with Darwen 15052 6639 2590 15475
12229 E01012619 Blackburn with Darwen 760 6138 476 16426
12230 E01012620 Blackburn with Darwen 11941 15109 12816 14905
12231 E01012621 Blackburn with Darwen 2074 4855 13140 16456
12232 E01012622 Blackburn with Darwen 29 3562 23195 18284
12233 E01012623 Blackburn with Darwen 4170 1003 28225 19022
12234 E01012624 Blackburn with Darwen 1810 855 15244 16124
12235 E01012625 Blackburn with Darwen 2340 2114 24637 18284
12236 E01012628 Blackburn with Darwen 23274 38962 57 11195
12237 E01012629 Blackburn with Darwen 4445 7352 32668 19447
12238 E01012630 Blackburn with Darwen 6201 6852 29414 22112
12239 E01012631 Blackburn with Darwen 744 5252 18905 20871
12240 E01012632 Blackburn with Darwen 6820 13438 6813 21580
12241 E01012633 Blackburn with Darwen 12498 14701 24981 14662
12242 E01012634 Blackburn with Darwen 10531 20779 25185 21442
12243 E01012635 Blackburn with Darwen 13416 17026 19880 17574
12244 E01012636 Blackburn with Darwen 22807 16655 29044 15217
12245 E01012637 Blackburn with Darwen 486 15041 5876 20461
12246 E01012638 Blackburn with Darwen 544 10087 5560 21350
12247 E01012639 Blackburn with Darwen 368 8976 1271 22103
12248 E01012640 Blackburn with Darwen 2472 4221 16676 22115
12249 E01012641 Blackburn with Darwen 1335 12657 8290 23287
12250 E01012642 Blackburn with Darwen 5122 3772 30672 20572
12251 E01012643 Blackburn with Darwen 2110 1339 34986 23940
12252 E01012644 Blackburn with Darwen 7612 250 40104 21539
12253 E01012645 Blackburn with Darwen 14639 3075 37225 18830
12254 E01012646 Blackburn with Darwen 1332 10316 35089 21243
12255 E01012647 Blackburn with Darwen 4171 20929 24054 21243
12256 E01012648 Blackburn with Darwen 3105 7973 26476 17921
12257 E01012649 Blackburn with Darwen 929 8114 15779 17927
12258 E01012650 Blackburn with Darwen 657 6292 38901 17921
12259 E01012651 Blackburn with Darwen 9337 7753 18194 17921
12260 E01012652 Blackburn with Darwen 23919 14056 4050 12489
12261 E01012653 Blackburn with Darwen 5373 2455 27214 10836
12262 E01012654 Blackburn with Darwen 3360 1164 37184 13930
12263 E01012655 Blackburn with Darwen 35 3991 39245 21477
12264 E01012656 Blackburn with Darwen 1795 2629 39027 21271
12265 E01012657 Blackburn with Darwen 2219 2028 39331 16097
12266 E01012658 Blackburn with Darwen 5073 5580 22368 20584
12267 E01012659 Blackburn with Darwen 19404 15343 20477 9449
12268 E01012660 Blackburn with Darwen 24806 25196 13434 9587
12269 E01012661 Blackburn with Darwen 10129 15865 40765 9739
12270 E01012662 Blackpool 5006 30382 27783 8777
12271 E01012663 Blackpool 8390 11001 24611 6660
12272 E01012664 Blackpool 11645 9812 26307 8382
12273 E01012665 Blackpool 9981 20423 26869 8365
12274 E01012666 Blackpool 4349 8066 22142 5373
12275 E01012667 Blackpool 15772 9283 24718 5302
12276 E01012668 Blackpool 8345 10179 24831 6470
12277 E01012669 Blackpool 7492 19708 31727 7089
12278 E01012670 Blackpool 8 5917 38491 7253
12279 E01012671 Blackpool 5 2660 36997 7342
12280 E01012672 Blackpool 4 5704 39248 7342
12281 E01012673 Blackpool 2 4642 35749 7253
12282 E01012674 Blackpool 12 2204 35465 7342
12283 E01012675 Blackpool 20 721 38892 6997
12284 E01012676 Blackpool 4763 10273 30018 12010
12285 E01012677 Blackpool 4672 3328 34292 12010
12286 E01012678 Blackpool 190 8162 38086 14962
12287 E01012679 Blackpool 16 887 39581 6997
12288 E01012680 Blackpool 279 8837 39666 11836
12289 E01012681 Blackpool 3 3954 39732 8995
12290 E01012682 Blackpool 9 6770 39714 9682
12291 E01012683 Blackpool 11 4794 34496 12333
12292 E01012684 Blackpool 660 13727 34529 16461
12293 E01012685 Blackpool 7317 17696 36204 16570
12294 E01012686 Blackpool 239 21376 23650 13706
12295 E01012687 Blackpool 531 19906 20580 9755
12296 E01012688 Blackpool 3780 21536 39219 15079
12297 E01012689 Blackpool 5448 22890 36155 16303
12298 E01012690 Blackpool 12907 22657 34364 12650
12299 E01012691 Blackpool 8199 17618 31183 10347
12300 E01012692 Blackpool 3815 21110 13302 13532
12301 E01012693 Blackpool 10922 18558 25719 15353
12302 E01012694 Blackpool 4498 8624 36296 18261
12303 E01012695 Blackpool 2085 10441 38415 14734
12304 E01012696 Blackpool 3622 9838 38469 16570
12305 E01012697 Blackpool 5592 11076 39044 14961
12306 E01012698 Blackpool 840 14226 34813 14734
12307 E01012699 Blackpool 8990 15218 39704 8049
12308 E01012700 Blackpool 13003 10238 37031 4317
12309 E01012701 Blackpool 11951 10440 36617 10494
12310 E01012702 Blackpool 1610 11215 36117 9129
12311 E01012703 Blackpool 12583 10569 22162 7017
12312 E01012704 Blackpool 861 22426 1120 11550
12313 E01012705 Blackpool 4131 4472 27358 7738
12314 E01012706 Blackpool 14959 7654 20806 8250
12315 E01012707 Blackpool 1529 1133 33790 18020
12316 E01012708 Blackpool 6998 9542 27381 18020
12317 E01012709 Blackpool 2259 2645 38681 17990
12318 E01012710 Blackpool 13011 6340 18044 17243
12319 E01012711 Blackpool 3491 12789 35223 17339
12320 E01012712 Blackpool 10449 18078 25340 18352
12321 E01012713 Blackpool 11160 21613 29505 17951
12322 E01012714 Blackpool 9431 24070 31809 14929
12323 E01012715 Blackpool 9494 10849 28736 17883
12324 E01012716 Blackpool 12073 21311 22428 5689
12325 E01012717 Blackpool 20617 26592 16995 7855
12326 E01012718 Blackpool 20325 18019 28548 6608
12327 E01012719 Blackpool 14832 21694 17384 8228
12328 E01012720 Blackpool 87 13895 13361 19055
12329 E01012721 Blackpool 52 21867 14514 18906
12330 E01012722 Blackpool 21322 6814 19407 16499
12331 E01012723 Blackpool 12890 24698 35797 17952
12332 E01012724 Blackpool 92 15885 18429 18260
12333 E01012725 Blackpool 10917 3834 35040 4317
12334 E01012726 Blackpool 7906 13216 28407 4230
12335 E01012727 Blackpool 15990 22992 19206 3829
12336 E01012728 Blackpool 3584 4877 36102 4230
12337 E01012729 Blackpool 10659 4936 38670 13866
12338 E01012730 Blackpool 15447 26954 35599 10091
12339 E01012731 Blackpool 9607 26579 41134 9137
12340 E01012732 Blackpool 4682 15574 33217 13099
12341 E01012733 Blackpool 1424 162 38462 7123
12342 E01012734 Blackpool 6047 858 36035 12244
12343 E01012735 Blackpool 110 1393 35247 7123
12344 E01012736 Blackpool 28 2099 35324 7123
12345 E01012737 Blackpool 7 165 39623 7082
12346 E01012738 Blackpool 59 7545 37874 7342
12347 E01012739 Blackpool 1004 8502 37429 7342
12348 E01012740 Blackpool 8202 3428 32014 12691
12349 E01012741 Blackpool 7168 7412 37882 14407
12350 E01012742 Blackpool 4819 1966 33766 12490
12351 E01012743 Blackpool 698 4508 38341 7342
12352 E01012744 Blackpool 1808 6164 38467 12864
12353 E01012745 Blackpool 2673 1658 36312 9356
12354 E01012746 Blackpool 2571 7982 37149 12962
12355 E01012747 Blackpool 19181 16975 25644 7673
12356 E01012748 Blackpool 234 9320 26204 9577
12357 E01012749 Blackpool 2234 11468 31472 8395
12358 E01012750 Blackpool 7295 13575 22618 10383
12359 E01012751 Blackpool 6 1389 24343 8069
12360 E01012752 Blackpool 1365 20279 33010 6170
12361 E01012753 Blackpool 9169 13862 32346 8635
12362 E01012754 Blackpool 395 13472 33442 8635
12363 E01012755 Blackpool 8304 14203 31430 6119
12364 E01012756 Kingston upon Hull, City of 11457 9458 40827 36096
12365 E01012757 Kingston upon Hull, City of 6904 6966 39818 36515
12366 E01012758 Kingston upon Hull, City of 13093 9426 15687 35754
12367 E01012759 Kingston upon Hull, City of 6873 6153 41470 35183
12368 E01012760 Kingston upon Hull, City of 10092 10169 41503 37093
12369 E01012761 Kingston upon Hull, City of 1673 4554 28800 36269
12370 E01012762 Kingston upon Hull, City of 11149 15008 22371 34819
12371 E01012763 Kingston upon Hull, City of 3639 12999 25051 36269
12372 E01012764 Kingston upon Hull, City of 15391 31361 11189 30847
12373 E01012765 Kingston upon Hull, City of 16491 19893 14443 30733
12374 E01012766 Kingston upon Hull, City of 19168 20979 16921 34376
12375 E01012767 Kingston upon Hull, City of 12641 7427 24551 33916
12376 E01012768 Kingston upon Hull, City of 15270 31641 16069 29850
12377 E01012769 Kingston upon Hull, City of 14723 23230 9745 30065
12378 E01012770 Kingston upon Hull, City of 28210 15879 24793 29706
12379 E01012771 Kingston upon Hull, City of 16810 25648 33367 33796
12380 E01012772 Kingston upon Hull, City of 13119 24779 34678 31333
12381 E01012773 Kingston upon Hull, City of 14582 24964 41367 31544
12382 E01012774 Kingston upon Hull, City of 8803 14680 40654 31632
12383 E01012775 Kingston upon Hull, City of 4490 9204 37746 31544
12384 E01012776 Kingston upon Hull, City of 11591 11195 40736 31503
12385 E01012777 Kingston upon Hull, City of 6494 25422 17109 30774
12386 E01012778 Kingston upon Hull, City of 838 16268 22758 40093
12387 E01012779 Kingston upon Hull, City of 905 28177 21682 25262
12388 E01012780 Kingston upon Hull, City of 900 8462 31934 31001
12389 E01012781 Kingston upon Hull, City of 405 8793 28546 25844
12390 E01012782 Kingston upon Hull, City of 383 30663 1875 33636
12391 E01012783 Kingston upon Hull, City of 344 24759 12410 30997
12392 E01012784 Kingston upon Hull, City of 7523 18322 19751 38287
12393 E01012785 Kingston upon Hull, City of 310 26795 9884 36333
12394 E01012786 Kingston upon Hull, City of 2188 23879 20961 34123
12395 E01012787 Kingston upon Hull, City of 518 15517 18336 39222
12396 E01012788 Kingston upon Hull, City of 377 29193 12729 36333
12397 E01012789 Kingston upon Hull, City of 1491 22532 21395 38651
12398 E01012790 Kingston upon Hull, City of 739 8697 28202 40212
12399 E01012791 Kingston upon Hull, City of 23179 22700 39256 33884
12400 E01012792 Kingston upon Hull, City of 19821 13051 33509 32099
12401 E01012793 Kingston upon Hull, City of 17634 12183 11518 34271
12402 E01012794 Kingston upon Hull, City of 21639 24650 40688 31287
12403 E01012795 Kingston upon Hull, City of 6003 28151 35411 30665
12404 E01012796 Kingston upon Hull, City of 14650 9713 41572 28779
12405 E01012797 Kingston upon Hull, City of 11621 32804 41630 28751
12406 E01012798 Kingston upon Hull, City of 2547 29804 40911 28487
12407 E01012799 Kingston upon Hull, City of 11706 21873 41430 29534
12408 E01012800 Kingston upon Hull, City of 9968 22017 41375 27651
12409 E01012801 Kingston upon Hull, City of 12261 28010 41456 31203
12410 E01012802 Kingston upon Hull, City of 12192 13946 41420 29380
12411 E01012803 Kingston upon Hull, City of 13171 15407 41631 29006
12412 E01012804 Kingston upon Hull, City of 12734 28446 22147 39471
12413 E01012805 Kingston upon Hull, City of 995 513 39680 38995
12414 E01012806 Kingston upon Hull, City of 2089 16887 33993 38770
12415 E01012807 Kingston upon Hull, City of 8704 12029 10893 39505
12416 E01012808 Kingston upon Hull, City of 449 4523 33848 39530
12417 E01012809 Kingston upon Hull, City of 938 11078 34933 39553
12418 E01012810 Kingston upon Hull, City of 17194 17564 22854 36387
12419 E01012811 Kingston upon Hull, City of 22023 27045 6873 35307
12420 E01012812 Kingston upon Hull, City of 26473 25909 13877 39179
12421 E01012813 Kingston upon Hull, City of 26590 23437 26580 39964
12422 E01012814 Kingston upon Hull, City of 23592 25279 18475 39941
12423 E01012815 Kingston upon Hull, City of 21950 26086 29031 39629
12424 E01012816 Kingston upon Hull, City of 10826 6960 19212 39278
12425 E01012817 Kingston upon Hull, City of 9185 31144 34921 36706
12426 E01012818 Kingston upon Hull, City of 20703 24073 10971 39041
12427 E01012819 Kingston upon Hull, City of 14641 21261 28689 39240
12428 E01012820 Kingston upon Hull, City of 10803 10529 34252 39354
12429 E01012821 Kingston upon Hull, City of 5028 19480 12717 35785
12430 E01012822 Kingston upon Hull, City of 16081 19380 14132 37920
12431 E01012823 Kingston upon Hull, City of 3519 19089 8546 37060
12432 E01012824 Kingston upon Hull, City of 15198 23687 6639 35490
12433 E01012825 Kingston upon Hull, City of 10246 27946 19802 34665
12434 E01012826 Kingston upon Hull, City of 4512 19207 12437 37969
12435 E01012827 Kingston upon Hull, City of 9983 23210 21910 38246
12436 E01012828 Kingston upon Hull, City of 11300 23921 17905 34906
12437 E01012829 Kingston upon Hull, City of 14660 28696 13904 31421
12438 E01012830 Kingston upon Hull, City of 12557 28598 29928 37776
12439 E01012832 Kingston upon Hull, City of 8900 31095 38443 29742
12440 E01012833 Kingston upon Hull, City of 2743 17114 18123 33360
12441 E01012834 Kingston upon Hull, City of 1378 21234 1618 33293
12442 E01012835 Kingston upon Hull, City of 21966 17119 37191 33258
12443 E01012836 Kingston upon Hull, City of 253 21320 11440 32923
12444 E01012837 Kingston upon Hull, City of 2698 18425 11848 34697
12445 E01012838 Kingston upon Hull, City of 2058 27297 4236 33521
12446 E01012839 Kingston upon Hull, City of 7912 23028 13698 33386
12447 E01012840 Kingston upon Hull, City of 1168 22702 14361 32720
12448 E01012841 Kingston upon Hull, City of 898 26007 19561 33640
12449 E01012842 Kingston upon Hull, City of 1679 26916 5020 33451
12450 E01012843 Kingston upon Hull, City of 358 21380 18500 34147
12451 E01012844 Kingston upon Hull, City of 834 22809 21567 35822
12452 E01012845 Kingston upon Hull, City of 1473 24071 10102 37439
12453 E01012846 Kingston upon Hull, City of 1233 19381 11656 33780
12454 E01012847 Kingston upon Hull, City of 1750 24924 16030 36415
12455 E01012848 Kingston upon Hull, City of 3188 33861 40779 33914
12456 E01012849 Kingston upon Hull, City of 1864 26874 12962 36361
12457 E01012850 Kingston upon Hull, City of 641 16063 37853 37344
12458 E01012851 Kingston upon Hull, City of 1085 1606 39018 38234
12459 E01012852 Kingston upon Hull, City of 1141 14036 39228 37509
12460 E01012854 Kingston upon Hull, City of 254 7801 30251 32775
12461 E01012855 Kingston upon Hull, City of 40 6541 31048 35575
12462 E01012856 Kingston upon Hull, City of 320 14964 16536 39090
12463 E01012857 Kingston upon Hull, City of 255 4626 33235 37026
12464 E01012858 Kingston upon Hull, City of 631 20456 14064 33868
12465 E01012859 Kingston upon Hull, City of 436 5697 41342 36536
12466 E01012860 Kingston upon Hull, City of 9279 25492 32157 33089
12467 E01012862 Kingston upon Hull, City of 732 18638 41373 36067
12468 E01012863 Kingston upon Hull, City of 5721 23450 41662 34295
12469 E01012864 Kingston upon Hull, City of 1458 7176 41450 35138
12470 E01012865 Kingston upon Hull, City of 2364 6542 41210 34947
12471 E01012866 Kingston upon Hull, City of 6733 10009 38663 34499
12472 E01012867 Kingston upon Hull, City of 1179 4985 28947 36749
12473 E01012868 Kingston upon Hull, City of 9753 3992 38856 34254
12474 E01012869 Kingston upon Hull, City of 4609 2647 35808 35127
12475 E01012870 Kingston upon Hull, City of 9534 4117 40461 34283
12476 E01012871 Kingston upon Hull, City of 4586 6104 33910 36272
12477 E01012872 Kingston upon Hull, City of 5621 3401 38651 34254
12478 E01012873 Kingston upon Hull, City of 390 19981 31963 30091
12479 E01012874 Kingston upon Hull, City of 668 17667 23991 26988
12480 E01012875 Kingston upon Hull, City of 382 8449 15065 27500
12481 E01012876 Kingston upon Hull, City of 285 16782 9095 26264
12482 E01012877 Kingston upon Hull, City of 623 29877 6350 23978
12483 E01012878 Kingston upon Hull, City of 578 22028 25595 28806
12484 E01012879 Kingston upon Hull, City of 260 24576 22670 26988
12485 E01012880 Kingston upon Hull, City of 387 20605 26819 30371
12486 E01012881 Kingston upon Hull, City of 756 20769 17641 30563
12487 E01012882 Kingston upon Hull, City of 16974 25423 28608 30683
12488 E01012883 Kingston upon Hull, City of 10161 26738 11127 32804
12489 E01012884 Kingston upon Hull, City of 4352 10121 20324 31804
12490 E01012886 Kingston upon Hull, City of 3511 12924 2857 33674
12491 E01012887 Kingston upon Hull, City of 520 10617 21869 31804
12492 E01012888 Kingston upon Hull, City of 420 8865 35997 34390
12493 E01012889 Kingston upon Hull, City of 42 13362 41477 31611
12494 E01012891 Kingston upon Hull, City of 272 3945 36261 35575
12495 E01012892 Kingston upon Hull, City of 770 7264 39738 34981
12496 E01012893 Kingston upon Hull, City of 187 12012 40559 35419
12497 E01012894 Kingston upon Hull, City of 2521 18127 31173 36029
12498 E01012895 Kingston upon Hull, City of 41 16964 28801 38189
12499 E01012896 Kingston upon Hull, City of 11844 10275 26554 38457
12500 E01012897 Kingston upon Hull, City of 21 5335 23950 35259
12501 E01012898 Kingston upon Hull, City of 2252 20383 21051 38220
12502 E01012899 Kingston upon Hull, City of 8577 9895 39278 37142
12503 E01012900 Kingston upon Hull, City of 1047 1835 40892 37963
12504 E01012901 Kingston upon Hull, City of 8209 9106 29411 38949
12505 E01012902 Kingston upon Hull, City of 13655 6952 33449 39286
12506 E01012903 Kingston upon Hull, City of 3125 996 39967 37963
12507 E01012904 Kingston upon Hull, City of 14705 10635 18165 39388
12508 E01012905 Kingston upon Hull, City of 1918 25856 28322 38651
12509 E01012906 Kingston upon Hull, City of 998 24535 34243 40189
12510 E01012907 Kingston upon Hull, City of 6714 13000 28753 40212
12511 E01012908 Kingston upon Hull, City of 1117 18743 27160 37028
12512 E01012909 Kingston upon Hull, City of 23344 20590 27750 37269
12513 E01012910 Kingston upon Hull, City of 16802 27155 29969 38651
12514 E01012911 Kingston upon Hull, City of 23192 17142 26888 38643
12515 E01012912 Kingston upon Hull, City of 18142 22032 23945 37776
12516 E01012913 Kingston upon Hull, City of 8421 10967 34694 31096
12517 E01012914 Kingston upon Hull, City of 16909 7204 32885 31575
12518 E01012915 Kingston upon Hull, City of 1778 16704 23915 30637
12519 E01012916 Kingston upon Hull, City of 17798 13643 20461 32286
12520 E01012917 Kingston upon Hull, City of 2360 19742 26523 30091
12521 E01012918 Kingston upon Hull, City of 1149 9325 33072 30996
12522 E01012919 East Riding of Yorkshire 29346 39648 34643 14756
12523 E01012920 East Riding of Yorkshire 24465 40252 21857 13597
12524 E01012921 East Riding of Yorkshire 32425 38160 34857 16569
12525 E01012922 East Riding of Yorkshire 18356 41460 34428 10512
12526 E01012923 East Riding of Yorkshire 19661 40724 9647 12014
12527 E01012924 East Riding of Yorkshire 29528 36254 4787 17198
12528 E01012925 East Riding of Yorkshire 31641 40175 35282 12502
12529 E01012926 East Riding of Yorkshire 31805 36864 6568 13529
12530 E01012927 East Riding of Yorkshire 32392 36840 22750 14320
12531 E01012928 East Riding of Yorkshire 1361 16236 27423 9794
12532 E01012929 East Riding of Yorkshire 11711 10296 30762 12030
12533 E01012930 East Riding of Yorkshire 16766 18995 23886 13288
12534 E01012931 East Riding of Yorkshire 2126 15277 30675 12030
12535 E01012932 East Riding of Yorkshire 3865 13017 36186 9573
12536 E01012933 East Riding of Yorkshire 19253 40200 16202 7630
12537 E01012934 East Riding of Yorkshire 8970 21831 31467 8210
12538 E01012935 East Riding of Yorkshire 23549 24667 15995 11048
12539 E01012936 East Riding of Yorkshire 8221 12714 8731 12522
12540 E01012937 East Riding of Yorkshire 17551 36382 14711 5954
12541 E01012938 East Riding of Yorkshire 8898 33711 36064 10207
12542 E01012939 East Riding of Yorkshire 22484 33668 21387 10928
12543 E01012940 East Riding of Yorkshire 18255 26518 31700 12436
12544 E01012941 East Riding of Yorkshire 14279 27027 34475 11338
12545 E01012942 East Riding of Yorkshire 20264 32741 18033 7575
12546 E01012943 East Riding of Yorkshire 7558 2152 32479 12026
12547 E01012944 East Riding of Yorkshire 101 37 20564 14215
12548 E01012945 East Riding of Yorkshire 3007 2119 30641 12026
12549 E01012946 East Riding of Yorkshire 1256 12267 26920 10307
12550 E01012947 East Riding of Yorkshire 12654 11380 22463 8999
12551 E01012948 East Riding of Yorkshire 44 2306 25603 12451
12552 E01012949 East Riding of Yorkshire 3160 8777 33944 9746
12553 E01012950 East Riding of Yorkshire 22840 25896 10448 10008
12554 E01012951 East Riding of Yorkshire 2349 14856 30531 9618
12555 E01012952 East Riding of Yorkshire 1877 4697 16781 14321
12556 E01012953 East Riding of Yorkshire 18653 30698 11107 24405
12557 E01012954 East Riding of Yorkshire 28033 28516 37114 22722
12558 E01012955 East Riding of Yorkshire 25168 6460 28117 21406
12559 E01012956 East Riding of Yorkshire 27898 13709 27556 22996
12560 E01012957 East Riding of Yorkshire 27761 2859 37923 22996
12561 E01012958 East Riding of Yorkshire 29650 18448 39481 22810
12562 E01012959 East Riding of Yorkshire 24324 23139 28026 25821
12563 E01012960 East Riding of Yorkshire 27172 3168 26628 21718
12564 E01012961 East Riding of Yorkshire 16932 22519 39941 22429
12565 E01012962 East Riding of Yorkshire 25927 15723 18606 22502
12566 E01012963 East Riding of Yorkshire 9033 19979 32481 22106
12567 E01012964 East Riding of Yorkshire 13066 25556 38699 26635
12568 E01012965 East Riding of Yorkshire 28328 40860 40921 17033
12569 E01012966 East Riding of Yorkshire 10855 38013 38592 20551
12570 E01012967 East Riding of Yorkshire 32513 35672 39110 18015
12571 E01012968 East Riding of Yorkshire 32683 36596 33784 15627
12572 E01012969 East Riding of Yorkshire 27177 38709 22080 14639
12573 E01012970 East Riding of Yorkshire 32147 36598 30147 19232
12574 E01012972 East Riding of Yorkshire 32703 33784 19505 18058
12575 E01012973 East Riding of Yorkshire 31713 36444 16411 15253
12576 E01012974 East Riding of Yorkshire 26812 16330 36076 25366
12577 E01012975 East Riding of Yorkshire 25981 24636 18382 11745
12578 E01012976 East Riding of Yorkshire 10127 17480 22348 14494
12579 E01012977 East Riding of Yorkshire 27216 26078 23872 10579
12580 E01012978 East Riding of Yorkshire 31392 22304 24362 11089
12581 E01012979 East Riding of Yorkshire 16874 8081 21758 11089
12582 E01012980 East Riding of Yorkshire 9932 9962 23569 11170
12583 E01012981 East Riding of Yorkshire 12485 40938 21128 8568
12584 E01012982 East Riding of Yorkshire 19567 1841 29403 10098
12585 E01012983 East Riding of Yorkshire 25005 33985 3990 10063
12586 E01012984 East Riding of Yorkshire 25688 39404 12692 9950
12587 E01012985 East Riding of Yorkshire 21656 38956 19461 9488
12588 E01012986 East Riding of Yorkshire 12108 40989 8487 10752
12589 E01012987 East Riding of Yorkshire 22233 40825 4802 9743
12590 E01012988 East Riding of Yorkshire 27235 40968 21981 12834
12591 E01012989 East Riding of Yorkshire 25033 40183 22148 10502
12592 E01012990 East Riding of Yorkshire 11875 41512 2736 7914
12593 E01012991 East Riding of Yorkshire 15372 41324 14681 8118
12594 E01012992 East Riding of Yorkshire 6005 40309 5366 9040
12595 E01012993 East Riding of Yorkshire 21303 8295 7784 31021
12596 E01012994 East Riding of Yorkshire 13998 5741 6845 32003
12597 E01012995 East Riding of Yorkshire 13252 11644 3283 26916
12598 E01012996 East Riding of Yorkshire 29325 37791 7956 27352
12599 E01012997 East Riding of Yorkshire 9095 2519 26544 26233
12600 E01012998 East Riding of Yorkshire 28758 19764 14000 28094
12601 E01012999 East Riding of Yorkshire 8314 2390 30677 28650
12602 E01013000 East Riding of Yorkshire 2824 4689 13791 21141
12603 E01013001 East Riding of Yorkshire 16818 16401 24511 27743
12604 E01013002 East Riding of Yorkshire 5162 14879 3676 22153
12605 E01013003 East Riding of Yorkshire 13423 31066 5172 23272
12606 E01013004 East Riding of Yorkshire 8780 7085 14963 25381
12607 E01013005 East Riding of Yorkshire 24861 35085 25101 29726
12608 E01013006 East Riding of Yorkshire 19084 12318 27739 30786
12609 E01013007 East Riding of Yorkshire 19574 2909 14280 30415
12610 E01013008 East Riding of Yorkshire 21210 5225 24157 30478
12611 E01013009 East Riding of Yorkshire 14046 8244 4307 27013
12612 E01013010 East Riding of Yorkshire 21513 19076 36579 31097
12613 E01013011 East Riding of Yorkshire 23363 2614 16308 30303
12614 E01013012 East Riding of Yorkshire 30050 30282 21819 32110
12615 E01013013 East Riding of Yorkshire 21534 6641 31343 30526
12616 E01013014 East Riding of Yorkshire 19920 6560 23281 29725
12617 E01013015 East Riding of Yorkshire 28036 14694 34240 28285
12618 E01013016 East Riding of Yorkshire 26673 34435 13032 21389
12619 E01013017 East Riding of Yorkshire 19724 19564 30717 22295
12620 E01013018 East Riding of Yorkshire 25542 30471 17196 19858
12621 E01013019 East Riding of Yorkshire 13114 40002 7722 16352
12622 E01013020 East Riding of Yorkshire 21010 38783 15414 20870
12623 E01013021 East Riding of Yorkshire 21485 36585 19176 17228
12624 E01013022 East Riding of Yorkshire 21533 41106 4930 15043
12625 E01013023 East Riding of Yorkshire 18598 40835 11844 14986
12626 E01013024 East Riding of Yorkshire 23502 40554 21794 13481
12627 E01013025 East Riding of Yorkshire 29399 38968 2982 20404
12628 E01013026 East Riding of Yorkshire 22100 38074 4340 19714
12629 E01013027 East Riding of Yorkshire 16343 39767 15683 24249
12630 E01013028 East Riding of Yorkshire 24025 41278 5448 26330
12631 E01013029 East Riding of Yorkshire 11964 41156 4225 20231
12632 E01013030 East Riding of Yorkshire 14426 40628 13636 22071
12633 E01013031 East Riding of Yorkshire 21583 32372 22983 30036
12634 E01013032 East Riding of Yorkshire 20593 34863 21379 30028
12635 E01013033 East Riding of Yorkshire 23767 39848 21450 29376
12636 E01013034 East Riding of Yorkshire 18885 40743 11514 17593
12637 E01013035 East Riding of Yorkshire 22451 40532 22586 22958
12638 E01013036 East Riding of Yorkshire 16581 7635 35956 18885
12639 E01013037 East Riding of Yorkshire 24798 21074 25755 21263
12640 E01013038 East Riding of Yorkshire 5038 3135 25247 18454
12641 E01013039 East Riding of Yorkshire 17858 35082 14866 22416
12642 E01013040 East Riding of Yorkshire 24482 19327 18124 20675
12643 E01013041 East Riding of Yorkshire 22189 8432 29084 17960
12644 E01013042 East Riding of Yorkshire 32595 33265 30466 17604
12645 E01013043 East Riding of Yorkshire 30295 34238 33608 18985
12646 E01013044 East Riding of Yorkshire 31672 34392 39285 19001
12647 E01013045 East Riding of Yorkshire 6681 7974 18866 20614
12648 E01013046 East Riding of Yorkshire 24990 23943 13469 12493
12649 E01013047 East Riding of Yorkshire 11269 24638 23444 12747
12650 E01013048 East Riding of Yorkshire 18049 39286 6585 14126
12651 E01013049 East Riding of Yorkshire 11183 22208 12936 10952
12652 E01013050 East Riding of Yorkshire 11422 33101 13299 15565
12653 E01013051 East Riding of Yorkshire 11710 24822 23883 11733
12654 E01013052 East Riding of Yorkshire 27675 31240 33350 10548
12655 E01013053 East Riding of Yorkshire 26194 32566 31592 12894
12656 E01013054 East Riding of Yorkshire 31893 17193 32920 12737
12657 E01013055 East Riding of Yorkshire 24532 26329 28199 12586
12658 E01013056 East Riding of Yorkshire 17885 11184 37199 12677
12659 E01013057 East Riding of Yorkshire 30479 40911 5057 11747
12660 E01013058 East Riding of Yorkshire 24185 38298 20241 11774
12661 E01013059 East Riding of Yorkshire 30594 40871 21138 13234
12662 E01013060 East Riding of Yorkshire 32721 35930 8600 15234
12663 E01013061 East Riding of Yorkshire 30662 37109 6332 14950
12664 E01013062 East Riding of Yorkshire 24702 1294 39968 14226
12665 E01013063 East Riding of Yorkshire 29871 9843 13537 16080
12666 E01013064 East Riding of Yorkshire 30396 24920 19534 15413
12667 E01013065 East Riding of Yorkshire 23879 11805 24436 17262
12668 E01013066 East Riding of Yorkshire 32661 31929 35488 14174
12669 E01013067 East Riding of Yorkshire 30779 30113 31662 14137
12670 E01013068 East Riding of Yorkshire 31561 33182 26021 15381
12671 E01013069 East Riding of Yorkshire 20960 6950 24767 18008
12672 E01013070 East Riding of Yorkshire 32571 24575 30327 13965
12673 E01013071 East Riding of Yorkshire 6704 2772 33328 17252
12674 E01013072 East Riding of Yorkshire 18871 38788 10672 29076
12675 E01013073 East Riding of Yorkshire 25371 29071 12817 23345
12676 E01013074 East Riding of Yorkshire 22650 38339 2288 22455
12677 E01013075 East Riding of Yorkshire 20110 39731 3625 24880
12678 E01013076 East Riding of Yorkshire 11384 40404 1182 18133
12679 E01013077 East Riding of Yorkshire 27534 26633 16284 31054
12680 E01013078 East Riding of Yorkshire 17046 39966 12557 22811
12681 E01013079 East Riding of Yorkshire 10313 35895 7995 23148
12682 E01013080 East Riding of Yorkshire 2030 5127 20980 20735
12683 E01013081 East Riding of Yorkshire 17636 40919 17096 27561
12684 E01013082 East Riding of Yorkshire 12277 20453 10018 21962
12685 E01013083 East Riding of Yorkshire 2206 6390 24593 20892
12686 E01013084 East Riding of Yorkshire 915 11597 12389 20992
12687 E01013085 East Riding of Yorkshire 17570 40357 20792 30076
12688 E01013086 East Riding of Yorkshire 10074 35640 8793 24631
12689 E01013087 East Riding of Yorkshire 7455 41386 2789 16195
12690 E01013088 East Riding of Yorkshire 32029 31026 12448 24972
12691 E01013089 East Riding of Yorkshire 31321 20200 8292 21688
12692 E01013090 East Riding of Yorkshire 31498 32823 16403 19949
12693 E01013091 East Riding of Yorkshire 31390 30670 31463 24484
12694 E01013092 East Riding of Yorkshire 30870 37086 10891 21027
12695 E01013093 East Riding of Yorkshire 32568 31853 20764 26991
12696 E01013094 East Riding of Yorkshire 20011 29283 22595 32224
12697 E01013095 East Riding of Yorkshire 16809 8877 18461 29772
12698 E01013096 East Riding of Yorkshire 21091 28628 26867 34791
12699 E01013097 East Riding of Yorkshire 18497 26489 18803 30086
12700 E01013098 East Riding of Yorkshire 22433 31579 20739 30044
12701 E01013099 East Riding of Yorkshire 6770 40344 3353 29709
12702 E01013100 East Riding of Yorkshire 22635 36446 27034 30489
12703 E01013101 East Riding of Yorkshire 22697 36101 33349 29811
12704 E01013102 East Riding of Yorkshire 23513 35294 29479 28922
12705 E01013103 East Riding of Yorkshire 27721 23878 40793 29142
12706 E01013104 East Riding of Yorkshire 24444 26022 41439 29446
12707 E01013105 East Riding of Yorkshire 18509 12790 35142 26508
12708 E01013106 East Riding of Yorkshire 13749 12143 33570 28600
12709 E01013107 East Riding of Yorkshire 13410 11178 39081 27323
12710 E01013108 East Riding of Yorkshire 31910 28442 26811 28233
12711 E01013110 East Riding of Yorkshire 28044 16730 37446 24672
12712 E01013111 East Riding of Yorkshire 31027 19125 40114 26930
12713 E01013112 East Riding of Yorkshire 30478 21233 38555 25070
12714 E01013113 East Riding of Yorkshire 31754 25333 41518 23989
12715 E01013114 East Riding of Yorkshire 30832 33999 30231 27491
12716 E01013115 East Riding of Yorkshire 28751 18382 39717 27248
12717 E01013116 East Riding of Yorkshire 32462 29362 36673 24328
12718 E01013117 East Riding of Yorkshire 31616 20193 36580 25018
12719 E01013118 East Riding of Yorkshire 31566 31371 34174 25587
12720 E01013119 East Riding of Yorkshire 17256 41019 14826 11054
12721 E01013120 East Riding of Yorkshire 27705 26944 37312 12754
12722 E01013121 East Riding of Yorkshire 26429 37305 34468 12155
12723 E01013122 East Riding of Yorkshire 19268 41168 13610 11542
12724 E01013123 East Riding of Yorkshire 28819 22755 41104 13056
12725 E01013124 East Riding of Yorkshire 20822 17503 40139 12212
12726 E01013125 East Riding of Yorkshire 17476 41375 36587 9068
12727 E01013126 East Riding of Yorkshire 22148 41026 11490 16402
12728 E01013127 East Riding of Yorkshire 23131 41520 1513 10264
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12730 E01013129 North East Lincolnshire 3387 7246 30188 25209
12731 E01013130 North East Lincolnshire 5187 20463 22144 28415
12732 E01013131 North East Lincolnshire 3749 3919 26810 26421
12733 E01013132 North East Lincolnshire 14269 13803 26675 28415
12734 E01013133 North East Lincolnshire 7702 12094 31406 27271
12735 E01013134 North East Lincolnshire 9429 12928 30346 28889
12736 E01013135 North East Lincolnshire 8777 16136 23081 29421
12737 E01013136 North East Lincolnshire 53 4691 38688 34457
12738 E01013137 North East Lincolnshire 104 2572 38616 34855
12739 E01013138 North East Lincolnshire 23 6134 34899 34855
12740 E01013139 North East Lincolnshire 22 5421 33421 34855
12741 E01013140 North East Lincolnshire 78 6765 36555 34318
12742 E01013141 North East Lincolnshire 2630 12771 36559 34318
12743 E01013142 North East Lincolnshire 113 4080 34681 32708
12744 E01013143 North East Lincolnshire 6703 10333 38198 31725
12745 E01013144 North East Lincolnshire 519 20977 27176 30969
12746 E01013145 North East Lincolnshire 20460 23270 24843 30218
12747 E01013146 North East Lincolnshire 12897 34268 23929 33014
12748 E01013147 North East Lincolnshire 4514 16793 25752 29857
12749 E01013148 North East Lincolnshire 25838 32781 24816 27481
12750 E01013149 North East Lincolnshire 26368 23557 13158 28901
12751 E01013150 North East Lincolnshire 22908 32039 19514 27822
12752 E01013151 North East Lincolnshire 25823 24276 5441 20684
12753 E01013152 North East Lincolnshire 30883 13123 16009 24322
12754 E01013153 North East Lincolnshire 19499 35015 32164 22740
12755 E01013154 North East Lincolnshire 25551 24806 20442 29089
12756 E01013155 North East Lincolnshire 25792 22897 2160 26610
12757 E01013156 North East Lincolnshire 6800 25135 3043 30182
12758 E01013157 North East Lincolnshire 29246 33569 10148 28103
12759 E01013158 North East Lincolnshire 9997 20250 35818 31725
12760 E01013159 North East Lincolnshire 575 5537 37680 31731
12761 E01013160 North East Lincolnshire 17485 25234 32366 30476
12762 E01013161 North East Lincolnshire 2438 9119 38454 28124
12763 E01013162 North East Lincolnshire 2623 7445 35453 28124
12764 E01013163 North East Lincolnshire 16780 25217 21448 28890
12765 E01013164 North East Lincolnshire 8348 9149 32005 28260
12766 E01013165 North East Lincolnshire 327 3657 32739 31725
12767 E01013166 North East Lincolnshire 20849 30891 20404 28453
12768 E01013167 North East Lincolnshire 20565 34944 23287 21906
12769 E01013168 North East Lincolnshire 28075 35188 31259 25794
12770 E01013169 North East Lincolnshire 15495 33574 8746 25645
12771 E01013170 North East Lincolnshire 23805 35485 31562 27188
12772 E01013171 North East Lincolnshire 31640 28742 38373 23547
12773 E01013172 North East Lincolnshire 26353 30410 35995 20813
12774 E01013173 North East Lincolnshire 17937 38856 27410 32322
12775 E01013174 North East Lincolnshire 1453 24434 37466 37236
12776 E01013175 North East Lincolnshire 19766 35189 12401 28909
12777 E01013176 North East Lincolnshire 16397 15406 21193 28731
12778 E01013177 North East Lincolnshire 1046 5051 27065 31858
12779 E01013178 North East Lincolnshire 20089 20178 17664 29321
12780 E01013179 North East Lincolnshire 10240 13725 24126 30155
12781 E01013180 North East Lincolnshire 14691 26762 24296 27092
12782 E01013181 North East Lincolnshire 1578 13141 36417 28100
12783 E01013182 North East Lincolnshire 20465 19540 10920 28292
12784 E01013183 North East Lincolnshire 11257 17028 32956 27426
12785 E01013184 North East Lincolnshire 7090 11932 11922 28100
12786 E01013185 North East Lincolnshire 21830 12919 33686 27038
12787 E01013186 North East Lincolnshire 23008 20046 29361 28805
12788 E01013187 North East Lincolnshire 3364 8110 20291 29621
12789 E01013188 North East Lincolnshire 17032 7997 31225 27875
12790 E01013189 North East Lincolnshire 25157 19495 40984 24778
12791 E01013190 North East Lincolnshire 27555 24392 40762 25606
12792 E01013191 North East Lincolnshire 28876 14123 31045 25583
12793 E01013192 North East Lincolnshire 7681 16390 33744 26612
12794 E01013193 North East Lincolnshire 26703 23823 32632 23164
12795 E01013194 North East Lincolnshire 28145 26318 38973 22973
12796 E01013195 North East Lincolnshire 5824 3343 25937 29808
12797 E01013196 North East Lincolnshire 2141 4355 26186 32345
12798 E01013197 North East Lincolnshire 9059 13431 31551 32345
12799 E01013198 North East Lincolnshire 8297 2094 11744 29344
12800 E01013199 North East Lincolnshire 2689 13295 33745 27026
12801 E01013200 North East Lincolnshire 15574 7579 21183 28274
12802 E01013201 North East Lincolnshire 650 3445 25124 33837
12803 E01013202 North East Lincolnshire 4831 2290 16702 31581
12804 E01013203 North East Lincolnshire 289 5081 31307 33471
12805 E01013204 North East Lincolnshire 3241 13886 27773 27517
12806 E01013205 North East Lincolnshire 513 13771 31324 27649
12807 E01013206 North East Lincolnshire 3167 10956 26475 26827
12808 E01013207 North East Lincolnshire 8570 6760 22011 27574
12809 E01013208 North East Lincolnshire 68 13737 32350 26680
12810 E01013209 North East Lincolnshire 271 20833 29098 25622
12811 E01013210 North East Lincolnshire 567 20527 33613 25345
12812 E01013211 North East Lincolnshire 12950 6551 31427 26776
12813 E01013212 North East Lincolnshire 274 6679 17593 26827
12814 E01013213 North East Lincolnshire 12026 17926 15323 20589
12815 E01013214 North East Lincolnshire 21661 36103 1629 19134
12816 E01013215 North East Lincolnshire 31104 26051 15882 20692
12817 E01013216 North East Lincolnshire 28407 36794 14593 20985
12818 E01013217 North East Lincolnshire 26906 31007 6539 20740
12819 E01013218 North East Lincolnshire 627 28842 34633 31321
12820 E01013219 North East Lincolnshire 2313 14667 35550 28155
12821 E01013220 North East Lincolnshire 1112 20563 30180 31105
12822 E01013221 North East Lincolnshire 345 7385 36719 33420
12823 E01013222 North East Lincolnshire 2015 10857 22197 31872
12824 E01013223 North East Lincolnshire 29166 34678 25800 32992
12825 E01013224 North East Lincolnshire 20036 39697 8390 21746
12826 E01013225 North East Lincolnshire 11461 39814 6473 18694
12827 E01013226 North East Lincolnshire 22843 39326 10062 23086
12828 E01013227 North East Lincolnshire 12985 26547 18704 26184
12829 E01013228 North East Lincolnshire 20251 28837 7360 28533
12830 E01013229 North East Lincolnshire 2946 10326 9838 27163
12831 E01013231 North East Lincolnshire 9156 122 36332 27782
12832 E01013233 North East Lincolnshire 9091 5736 37847 27803
12833 E01013234 North East Lincolnshire 19952 12334 26222 28012
12834 E01013236 North Lincolnshire 15275 11300 32642 24372
12835 E01013237 North Lincolnshire 4855 18755 22293 24372
12836 E01013238 North Lincolnshire 4334 11985 31021 25052
12837 E01013239 North Lincolnshire 11997 2234 37936 24428
12838 E01013240 North Lincolnshire 5970 29107 28747 24517
12839 E01013241 North Lincolnshire 28718 19901 36519 17760
12840 E01013242 North Lincolnshire 23051 39147 12560 24542
12841 E01013243 North Lincolnshire 27048 35530 19369 17362
12842 E01013244 North Lincolnshire 14603 23723 20638 18406
12843 E01013245 North Lincolnshire 7422 35073 298 20909
12844 E01013246 North Lincolnshire 11592 41254 11741 19545
12845 E01013247 North Lincolnshire 20122 39385 1612 20754
12846 E01013248 North Lincolnshire 25679 35429 25320 18818
12847 E01013249 North Lincolnshire 15964 34789 15731 19467
12848 E01013250 North Lincolnshire 19945 35263 17965 18604
12849 E01013251 North Lincolnshire 26715 37911 10169 18045
12850 E01013252 North Lincolnshire 29314 33584 24129 19154
12851 E01013253 North Lincolnshire 19126 39937 11509 18494
12852 E01013254 North Lincolnshire 9679 3564 18325 30215
12853 E01013255 North Lincolnshire 12719 2897 27444 30800
12854 E01013256 North Lincolnshire 24833 13839 16325 28682
12855 E01013257 North Lincolnshire 25754 21465 24464 28721
12856 E01013258 North Lincolnshire 9877 7773 17312 30429
12857 E01013259 North Lincolnshire 6065 29210 26454 30693
12858 E01013260 North Lincolnshire 26293 22936 34497 27739
12859 E01013261 North Lincolnshire 29778 24585 25642 25558
12860 E01013262 North Lincolnshire 26033 21582 21568 24677
12861 E01013263 North Lincolnshire 24796 8752 30692 24055
12862 E01013264 North Lincolnshire 20084 31740 37387 24688
12863 E01013265 North Lincolnshire 25483 31909 33268 26966
12864 E01013266 North Lincolnshire 28362 34420 31623 25216
12865 E01013267 North Lincolnshire 16027 40292 2554 28255
12866 E01013268 North Lincolnshire 14183 38953 1874 29106
12867 E01013269 North Lincolnshire 20467 36818 24387 30411
12868 E01013270 North Lincolnshire 17950 38976 18216 27816
12869 E01013271 North Lincolnshire 13249 21500 26812 35102
12870 E01013272 North Lincolnshire 7273 4077 36137 36053
12871 E01013273 North Lincolnshire 24411 21070 26716 30176
12872 E01013274 North Lincolnshire 13468 37511 3035 29512
12873 E01013275 North Lincolnshire 29753 34851 32450 22585
12874 E01013276 North Lincolnshire 17286 33074 26119 22983
12875 E01013277 North Lincolnshire 27706 35354 38239 21737
12876 E01013278 North Lincolnshire 250 13207 18028 27141
12877 E01013279 North Lincolnshire 374 16175 17261 27154
12878 E01013280 North Lincolnshire 11888 24247 7896 27141
12879 E01013281 North Lincolnshire 3084 22783 13479 26718
12880 E01013282 North Lincolnshire 6658 15739 30128 28253
12881 E01013283 North Lincolnshire 3585 26977 13349 29477
12882 E01013284 North Lincolnshire 3090 16836 23851 26906
12883 E01013285 North Lincolnshire 15285 17472 21418 26477
12884 E01013286 North Lincolnshire 8962 32198 10913 27046
12885 E01013287 North Lincolnshire 15807 37425 7935 23460
12886 E01013288 North Lincolnshire 20014 26606 25964 24656
12887 E01013289 North Lincolnshire 21590 37148 28176 25241
12888 E01013290 North Lincolnshire 18848 39201 8639 20008
12889 E01013291 North Lincolnshire 4461 22962 17066 23858
12890 E01013292 North Lincolnshire 22971 19225 19842 26146
12891 E01013293 North Lincolnshire 29278 38720 14304 22532
12892 E01013294 North Lincolnshire 20234 39222 1002 19319
12893 E01013295 North Lincolnshire 20868 29665 36169 27337
12894 E01013296 North Lincolnshire 1452 6442 40178 26451
12895 E01013297 North Lincolnshire 13886 29457 34493 28183
12896 E01013298 North Lincolnshire 2606 18656 28684 25313
12897 E01013299 North Lincolnshire 2189 24121 32466 25313
12898 E01013300 North Lincolnshire 2703 5036 38606 29729
12899 E01013301 North Lincolnshire 19877 28550 33756 27361
12900 E01013302 North Lincolnshire 17814 35384 30077 27081
12901 E01013303 North Lincolnshire 8455 39830 7046 30538
12902 E01013304 North Lincolnshire 25518 40531 24629 29965
12903 E01013305 North Lincolnshire 23316 36710 20321 29123
12904 E01013306 North Lincolnshire 15128 40698 11201 29559
12905 E01013307 North Lincolnshire 21437 36386 25742 29731
12906 E01013308 North Lincolnshire 10795 38465 27823 34795
12907 E01013309 North Lincolnshire 17820 40864 12090 29568
12908 E01013310 North Lincolnshire 7359 33373 37484 27852
12909 E01013311 North Lincolnshire 1893 29317 25098 25998
12910 E01013312 North Lincolnshire 2817 29467 40851 28178
12911 E01013313 North Lincolnshire 16116 32999 40342 33945
12912 E01013314 North Lincolnshire 10778 16101 38968 24679
12913 E01013315 North Lincolnshire 4910 9898 28482 25011
12914 E01013316 North Lincolnshire 28083 14942 29149 25356
12915 E01013317 North Lincolnshire 14174 12474 30890 24128
12916 E01013318 North Lincolnshire 16485 4559 33703 25377
12917 E01013319 North Lincolnshire 7302 18509 28053 25625
12918 E01013320 North Lincolnshire 11323 12829 35387 25212
12919 E01013321 North Lincolnshire 24516 14146 29116 24552
12920 E01013322 North Lincolnshire 21821 20931 14284 21360
12921 E01013323 North Lincolnshire 16595 35918 14121 21679
12922 E01013324 North Lincolnshire 17277 39086 8355 21077
12923 E01013325 North Lincolnshire 17290 36558 10470 26102
12924 E01013326 North Lincolnshire 22567 37479 7048 29054
12925 E01013327 North Lincolnshire 22418 33249 34018 19782
12926 E01013328 North Lincolnshire 31658 34471 28076 20111
12927 E01013329 North Lincolnshire 13610 30605 20805 23058
12928 E01013330 North Lincolnshire 4290 368 40888 23685
12929 E01013331 North Lincolnshire 2851 1818 34703 33530
12930 E01013332 North Lincolnshire 5165 489 39654 24008
12931 E01013333 North Lincolnshire 21620 7600 38492 23873
12932 E01013334 North Lincolnshire 13068 27416 31464 26006
12933 E01013335 York 7375 18700 18976 14165
12934 E01013336 York 20400 13935 23235 14573
12935 E01013337 York 29823 14184 31546 13921
12936 E01013338 York 26494 21312 29762 15152
12937 E01013339 York 30488 21664 25190 14932
12938 E01013340 York 32630 33585 8933 15153
12939 E01013341 York 27347 31171 12918 11474
12940 E01013342 York 27604 39732 13475 12038
12941 E01013343 York 24596 9974 33518 20112
12942 E01013344 York 28393 5261 13606 20281
12943 E01013345 York 20726 10242 32647 20112
12944 E01013346 York 21662 5767 12105 20275
12945 E01013347 York 5135 17201 27511 19601
12946 E01013348 York 24784 14789 28557 19696
12947 E01013349 York 4772 26758 24105 19615
12948 E01013350 York 7982 19249 18628 18288
12949 E01013351 York 31231 38679 24659 13307
12950 E01013352 York 31145 33630 36833 15034
12951 E01013353 York 13035 24286 5401 16355
12952 E01013354 York 31965 34733 20539 14724
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12961 E01013363 York 20226 14943 22074 18004
12962 E01013364 York 18559 10147 15162 16876
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12964 E01013366 York 8661 1713 18439 18930
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12966 E01013369 York 17523 2162 24873 19529
12967 E01013370 York 28813 13103 33460 11269
12968 E01013371 York 32606 32036 33994 11702
12969 E01013372 York 29549 18344 28218 9797
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12971 E01013374 York 32253 32670 28884 12801
12972 E01013375 York 32043 30072 12166 13235
12973 E01013376 York 31705 19780 22689 10209
12974 E01013377 York 31850 24578 35718 10023
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12976 E01013379 York 32089 13080 22016 22621
12977 E01013380 York 30770 10770 25891 22285
12978 E01013381 York 29684 17154 29997 19410
12979 E01013382 York 14115 14161 10602 22752
12980 E01013383 York 17329 5317 24868 21372
12981 E01013384 York 17068 14190 19220 20956
12982 E01013385 York 8680 25498 8737 24035
12983 E01013386 York 8635 24009 8683 23282
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12986 E01013389 York 30233 30248 30689 19024
12987 E01013390 York 13045 28147 15756 20905
12988 E01013391 York 23701 26319 30020 18331
12989 E01013392 York 26925 21681 26382 17195
12990 E01013393 York 21051 6394 19895 18328
12991 E01013394 York 6877 10020 10191 16599
12992 E01013395 York 28524 10103 21838 15678
12993 E01013396 York 22654 4032 14611 15168
12994 E01013397 York 29103 16676 21446 15678
12995 E01013398 York 19465 28947 27517 18491
12996 E01013399 York 6177 11561 18292 19571
12997 E01013400 York 25011 11641 24569 19571
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12999 E01013402 York 32644 26914 18899 16144
13000 E01013403 York 25896 5278 24172 17075
13001 E01013404 York 13082 28060 21863 18835
13002 E01013405 York 29774 23348 26804 24782
13003 E01013406 York 21794 24734 16896 22088
13004 E01013407 York 25530 34369 30012 15778
13005 E01013408 York 30450 31324 40400 12671
13006 E01013409 York 24831 32188 37365 16540
13007 E01013410 York 7237 33300 22679 16699
13008 E01013411 York 29621 20939 30112 19801
13009 E01013412 York 21807 18236 20487 16578
13010 E01013413 York 31395 8670 14142 14485
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13012 E01013416 York 10354 4692 23666 15920
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13017 E01013421 York 25695 37935 23220 12812
13018 E01013422 York 28981 26690 14229 13704
13019 E01013423 York 32720 35657 6231 15660
13020 E01013424 York 32758 22778 23706 14790
13021 E01013425 York 29606 28547 15769 13974
13022 E01013426 York 29367 33794 15023 12129
13023 E01013427 York 32833 29674 16656 13332
13024 E01013428 York 24281 27563 24055 17984
13025 E01013429 York 28773 20117 15407 13201
13026 E01013430 York 29202 34882 9216 11114
13027 E01013431 York 27992 17359 27677 17791
13028 E01013432 York 30696 24389 16456 14009
13029 E01013433 York 32474 24289 11672 16364
13030 E01013434 York 25922 19932 11589 17094
13031 E01013435 York 29951 22771 16914 16895
13032 E01013436 York 31191 37260 15871 10649
13033 E01013437 York 14367 40223 37875 11314
13034 E01013438 York 27245 30726 12443 8723
13035 E01013439 York 31860 31758 2280 7967
13036 E01013440 York 32348 35650 29862 9753
13037 E01013441 York 17631 1077 38625 15168
13038 E01013442 York 18713 21003 23941 14403
13039 E01013443 York 3155 15856 24478 15105
13040 E01013444 York 6469 27984 34944 14249
13041 E01013445 York 8881 1467 32281 14486
13042 E01013446 York 14044 15931 32505 14403
13043 E01013447 York 8117 7530 27971 14403
13044 E01013448 York 5151 31916 33752 14452
13045 E01013449 York 18615 27952 28388 14382
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13047 E01013451 York 32317 39296 9430 11032
13048 E01013452 York 32779 41559 19897 11805
13049 E01013453 Derby 6073 13627 29763 30556
13050 E01013454 Derby 8187 11535 30246 29589
13051 E01013455 Derby 9307 21249 29017 27558
13052 E01013456 Derby 1646 11731 32511 31691
13053 E01013457 Derby 8766 11116 35746 28282
13054 E01013458 Derby 13075 16963 14839 28282
13055 E01013459 Derby 12807 11253 38071 26888
13056 E01013460 Derby 9920 10673 33682 31390
13057 E01013461 Derby 31295 20725 2431 27306
13058 E01013462 Derby 27757 25953 15235 24308
13059 E01013463 Derby 31832 13908 4754 22288
13060 E01013464 Derby 27687 24033 21865 27440
13061 E01013465 Derby 31236 24079 24851 22744
13062 E01013466 Derby 32465 22672 16404 26862
13063 E01013467 Derby 31093 23914 25409 31165
13064 E01013468 Derby 31604 22073 10704 30965
13065 E01013469 Derby 27422 19056 21812 28685
13066 E01013470 Derby 10374 19535 26497 32263
13067 E01013471 Derby 7044 14018 31830 35132
13068 E01013472 Derby 1809 19308 38329 31689
13069 E01013473 Derby 3676 3486 31647 33733
13070 E01013474 Derby 8010 11168 25206 29998
13071 E01013475 Derby 3485 9919 30431 33506
13072 E01013476 Derby 19528 22802 32940 30436
13073 E01013477 Derby 6190 9674 28704 34409
13074 E01013479 Derby 2150 1869 35680 35381
13075 E01013480 Derby 563 3440 34216 35417
13076 E01013481 Derby 2644 4683 35546 37186
13077 E01013483 Derby 5007 2153 37740 34263
13078 E01013484 Derby 839 3700 40646 37186
13079 E01013485 Derby 3040 2732 38303 34263
13080 E01013486 Derby 3283 11204 39889 36241
13081 E01013487 Derby 2464 8868 40750 33891
13082 E01013488 Derby 26785 29443 39485 27278
13083 E01013489 Derby 25113 33246 40232 23423
13084 E01013490 Derby 21713 32004 37120 23931
13085 E01013491 Derby 18938 17375 36274 27447
13086 E01013492 Derby 21943 32497 40126 24095
13087 E01013493 Derby 13329 24133 41003 26514
13088 E01013494 Derby 10005 32476 40067 24479
13089 E01013495 Derby 17262 33079 40379 28566
13090 E01013496 Derby 2111 30397 37442 27012
13091 E01013497 Derby 5219 11792 35155 29667
13092 E01013498 Derby 14262 27101 36872 26295
13093 E01013499 Derby 4887 18822 36523 28625
13094 E01013500 Derby 14339 20096 38534 25966
13095 E01013501 Derby 12707 19757 35982 29205
13096 E01013502 Derby 6885 17176 32452 31901
13097 E01013503 Derby 12973 11521 36221 29732
13098 E01013504 Derby 5245 12849 39190 29238
13099 E01013505 Derby 18107 20798 39542 32734
13100 E01013506 Derby 16431 24257 35537 32680
13101 E01013507 Derby 17759 21384 33986 33148
13102 E01013508 Derby 4783 29116 31828 33211
13103 E01013509 Derby 14402 28756 36854 35158
13104 E01013510 Derby 5746 29722 33508 34347
13105 E01013511 Derby 23144 29973 35498 34137
13106 E01013512 Derby 6534 30866 32123 35923
13107 E01013513 Derby 7737 27705 37105 31974
13108 E01013514 Derby 29017 26472 28637 30793
13109 E01013515 Derby 15290 30348 27468 30865
13110 E01013517 Derby 9480 24978 29730 30119
13111 E01013518 Derby 17739 22807 33815 30976
13112 E01013519 Derby 19288 19617 35311 30025
13113 E01013520 Derby 30777 30929 34197 31060
13114 E01013521 Derby 3570 24342 32646 30172
13115 E01013522 Derby 4886 3761 8159 32549
13116 E01013523 Derby 6393 3872 22327 34618
13117 E01013524 Derby 9400 1712 26308 32793
13118 E01013525 Derby 12500 28084 20074 33374
13119 E01013526 Derby 27079 28619 3138 30912
13120 E01013527 Derby 29692 20535 7075 32889
13121 E01013528 Derby 19403 7065 5809 33994
13122 E01013529 Derby 19552 17197 3526 32272
13123 E01013530 Derby 13596 29109 35861 32428
13124 E01013531 Derby 8208 27236 33724 33336
13125 E01013532 Derby 8932 24397 38224 33140
13126 E01013533 Derby 671 8080 28635 33968
13127 E01013534 Derby 12918 19263 39214 32583
13128 E01013535 Derby 1290 2986 28511 35136
13129 E01013536 Derby 1316 10495 32020 36664
13130 E01013537 Derby 12038 9412 34589 34652
13131 E01013538 Derby 4328 3277 34904 36107
13132 E01013539 Derby 32277 29628 41632 23489
13133 E01013540 Derby 25457 30167 41628 22149
13134 E01013541 Derby 17367 19633 41289 23035
13135 E01013542 Derby 14797 25384 37713 25555
13136 E01013543 Derby 29465 29755 38260 24809
13137 E01013544 Derby 30294 34683 36823 23902
13138 E01013545 Derby 16844 30914 27433 24224
13139 E01013546 Derby 26074 21717 30223 23869
13140 E01013547 Derby 8049 8851 11418 31459
13141 E01013548 Derby 8861 22969 17734 29224
13142 E01013549 Derby 7333 33326 29337 22535
13143 E01013550 Derby 3532 21532 14039 27937
13144 E01013551 Derby 14824 8949 23688 31459
13145 E01013552 Derby 5283 21141 23326 25384
13146 E01013553 Derby 9320 31383 25518 23690
13147 E01013554 Derby 6593 1768 23346 31459
13148 E01013555 Derby 12297 27381 35759 26260
13149 E01013556 Derby 30611 35406 41587 17627
13150 E01013557 Derby 30849 20367 40577 21000
13151 E01013558 Derby 23331 24782 40963 23780
13152 E01013559 Derby 29451 30029 41180 18750
13153 E01013560 Derby 31679 19190 40639 21047
13154 E01013561 Derby 29519 11680 39468 22382
13155 E01013562 Derby 21079 12238 40162 19289
13156 E01013563 Derby 28955 30364 41432 19289
13157 E01013564 Derby 31287 32008 40414 20169
13158 E01013565 Derby 5887 5574 40576 29180
13159 E01013566 Derby 1295 3752 41100 33128
13160 E01013567 Derby 2506 1269 41316 32475
13161 E01013568 Derby 2647 4570 41215 32696
13162 E01013569 Derby 4577 422 40121 33185
13163 E01013570 Derby 3717 2690 38502 32330
13164 E01013571 Derby 3641 3749 33821 30398
13165 E01013572 Derby 10274 21541 39910 30064
13166 E01013573 Derby 3108 2834 32844 29895
13167 E01013574 Derby 30330 35136 38607 31242
13168 E01013575 Derby 25607 34554 37906 30869
13169 E01013576 Derby 30942 34302 40440 30461
13170 E01013577 Derby 31107 34168 40644 30525
13171 E01013578 Derby 31586 36150 40855 30461
13172 E01013579 Derby 29354 33196 40618 31325
13173 E01013580 Derby 26404 25674 40952 31667
13174 E01013581 Derby 6097 27827 36272 32681
13175 E01013582 Derby 13437 27063 38485 32139
13176 E01013583 Derby 2072 13493 39838 28365
13177 E01013584 Derby 2001 34235 39678 28684
13178 E01013585 Derby 3869 35914 38878 28875
13179 E01013586 Derby 2572 32983 35418 31810
13180 E01013587 Derby 15463 36696 38664 29652
13181 E01013588 Derby 4494 26541 27211 29178
13182 E01013589 Derby 16684 34288 26651 26768
13183 E01013590 Derby 1461 21084 35592 34288
13184 E01013591 Derby 1208 21090 39683 34685
13185 E01013592 Derby 27957 6888 38689 31865
13186 E01013593 Derby 24778 27240 38490 29724
13187 E01013594 Derby 26130 20764 38665 32943
13188 E01013595 Derby 13518 24340 35255 32552
13189 E01013596 Derby 28948 14009 32944 32444
13190 E01013597 Derby 4200 22220 32861 30663
13191 E01013598 Derby 5950 29067 25768 27074
13192 E01013599 Derby 30773 24772 38618 31969
13193 E01013600 Leicester 1928 18862 29732 33731
13194 E01013601 Leicester 2692 17493 23741 33445
13195 E01013602 Leicester 2570 20699 17012 33815
13196 E01013603 Leicester 705 28708 9063 36110
13197 E01013604 Leicester 3391 12865 16142 32335
13198 E01013605 Leicester 7363 24154 19874 36110
13199 E01013606 Leicester 17825 5902 31684 33346
13200 E01013607 Leicester 12400 13622 25204 36243
13201 E01013608 Leicester 13974 11866 22002 29949
13202 E01013609 Leicester 17321 13549 11567 30543
13203 E01013610 Leicester 5435 17426 11062 29949
13204 E01013611 Leicester 5980 23703 3889 28940
13205 E01013612 Leicester 15515 9460 7383 31328
13206 E01013613 Leicester 7914 15464 20540 30804
13207 E01013614 Leicester 9182 13043 26777 30132
13208 E01013615 Leicester 21145 27275 35020 34014
13209 E01013616 Leicester 14181 19232 37494 35982
13210 E01013617 Leicester 11782 24061 30329 32373
13211 E01013618 Leicester 9568 7780 37003 33406
13212 E01013619 Leicester 1811 10515 26732 34408
13213 E01013620 Leicester 1077 11524 23858 32189
13214 E01013621 Leicester 1638 18718 26370 32542
13215 E01013622 Leicester 1600 13107 28161 32835
13216 E01013623 Leicester 13677 21416 26730 32006
13217 E01013624 Leicester 5712 15167 20544 38283
13218 E01013625 Leicester 8133 42 15565 37414
13219 E01013626 Leicester 8255 389 34061 37729
13220 E01013627 Leicester 17528 8189 27051 37729
13221 E01013628 Leicester 3513 12556 9602 37414
13222 E01013629 Leicester 10258 5142 27810 37240
13223 E01013630 Leicester 11102 116 32884 37240
13224 E01013631 Leicester 3615 14196 5231 35256
13225 E01013632 Leicester 304 30574 4803 36139
13226 E01013633 Leicester 1735 4387 14322 34005
13227 E01013634 Leicester 3309 10145 9366 34714
13228 E01013635 Leicester 8427 15651 11653 33257
13229 E01013636 Leicester 21155 15465 9993 32567
13230 E01013637 Leicester 2329 25663 19571 35300
13231 E01013638 Leicester 308 23768 20979 35856
13232 E01013639 Leicester 4778 15765 12677 33484
13233 E01013640 Leicester 887 30457 17464 37019
13234 E01013641 Leicester 8586 3414 20219 34823
13235 E01013642 Leicester 22540 4035 38974 34948
13236 E01013643 Leicester 24894 4709 34154 34699
13237 E01013646 Leicester 5490 1304 37032 36831
13238 E01013647 Leicester 7491 1728 33053 36433
13239 E01013648 Leicester 15696 3573 17870 34210
13240 E01013649 Leicester 15931 5582 31387 35410
13241 E01013650 Leicester 28199 5957 35331 34674
13242 E01013651 Leicester 2852 19895 32557 39114
13243 E01013652 Leicester 2554 20082 31516 38997
13244 E01013653 Leicester 2452 9788 34378 39309
13245 E01013654 Leicester 5020 1766 40027 38567
13246 E01013655 Leicester 6824 6385 41320 39389
13247 E01013656 Leicester 8925 2020 41519 39203
13248 E01013657 Leicester 5449 2209 40571 39203
13249 E01013658 Leicester 7862 1751 41643 39109
13250 E01013659 Leicester 8379 1715 41467 39203
13251 E01013660 Leicester 9272 9720 39326 37748
13252 E01013661 Leicester 2351 10647 29087 36629
13253 E01013662 Leicester 11212 5074 41659 38724
13254 E01013663 Leicester 11871 10861 41068 38557
13255 E01013664 Leicester 3250 14460 35484 36970
13256 E01013665 Leicester 12615 7978 41547 39109
13257 E01013666 Leicester 21733 9269 37458 26411
13258 E01013667 Leicester 5912 24635 29721 31677
13259 E01013668 Leicester 16647 20613 33513 34024
13260 E01013669 Leicester 22630 7738 38235 26004
13261 E01013670 Leicester 19673 17408 29621 29622
13262 E01013671 Leicester 14914 23167 27047 33947
13263 E01013672 Leicester 20000 18126 32931 30817
13264 E01013673 Leicester 2478 8693 18489 29794
13265 E01013674 Leicester 1024 7749 19713 27042
13266 E01013675 Leicester 2713 17312 14763 29917
13267 E01013676 Leicester 3093 17552 17901 25891
13268 E01013677 Leicester 1879 11467 17524 26093
13269 E01013678 Leicester 5112 12279 18924 29704
13270 E01013679 Leicester 1386 21991 21594 29963
13271 E01013680 Leicester 18544 7376 22638 35445
13272 E01013681 Leicester 6999 5359 26537 36168
13273 E01013682 Leicester 6902 10417 30259 34990
13274 E01013683 Leicester 6879 5327 26621 35956
13275 E01013684 Leicester 3407 2868 12533 36261
13276 E01013685 Leicester 21615 18837 17595 33957
13277 E01013686 Leicester 20692 13148 22908 34349
13278 E01013687 Leicester 5535 12207 15221 33110
13279 E01013688 Leicester 3227 11709 21075 30280
13280 E01013689 Leicester 13041 7101 37980 33309
13281 E01013690 Leicester 7406 11127 12851 32087
13282 E01013691 Leicester 203 12315 14545 30520
13283 E01013692 Leicester 361 18473 18972 32172
13284 E01013693 Leicester 172 7491 27487 30189
13285 E01013694 Leicester 5134 4694 20082 30506
13286 E01013695 Leicester 4135 22735 13907 29229
13287 E01013696 Leicester 12271 18094 14408 33838
13288 E01013697 Leicester 10848 16540 27399 36617
13289 E01013698 Leicester 8531 21402 11460 29785
13290 E01013699 Leicester 15440 15233 25171 36705
13291 E01013700 Leicester 14113 12446 20522 34549
13292 E01013702 Leicester 25576 11653 20685 33768
13293 E01013703 Leicester 29504 19282 21524 31970
13294 E01013704 Leicester 27265 22823 22004 29364
13295 E01013705 Leicester 11362 18323 21118 31631
13296 E01013706 Leicester 30561 22131 21422 29681
13297 E01013707 Leicester 27619 14779 31103 31762
13298 E01013709 Leicester 20293 13645 33832 31080
13299 E01013710 Leicester 17183 8376 25696 33001
13300 E01013711 Leicester 9857 12772 19527 33421
13301 E01013712 Leicester 22645 14788 21380 31357
13302 E01013713 Leicester 12036 479 33156 37485
13303 E01013714 Leicester 12773 2631 34650 38404
13304 E01013715 Leicester 10759 2067 32977 37121
13305 E01013716 Leicester 5618 6520 24275 37120
13306 E01013717 Leicester 12014 12219 29510 38574
13307 E01013718 Leicester 10444 3387 35688 38296
13308 E01013719 Leicester 9738 2199 29319 37485
13309 E01013720 Leicester 3319 10830 29073 38282
13310 E01013721 Leicester 5039 16981 21828 33956
13311 E01013722 Leicester 2332 11369 28035 33311
13312 E01013723 Leicester 3140 7794 23430 33311
13313 E01013725 Leicester 313 15202 9851 35203
13314 E01013726 Leicester 225 19941 16083 35067
13315 E01013727 Leicester 1847 24381 30946 36499
13316 E01013728 Leicester 1658 20329 19272 33997
13317 E01013729 Leicester 11141 17999 36676 34352
13318 E01013730 Leicester 338 26951 33340 36807
13319 E01013731 Leicester 7321 30065 31404 33497
13320 E01013732 Leicester 9151 22486 35291 38751
13321 E01013733 Leicester 14151 29880 33948 35087
13322 E01013734 Leicester 11886 22446 14906 35028
13323 E01013735 Leicester 16997 14971 26076 34826
13324 E01013736 Leicester 14900 28384 35095 35294
13325 E01013737 Leicester 15700 21137 31609 34724
13326 E01013738 Leicester 17469 13465 15922 35963
13327 E01013739 Leicester 6671 26791 21989 34896
13328 E01013740 Leicester 13144 29491 29462 37195
13329 E01013741 Leicester 13257 28417 35804 37848
13330 E01013742 Leicester 6725 820 40927 38381
13331 E01013743 Leicester 8206 1544 41059 38863
13332 E01013744 Leicester 8988 608 41243 38863
13333 E01013745 Leicester 9221 693 41091 38724
13334 E01013746 Leicester 3352 4577 40193 38567
13335 E01013747 Leicester 12434 7766 41621 37996
13336 E01013748 Leicester 2367 6239 39401 37337
13337 E01013749 Leicester 12405 16548 38565 37293
13338 E01013750 Leicester 9523 259 40978 38515
13339 E01013751 Leicester 9663 1899 41404 38340
13340 E01013752 Leicester 6146 678 41502 38515
13341 E01013753 Leicester 6053 10119 41293 37582
13342 E01013754 Leicester 2936 10060 16240 37297
13343 E01013755 Leicester 3149 5918 25359 37820
13344 E01013756 Leicester 14855 6462 32777 36906
13345 E01013757 Leicester 16779 17636 37404 33349
13346 E01013758 Leicester 12814 5195 41057 38160
13347 E01013759 Leicester 19806 10077 37101 35308
13348 E01013760 Leicester 4408 2981 40050 36673
13349 E01013761 Leicester 4264 7657 41124 36673
13350 E01013762 Leicester 7304 1092 41614 38160
13351 E01013763 Leicester 8738 6014 40243 36673
13352 E01013764 Leicester 17868 15481 39098 37114
13353 E01013765 Leicester 7312 4824 41545 38160
13354 E01013766 Leicester 17297 8583 40013 35308
13355 E01013767 Leicester 12684 19202 25562 29057
13356 E01013768 Leicester 4585 16437 25132 28694
13357 E01013770 Leicester 13405 17677 25896 33384
13358 E01013771 Leicester 16760 16021 34610 36182
13359 E01013772 Leicester 7372 7891 32042 27647
13360 E01013773 Leicester 9280 21706 28126 33384
13361 E01013774 Leicester 7942 367 14202 36058
13362 E01013775 Leicester 12947 8729 19958 34539
13363 E01013776 Leicester 7493 1401 21835 36509
13364 E01013777 Leicester 7109 2410 32067 34873
13365 E01013778 Leicester 8762 1238 9579 36595
13366 E01013779 Leicester 8891 517 19685 36058
13367 E01013780 Leicester 23106 15366 26864 33484
13368 E01013781 Leicester 4610 5068 25609 35566
13369 E01013782 Leicester 12302 4668 20215 34799
13370 E01013783 Leicester 23493 14683 21787 34799
13371 E01013784 Leicester 14674 4563 20349 34823
13372 E01013785 Leicester 18797 26122 17110 35067
13373 E01013786 Leicester 10189 14598 31388 34766
13374 E01013787 Rutland 19612 39920 4482 10085
13375 E01013788 Rutland 28543 38919 10597 14082
13376 E01013789 Rutland 21199 39424 5776 12855
13377 E01013790 Rutland 14267 40879 25936 16210
13378 E01013791 Rutland 23764 38628 1494 18739
13379 E01013792 Rutland 25453 40616 410 14888
13380 E01013793 Rutland 31646 35283 30541 12719
13381 E01013794 Rutland 22224 39597 8971 11374
13382 E01013795 Rutland 21352 40338 6549 11946
13383 E01013796 Rutland 30614 38169 4711 13379
13384 E01013797 Rutland 32120 41124 7736 13830
13385 E01013798 Rutland 32010 30346 15475 18387
13386 E01013799 Rutland 24291 842 36533 15571
13387 E01013800 Rutland 28296 18775 29007 10489
13388 E01013801 Rutland 19402 22117 36275 12250
13389 E01013802 Rutland 30156 19375 9239 14723
13390 E01013803 Rutland 31266 21200 24121 11901
13391 E01013804 Rutland 29700 37312 507 21412
13392 E01013805 Rutland 24043 36878 2195 18829
13393 E01013806 Rutland 30565 27836 29298 10352
13394 E01013807 Rutland 27558 26642 30772 13362
13395 E01013808 Rutland 23849 24711 27602 11574
13396 E01013809 Rutland 29678 40577 7225 12396
13397 E01013810 Nottingham 1767 2613 38767 34711
13398 E01013811 Nottingham 1688 562 37478 35428
13399 E01013812 Nottingham 1042 20 38619 34523
13400 E01013813 Nottingham 6329 3845 31261 37711
13401 E01013814 Nottingham 3499 3994 39737 36228
13402 E01013815 Nottingham 3805 10502 29391 36620
13403 E01013816 Nottingham 13429 1178 39083 38562
13404 E01013817 Nottingham 594 14469 37935 30882
13405 E01013818 Nottingham 265 13912 36189 32721
13406 E01013819 Nottingham 1860 3622 32058 32407
13407 E01013820 Nottingham 1432 5533 31742 31166
13408 E01013821 Nottingham 1197 8267 30536 30191
13409 E01013822 Nottingham 1266 9019 38395 30191
13410 E01013823 Nottingham 3496 4356 28447 32370
13411 E01013824 Nottingham 2823 5090 29847 31434
13412 E01013825 Nottingham 2787 7798 32698 32407
13413 E01013826 Nottingham 1298 14308 34454 30882
13414 E01013827 Nottingham 4521 11974 34531 35123
13415 E01013828 Nottingham 8583 11590 40752 34351
13416 E01013829 Nottingham 5949 13998 38841 33862
13417 E01013830 Nottingham 8218 4391 35678 33058
13418 E01013831 Nottingham 16023 22569 38686 33463
13419 E01013832 Nottingham 5713 4926 39171 33944
13420 E01013833 Nottingham 3018 8158 27284 33962
13421 E01013834 Nottingham 4118 14153 27908 33234
13422 E01013835 Nottingham 4710 10463 34073 34386
13423 E01013836 Nottingham 4860 13251 41527 33634
13424 E01013837 Nottingham 19695 11519 39126 35891
13425 E01013838 Nottingham 16531 11551 37748 35134
13426 E01013839 Nottingham 2317 3665 41584 35153
13427 E01013840 Nottingham 16751 12886 40182 35153
13428 E01013841 Nottingham 2577 2716 41264 35281
13429 E01013842 Nottingham 3522 12090 41332 35007
13430 E01013843 Nottingham 7309 3312 38429 36158
13431 E01013844 Nottingham 3253 3029 40562 36158
13432 E01013845 Nottingham 4273 6946 41557 35428
13433 E01013846 Nottingham 2859 4039 40430 35428
13434 E01013847 Nottingham 4065 4929 40957 36158
13435 E01013849 Nottingham 1521 26139 32113 31961
13436 E01013850 Nottingham 2209 9397 33478 33439
13437 E01013851 Nottingham 847 22286 27679 31811
13438 E01013852 Nottingham 4127 12967 31702 31668
13439 E01013853 Nottingham 5000 12654 31710 33274
13440 E01013854 Nottingham 3891 16916 30395 33204
13441 E01013855 Nottingham 2553 12801 27654 32850
13442 E01013856 Nottingham 6493 11522 33021 33660
13443 E01013858 Nottingham 5301 6458 23141 32067
13444 E01013859 Nottingham 1997 24080 29303 30470
13445 E01013860 Nottingham 1992 10767 23884 30897
13446 E01013861 Nottingham 145 20612 28887 30101
13447 E01013862 Nottingham 2003 24444 17988 32755
13448 E01013863 Nottingham 9387 20440 15239 32755
13449 E01013864 Nottingham 2885 21752 38838 33047
13450 E01013865 Nottingham 2366 6750 33398 33520
13451 E01013866 Nottingham 3330 5837 31248 32486
13452 E01013867 Nottingham 2191 13402 34214 30907
13453 E01013868 Nottingham 1471 8039 23003 30897
13454 E01013870 Nottingham 4715 21222 9546 38186
13455 E01013871 Nottingham 1743 5033 6722 38067
13456 E01013872 Nottingham 5602 9411 3780 36951
13457 E01013873 Nottingham 8329 2703 22380 36936
13458 E01013874 Nottingham 8936 5492 18155 34442
13459 E01013875 Nottingham 17550 34047 35448 34223
13460 E01013876 Nottingham 1577 27435 37438 33701
13461 E01013877 Nottingham 130 26328 38933 34566
13462 E01013878 Nottingham 1963 30279 31649 35260
13463 E01013879 Nottingham 813 20700 12732 29944
13464 E01013880 Nottingham 872 16440 30294 33909
13465 E01013881 Nottingham 1113 19551 15539 31929
13466 E01013882 Nottingham 2175 6835 33081 32614
13467 E01013883 Nottingham 2876 30107 36524 34479
13468 E01013884 Nottingham 2184 30267 29492 34953
13469 E01013885 Nottingham 1188 3785 40653 33509
13470 E01013886 Nottingham 4236 9710 28331 32181
13471 E01013887 Nottingham 18714 6646 36131 31626
13472 E01013888 Nottingham 7173 6321 39541 32315
13473 E01013889 Nottingham 13592 12237 37627 32713
13474 E01013890 Nottingham 10108 8723 40641 32315
13475 E01013891 Nottingham 3169 8455 38281 33459
13476 E01013892 Nottingham 19225 8419 31688 31372
13477 E01013893 Nottingham 4353 27054 35530 33268
13478 E01013894 Nottingham 15941 18590 32098 31977
13479 E01013895 Nottingham 18523 31131 3685 31573
13480 E01013896 Nottingham 2889 19118 19569 32086
13481 E01013897 Nottingham 4404 4552 15478 31458
13482 E01013898 Nottingham 13243 12454 14625 30599
13483 E01013899 Nottingham 5513 10885 8152 30087
13484 E01013900 Nottingham 4215 16395 6305 28202
13485 E01013901 Nottingham 26632 32163 7844 36034
13486 E01013902 Nottingham 22415 32557 13186 31573
13487 E01013903 Nottingham 11195 23765 24867 31630
13488 E01013904 Nottingham 5440 14993 10327 30389
13489 E01013905 Nottingham 3927 22505 13076 30801
13490 E01013906 Nottingham 6155 7748 5456 27463
13491 E01013907 Nottingham 4587 6640 18652 30389
13492 E01013908 Nottingham 4386 27981 14519 29840
13493 E01013909 Nottingham 1575 33570 22809 30524
13494 E01013910 Nottingham 5057 17369 2489 30023
13495 E01013911 Nottingham 5778 21656 2185 27696
13496 E01013912 Nottingham 12738 26372 9760 30775
13497 E01013913 Nottingham 14607 8519 35672 34767
13498 E01013914 Nottingham 16389 8720 38506 34649
13499 E01013915 Nottingham 9698 18474 35504 31950
13500 E01013916 Nottingham 3318 12361 25497 35289
13501 E01013917 Nottingham 4980 11504 11006 34316
13502 E01013918 Nottingham 3579 6757 36235 36690
13503 E01013919 Nottingham 2861 3828 33356 38116
13504 E01013920 Nottingham 2974 13565 34990 33343
13505 E01013921 Nottingham 1526 3787 33068 34420
13506 E01013924 Nottingham 12700 3351 25044 38203
13507 E01013926 Nottingham 9473 11120 13234 36311
13508 E01013928 Nottingham 18077 34280 31860 35396
13509 E01013929 Nottingham 10586 9346 34076 30230
13510 E01013930 Nottingham 8405 17136 38677 34090
