Writing Data
Last updated on 2024-12-04 | Edit this page
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$country == "Australia",]
write.table(aust_subset,
file="cleaned-data/gapminder-aus.csv",
sep=","
)
Let’s switch back to the shell to take a look at the data to make sure it looks OK:
OUTPUT
"country","year","pop","continent","lifeExp","gdpPercap"
"61","Australia",1952,8691212,"Oceania",69.12,10039.59564
"62","Australia",1957,9712569,"Oceania",70.33,10949.64959
"63","Australia",1962,10794968,"Oceania",70.93,12217.22686
"64","Australia",1967,11872264,"Oceania",71.1,14526.12465
"65","Australia",1972,13177000,"Oceania",71.93,16788.62948
"66","Australia",1977,14074100,"Oceania",73.49,18334.19751
"67","Australia",1982,15184200,"Oceania",74.74,19477.00928
"68","Australia",1987,16257249,"Oceania",76.32,21888.88903
"69","Australia",1992,17481977,"Oceania",77.56,23424.76683
Hmm, that’s not quite what we wanted. Where did all these quotation marks come from? Also the row numbers are meaningless.
Let’s look at the help file to work out how to change this behaviour.
R
?write.table
By default R will wrap character vectors with quotation marks when writing out to file. It will also write out the row and column names.
Let’s fix this:
R
write.table(
gapminder[gapminder$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,77.56,23424.76683
That 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.table
to save tabular data.