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AÂ **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 theÂ **histogram()** function from theÂ **lattice**, which uses the following syntax:

**histogram(x,Â type)**

where:

**x:Â**data**type:**type of relative frequency histogram youâ€™d like to create; options includeÂ percent, count, andÂ density.

**Default Histogram**

First, load theÂ **latticeÂ **package:

library(lattice)

By default, this package creates a relative frequency histogram withÂ **percentÂ **along the y-axis:

#create data data #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:Â**the title**xlab:Â**the x-axis label**ylab:Â**the y-axis label**col:Â**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 theÂ **breaksÂ **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 Sturgesâ€™ Rule to identify the optimal number of bins to use in a histogram.