# How to Create a Relative Frequency Histogram in R

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

`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 Sturges’ Rule to identify the optimal number of bins to use in a histogram.