13511 E01013931 Nottingham 14398 13558 34379 32380
13512 E01013932 Nottingham 9641 13759 36888 31320
13513 E01013933 Nottingham 4737 7033 5976 30255
13514 E01013934 Nottingham 10833 14524 33178 33840
13515 E01013935 Nottingham 17018 11713 38481 34252
13516 E01013936 Nottingham 10225 20750 37636 34555
13517 E01013937 Nottingham 13370 10810 27252 35552
13518 E01013938 Nottingham 12854 5621 15466 36158
13519 E01013939 Nottingham 9357 16637 34569 35663
13520 E01013940 Nottingham 2305 30734 28005 35250
13521 E01013941 Nottingham 11411 3228 17103 36158
13522 E01013942 Nottingham 2607 23641 31599 35095
13523 E01013943 Nottingham 3549 6722 20833 36554
13524 E01013944 Nottingham 7026 7622 35727 33362
13525 E01013945 Nottingham 3727 3326 33722 34523
13526 E01013947 Nottingham 2594 10282 29246 34331
13527 E01013948 Nottingham 207 3793 28891 36899
13528 E01013953 Nottingham 21258 5460 28672 38203
13529 E01013954 Nottingham 2290 1733 30888 38332
13530 E01013957 Nottingham 4697 1299 20991 37640
13531 E01013958 Nottingham 1796 11126 24377 37760
13532 E01013959 Nottingham 1705 19122 29135 38068
13533 E01013960 Nottingham 800 5862 25014 38068
13534 E01013961 Nottingham 5760 4836 36568 37285
13535 E01013962 Nottingham 3525 11371 24149 36941
13536 E01013963 Nottingham 3992 14278 30955 33714
13537 E01013964 Nottingham 11001 21034 33305 34779
13538 E01013965 Nottingham 6435 2505 31223 34629
13539 E01013966 Nottingham 4935 6474 34250 35577
13540 E01013967 Nottingham 10934 5058 37676 34779
13541 E01013968 Nottingham 16487 5559 26165 35097
13542 E01013969 Nottingham 11081 945 41428 35372
13543 E01013970 Nottingham 17336 6995 40919 35863
13544 E01013971 Nottingham 9206 2039 39301 35931
13545 E01013972 Nottingham 6814 4622 40216 36158
13546 E01013973 Nottingham 14528 19743 6112 34986
13547 E01013974 Nottingham 11399 12351 5385 34777
13548 E01013975 Nottingham 22177 21494 4722 34049
13549 E01013976 Nottingham 6722 15669 3361 33364
13550 E01013977 Nottingham 21357 19848 6299 31922
13551 E01013978 Nottingham 16881 8923 5382 29246
13552 E01013979 Nottingham 27054 1820 3802 32311
13553 E01013980 Nottingham 27711 19534 8924 30213
13554 E01013981 Nottingham 28344 27042 879 29736
13555 E01013982 Nottingham 29073 15026 6512 30340
13556 E01013983 Nottingham 8773 17005 11120 30373
13557 E01013984 Nottingham 30163 8370 24021 30074
13558 E01013985 Nottingham 29645 19858 14972 29479
13559 E01013986 Herefordshire, County of 13600 22577 23603 17192
13560 E01013987 Herefordshire, County of 26371 24957 7142 15981
13561 E01013988 Herefordshire, County of 24315 19341 8435 15699
13562 E01013989 Herefordshire, County of 11851 28584 27287 18875
13563 E01013990 Herefordshire, County of 23230 39193 1677 7101
13564 E01013991 Herefordshire, County of 13393 40650 3250 6225
13565 E01013992 Herefordshire, County of 8804 21963 5765 7162
13566 E01013993 Herefordshire, County of 5081 22737 12064 6661
13567 E01013994 Herefordshire, County of 5027 21529 16282 11243
13568 E01013995 Herefordshire, County of 2871 12579 17119 8469
13569 E01013996 Herefordshire, County of 24147 23880 10677 9258
13570 E01013997 Herefordshire, County of 25748 25785 6795 6835
13571 E01013998 Herefordshire, County of 22031 40603 22445 4586
13572 E01013999 Herefordshire, County of 20658 39629 1698 5188
13573 E01014000 Herefordshire, County of 14000 40451 7295 5932
13574 E01014001 Herefordshire, County of 13109 39475 1399 6451
13575 E01014002 Herefordshire, County of 24040 21950 7019 7248
13576 E01014003 Herefordshire, County of 12394 25299 3234 6337
13577 E01014004 Herefordshire, County of 13420 41245 2636 6408
13578 E01014005 Herefordshire, County of 6955 6455 15556 8588
13579 E01014006 Herefordshire, County of 21288 39509 26642 6448
13580 E01014007 Herefordshire, County of 22923 33708 19365 12639
13581 E01014008 Herefordshire, County of 14449 41077 3814 4153
13582 E01014009 Herefordshire, County of 13293 41342 4076 3324
13583 E01014010 Herefordshire, County of 8153 56 38203 16982
13584 E01014011 Herefordshire, County of 12649 299 19445 15025
13585 E01014012 Herefordshire, County of 20470 37030 9433 6074
13586 E01014013 Herefordshire, County of 21532 37392 19614 5839
13587 E01014014 Herefordshire, County of 13636 41072 6947 7104
13588 E01014015 Herefordshire, County of 11781 40722 4901 7043
13589 E01014016 Herefordshire, County of 10671 38661 8656 5621
13590 E01014017 Herefordshire, County of 13989 40742 1518 5533
13591 E01014018 Herefordshire, County of 14208 41475 771 3252
13592 E01014019 Herefordshire, County of 13744 41229 2303 3747
13593 E01014020 Herefordshire, County of 13462 41612 1137 3284
13594 E01014021 Herefordshire, County of 16083 39605 1267 4032
13595 E01014022 Herefordshire, County of 28588 37407 4521 9624
13596 E01014023 Herefordshire, County of 17832 39362 13068 8289
13597 E01014024 Herefordshire, County of 11614 41076 1786 5034
13598 E01014025 Herefordshire, County of 13261 41008 1673 5657
13599 E01014026 Herefordshire, County of 12562 38662 12530 6474
13600 E01014027 Herefordshire, County of 11714 40285 12657 7269
13601 E01014028 Herefordshire, County of 21325 36414 6621 6315
13602 E01014029 Herefordshire, County of 23173 28784 19894 7035
13603 E01014030 Herefordshire, County of 22775 38238 1211 6395
13604 E01014031 Herefordshire, County of 13631 40521 5812 6363
13605 E01014032 Herefordshire, County of 16442 39055 3731 8048
13606 E01014033 Herefordshire, County of 12002 37259 1009 3358
13607 E01014034 Herefordshire, County of 11153 29791 6035 3501
13608 E01014035 Herefordshire, County of 13561 11822 22816 13870
13609 E01014036 Herefordshire, County of 23031 36741 7040 8557
13610 E01014037 Herefordshire, County of 22305 23069 22490 11098
13611 E01014038 Herefordshire, County of 14003 29619 18183 9467
13612 E01014039 Herefordshire, County of 29900 34510 5454 15667
13613 E01014040 Herefordshire, County of 23148 23145 7256 10702
13614 E01014041 Herefordshire, County of 15369 14238 9929 8111
13615 E01014042 Herefordshire, County of 4154 22658 15143 7259
13616 E01014043 Herefordshire, County of 25828 30400 11054 6075
13617 E01014044 Herefordshire, County of 10772 35638 11368 5731
13618 E01014045 Herefordshire, County of 15213 36010 13107 5806
13619 E01014046 Herefordshire, County of 15283 26985 5337 5236
13620 E01014047 Herefordshire, County of 5154 11383 13853 6473
13621 E01014048 Herefordshire, County of 3288 9688 29903 8031
13622 E01014049 Herefordshire, County of 16251 39244 9274 7440
13623 E01014050 Herefordshire, County of 15453 41035 2903 5150
13624 E01014051 Herefordshire, County of 16528 41161 2610 3665
13625 E01014052 Herefordshire, County of 13371 41394 1386 3725
13626 E01014053 Herefordshire, County of 17137 40781 8448 7389
13627 E01014054 Herefordshire, County of 16811 41218 11162 6200
13628 E01014055 Herefordshire, County of 16571 41120 1322 4663
13629 E01014056 Herefordshire, County of 13318 40217 5159 3844
13630 E01014057 Herefordshire, County of 13591 39038 6914 8740
13631 E01014058 Herefordshire, County of 18583 39353 5168 8495
13632 E01014059 Herefordshire, County of 14818 41332 3345 4782
13633 E01014060 Herefordshire, County of 14908 39361 19381 5555
13634 E01014061 Herefordshire, County of 25624 32203 18799 11343
13635 E01014062 Herefordshire, County of 15224 9259 14949 11395
13636 E01014063 Herefordshire, County of 16298 23923 9805 12937
13637 E01014064 Herefordshire, County of 6448 28721 10708 13002
13638 E01014065 Herefordshire, County of 16018 33343 4430 13002
13639 E01014066 Herefordshire, County of 13995 4520 4301 11389
13640 E01014067 Herefordshire, County of 30418 34638 20917 13725
13641 E01014068 Herefordshire, County of 12983 16072 9138 10012
13642 E01014069 Herefordshire, County of 18325 33094 4240 9638
13643 E01014070 Herefordshire, County of 15560 20496 21403 9894
13644 E01014071 Herefordshire, County of 4082 18462 21880 12213
13645 E01014072 Herefordshire, County of 9392 24785 19467 7832
13646 E01014073 Herefordshire, County of 8967 26156 6198 9012
13647 E01014074 Herefordshire, County of 5958 6431 15775 12140
13648 E01014075 Herefordshire, County of 21813 15011 14576 12327
13649 E01014076 Herefordshire, County of 15558 5232 32543 12327
13650 E01014077 Herefordshire, County of 26222 27762 28767 8236
13651 E01014078 Herefordshire, County of 18019 18001 28949 10275
13652 E01014079 Herefordshire, County of 16381 40178 10952 5029
13653 E01014080 Herefordshire, County of 20195 37923 2799 6190
13654 E01014081 Herefordshire, County of 20480 41260 1868 7592
13655 E01014082 Herefordshire, County of 22234 41463 2873 7057
13656 E01014083 Herefordshire, County of 27517 31289 28273 7971
13657 E01014084 Herefordshire, County of 16778 19243 38583 15832
13658 E01014085 Herefordshire, County of 11009 23714 23811 10728
13659 E01014086 Herefordshire, County of 10111 6048 32653 19430
13660 E01014087 Herefordshire, County of 24110 33992 36486 9588
13661 E01014088 Herefordshire, County of 18141 33586 35143 15564
13662 E01014089 Herefordshire, County of 17699 32800 37007 13566
13663 E01014090 Herefordshire, County of 31845 20580 6230 13869
13664 E01014091 Herefordshire, County of 30071 19638 3395 14727
13665 E01014092 Herefordshire, County of 18852 5505 10912 12049
13666 E01014093 Herefordshire, County of 22164 27600 1928 14872
13667 E01014094 Herefordshire, County of 28569 22613 5263 13956
13668 E01014095 Herefordshire, County of 16642 20056 7284 14830
13669 E01014096 Herefordshire, County of 14911 40671 6166 4896
13670 E01014097 Herefordshire, County of 13065 39249 1152 5416
13671 E01014098 Herefordshire, County of 12251 38612 9167 5438
13672 E01014099 Herefordshire, County of 13447 39897 4603 5193
13673 E01014100 Herefordshire, County of 22197 40848 7419 5553
13674 E01014101 Herefordshire, County of 14467 40850 6670 4795
13675 E01014102 Telford and Wrekin 29566 32331 17602 15075
13676 E01014103 Telford and Wrekin 26267 18607 26013 16857
13677 E01014104 Telford and Wrekin 8269 31681 36283 9590
13678 E01014105 Telford and Wrekin 6330 26053 37424 12112
13679 E01014106 Telford and Wrekin 7957 34684 30960 12390
13680 E01014107 Telford and Wrekin 21296 32767 20281 11806
13681 E01014108 Telford and Wrekin 346 32404 16007 13610
13682 E01014109 Telford and Wrekin 11092 29483 7509 17145
13683 E01014110 Telford and Wrekin 747 36099 20911 12390
13684 E01014111 Telford and Wrekin 25459 38415 15424 13439
13685 E01014112 Telford and Wrekin 23917 31550 11647 10817
13686 E01014113 Telford and Wrekin 2211 14138 39543 13862
13687 E01014114 Telford and Wrekin 20184 9654 27945 17679
13688 E01014115 Telford and Wrekin 2582 33639 39873 10065
13689 E01014116 Telford and Wrekin 2767 32777 32651 13828
13690 E01014117 Telford and Wrekin 16841 33205 38705 7472
13691 E01014118 Telford and Wrekin 409 31647 40215 8844
13692 E01014119 Telford and Wrekin 16952 22582 15589 10781
13693 E01014120 Telford and Wrekin 2750 11935 14849 9305
13694 E01014121 Telford and Wrekin 11331 28850 8418 9398
13695 E01014122 Telford and Wrekin 12385 27332 5789 10539
13696 E01014123 Telford and Wrekin 24810 29088 10654 10539
13697 E01014124 Telford and Wrekin 2137 2841 15523 10924
13698 E01014125 Telford and Wrekin 3989 20812 35446 21289
13699 E01014126 Telford and Wrekin 7714 14055 35497 18693
13700 E01014127 Telford and Wrekin 3209 15904 35737 17406
13701 E01014128 Telford and Wrekin 12981 16824 34593 18374
13702 E01014129 Telford and Wrekin 9375 28081 4727 15360
13703 E01014130 Telford and Wrekin 23015 29268 6254 15231
13704 E01014131 Telford and Wrekin 23555 40268 3213 7745
13705 E01014132 Telford and Wrekin 31279 37358 12291 8865
13706 E01014133 Telford and Wrekin 16863 22161 32307 11885
13707 E01014134 Telford and Wrekin 27424 31990 31637 11100
13708 E01014135 Telford and Wrekin 18204 40232 663 8858
13709 E01014136 Telford and Wrekin 12565 40043 8368 7530
13710 E01014137 Telford and Wrekin 22359 36519 34272 20631
13711 E01014138 Telford and Wrekin 11899 35295 16735 16891
13712 E01014139 Telford and Wrekin 6789 31192 34005 19343
13713 E01014140 Telford and Wrekin 6436 35587 29238 18301
13714 E01014141 Telford and Wrekin 13813 33144 29953 20242
13715 E01014142 Telford and Wrekin 1480 28363 31980 19834
13716 E01014143 Telford and Wrekin 6842 19353 30674 20037
13717 E01014144 Telford and Wrekin 4360 26516 28093 14576
13718 E01014145 Telford and Wrekin 7383 9513 39791 13315
13719 E01014146 Telford and Wrekin 21024 36202 25746 8488
13720 E01014147 Telford and Wrekin 22159 32388 24801 9121
13721 E01014148 Telford and Wrekin 21498 30464 173 9525
13722 E01014149 Telford and Wrekin 10068 34379 974 7925
13723 E01014150 Telford and Wrekin 20631 30422 18105 13211
13724 E01014151 Telford and Wrekin 5680 28256 20375 16286
13725 E01014152 Telford and Wrekin 6663 27225 13460 21684
13726 E01014153 Telford and Wrekin 9336 10155 24507 18564
13727 E01014154 Telford and Wrekin 12579 34113 24889 16386
13728 E01014155 Telford and Wrekin 9793 34935 32190 15865
13729 E01014156 Telford and Wrekin 10711 30536 39153 10602
13730 E01014157 Telford and Wrekin 22773 14647 28581 13188
13731 E01014158 Telford and Wrekin 13305 28672 23099 12080
13732 E01014159 Telford and Wrekin 6811 15490 20470 11544
13733 E01014160 Telford and Wrekin 19860 19654 19033 11544
13734 E01014161 Telford and Wrekin 10550 24490 6659 12004
13735 E01014162 Telford and Wrekin 2610 9822 28339 11069
13736 E01014163 Telford and Wrekin 980 28383 26078 12670
13737 E01014164 Telford and Wrekin 951 9015 29131 12414
13738 E01014165 Telford and Wrekin 2658 24077 12622 13249
13739 E01014166 Telford and Wrekin 8398 21812 27242 13104
13740 E01014167 Telford and Wrekin 24414 34033 34268 16671
13741 E01014168 Telford and Wrekin 30689 26263 36407 19141
13742 E01014169 Telford and Wrekin 12254 26825 34951 17372
13743 E01014170 Telford and Wrekin 28054 34493 39773 18179
13744 E01014171 Telford and Wrekin 17417 23789 19735 10042
13745 E01014172 Telford and Wrekin 29473 29893 23377 10753
13746 E01014173 Telford and Wrekin 17035 24168 5902 9179
13747 E01014174 Telford and Wrekin 30618 35257 8344 10097
13748 E01014175 Telford and Wrekin 16665 19017 22388 10898
13749 E01014176 Telford and Wrekin 26215 11445 28542 11899
13750 E01014177 Telford and Wrekin 29052 14874 21616 10046
13751 E01014178 Telford and Wrekin 17222 7981 28011 9614
13752 E01014179 Telford and Wrekin 23801 25005 20187 16530
13753 E01014180 Telford and Wrekin 16324 23102 13168 17663
13754 E01014181 Telford and Wrekin 32365 34262 16358 24611
13755 E01014182 Telford and Wrekin 32242 35030 8926 24632
13756 E01014183 Telford and Wrekin 29853 31189 10310 20494
13757 E01014184 Telford and Wrekin 16945 34289 15351 19381
13758 E01014185 Telford and Wrekin 3765 29571 16477 19365
13759 E01014186 Telford and Wrekin 15273 33194 14498 20095
13760 E01014187 Telford and Wrekin 11217 30913 16319 21579
13761 E01014188 Telford and Wrekin 24114 33399 24208 19925
13762 E01014189 Telford and Wrekin 19564 24176 16552 12488
13763 E01014190 Telford and Wrekin 30303 22189 12697 13992
13764 E01014191 Telford and Wrekin 11347 21590 15894 13615
13765 E01014192 Telford and Wrekin 9882 31693 19772 20252
13766 E01014193 Telford and Wrekin 4441 34078 27418 16109
13767 E01014194 Telford and Wrekin 8234 35632 7578 13050
13768 E01014195 Telford and Wrekin 22802 35962 11794 15620
13769 E01014196 Telford and Wrekin 5510 21260 22230 15396
13770 E01014197 Telford and Wrekin 1385 7301 29114 11070
13771 E01014198 Telford and Wrekin 541 22210 33232 11598
13772 E01014199 Telford and Wrekin 5203 31275 19280 10599
13773 E01014200 Telford and Wrekin 1058 29736 28768 11924
13774 E01014201 Telford and Wrekin 832 33446 26614 11046
13775 E01014202 Telford and Wrekin 22785 36913 11762 8286
13776 E01014203 Telford and Wrekin 24470 33792 23442 13694
13777 E01014204 Telford and Wrekin 21268 38286 7806 9392
13778 E01014205 Telford and Wrekin 21097 31687 20097 26665
13779 E01014206 Telford and Wrekin 12714 33046 26456 26836
13780 E01014207 Telford and Wrekin 16669 31714 15012 26665
13781 E01014208 Telford and Wrekin 4839 26003 26295 22801
13782 E01014209 Telford and Wrekin 12758 28203 7582 23240
13783 E01014210 Stoke-on-Trent 2167 5170 28815 32690
13784 E01014211 Stoke-on-Trent 1380 9990 31566 30239
13785 E01014212 Stoke-on-Trent 1968 21509 31181 28898
13786 E01014213 Stoke-on-Trent 2283 16016 16421 32987
13787 E01014214 Stoke-on-Trent 24361 27171 2984 21481
13788 E01014215 Stoke-on-Trent 18358 23008 16683 23921
13789 E01014216 Stoke-on-Trent 19207 24523 31746 26539
13790 E01014217 Stoke-on-Trent 1373 13128 20407 28251
13791 E01014218 Stoke-on-Trent 1355 15843 34144 26420
13792 E01014219 Stoke-on-Trent 12930 14060 32524 28734
13793 E01014220 Stoke-on-Trent 940 18032 29515 24006
13794 E01014221 Stoke-on-Trent 1957 14086 33162 25902
13795 E01014222 Stoke-on-Trent 603 6997 29331 26667
13796 E01014223 Stoke-on-Trent 674 22817 28102 26449
13797 E01014224 Stoke-on-Trent 445 14585 33212 28860
13798 E01014225 Stoke-on-Trent 17335 21682 36975 25463
13799 E01014226 Stoke-on-Trent 4918 16186 35884 29832
13800 E01014228 Stoke-on-Trent 18611 22276 40724 30670
13801 E01014229 Stoke-on-Trent 2441 24310 34709 29090
13802 E01014230 Stoke-on-Trent 5409 22041 24494 31137
13803 E01014231 Stoke-on-Trent 2777 5432 34795 33759
13804 E01014233 Stoke-on-Trent 15899 22668 8094 20637
13805 E01014234 Stoke-on-Trent 3750 27485 30393 22709
13806 E01014235 Stoke-on-Trent 5284 10782 17819 20637
13807 E01014236 Stoke-on-Trent 7417 25062 22850 19626
13808 E01014237 Stoke-on-Trent 1629 10644 25839 19604
13809 E01014238 Stoke-on-Trent 1354 32110 30159 17766
13810 E01014239 Stoke-on-Trent 13254 22398 36658 23312
13811 E01014240 Stoke-on-Trent 8163 22912 34603 22569
13812 E01014241 Stoke-on-Trent 4612 8525 30412 29980
13813 E01014242 Stoke-on-Trent 2970 26888 14236 29980
13814 E01014243 Stoke-on-Trent 12659 22570 32201 33046
13815 E01014244 Stoke-on-Trent 967 22803 17921 33096
13816 E01014245 Stoke-on-Trent 10162 13129 29864 33300
13817 E01014246 Stoke-on-Trent 2501 5165 19344 33337
13818 E01014247 Stoke-on-Trent 3460 1915 37269 32535
13819 E01014248 Stoke-on-Trent 3449 7490 38724 33337
13820 E01014249 Stoke-on-Trent 1048 8178 36403 33027
13821 E01014250 Stoke-on-Trent 772 6133 18431 30333
13822 E01014251 Stoke-on-Trent 1364 2889 32162 32490
13823 E01014252 Stoke-on-Trent 5430 13706 27060 32199
13824 E01014253 Stoke-on-Trent 12908 11450 9855 31899
13825 E01014254 Stoke-on-Trent 814 3336 35768 34031
13826 E01014255 Stoke-on-Trent 2591 7399 21750 32131
13827 E01014256 Stoke-on-Trent 2362 10660 16277 33125
13828 E01014257 Stoke-on-Trent 7976 31506 32463 22586
13829 E01014258 Stoke-on-Trent 26441 33240 38517 21750
13830 E01014259 Stoke-on-Trent 10754 18445 39166 25909
13831 E01014260 Stoke-on-Trent 3153 20742 29269 25971
13832 E01014261 Stoke-on-Trent 1016 19218 32141 26559
13833 E01014262 Stoke-on-Trent 3372 13099 26631 30410
13834 E01014263 Stoke-on-Trent 3232 25457 23619 29199
13835 E01014264 Stoke-on-Trent 17272 29952 37308 22020
13836 E01014265 Stoke-on-Trent 27170 19101 30753 26198
13837 E01014266 Stoke-on-Trent 3132 5675 23850 32701
13838 E01014267 Stoke-on-Trent 17010 29044 22432 27045
13839 E01014268 Stoke-on-Trent 10114 15592 19296 29585
13840 E01014269 Stoke-on-Trent 1591 24006 5796 27374
13841 E01014270 Stoke-on-Trent 18365 10321 17262 30225
13842 E01014271 Stoke-on-Trent 10994 19986 6945 28844
13843 E01014272 Stoke-on-Trent 22900 20110 27155 22092
13844 E01014273 Stoke-on-Trent 1007 10853 41409 27900
13845 E01014274 Stoke-on-Trent 3851 5303 31061 33928
13846 E01014275 Stoke-on-Trent 817 3615 29916 38007
13847 E01014276 Stoke-on-Trent 6256 5315 16087 38007
13848 E01014277 Stoke-on-Trent 9777 21571 7371 29690
13849 E01014278 Stoke-on-Trent 4061 16758 39877 29924
13850 E01014279 Stoke-on-Trent 4323 11160 36775 29773
13851 E01014280 Stoke-on-Trent 14199 22804 37472 35629
13852 E01014281 Stoke-on-Trent 5202 1814 15530 34764
13853 E01014282 Stoke-on-Trent 7787 11469 15917 36613
13854 E01014283 Stoke-on-Trent 8292 3857 22294 35493
13855 E01014284 Stoke-on-Trent 12852 10645 22640 35955
13856 E01014285 Stoke-on-Trent 7566 17540 19818 33595
13857 E01014286 Stoke-on-Trent 1031 2273 14192 34058
13858 E01014287 Stoke-on-Trent 447 1380 40301 34087
13859 E01014288 Stoke-on-Trent 13022 2334 37020 29242
13860 E01014289 Stoke-on-Trent 20452 1827 28465 28232
13861 E01014290 Stoke-on-Trent 18518 3529 35031 30756
13862 E01014291 Stoke-on-Trent 6831 14611 28613 31415
13863 E01014292 Stoke-on-Trent 18742 10786 21971 24935
13864 E01014293 Stoke-on-Trent 5011 4011 36026 35020
13865 E01014294 Stoke-on-Trent 5620 13651 20871 23794
13866 E01014295 Stoke-on-Trent 15530 14463 19179 25363
13867 E01014296 Stoke-on-Trent 7555 27043 33127 30096
13868 E01014297 Stoke-on-Trent 18217 29061 39377 31813
13869 E01014298 Stoke-on-Trent 3814 15905 34217 29924
13870 E01014299 Stoke-on-Trent 17958 6229 38798 28661
13871 E01014300 Stoke-on-Trent 2489 12461 36537 26809
13872 E01014301 Stoke-on-Trent 20427 22637 40290 29095
13873 E01014302 Stoke-on-Trent 3072 8599 40545 25964
13874 E01014303 Stoke-on-Trent 21347 12708 40142 28002
13875 E01014304 Stoke-on-Trent 15068 29723 34010 24312
13876 E01014305 Stoke-on-Trent 2372 5410 28642 17452
13877 E01014306 Stoke-on-Trent 2542 1109 31285 21870
13878 E01014307 Stoke-on-Trent 2369 11711 34885 16880
13879 E01014308 Stoke-on-Trent 15144 26719 18588 23140
13880 E01014309 Stoke-on-Trent 4035 7198 14019 17333
13881 E01014310 Stoke-on-Trent 17990 22955 21911 15573
13882 E01014311 Stoke-on-Trent 4042 10889 26143 21298
13883 E01014312 Stoke-on-Trent 10219 11044 20233 18250
13884 E01014313 Stoke-on-Trent 2831 12670 24784 23140
13885 E01014314 Stoke-on-Trent 22659 31580 23788 13068
13886 E01014315 Stoke-on-Trent 22813 29809 40678 16974
13887 E01014316 Stoke-on-Trent 691 12955 28204 17054
13888 E01014317 Stoke-on-Trent 960 23443 34177 17303
13889 E01014318 Stoke-on-Trent 27416 29678 40508 12885
13890 E01014319 Stoke-on-Trent 14748 30720 34049 13396
13891 E01014320 Stoke-on-Trent 26114 31725 39633 13448
13892 E01014321 Stoke-on-Trent 9811 6592 36061 19669
13893 E01014322 Stoke-on-Trent 5714 21067 29927 15324
13894 E01014323 Stoke-on-Trent 6726 7240 14844 32306
13895 E01014324 Stoke-on-Trent 17079 9525 17359 31226
13896 E01014325 Stoke-on-Trent 27313 17817 3136 34356
13897 E01014326 Stoke-on-Trent 24075 9572 18047 31614
13898 E01014327 Stoke-on-Trent 7565 9998 24029 32306
13899 E01014328 Stoke-on-Trent 2165 3681 23629 32174
13900 E01014329 Stoke-on-Trent 6062 9881 16741 32174
13901 E01014330 Stoke-on-Trent 580 2053 25326 31928
13902 E01014331 Stoke-on-Trent 2424 12217 8773 29751
13903 E01014332 Stoke-on-Trent 14139 21300 7653 26169
13904 E01014333 Stoke-on-Trent 17141 18253 20296 32814
13905 E01014334 Stoke-on-Trent 8614 11090 25177 32947
13906 E01014335 Stoke-on-Trent 16087 29701 5676 23192
13907 E01014336 Stoke-on-Trent 1613 12983 12276 26236
13908 E01014337 Stoke-on-Trent 3884 31667 30471 22408
13909 E01014338 Stoke-on-Trent 16565 9685 15078 26794
13910 E01014339 Stoke-on-Trent 4300 9724 39460 33881
13911 E01014340 Stoke-on-Trent 5603 6160 34091 26082
13912 E01014341 Stoke-on-Trent 8252 13877 20591 25035
13913 E01014342 Stoke-on-Trent 3733 8185 12878 25626
13914 E01014343 Stoke-on-Trent 13138 5684 31279 26651
13915 E01014344 Stoke-on-Trent 7005 8926 11408 26215
13916 E01014345 Stoke-on-Trent 3705 3125 37187 33881
13917 E01014346 Stoke-on-Trent 24010 23974 6082 21994
13918 E01014347 Stoke-on-Trent 27853 29655 3897 19032
13919 E01014348 Stoke-on-Trent 26554 19503 11695 20045
13920 E01014349 Stoke-on-Trent 27654 11951 11426 17043
13921 E01014350 Stoke-on-Trent 29603 24579 5926 16517
13922 E01014351 Stoke-on-Trent 17259 36171 7515 16703
13923 E01014352 Stoke-on-Trent 29872 35917 3098 16389
13924 E01014353 Stoke-on-Trent 11027 19566 8755 20285
13925 E01014354 Stoke-on-Trent 1624 3362 28969 33552
13926 E01014355 Stoke-on-Trent 6066 1808 37455 31864
13927 E01014356 Stoke-on-Trent 5233 7442 32112 33075
13928 E01014357 Stoke-on-Trent 6250 10797 26253 22154
13929 E01014358 Stoke-on-Trent 1446 17750 20832 27439
13930 E01014359 Stoke-on-Trent 5879 7928 30339 30085
13931 E01014360 Stoke-on-Trent 17246 25094 35527 28065
13932 E01014361 Stoke-on-Trent 1709 5035 39628 31487
13933 E01014362 Stoke-on-Trent 21741 32616 8330 28985
13934 E01014363 Stoke-on-Trent 17610 25739 17538 23383
13935 E01014364 Stoke-on-Trent 8021 21886 14021 25386
13936 E01014365 Stoke-on-Trent 14089 22900 14102 27212
13937 E01014366 Stoke-on-Trent 1479 21064 24840 25355
13938 E01014367 Stoke-on-Trent 953 16493 22921 20924
13939 E01014368 Stoke-on-Trent 2444 6283 26742 24571
13940 E01014369 Stoke-on-Trent 13048 30774 21294 23595
13941 E01014370 Bath and North East Somerset 12188 1363 16615 19868
13942 E01014371 Bath and North East Somerset 16329 2782 19430 17994
13943 E01014372 Bath and North East Somerset 19305 1923 20225 23977
13944 E01014373 Bath and North East Somerset 23644 29430 1093 14661
13945 E01014374 Bath and North East Somerset 27670 35319 1648 11874
13946 E01014375 Bath and North East Somerset 22770 37029 1823 10053
13947 E01014376 Bath and North East Somerset 32269 36230 2283 10107
13948 E01014377 Bath and North East Somerset 30918 32234 1543 11328
13949 E01014379 Bath and North East Somerset 19296 37491 6974 9446
13950 E01014380 Bath and North East Somerset 32636 31000 8850 13525
13951 E01014381 Bath and North East Somerset 32511 7637 2322 17000
13952 E01014382 Bath and North East Somerset 28239 33153 1315 6517
13953 E01014383 Bath and North East Somerset 26882 38523 4684 5551
13954 E01014384 Bath and North East Somerset 30916 38262 4685 5392
13955 E01014385 Bath and North East Somerset 21955 39707 6517 6675
13956 E01014386 Bath and North East Somerset 24815 39876 24463 5707
13957 E01014387 Bath and North East Somerset 28318 11799 16331 8370
13958 E01014388 Bath and North East Somerset 32497 23004 11665 9532
13959 E01014389 Bath and North East Somerset 29674 20262 20502 9215
13960 E01014390 Bath and North East Somerset 3758 14857 24774 11275
13961 E01014391 Bath and North East Somerset 26359 39276 25045 7726
13962 E01014392 Bath and North East Somerset 17767 37532 1286 7945
13963 E01014393 Bath and North East Somerset 32656 37024 30376 7717
13964 E01014394 Bath and North East Somerset 23077 36664 14283 6318
13965 E01014395 Bath and North East Somerset 31480 30187 6099 9785
13966 E01014396 Bath and North East Somerset 26401 11747 7954 14311
13967 E01014397 Bath and North East Somerset 32768 19772 4207 13179
13968 E01014398 Bath and North East Somerset 24832 24539 7648 13782
13969 E01014399 Bath and North East Somerset 18853 26251 17488 13502
13970 E01014400 Bath and North East Somerset 25118 5692 13152 12805
13971 E01014401 Bath and North East Somerset 12117 18646 17829 10651
13972 E01014402 Bath and North East Somerset 18396 26870 25920 8719
13973 E01014403 Bath and North East Somerset 18364 1059 8010 12381
13974 E01014404 Bath and North East Somerset 9638 13713 10899 10573
13975 E01014405 Bath and North East Somerset 31930 12838 10336 17519
13976 E01014407 Bath and North East Somerset 9836 641 18228 21589
13977 E01014409 Bath and North East Somerset 18201 5294 1689 19064
13978 E01014410 Bath and North East Somerset 32506 10806 7942 16824
13979 E01014411 Bath and North East Somerset 30867 12653 1101 18032
13980 E01014412 Bath and North East Somerset 31817 17318 4970 18860
13981 E01014413 Bath and North East Somerset 31003 28230 6089 15279
13982 E01014414 Bath and North East Somerset 17804 9875 14235 20421
13983 E01014415 Bath and North East Somerset 32604 7573 13991 17451
13984 E01014416 Bath and North East Somerset 27788 14785 12270 11876
13985 E01014417 Bath and North East Somerset 30880 14269 9151 13005
13986 E01014418 Bath and North East Somerset 25502 37874 3914 4632
13987 E01014419 Bath and North East Somerset 25898 38377 13509 5397
13988 E01014420 Bath and North East Somerset 22496 13338 22404 20771
13989 E01014421 Bath and North East Somerset 29959 20836 18665 13551
13990 E01014422 Bath and North East Somerset 31159 19099 7813 13551
13991 E01014423 Bath and North East Somerset 24284 1868 27221 16229
13992 E01014424 Bath and North East Somerset 30929 32792 31221 8043
13993 E01014425 Bath and North East Somerset 24869 21468 20948 8714
13994 E01014426 Bath and North East Somerset 12047 22522 11631 8698
13995 E01014427 Bath and North East Somerset 25880 6652 12061 15050
13996 E01014428 Bath and North East Somerset 31452 7319 7270 15393
13997 E01014429 Bath and North East Somerset 30814 13614 9578 11375
13998 E01014430 Bath and North East Somerset 27960 16310 11524 11650
13999 E01014431 Bath and North East Somerset 16051 24163 29841 10499
14000 E01014432 Bath and North East Somerset 19118 18165 30818 9959
14001 E01014433 Bath and North East Somerset 16272 30938 27721 8893
14002 E01014434 Bath and North East Somerset 30206 28552 32036 11684
14003 E01014435 Bath and North East Somerset 31764 1468 25749 17572
14004 E01014436 Bath and North East Somerset 29433 5391 16697 17131
14005 E01014437 Bath and North East Somerset 12016 19529 7018 16690
14006 E01014438 Bath and North East Somerset 14778 22813 12811 16653
14007 E01014439 Bath and North East Somerset 17055 14011 21229 10390
14008 E01014440 Bath and North East Somerset 28479 22690 31123 8379
14009 E01014441 Bath and North East Somerset 26434 29209 31039 12556
14010 E01014442 Bath and North East Somerset 24837 35046 29058 11229
14011 E01014443 Bath and North East Somerset 25887 27425 22607 8873
14012 E01014444 Bath and North East Somerset 25215 30481 28170 11129
14013 E01014445 Bath and North East Somerset 9106 26853 29089 10336
14014 E01014446 Bath and North East Somerset 20141 38336 449 7189
14015 E01014447 Bath and North East Somerset 16539 27591 34460 9419
14016 E01014448 Bath and North East Somerset 10098 18816 17885 18056
14017 E01014449 Bath and North East Somerset 25490 14032 21073 13581
14018 E01014450 Bath and North East Somerset 12365 25522 9382 10720
14019 E01014451 Bath and North East Somerset 15177 10735 29470 13159
14020 E01014452 Bath and North East Somerset 24946 22741 2898 12007
14021 E01014453 Bath and North East Somerset 32115 25588 3725 9649
14022 E01014454 Bath and North East Somerset 32555 31966 17973 10462
14023 E01014455 Bath and North East Somerset 15206 18368 15035 10260
14024 E01014456 Bath and North East Somerset 25357 22880 16168 12095
14025 E01014457 Bath and North East Somerset 31101 21978 14896 13701
14026 E01014458 Bath and North East Somerset 3278 21865 17746 10172
14027 E01014459 Bath and North East Somerset 18715 30919 32335 8454
14028 E01014460 Bath and North East Somerset 32180 34406 31008 8295
14029 E01014461 Bath and North East Somerset 9117 17407 4793 12661
14030 E01014462 Bath and North East Somerset 4576 19414 5465 10118
14031 E01014463 Bath and North East Somerset 3120 9690 1898 11017
14032 E01014464 Bath and North East Somerset 3774 7867 1070 10717
14033 E01014465 Bath and North East Somerset 29295 4076 8754 21019
14034 E01014466 Bath and North East Somerset 16412 7153 2446 21019
14035 E01014467 Bath and North East Somerset 28411 4551 2236 20945
14036 E01014468 Bath and North East Somerset 29581 6464 2971 21019
14037 E01014469 Bath and North East Somerset 11976 16847 35167 19084
14038 E01014470 Bath and North East Somerset 27412 23242 39572 15186
14039 E01014471 Bath and North East Somerset 19636 13228 28022 20000
14040 E01014472 Bath and North East Somerset 22355 29850 38921 14744
14041 E01014473 Bath and North East Somerset 29622 10056 10778 16653
14042 E01014474 Bath and North East Somerset 17849 17474 15594 13701
14043 E01014475 Bath and North East Somerset 25042 12612 13613 18273
14044 E01014476 Bath and North East Somerset 31182 22385 18981 16653
14045 E01014477 Bath and North East Somerset 32001 30099 27591 13682
14046 E01014478 Bath and North East Somerset 12295 15225 18598 14184
14047 E01014479 Bath and North East Somerset 31271 16388 9371 17851
14048 E01014480 Bath and North East Somerset 19081 4822 24665 14518
14049 E01014481 Bath and North East Somerset 28870 7182 3075 15993
14050 E01014482 Bath and North East Somerset 31537 11944 458 11872
14051 E01014483 Bath and North East Somerset 26007 1944 4876 15471
14052 E01014484 Bath and North East Somerset 26970 6319 11761 19157
14053 E01014485 Bristol, City of 12992 12215 33204 33816
14054 E01014486 Bristol, City of 3573 5369 27909 33949
14055 E01014487 Bristol, City of 17138 9697 32814 31217
14056 E01014488 Bristol, City of 11617 6951 20099 34627
14057 E01014489 Bristol, City of 5787 1789 34455 33597
14058 E01014491 Bristol, City of 21380 15473 21602 33469
14059 E01014492 Bristol, City of 5144 8121 5244 24257
14060 E01014493 Bristol, City of 5986 5695 11386 25791
14061 E01014494 Bristol, City of 18309 7754 10819 22457
14062 E01014495 Bristol, City of 12862 9138 10404 21326
14063 E01014496 Bristol, City of 11235 9646 29292 7324
14064 E01014497 Bristol, City of 3871 21849 9601 23199
14065 E01014498 Bristol, City of 7473 26528 22493 22400
14066 E01014499 Bristol, City of 6363 15316 19367 25603
14067 E01014500 Bristol, City of 13997 19465 36667 22493
14068 E01014501 Bristol, City of 7041 27937 37074 20246
14069 E01014502 Bristol, City of 7668 19452 29774 25565
14070 E01014504 Bristol, City of 21462 12311 35300 21891
14071 E01014505 Bristol, City of 22238 5511 34153 25087
14072 E01014506 Bristol, City of 24197 18172 34662 20800
14073 E01014507 Bristol, City of 25753 1646 38657 28863
14074 E01014508 Bristol, City of 18629 2830 39897 28045
14075 E01014509 Bristol, City of 26948 7841 35687 31524
14076 E01014510 Bristol, City of 26251 6482 33768 31524
14077 E01014511 Bristol, City of 24538 5606 38987 27624
14078 E01014512 Bristol, City of 21945 4970 36015 27624
14079 E01014513 Bristol, City of 29628 10760 26641 26808
14080 E01014514 Bristol, City of 23611 310 39511 27313
14081 E01014515 Bristol, City of 4064 15959 34871 12306
14082 E01014516 Bristol, City of 890 23001 31567 11508
14083 E01014517 Bristol, City of 2813 26310 26061 10552
14084 E01014518 Bristol, City of 14514 26748 36101 21167
14085 E01014519 Bristol, City of 9977 24921 30998 19107
14086 E01014520 Bristol, City of 19975 29423 31883 16677
14087 E01014521 Bristol, City of 10716 20286 30390 15859
14088 E01014522 Bristol, City of 4031 16868 29743 15155
14089 E01014523 Bristol, City of 9490 24770 17231 28001
14090 E01014524 Bristol, City of 16362 29056 35030 27708
14091 E01014525 Bristol, City of 22495 18161 29926 28185
14092 E01014526 Bristol, City of 4726 30524 30616 20874
14093 E01014527 Bristol, City of 11984 15333 28575 27934
14094 E01014528 Bristol, City of 21215 21797 12103 30634
14095 E01014529 Bristol, City of 6232 26430 20986 26441
14096 E01014530 Bristol, City of 16297 33703 9586 28992
14097 E01014531 Bristol, City of 18045 21545 31059 30857
14098 E01014532 Bristol, City of 15583 18802 30272 28976
14099 E01014533 Bristol, City of 16071 20734 28671 28706
14100 E01014534 Bristol, City of 14604 19853 20837 28395
14101 E01014535 Bristol, City of 20248 22222 33861 24959
14102 E01014536 Bristol, City of 3177 26465 26424 18628
14103 E01014537 Bristol, City of 14247 12851 22175 29545
