Storing Multiple Values in Lists
Last updated on 2024-02-23 | Edit this page
Overview
Questions
- How can I store many values together?
Objectives
- Explain what a list is.
- Create and index lists of simple values.
- Change the values of individual elements
- Append values to an existing list
- Reorder and slice list elements
- Create and manipulate nested lists
In the previous episode, we analysed a single .csv
data
file containing GDP data for countries in Europe. However we also have
similar data for the other continents, and we would like to repeat our
analysis on each of them. This means that we still have 5 more data
files to process!
The natural first step is to collect the names of all the files that we have to process. In Python, a list is a way to store multiple values together. In this episode, we will learn how to store multiple values in a list as well as how to work with lists.
Python lists
Unlike dataframes, lists are built into the language so we do not have to load a library to use them. We create a list by putting values inside square brackets and separating the values with commas:
OUTPUT
odds are: [1, 3, 5, 7]
We can access elements of a list using indices – numbered positions of elements in the list. These positions are numbered starting at 0, so the first element has an index of 0.
PYTHON
print('first element:', odds[0])
print('last element:', odds[3])
print('"-1" element:', odds[-1])
OUTPUT
first element: 1
last element: 7
"-1" element: 7
Yes, we can use negative numbers as indices in Python. When we do so,
the index -1
gives us the last element in the list,
-2
the second to last, and so on. Because of this,
odds[3]
and odds[-1]
point to the same element
here.
There is one important difference between lists and strings: we can change the values in a list, but we cannot change individual characters in a string. For example:
PYTHON
names = ['Curie', 'Darwing', 'Turing'] # typo in Darwin's name
print('names is originally:', names)
names[1] = 'Darwin' # correct the name
print('final value of names:', names)
OUTPUT
names is originally: ['Curie', 'Darwing', 'Turing']
final value of names: ['Curie', 'Darwin', 'Turing']
works, but:
ERROR
---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
<ipython-input-8-220df48aeb2e> in <module>()
1 name = 'Darwin'
----> 2 name[0] = 'd'
TypeError: 'str' object does not support item assignment
does not.
Ch-Ch-Ch-Ch-Changes
Data which can be modified in place is called mutable, while data which cannot be modified is called immutable. Strings and numbers are immutable. This does not mean that variables with string or number values are constants, but when we want to change the value of a string or number variable, we can only replace the old value with a completely new value.
Lists on the other hand, are mutable: we can modify them after they have been created. We can change individual elements, append new elements, or reorder the whole list. For some operations, like sorting, we can choose whether to use a function that modifies the data in-place or a function that returns a modified copy and leaves the original unchanged.
Be careful when modifying data in-place. If two variables refer to the same list, and you modify the list value, it will change for both variables!
PYTHON
mild_salsa = ['peppers', 'onions', 'cilantro', 'tomatoes']
hot_salsa = mild_salsa # <-- mild_salsa and hot_salsa point to the *same* list data in memory
hot_salsa[0] = 'hot peppers'
print('Ingredients in mild salsa:', mild_salsa)
print('Ingredients in hot salsa:', hot_salsa)
OUTPUT
Ingredients in mild salsa: ['hot peppers', 'onions', 'cilantro', 'tomatoes']
Ingredients in hot salsa: ['hot peppers', 'onions', 'cilantro', 'tomatoes']
If you want variables with mutable values to be independent, you must make a copy of the value when you assign it.
PYTHON
mild_salsa = ['peppers', 'onions', 'cilantro', 'tomatoes']
hot_salsa = list(mild_salsa) # <-- makes a *copy* of the list
hot_salsa[0] = 'hot peppers'
print('Ingredients in mild salsa:', mild_salsa)
print('Ingredients in hot salsa:', hot_salsa)
OUTPUT
Ingredients in mild salsa: ['peppers', 'onions', 'cilantro', 'tomatoes']
Ingredients in hot salsa: ['hot peppers', 'onions', 'cilantro', 'tomatoes']
Because of pitfalls like this, code which modifies data in place can be more difficult to understand. However, it is often far more efficient to modify a large data structure in place than to create a modified copy for every small change. You should consider both of these aspects when writing your code.
Nested Lists
Since a list can contain any Python variables, it can even contain other lists.
For example, you could represent the products on the shelves of a
small grocery shop as a nested list called veg
:
To store the contents of the shelf in a nested list, you write it this way:
PYTHON
veg = [['lettuce', 'lettuce', 'peppers', 'zucchini'],
['lettuce', 'lettuce', 'peppers', 'zucchini'],
['lettuce', 'cilantro', 'peppers', 'zucchini']]
Here are some visual examples of how indexing a list of lists
veg
works. First, you can reference each row on the shelf
as a separate list. For example, veg[2]
represents the
bottom row, which is a list of the baskets in that row.
Index operations using the image would work like this:
OUTPUT
['lettuce', 'cilantro', 'peppers', 'zucchini']
OUTPUT
['lettuce', 'lettuce', 'peppers', 'zucchini']
To reference a specific basket on a specific shelf, you use two indexes. The first index represents the row (from top to bottom) and the second index represents the specific basket (from left to right).
OUTPUT
'lettuce'
OUTPUT
'peppers'
There are many ways to change the contents of lists besides assigning new values to individual elements:
OUTPUT
odds after adding a value: [1, 3, 5, 7, 11]
PYTHON
removed_element = odds.pop(0)
print('odds after removing the first element:', odds)
print('removed_element:', removed_element)
OUTPUT
odds after removing the first element: [3, 5, 7, 11]
removed_element: 1
OUTPUT
odds after reversing: [11, 7, 5, 3]
While modifying in place, it is useful to remember that Python treats lists in a slightly counter-intuitive way.
