Table of Contents
To create a relative frequency histogram in R, you need to first create a vector with your data, then use the hist() function to create a histogram and set the freq argument to FALSE to make the histogram a relative frequency histogram. You can also adjust the aesthetics of the histogram using the argument names such as color, fill, and xlab. Finally, you can use the lines() or rug() functions to add extra lines or points to your histogram.
A relative frequency histogram is a graph that displays the relative frequencies of values in a dataset.
This tutorial explains how to create a relative frequency histogram in R by using the histogram() function from the lattice, which uses the following syntax:
histogram(x, type)
where:
- x: data
- type: type of relative frequency histogram you’d like to create; options include percent, count, and density.
Default Histogram
First, load the lattice package:
library(lattice)
By default, this package creates a relative frequency histogram with percent along the y-axis:
#create data data <- c(0, 0, 2, 3, 4, 4, 5, 6, 7, 12, 12, 14) #create relative frequency histogram histogram(data)
Modifying the Histogram
We can modify the histogram to include a title, different axes labels, and a different color using the following arguments:
- main: the title
- xlab: the x-axis label
- ylab: the y-axis label
- col: the fill color to use in the histogram
For example:
#modify the histogram
histogram(data,
main='Points per Game by Player',
xlab='Points per Game',
col='steelblue')
Modifying the Numbers of Bins
We can specify the number of bins to use in the histogram using the breaks argument:
#modify the number of bins histogram(data, main='Points per Game by Player', xlab='Points per Game', col='steelblue', breaks=15)
The more bins you specify, the more you will be able to get a granular look at your data. Conversely, the fewer number of bins you specify, the more aggregated the data will become:
#modify the number of bins histogram(data, main='Points per Game by Player', xlab='Points per Game', col='steelblue', breaks=3)
Related: Use to identify the optimal number of bins to use in a histogram.