14104 E01014538 Bristol, City of 22489 3447 29215 26052
14105 E01014539 Bristol, City of 21001 3803 23623 29040
14106 E01014540 Bristol, City of 12154 3089 25472 31647
14107 E01014542 Bristol, City of 18266 1866 32731 28302
14108 E01014544 Bristol, City of 28589 6116 2088 19967
14109 E01014545 Bristol, City of 27222 3154 11781 19745
14110 E01014546 Bristol, City of 25141 993 18690 22094
14111 E01014547 Bristol, City of 28155 6099 14950 22073
14112 E01014548 Bristol, City of 15891 6019 10030 22073
14113 E01014549 Bristol, City of 15519 8652 2525 26150
14114 E01014550 Bristol, City of 27713 5187 9706 24491
14115 E01014551 Bristol, City of 20720 2502 24234 21383
14116 E01014552 Bristol, City of 27927 3547 16146 21383
14117 E01014553 Bristol, City of 27302 1765 31969 21383
14118 E01014554 Bristol, City of 24154 1727 20088 22182
14119 E01014555 Bristol, City of 18589 2753 9445 24195
14120 E01014556 Bristol, City of 27986 3439 22691 20566
14121 E01014557 Bristol, City of 25672 5877 25978 29040
14122 E01014558 Bristol, City of 18383 2453 30071 25498
14123 E01014559 Bristol, City of 26995 2337 30156 22994
14124 E01014560 Bristol, City of 25109 3404 26762 24933
14125 E01014561 Bristol, City of 25365 8368 22730 28718
14126 E01014562 Bristol, City of 22212 7107 31509 24933
14127 E01014563 Bristol, City of 18928 6718 29090 32127
14128 E01014564 Bristol, City of 9374 11806 31800 34639
14129 E01014565 Bristol, City of 6176 6509 35693 33322
14130 E01014566 Bristol, City of 8649 4230 34758 34691
14131 E01014567 Bristol, City of 10881 3944 28008 33814
14132 E01014568 Bristol, City of 4274 4611 35202 34976
14133 E01014569 Bristol, City of 8449 8478 32772 35224
14134 E01014570 Bristol, City of 11159 14247 34998 34691
14135 E01014571 Bristol, City of 9293 16562 6060 32194
14136 E01014572 Bristol, City of 8195 14657 36741 33600
14137 E01014573 Bristol, City of 13598 24039 10653 33083
14138 E01014574 Bristol, City of 3724 7294 22120 35120
14139 E01014575 Bristol, City of 5852 18873 10719 34741
14140 E01014576 Bristol, City of 12202 24399 28991 34730
14141 E01014577 Bristol, City of 22778 24292 1941 32194
14142 E01014578 Bristol, City of 5459 15619 17724 25817
14143 E01014579 Bristol, City of 6107 25410 35740 22704
14144 E01014580 Bristol, City of 379 29373 35019 19059
14145 E01014581 Bristol, City of 477 12726 36958 19059
14146 E01014582 Bristol, City of 1426 16922 34630 22515
14147 E01014583 Bristol, City of 573 19912 37189 19391
14148 E01014584 Bristol, City of 2625 10229 30785 22807
14149 E01014585 Bristol, City of 416 15709 35736 22918
14150 E01014586 Bristol, City of 10297 19329 1932 28833
14151 E01014587 Bristol, City of 11704 18469 5110 28968
14152 E01014588 Bristol, City of 8149 6252 28896 32072
14153 E01014589 Bristol, City of 979 17900 8777 29494
14154 E01014590 Bristol, City of 9254 1493 34446 31773
14155 E01014591 Bristol, City of 17176 14676 11743 30047
14156 E01014592 Bristol, City of 11699 2059 28009 31639
14157 E01014593 Bristol, City of 334 5753 35099 13664
14158 E01014594 Bristol, City of 359 10608 34996 14890
14159 E01014595 Bristol, City of 2108 18871 37745 11481
14160 E01014596 Bristol, City of 1470 16698 36886 13664
14161 E01014597 Bristol, City of 483 17701 33481 9222
14162 E01014598 Bristol, City of 22534 27973 37375 17359
14163 E01014599 Bristol, City of 20116 23074 40449 15915
14164 E01014600 Bristol, City of 7965 15855 39400 12267
14165 E01014601 Bristol, City of 7858 10906 28549 23368
14166 E01014602 Bristol, City of 4647 18218 28831 20825
14167 E01014603 Bristol, City of 10076 27832 26439 24161
14168 E01014605 Bristol, City of 1697 9150 29934 22179
14169 E01014607 Bristol, City of 11390 19457 40586 18226
14170 E01014608 Bristol, City of 3118 19674 37151 18613
14171 E01014609 Bristol, City of 6571 24565 37832 18926
14172 E01014610 Bristol, City of 3439 24222 38221 16328
14173 E01014611 Bristol, City of 21270 22238 40183 13975
14174 E01014612 Bristol, City of 9132 24156 40284 12852
14175 E01014613 Bristol, City of 15211 17488 37579 18730
14176 E01014614 Bristol, City of 16919 23824 36629 17740
14177 E01014615 Bristol, City of 31994 9273 12674 22059
14178 E01014616 Bristol, City of 29738 4832 19204 21022
14179 E01014617 Bristol, City of 30147 15628 9364 26364
14180 E01014618 Bristol, City of 31777 8598 8349 22974
14181 E01014619 Bristol, City of 28213 2854 33891 19012
14182 E01014620 Bristol, City of 30412 4382 21656 22406
14183 E01014621 Bristol, City of 24190 4978 36114 19012
14184 E01014622 Bristol, City of 10326 6486 37902 33082
14185 E01014623 Bristol, City of 11989 12195 31144 33617
14186 E01014624 Bristol, City of 6982 4795 27678 33010
14187 E01014626 Bristol, City of 6515 20607 36829 33700
14188 E01014627 Bristol, City of 13524 9636 37160 32694
14189 E01014629 Bristol, City of 4638 12363 19978 33333
14190 E01014630 Bristol, City of 6276 10586 35714 30826
14191 E01014631 Bristol, City of 16300 20070 18049 27885
14192 E01014632 Bristol, City of 11439 9360 28286 28804
14193 E01014633 Bristol, City of 14739 15917 12015 27921
14194 E01014634 Bristol, City of 23040 4257 39120 31144
14195 E01014635 Bristol, City of 20291 3078 36904 30396
14196 E01014636 Bristol, City of 4934 16431 11455 27421
14197 E01014637 Bristol, City of 23494 1368 35849 28863
14198 E01014638 Bristol, City of 1587 13559 15245 24029
14199 E01014639 Bristol, City of 1445 22180 11493 22018
14200 E01014640 Bristol, City of 3934 17799 23445 26190
14201 E01014641 Bristol, City of 16327 19141 6529 19849
14202 E01014642 Bristol, City of 17299 21329 7979 21594
14203 E01014643 Bristol, City of 4593 1153 860 18065
14204 E01014644 Bristol, City of 9056 8463 6196 19704
14205 E01014645 Bristol, City of 11053 11211 23673 24614
14206 E01014646 Bristol, City of 9416 14784 24070 22684
14207 E01014647 Bristol, City of 2467 12567 30934 22792
14208 E01014648 Bristol, City of 21206 4850 29963 28107
14209 E01014649 Bristol, City of 22285 5096 25104 27842
14210 E01014650 Bristol, City of 10224 14152 21111 27842
14211 E01014651 Bristol, City of 22686 7724 27498 28176
14212 E01014653 Bristol, City of 743 7535 33981 34564
14213 E01014654 Bristol, City of 1881 3502 28868 34065
14214 E01014655 Bristol, City of 2334 2088 32386 34564
14215 E01014658 Bristol, City of 1634 14998 18835 32585
14216 E01014659 Bristol, City of 6246 14999 36760 31152
14217 E01014660 Bristol, City of 4499 18895 23116 29849
14218 E01014661 Bristol, City of 6222 10385 27872 31057
14219 E01014662 Bristol, City of 12497 11179 24219 31057
14220 E01014663 Bristol, City of 3249 21278 17781 30836
14221 E01014664 Bristol, City of 6979 21868 12922 31870
14222 E01014665 Bristol, City of 13351 12646 15249 34204
14223 E01014666 Bristol, City of 30477 11210 24459 25712
14224 E01014667 Bristol, City of 30062 9299 32352 23495
14225 E01014668 Bristol, City of 27824 7251 39067 30054
14226 E01014669 Bristol, City of 26645 12186 27039 25459
14227 E01014670 Bristol, City of 21086 5667 32516 30418
14228 E01014671 Bristol, City of 16268 3964 36482 31217
14229 E01014672 Bristol, City of 24618 6325 30161 23919
14230 E01014673 Bristol, City of 8667 1511 40896 32004
14231 E01014674 Bristol, City of 8933 13327 36134 32280
14232 E01014675 Bristol, City of 13783 6727 38134 32040
14233 E01014676 Bristol, City of 11238 10531 29995 31432
14234 E01014677 Bristol, City of 19709 19499 8681 28215
14235 E01014678 Bristol, City of 13932 9008 25525 27325
14236 E01014679 Bristol, City of 16600 17845 25836 27118
14237 E01014680 Bristol, City of 19981 21041 23511 24582
14238 E01014681 Bristol, City of 11208 9377 28854 33753
14239 E01014682 Bristol, City of 7789 9363 32916 31351
14240 E01014683 Bristol, City of 6245 14760 29043 31046
14241 E01014684 Bristol, City of 7821 15115 30408 31347
14242 E01014685 Bristol, City of 4560 16869 29853 32865
14243 E01014686 Bristol, City of 10698 20028 28773 32510
14244 E01014687 Bristol, City of 8389 3023 34613 31351
14245 E01014688 Bristol, City of 2480 10157 13718 25077
14246 E01014689 Bristol, City of 613 1976 15115 24161
14247 E01014690 Bristol, City of 7419 6328 24419 24958
14248 E01014691 Bristol, City of 5368 6285 21129 24094
14249 E01014692 Bristol, City of 4677 15852 24845 27841
14250 E01014693 Bristol, City of 23312 33987 36647 27063
14251 E01014694 Bristol, City of 4996 7737 23276 24419
14252 E01014695 Bristol, City of 8839 12083 27860 20869
14253 E01014696 Bristol, City of 26803 3006 26462 26948
14254 E01014698 Bristol, City of 22763 1375 23465 26948
14255 E01014699 Bristol, City of 10787 8621 24498 24323
14256 E01014700 Bristol, City of 25217 10086 30456 21252
14257 E01014701 Bristol, City of 19457 4275 11171 28234
14258 E01014702 Bristol, City of 20740 20062 41516 13414
14259 E01014703 Bristol, City of 2246 29801 27565 15963
14260 E01014704 Bristol, City of 11746 29241 32863 14399
14261 E01014705 Bristol, City of 23920 11223 40756 12107
14262 E01014706 Bristol, City of 2676 16696 36113 11182
14263 E01014707 Bristol, City of 14910 8065 40642 10454
14264 E01014708 Bristol, City of 15316 24689 29685 21535
14265 E01014709 Bristol, City of 22851 29052 512 17401
14266 E01014710 Bristol, City of 29847 24466 3919 16392
14267 E01014711 Bristol, City of 30805 12614 6092 18455
14268 E01014712 Bristol, City of 22463 18906 8024 16971
14269 E01014713 Bristol, City of 30769 24386 2648 15526
14270 E01014714 Bristol, City of 30599 24627 8284 17238
14271 E01014715 Bristol, City of 31914 9665 24879 20168
14272 E01014716 Bristol, City of 31522 22014 13807 19471
14273 E01014717 Bristol, City of 31704 16302 17576 18398
14274 E01014718 Bristol, City of 30787 19350 16629 21327
14275 E01014719 Bristol, City of 26487 3313 28872 20897
14276 E01014720 Bristol, City of 14010 8887 2551 24019
14277 E01014721 Bristol, City of 24058 5612 14529 22476
14278 E01014722 Bristol, City of 22322 27371 41459 9191
14279 E01014723 Bristol, City of 23169 21834 38435 9191
14280 E01014725 Bristol, City of 27319 29817 41082 9155
14281 E01014726 Bristol, City of 91 14400 37063 11442
14282 E01014727 Bristol, City of 226 9373 36381 12645
14283 E01014729 Bristol, City of 2892 20640 22001 27052
14284 E01014730 Bristol, City of 8845 11017 8598 30668
14285 E01014731 Bristol, City of 11426 20316 12162 29411
ah3r_rnk
1 41111
2 40437
3 41376
4 41260
5 38120
6 38715
7 20297
8 41630
9 40626
10 38980
11 36495
12 35102
13 27284
14 28020
15 29430
16 28913
17 31127
18 30173
19 30652
20 32103
21 30533
22 33509
23 32659
24 31292
25 23156
26 18849
27 26997
28 24003
29 32836
30 38747
31 22968
32 16688
33 37275
34 39769
35 16430
36 27055
37 9079
38 28665
39 31758
40 21831
41 25377
42 24543
43 35628
44 24039
45 23887
46 34804
47 38421
48 35803
49 31169
50 29323
51 23478
52 20806
53 21215
54 27997
55 25442
56 28501
57 29158
58 30139
59 31734
60 35904
61 27847
62 32375
63 25640
64 30443
65 36163
66 28559
67 39089
68 24571
69 36342
70 35412
71 30921
72 24791
73 33489
74 32916
75 35963
76 28016
77 30049
78 30623
79 36014
80 35677
81 37696
82 39689
83 36324
84 37399
85 33354
86 22570
87 21657
88 29311
89 11087
90 35726
91 19971
92 10476
93 16949
94 31327
95 36802
96 30466
97 36406
98 37023
99 35052
100 22729
101 30851
102 37923
103 31203
104 25420
105 36617
106 26990
107 29517
108 33274
109 38270
110 41254
111 37533
112 29896
113 30546
114 28420
115 26806
116 35509
117 35199
118 16655
119 26730
120 25937
121 31934
122 29490
123 21679
124 31943
125 34230
126 40124
127 28167
128 32928
129 33778
130 30531
131 28213
132 31404
133 34214
134 30285
135 20080
136 27518
137 32991
138 39269
139 30074
140 31251
141 40215
142 32975
143 41385
144 32807
145 34040
146 27301
147 22393
148 24158
149 23351
150 23895
151 25465
152 36232
153 31858
154 31317
155 30760
156 23910
157 36175
158 41180
159 25401
160 29632
161 26744
162 28333
163 31879
164 29007
165 34286
166 36826
167 37412
168 24188
169 35802
170 39576
171 31139
172 27399
173 35809
174 35388
175 29881
176 32682
177 40851
178 35272
179 32420
180 30625
181 32825
182 31827
183 26158
184 18095
185 16310
186 25706
187 23103
188 35640
189 37396
190 35162
191 19428
192 37885
193 33324
194 22673
195 27318
196 30631
197 23971
198 29381
199 23453
200 38332
201 24081
202 19665
203 27750
204 21169
205 28862
206 29875
207 34439
208 31359
209 22495
210 31017
211 34616
212 34470
213 34557
214 34797
215 28257
216 32936
217 13808
218 19031
219 20526
220 21170
221 31052
222 29269
223 32616
224 22829
225 22381
226 30003
227 32020
228 35557
229 37915
230 37983
231 34309
232 29307
233 35916
234 30801
235 28504
236 19739
237 28539
238 29749
239 39013
240 38247
241 38542
242 23176
243 25287
244 37032
245 27470
246 38854
247 36069
248 29109
249 12628
250 29056
251 15369
252 19565
253 28942
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14012 4927
14013 4895
14014 5387
14015 26066
14016 14163
14017 15812
14018 11185
14019 17592
14020 17176
14021 16653
14022 12358
14023 25300
14024 19009
14025 28829
14026 22064
14027 2678
14028 2664
14029 31319
14030 19458
14031 18256
14032 26305
14033 32564
14034 37585
14035 31730
14036 37371
14037 18916
14038 19387
14039 22358
14040 16941
14041 39278
14042 32019
14043 37457
14044 29726
14045 7441
14046 11205
14047 14838
14048 14923
14049 33030
14050 19334
14051 26729
14052 36901
14053 31832
14054 35387
14055 35558
14056 32437
14057 36565
14058 29303
14059 38250
14060 36222
14061 33848
14062 35447
14063 30859
14064 22346
14065 20948
14066 27189
14067 35980
14068 22283
14069 30720
14070 36652
14071 39906
14072 32312
14073 38800
14074 39135
14075 35073
14076 34799
14077 36932
14078 39395
14079 32177
14080 35892
14081 27715
14082 14360
14083 14214
14084 24006
14085 19030
14086 19608
14087 20826
14088 27130
14089 27031
14090 26677
14091 34615
14092 16536
14093 32730
14094 17195
14095 23021
14096 14472
14097 36647
14098 36038
14099 28411
14100 26200
14101 24273
14102 20197
14103 26208
14104 37035
14105 36286
14106 41393
14107 40376
14108 29807
14109 35826
14110 38340
14111 33877
14112 31800
14113 34073
14114 35320
14115 39690
14116 37105
14117 38734
14118 39270
14119 38143
14120 35701
14121 33601
14122 40309
14123 37566
14124 39723
14125 33008
14126 37870
14127 36659
14128 30571
14129 38935
14130 39281
14131 32638
14132 39605
14133 32830
14134 29181
14135 25243
14136 38300
14137 26807
14138 34102
14139 24033
14140 25137
14141 11669
14142 28489
14143 13486
14144 11279
14145 21105
14146 17525
14147 18935
14148 18608
14149 21278
14150 13790
14151 11641
14152 36372
14153 24870
14154 40113
14155 28778
14156 38856
14157 14915
14158 14801
14159 19446
14160 15129
14161 17120
14162 14764
14163 15480
14164 21607
14165 19644
14166 14216
14167 13231
14168 28599
14169 24726
14170 27362
14171 18425
14172 30614
14173 29011
14174 26813
14175 17415
14176 19041
14177 30759
14178 38397
14179 23275
14180 29523
14181 36264
14182 37034
14183 35532
14184 39405
14185 35547
14186 34602
14187 26670
14188 29811
14189 31369
14190 33482
14191 23513
14192 28184
14193 30217
14194 39217
14195 30637
14196 25261
14197 34168
14198 28018
14199 15189
14200 18693
14201 21295
14202 20465
14203 20050
14204 24350
14205 28023
14206 25257
14207 20759
14208 39959
14209 37073
14210 28540
14211 35166
14212 31528
14213 38165
14214 39087
14215 21017
14216 27419
14217 20225
14218 25337
14219 24397
14220 17452
14221 18909
14222 17865
14223 32111
14224 33062
14225 39673
14226 32736
14227 38453
14228 40448
14229 33695
14230 40861
14231 28841
14232 38002
14233 34819
14234 26770
14235 28884
14236 34992
14237 30380
14238 37388
14239 22426
14240 25070
14241 32460
14242 22313
14243 24743
14244 29168
14245 36106
14246 37100
14247 32001
14248 28910
14249 26592
14250 9617
14251 27177
14252 34406
14253 39898
14254 40149
14255 37026
14256 38203
14257 34082
14258 15254
14259 11994
14260 26223
14261 25258
14262 21198
14263 24247
14264 17747
14265 10971
14266 13826
14267 19712
14268 14712
14269 10156
14270 15226
14271 26522
14272 17354
14273 24153
14274 20941
14275 34703
14276 33480
14277 36454
14278 30598
14279 31370
14280 21303
14281 16118
14282 21011
14283 26502
14284 36569
14285 33505
[ reached 'max' / getOption("max.print") -- omitted 27444 rows ]Joins can be combined with sorting, filtering, and aggregation. So, if we wanted the average imd rank and ah3h_rnk for each LANAME we would use:
R
dbGetQuery (cdrcDB, "SELECT DISTINCT imd.LANAME, AVG(imd.Rank),
AVG(ahah.ah3h_rnk)
FROM ahah
JOIN imd
ON ahah.lsoa11 = imd.LSOA
GROUP BY imd.LANAME
")
OUTPUT
LANAME AVG(imd.Rank) AVG(ahah.ah3h_rnk)
1 Aberdeen City 4230.3640 21333.830
2 Aberdeenshire 4674.3647 33110.294
3 Adur 17774.9762 21148.738
4 Allerdale 15163.9667 25393.250
5 Amber Valley 18042.5897 23384.538
6 Angus 3766.3806 29530.561
7 Argyll and Bute 3549.5440 30233.448
8 Arun 17267.0106 22955.926
9 Ashfield 12486.3649 21174.932
10 Ashford 17247.7821 28585.679
11 Aylesbury Vale 24008.8696 28285.443
12 Babergh 20405.2222 30616.333
13 Barking and Dagenham 7244.5000 9580.864
14 Barnet 19287.4502 10117.867
15 Barnsley 10996.1429 21417.231
16 Barrow-in-Furness 11460.4898 17126.265
17 Basildon 15487.9273 19106.945
18 Basingstoke and Deane 22468.9266 28463.862
19 Bassetlaw 14626.9714 25736.771
20 Bath and North East Somerset 23317.5913 20224.991
21 Bedford 17450.0777 22908.670
22 Bexley 19696.1096 14764.959
23 Birmingham 7752.4491 13522.588
24 Blaby 23774.6500 28452.883
25 Blackburn with Darwen 9192.4945 12955.154
26 Blackpool 5885.3404 11663.819
27 Blaenau Gwent 528.4681 30859.638
28 Bolsover 12545.3958 25402.854
29 Bolton 12005.4802 14352.339
30 Boston 13713.1389 24743.167
31 Bournemouth, Christchurch and Poole 18284.0472 16105.554
32 Bracknell Forest 24498.4267 26899.413
