**In this blog post we’ll tackle an aesthetic aspect in R & ggplot2 — namely, displaying your the labels on your axis as millions or thousands.**

Assume, you have a data set with a column that has numbers ranging into the millions. To emulate this, I loaded the *mtcars* dataset and multiplied the *disp* column by a million.

library(ggplot2)
options(scipen=999)
data('mtcars')
mtcars$disp <- mtcars$disp * 1000000
ggplot(mtcars,aes(x=mpg, y=disp)) +
geom_point()

Depending on your options, you’ll either see a very large number with many zeroes or in scientific notation.

As a matter of fact, no one wants to see those zeroes. They want to see ‘million’ or ‘M’. Using the *scales* library this is extremely easy to achieve.

Historically, *scales* provided the *unit_format()* function, which provided a way to set the unit and the scale. However, this function has been retired, and has been replaced with new *label_* functions.

*Labelling functions are designed to be used with the labels argument of ggplot2 scales.*

In this example, we show the number as millions ‘M’, by providing the suffix and the scale of 1^{(-6)}. In the comments I’ve also entered the code to display the values as thousands on the Y-axis.

library(scales)
ggplot(mtcars,aes(x=mpg, y=disp)) +
geom_point() +
scale_y_continuous(labels = label_number(suffix = " M", scale = 1e-6)) # millions
# scale_y_continuous(labels = label_number(suffix = " K", scale = 1e-6)) # thousands

And this is the resulting chart:

By the way, if you’re having trouble understanding some of the code and concepts, I can highly recommend “An Introduction to Statistical Learning: with Applications in R”, which is the must-have data science bible. If you simply need an introduction into R, and less into the Data Science part, I can absolutely recommend this book by Richard Cotton. Hope it helps!

Great success!

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