R is Not So Hard! A Tutorial, Part 12: Creating Histograms & Setting Bin Widths

by David Lillis, Ph.D.

This is Part 12 in my R Tutorial Series: R is Not so Hard.  Go back to Part 11 or start with Part 1.

I’m sure you’ve heard that R creates beautiful graphics.

It’s true, and it doesn’t have to be hard to do so.  Let’s start with a simple histogram using the hist() command, which is easy to use, but actually quite sophisticated.

First, we set up a vector of numbers and then we create a histogram.

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

That was easy, but you need more from your histogram. Note that R decided on an appropriate bin width. OK. Now we create a histogram from all the data in an array.

A <- structure(list(James = c(1L, 3L, 6L, 4L, 9L), Robert = c(2L, 5L,
4L, 5L, 12L), David = c(4L, 4L, 6L, 6L, 16L), Anne = c(3L, 5L,
6L, 7L, 6L)), .Names = c("James", "Robert", "David", "Anne"), class = "data.frame", row.names = c(NA, -5L))
attach(A)
A
  James Robert David Anne
1     1      2     4    3
2     3      5     4    5
3     6      4     6    6
4     4      5     6    7
5     9     12    16    6

The trick is to transform the four variables into a single vector and make a histogram of all elements.

B <- c(A$James, A$Robert, A$David, A$Anne)
Let’s create a histogram of B in dark green and include axis labels.
hist(B, col="darkgreen", ylim=c(0,10), ylab ="MY HISTOGRAM", xlab
="FREQUENCY")

However, controlling bin numbers can be problematic. Try setting the number of bins at 6 using the breaks argument.

hist(B, col = "red", breaks=6, xlim=c(0,max),
main="My Histogram", las=2, xlab = "Values", cex.lab = 1.3)

You can see that R has taken the number of bins (6) as indicative only. However, setting up histogram bins as a vector gives you more control over the output. Now we set up the bins as a vector, each bin four units wide, and starting at zero.

bins<- c(0, 4, 8, 12, 16)
hist(B, col = "blue", breaks=bins, xlim=c(0,max),
main="My Histogram", las=2, xlab = "Values", cex.lab = 1.3)

Now we have four bins of the right width. That wasn’t so hard! In Part 13 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.

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