33 Bradford 10199.2581 16381.274
34 Braintree 20081.9195 27517.126
35 Breckland 15965.8718 30308.359
36 Brent 12034.7052 8221.890
37 Brentwood 24755.0870 25650.630
38 Bridgend 927.3295 28597.716
39 Brighton and Hove 16575.8000 10650.364
40 Bristol, City of 13542.1521 12803.586
41 Broadland 22861.2857 29939.131
42 Bromley 21707.9848 15253.431
43 Bromsgrove 23499.3966 25059.621
44 Broxbourne 17751.9821 20480.518
45 Broxtowe 20958.2535 19540.324
46 Burnley 8735.8333 16891.633
47 Bury 15383.2583 15669.583
48 Caerphilly 816.0273 27389.818
49 Calderdale 12981.3906 20139.742
50 Cambridge 19797.1739 15345.420
51 Camden 16247.7444 2916.534
52 Cannock Chase 15654.5500 20432.133
53 Canterbury 18476.9222 21698.078
54 Cardiff 984.4766 16696.640
55 Carlisle 15225.9412 23354.265
56 Carmarthenshire 890.9821 32070.321
57 Castle Point 18865.1053 17770.596
58 Central Bedfordshire 23200.5987 28496.904
59 Ceredigion 1026.1739 35485.500
60 Charnwood 22146.3030 25638.141
61 Chelmsford 23008.5140 24371.168
62 Cheltenham 21866.5200 17927.347
63 Cherwell 20883.3118 27948.882
64 Cheshire East 21700.1709 22718.184
65 Cheshire West and Chester 18877.2736 22960.901
66 Chesterfield 13778.5507 21057.043
67 Chichester 20451.5634 28709.732
68 Chiltern 27875.3860 24695.351
69 Chorley 19538.8333 23797.409
70 City of Edinburgh 4518.9481 15113.621
71 City of London 20275.1667 1373.500
72 Clackmannanshire 3043.3472 28370.333
73 Colchester 18653.8190 24475.029
74 Conwy 1056.3239 27591.535
75 Copeland 12980.8163 26637.122
76 Corby 12284.1463 22524.805
77 Cornwall 13324.5890 28061.497
78 Cotswold 23618.1765 31790.431
79 County Durham 12317.7994 22961.806
80 Coventry 13739.5026 15053.662
81 Craven 21711.6875 27381.969
82 Crawley 16269.3182 20945.485
83 Croydon 14926.6364 12362.991
84 Dacorum 22246.2447 19216.223
85 Darlington 14055.9385 21370.415
86 Dartford 17163.3276 23483.224
87 Daventry 21956.9091 33401.955
88 Denbighshire 945.0690 30925.879
89 Derby 14529.1788 20157.656
90 Derbyshire Dales 23092.8140 31655.535
91 Doncaster 11275.1495 24074.691
92 Dorset 19776.0411 27777.607
93 Dover 14972.2985 23384.358
94 Dudley 15148.8507 16123.000
95 Dumfries and Galloway 3374.7811 30752.602
96 Dundee City 2748.6862 24666.239
97 Ealing 14031.1990 7953.750
98 East Ayrshire 2759.1902 28976.546
99 East Cambridgeshire 23106.1000 32030.920
100 East Devon 22003.1852 28319.432
101 East Dunbartonshire 4899.9385 22804.408
102 East Hampshire 24518.2500 28490.083
103 East Hertfordshire 26583.4762 27067.714
104 East Lindsey 10879.9012 28859.210
105 East Lothian 3813.3409 27818.083
106 East Northamptonshire 21069.7143 24292.612
107 East Renfrewshire 5178.5820 23932.205
108 East Riding of Yorkshire 20628.6286 26033.962
109 East Staffordshire 17986.7083 21740.306
110 East Suffolk 17196.8904 26230.767
111 Eastbourne 15040.6721 14759.607
112 Eastleigh 24970.1299 20608.688
113 Eden 18237.3333 29656.889
114 Elmbridge 27159.1111 18607.099
115 Enfield 12698.5191 11538.634
116 Epping Forest 20239.6538 23068.936
117 Epsom and Ewell 26723.6364 17375.000
118 Erewash 18127.0137 18935.356
119 Exeter 19288.8784 17174.946
120 Falkirk 3406.6542 27383.131
121 Fareham 25983.0959 24447.452
122 Fenland 11877.0909 28914.200
123 Fife 3494.2510 27558.832
124 Flintshire 1208.0000 28647.543
125 Folkestone and Hythe 13539.0896 20174.776
126 Forest of Dean 16772.9400 33109.260
127 Fylde 19611.0196 19675.745
128 Gateshead 12238.1667 17057.865
129 Gedling 20429.4286 20255.325
130 Glasgow City 2356.9759 13744.987
131 Gloucester 16389.4872 22418.731
132 Gosport 16463.0755 15617.755
133 Gravesham 16007.3750 20224.875
134 Great Yarmouth 10160.3770 24053.770
135 Greenwich 12654.5166 10526.417
136 Guildford 25310.4167 24811.179
137 Gwynedd 1081.4795 32092.425
138 Hackney 7420.6111 3755.431
139 Halton 10692.7848 20554.810
140 Hambleton 22844.6538 27806.885
141 Hammersmith and Fulham 14202.6018 3813.460
142 Harborough 26858.6809 31430.723
143 Haringey 11291.9172 6526.772
144 Harlow 14011.6111 20934.667
145 Harrogate 24081.8558 22961.635
146 Harrow 19977.0000 11637.182
147 Hart 29401.7368 26404.474
148 Hartlepool 10395.9655 17973.862
149 Hastings 8860.9245 14166.660
150 Havant 16190.8974 21726.077
151 Havering 19197.0200 17220.073
152 Herefordshire, County of 16395.1466 30251.371
153 Hertsmere 21120.7419 20090.452
154 High Peak 19897.7627 19960.390
155 Highland 3606.6763 32798.413
156 Hillingdon 17705.3851 16764.273
157 Hinckley and Bosworth 21580.5909 29143.515
158 Horsham 25199.1358 30474.642
159 Hounslow 14338.8028 13888.507
160 Huntingdonshire 22492.0190 26389.771
161 Hyndburn 9739.0577 13877.173
162 Inverclyde 2532.3860 27554.605
163 Ipswich 13231.6353 14554.541
164 Isle of Anglesey 1034.4545 34208.977
165 Isle of Wight 13356.4045 25608.562
166 Isles of Scilly 22165.0000 25366.000
167 Islington 10296.5122 3034.480
168 Kensington and Chelsea 15419.3398 2028.738
169 Kettering 18504.5088 23458.088
170 King's Lynn and West Norfolk 13390.0562 31323.618
171 Kingston upon Hull, City of 7693.6988 17549.892
172 Kingston upon Thames 23519.4286 11820.429
173 Kirklees 13913.9884 20171.452
174 Knowsley 6473.6122 17365.735
175 Lambeth 11294.5899 5093.438
176 Lancaster 14832.8652 19888.787
177 Leeds 14058.0249 15186.869
178 Leicester 10098.5156 12342.698
179 Lewes 19504.8548 22512.581
180 Lewisham 10781.3787 8424.071
181 Lichfield 22330.0172 26371.534
182 Lincoln 12675.1930 15839.386
183 Liverpool 7023.4027 10900.530
184 Luton 12621.2479 15975.240
185 Maidstone 19503.7158 23665.179
186 Maldon 20575.6500 31400.775
187 Malvern Hills 19185.1333 27149.311
188 Manchester 6598.6277 9389.691
189 Mansfield 12053.5373 20477.687
190 Medway 14440.9509 18837.896
191 Melton 22382.3000 29911.900
192 Mendip 18237.3485 25456.955
193 Merthyr Tydfil 617.1667 27718.111
194 Merton 20967.6048 9255.661
195 Mid Devon 17468.3953 32624.721
196 Mid Suffolk 21330.9107 33407.339
197 Mid Sussex 27282.3256 24883.198
198 Middlesbrough 9189.5698 18490.000
199 Midlothian 3367.1826 27562.609
200 Milton Keynes 18513.5658 20809.612
201 Mole Valley 25788.8519 22183.426
202 Monmouthshire 1271.8214 33199.036
203 Moray 3987.3968 31843.722
204 Na h-Eileanan an Iar 3317.5556 38413.472
205 Neath Port Talbot 727.7253 27778.022
206 New Forest 21970.0702 26562.114
207 Newark and Sherwood 17376.5714 25595.314
208 Newcastle upon Tyne 13043.3657 14594.777
209 Newcastle-under-Lyme 17065.6625 20107.900
210 Newham 8650.0183 7254.183
211 Newport 840.3368 21589.095
212 North Ayrshire 2610.3710 25090.780
213 North Devon 15572.0690 26648.914
214 North East Derbyshire 18963.9841 27561.730
215 North East Lincolnshire 12239.7264 17980.226
216 North Hertfordshire 23234.0976 26459.549
217 North Kesteven 23256.9219 29175.766
218 North Lanarkshire 2620.6421 28004.192
219 North Lincolnshire 15797.3465 25806.158
220 North Norfolk 14165.0323 30187.774
221 North Somerset 20995.1556 26053.859
222 North Tyneside 16157.8473 17392.053
223 North Warwickshire 17442.8421 29175.368
224 North West Leicestershire 20548.2586 32424.534
225 Northampton 14906.1579 21506.481
226 Northumberland 16157.8426 25275.746
227 Norwich 12152.4699 13728.518
228 Nottingham 8024.0110 11945.736
229 Nuneaton and Bedworth 14828.8889 19508.790
230 Oadby and Wigston 22231.9167 19081.972
231 Oldham 10891.1135 13715.383
232 Orkney Islands 4052.2069 35574.552
233 Oxford 18989.8795 14353.506
234 Pembrokeshire 985.0845 34938.789
235 Pendle 11109.2807 14513.053
236 Perth and Kinross 4268.7581 29808.753
237 Peterborough 12215.7321 25504.768
238 Plymouth 13140.7826 22475.286
239 Portsmouth 12280.6560 8874.032
240 Powys 1139.3671 33771.734
241 Preston 11962.4070 14934.105
242 Reading 16551.3918 16025.804
243 Redbridge 18068.7019 10221.578
244 Redcar and Cleveland 12470.9773 20614.023
245 Redditch 15635.4000 24537.218
246 Reigate and Banstead 23706.9535 22110.721
247 Renfrewshire 3312.5644 27603.769
248 Rhondda Cynon Taf 742.6429 30808.442
249 Ribble Valley 24478.2250 27717.100
250 Richmond upon Thames 25694.4609 9023.157
251 Richmondshire 22248.4706 30820.706
252 Rochdale 9892.1119 17044.672
253 Rochford 24637.7358 25151.906
254 Rossendale 13356.9767 22647.093
255 Rother 16276.7931 25854.259
256 Rotherham 11857.9042 21997.437
257 Rugby 21276.0820 24577.787
258 Runnymede 22526.5000 21203.019
259 Rushcliffe 27645.0000 23043.000
260 Rushmoor 19886.7759 19051.241
261 Rutland 26156.8696 32152.522
262 Ryedale 18839.4333 29616.133
263 Salford 9775.5133 15429.233
264 Sandwell 7633.3602 15016.226
265 Scarborough 13137.2958 19672.859
266 Scottish Borders 3806.0490 29994.678
267 Sedgemoor 15622.9714 27007.971
268 Sefton 13850.7037 15187.328
269 Selby 22550.2800 29688.240
270 Sevenoaks 22377.7973 26606.662
271 Sheffield 14221.7333 16291.009
272 Shetland Islands 4223.8000 37303.767
273 Shropshire 17785.1503 27627.648
274 Slough 13063.6250 15331.750
275 Solihull 20075.8358 19513.582
276 Somerset West and Taunton 16555.7273 25488.602
277 South Ayrshire 3438.8366 26578.157
278 South Bucks 25094.8000 25193.975
279 South Cambridgeshire 26193.9271 34132.135
280 South Derbyshire 20782.0690 28451.362
281 South Gloucestershire 23301.5697 22098.897
282 South Hams 20973.1224 30572.673
283 South Holland 16790.7347 29023.449
284 South Kesteven 21981.6296 25629.407
285 South Lakeland 22326.9661 25069.915
286 South Lanarkshire 3277.6056 25980.035
287 South Norfolk 20911.9753 34702.519
288 South Northamptonshire 27280.3725 31797.098
289 South Oxfordshire 26566.4045 29492.225
290 South Ribble 20209.3571 20432.229
291 South Somerset 17802.4563 28043.417
292 South Staffordshire 21663.8529 27637.471
293 South Tyneside 10343.8137 19086.853
294 Southampton 11886.2568 13068.730
295 Southend-on-Sea 16471.8037 11792.346
296 Southwark 11546.4819 6544.241
297 Spelthorne 20010.0833 19997.983
298 St Albans 26593.1724 22119.621
299 St. Helens 11295.6218 18122.807
300 Stafford 21757.2125 25868.075
301 Staffordshire Moorlands 20127.0508 24305.763
302 Stevenage 15500.1346 24127.654
303 Stirling 4203.9008 28905.397
304 Stockport 17735.8474 15608.042
305 Stockton-on-Tees 15477.1583 22601.983
306 Stoke-on-Trent 9350.4340 15646.447
307 Stratford-on-Avon 22825.0000 30492.822
308 Stroud 24046.5362 29516.884
309 Sunderland 10915.9838 18046.762
310 Surrey Heath 27092.2909 23241.036
311 Sutton 21630.7190 10513.413
312 Swale 12859.9765 24296.153
313 Swansea 1026.5811 23989.142
314 Swindon 18573.3864 19553.114
315 Tameside 10280.7305 17269.894
316 Tamworth 16091.0784 25838.137
317 Tandridge 22664.5400 26467.100
318 Teignbridge 19367.7024 31033.881
319 Telford and Wrekin 14165.6111 27292.231
320 Tendring 10884.3596 23278.697
321 Test Valley 23348.6338 27848.451
322 Tewkesbury 22984.2000 29649.280
323 Thanet 11175.2143 15734.857
324 Three Rivers 25161.6604 24022.566
325 Thurrock 15783.9490 22143.480
326 Tonbridge and Malling 22026.4444 25956.306
327 Torbay 11887.6517 18594.933
328 Torfaen 850.2333 27170.083
329 Torridge 12907.8378 30609.081
330 Tower Hamlets 10369.3125 6075.562
331 Trafford 20576.3841 13212.949
332 Tunbridge Wells 23489.7353 23285.265
333 Uttlesford 25428.0870 30919.848
334 Vale of Glamorgan 1254.6835 23002.595
335 Vale of White Horse 26577.5395 29554.197
336 Wakefield 12568.3493 21960.129
337 Walsall 11090.3593 14772.778
338 Waltham Forest 11735.3750 6913.458
339 Wandsworth 18713.1564 4375.966
340 Warrington 18533.7874 20947.370
341 Warwick 22966.8372 18520.442
342 Watford 19584.3396 16344.000
343 Waverley 27374.7683 24327.037
344 Wealden 22421.6526 28584.463
345 Wellingborough 15679.2340 21980.638
346 Welwyn Hatfield 20902.4776 23296.567
347 West Berkshire 24962.2784 28236.361
348 West Devon 16630.3871 33192.548
349 West Dunbartonshire 2362.9421 24323.471
350 West Lancashire 18716.6575 26369.137
351 West Lindsey 16899.6731 31193.827
352 West Lothian 3486.3431 26448.096
353 West Oxfordshire 26272.1818 28867.152
354 West Suffolk 18841.1300 27389.830
355 Westminster 16194.9688 2171.922
356 Wigan 14322.7600 18172.170
357 Wiltshire 21461.6105 29081.561
358 Winchester 25221.6143 26630.286
359 Windsor and Maidenhead 26475.8989 22119.281
360 Wirral 13399.9417 14586.893
361 Woking 24528.8525 18788.180
362 Wokingham 29227.0808 26023.172
363 Wolverhampton 9920.0063 17044.627
364 Worcester 17165.2540 15411.254
365 Worthing 18834.6615 15066.308
366 Wrexham 1034.3882 27346.129
367 Wychavon 19422.6410 29455.051
368 Wycombe 24505.4299 23396.757
369 Wyre 16527.1449 21459.754
370 Wyre Forest 16033.6308 22658.908
371 York 23593.4750 21281.158Challenge 4
Write a query that JOINS the imd and aha tables and that returns the LANAME and maximum values of Rank and ah3h_rnk for each LANAME. Sorted by RANK in descending order.
R
dbGetQuery (cdrcDB, "SELECT DISTINCT imd.LANAME, MAX(imd.Rank),
MAX(ahah.ah3h_rnk)
FROM ahah
JOIN imd
ON ahah.lsoa11 = imd.LSOA
GROUP BY imd.LANAME
ORDER BY MAX(imd.Rank) DESC
LIMIT 10
")
OUTPUT
LANAME MAX(imd.Rank) MAX(ahah.ah3h_rnk)
1 Chiltern 32844 39407
2 Harrogate 32843 41321
3 Mid Sussex 32842 41013
4 Bracknell Forest 32841 37897
5 South Cambridgeshire 32840 41123
6 Wokingham 32839 38433
7 Rushmoor 32837 37225
8 Three Rivers 32835 40029
9 Wycombe 32834 40189
10 York 32833 41559Disconnection
Once we have completed our analysis we need to disconnect from our database:
R
dbDisconnect(cdrcDB)
Content from Writing Good Software
Last updated on 2024-12-04 | Edit this page
Estimated time: 15 minutes
Overview
Questions
- How can I write software that other people can use?
Objectives
- Describe best practices for writing R and explain the justification for each.
Structure your project folder
Keep your project folder structured, organized and tidy, by creating
subfolders for your code files, manuals, data, binaries, output plots,
etc. It can be done completely manually, or with the help of RStudio’s
New Project functionality, or a designated package, such as
ProjectTemplate.
Tip: ProjectTemplate - a possible solution
One way to automate the management of projects is to install the
third-party package, ProjectTemplate. This package will set
up an ideal directory structure for project management. This is very
useful as it enables you to have your analysis pipeline/workflow
organised and structured. Together with the default RStudio project
functionality and Git you will be able to keep track of your work as
well as be able to share your work with collaborators.
- Install
ProjectTemplate. - Load the library
- Initialise the project:
R
install.packages("ProjectTemplate")
library("ProjectTemplate")
create.project("../my_project_2", merge.strategy = "allow.non.conflict")
For more information on ProjectTemplate and its functionality visit the home page ProjectTemplate
Make code readable
The most important part of writing code is making it readable and understandable. You want someone else to be able to pick up your code and be able to understand what it does: more often than not this someone will be you 6 months down the line, who will otherwise be cursing past-self.
Documentation: tell us what and why, not how
When you first start out, your comments will often describe what a command does, since you’re still learning yourself and it can help to clarify concepts and remind you later. However, these comments aren’t particularly useful later on when you don’t remember what problem your code is trying to solve. Try to also include comments that tell you why you’re solving a problem, and what problem that is. The how can come after that: it’s an implementation detail you ideally shouldn’t have to worry about.
Keep your code modular
Our recommendation is that you should separate your functions from
your analysis scripts, and store them in a separate file that you
source when you open the R session in your project. This
approach is nice because it leaves you with an uncluttered analysis
script, and a repository of useful functions that can be loaded into any
analysis script in your project. It also lets you group related
functions together easily.
Break down problem into bite size pieces
When you first start out, problem solving and function writing can be daunting tasks, and hard to separate from code inexperience. Try to break down your problem into digestible chunks and worry about the implementation details later: keep breaking down the problem into smaller and smaller functions until you reach a point where you can code a solution, and build back up from there.
Know that your code is doing the right thing
Make sure to test your functions!
Don’t repeat yourself
Functions enable easy reuse within a project. If you see blocks of similar lines of code through your project, those are usually candidates for being moved into functions.
If your calculations are performed through a series of functions, then the project becomes more modular and easier to change. This is especially the case for which a particular input always gives a particular output.
Remember to be stylish
Apply consistent style to your code.
Key Points
- Keep your project folder structured, organized and tidy.
- Document what and why, not how.
- Break programs into short single-purpose functions.
- Write re-runnable tests.
- Don’t repeat yourself.
- Be consistent in naming, indentation, and other aspects of style.
Comment Changes in GitHub
The Collaborator has some questions about one line change made by the Owner and has some suggestions to propose.
With GitHub, it is possible to comment on the diff of a commit. Over the line of code to comment, a blue comment icon appears to open a comment window.
The Collaborator posts her comments and suggestions using the GitHub interface.