As we saw earlier, when we modified the mild_salsa
list
item in-place, if we make a list, (attempt to) copy it and then modify
this list, we can cause all sorts of trouble. This also applies to
modifying the list using the above functions:
PYTHON
odds = [3, 5, 7]
primes = odds
primes.append(2)
print('primes:', primes)
print('odds:', odds)
OUTPUT
primes: [3, 5, 7, 2]
odds: [3, 5, 7, 2]
This is because Python stores a list in memory, and then can use
multiple names to refer to the same list. If all we want to do is copy a
(simple) list, we can again use the list
function, so we do
not modify a list we did not mean to:
PYTHON
odds = [3, 5, 7]
primes = list(odds)
primes.append(2)
print('primes:', primes)
print('odds:', odds)
OUTPUT
primes: [3, 5, 7, 2]
odds: [3, 5, 7]
Subsets of lists and strings can be accessed by specifying ranges of
values in brackets, similar to how we accessed ranges of entries in a
dataframe via the .iloc
function. This is commonly referred
to as “slicing” the list/string.
PYTHON
binomial_name = 'Drosophila melanogaster'
group = binomial_name[0:10]
print('group:', group)
species = binomial_name[11:23]
print('species:', species)
chromosomes = ['X', 'Y', '2', '3', '4']
autosomes = chromosomes[2:5]
print('autosomes:', autosomes)
last = chromosomes[-1]
print('last:', last)
OUTPUT
group: Drosophila
species: melanogaster
autosomes: ['2', '3', '4']
last: 4
Slicing From the End
Use slicing to access only the last four characters of a string or entries of a list.
PYTHON
string_for_slicing = 'Observation date: 02-Feb-2013'
list_for_slicing = [['fluorine', 'F'],
['chlorine', 'Cl'],
['bromine', 'Br'],
['iodine', 'I'],
['astatine', 'At']]
OUTPUT
'2013'
[['chlorine', 'Cl'], ['bromine', 'Br'], ['iodine', 'I'], ['astatine', 'At']]
Would your solution work regardless of whether you knew beforehand the length of the string or list (e.g. if you wanted to apply the solution to a set of lists of different lengths)? If not, try to change your approach to make it more robust.
Hint: Remember that indices can be negative as well as positive
Non-Continuous Slices
So far we’ve seen how to use slicing to take single blocks of successive entries from a sequence. But what if we want to take a subset of entries that aren’t next to each other in the sequence?
You can achieve this by providing a third argument to the range within the brackets, called the step size. The example below shows how you can take every third entry in a list:
PYTHON
primes = [2, 3, 5, 7, 11, 13, 17, 19, 23, 29, 31, 37]
subset = primes[0:12:3]
print('subset', subset)
OUTPUT
subset [2, 7, 17, 29]
Notice that the slice taken begins with the first entry in the range, followed by entries taken at equally-spaced intervals (the steps) thereafter. If you wanted to begin the subset with the third entry, you would need to specify that as the starting point of the sliced range:
PYTHON
primes = [2, 3, 5, 7, 11, 13, 17, 19, 23, 29, 31, 37]
subset = primes[2:12:3]
print('subset', subset)
OUTPUT
subset [5, 13, 23, 37]
Use the step size argument to create a new string that contains only every other character in the string “In an octopus’s garden in the shade”. Start with creating a variable to hold the string:
What slice of beatles
will produce the following output
(i.e., the first character, third character, and every other character
through the end of the string)?
OUTPUT
I notpssgre ntesae
If you want to take a slice from the beginning of a sequence, you can omit the first index in the range:
PYTHON
date = 'Monday 4 January 2016'
day = date[0:6]
print('Using 0 to begin range:', day)
day = date[:6]
print('Omitting beginning index:', day)
OUTPUT
Using 0 to begin range: Monday
Omitting beginning index: Monday
And similarly, you can omit the ending index in the range to take a slice to the very end of the sequence:
PYTHON
months = ['jan', 'feb', 'mar', 'apr', 'may', 'jun', 'jul', 'aug', 'sep', 'oct', 'nov', 'dec']
sond = months[8:12]
print('With known last position:', sond)
sond = months[8:len(months)]
print('Using len() to get last entry:', sond)
sond = months[8:]
print('Omitting ending index:', sond)
OUTPUT
With known last position: ['sep', 'oct', 'nov', 'dec']
Using len() to get last entry: ['sep', 'oct', 'nov', 'dec']
Omitting ending index: ['sep', 'oct', 'nov', 'dec']
Overloading
+
usually means addition, but when used on strings or
lists, it means “concatenate”. Given that, what do you think the
multiplication operator *
does on lists? In particular,
what will be the output of the following code?
[2, 4, 6, 8, 10, 2, 4, 6, 8, 10]
[4, 8, 12, 16, 20]
[[2, 4, 6, 8, 10],[2, 4, 6, 8, 10]]
[2, 4, 6, 8, 10, 4, 8, 12, 16, 20]
The technical term for this is operator overloading: a
single operator, like +
or *
, can do different
things depending on what it’s applied to.
Key Points
-
[value1, value2, value3, ...]
creates a list. - Lists can contain any Python object, including lists (i.e., list of lists).
- Lists are indexed and sliced with square brackets (e.g., list\[0\] and list\[2:9\]), in the same way as strings and arrays.
- Lists are mutable (i.e., their values can be changed in place).
- Strings are immutable (i.e., the characters in them cannot be changed).