# Adding Measures of Central Tendency to Histograms in R

October 4, 2012
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(This article was first published on Mollie's Research Blog, and kindly contributed to R-bloggers)

Building on the basic histogram with a density plot, we can add measures of central tendency (in this case, mean and median) and a legend.

Like last time, we'll use the beaver data from the datasets package.

hist(beaver1$temp, # histogram col = "peachpuff", # column color border = "black", prob = TRUE, # show densities instead of frequencies xlim = c(36,38.5), ylim = c(0,3), xlab = "Temperature", main = "Beaver #1")lines(density(beaver1$temp), # density plot lwd = 2, # thickness of line col = "chocolate3")

Next we'll add a line for the mean:

abline(v = mean(beaver1$temp), col = "royalblue", lwd = 2) And a line for the median: abline(v = median(beaver1$temp), col = "red", lwd = 2)

And then we can also add a legend, so it will be easy to tell which line is which.
legend(x = "topright", # location of legend within plot area c("Density plot", "Mean", "Median"), col = c("chocolate3", "royalblue", "red"), lwd = c(2, 2, 2))

All of this together gives us the following graphic:

In this example, the mean and median are very close, as we can see by using median() and mode().
> mean(beaver1$temp)[1] 36.86219 > median(beaver1$temp)[1] 36.87

We can do like we did in the previous post and graph beaver1 and beaver2 together by adding a layout line and changing the limits of x and y. The full code for this is available in a gist.

Here's the output from that code: