*by David Lillis, Ph.D.*

In Part 14, let’s see how to create pie charts in R. Let’s create a simple pie chart using the pie() command. As always, we set up a vector of numbers and then we plot them.

`B <- c(2, 4, 5, 7, 12, 14, 16)`

Create a simple pie chart.

`pie(B)`

Now let’s create a pie chart with a heading, using nice colours, and define our own labels using R’s rainbow palette. We control the number of colours using length(B).

`B <- c(2, 4, 5, 7, 12, 14, 16)`

`pie(B, main="My Piechart", col=rainbow(length(B)),`

`labels=c("Mon","Tue","Wed","Thu","Fri","Sat","Sun"))`

Here is a more complex example, using percentages and a legend. We create a vector of data, one for each day of the week

`B <- c(5, 3, 1, 8, 9, 4, 6)`

Set up black, grey and white for clear printing.

`cols <- c("grey90","grey50","black","grey30","white","grey70","grey50")`

Calculate the percentage for each day, using one decimal place.

`percentlabels<- round(100*B/sum(B), 1)`

Add a ‘%’ sign to each percentage value using the paste command.

`pielabels<- paste(percentlabels, "%", sep="")`

What does the paste command do?

`pie(B, main="My Best Piechart", col=cols, labels=pielabels, cex=0.8)`

Create a legend at the right.

`legend("topright", c("Mon","Tue","Wed","Thu","Fri","Sat","Sun"), cex=0.8, fill=cols)`

Here is your pie chart:

OK. Now let’s create a pie chart from a data frame and include sample sizes. First create a table of counts of cylinder numbers from the mtcars data set.

`cyltable<- table(mtcars$cyl)`

`cyltable`

`4 6 8`

`11 7 14`

We have eleven cars with four cylinders, seven cars with six cylinders, and fourteen cars with eight cylinders.

Now we create labels.

`labs<- paste("(",names(cyltable),")", "\n", cyltable, sep="")`

Now we plot.

`pie(cyltable, labels = labs, col = c("red", "yellow", "blue"),`

main="PIE CHART OF CYLINDER NUMBERS\n with sample sizes")

That wasn’t so hard! In Part 15 we will look at further plotting techniques in R.

**About the Author:***David Lillis has taught R to many researchers and statisticians. His company, Sigma Statistics and Research Limited, provides both on-line instruction and face-to-face workshops on R, and coding services in R. David holds a doctorate in applied statistics.*

{ 3 comments… read them below or add one }

Yeah, after reading this article I realized that it is easy to learn R. Thanks for posting such types of articles and motivating us to learn R Language.

How do you combine the names (labels) and the percentages (relative frequencies) on the graphs?

Awesome instruction. Real easy and effective to see how R works. I pasted your coding into Wordpad, cleaned out the notes, and pasted it straight into R and saw instantaneous results. Beautiful.