# Chapter 6. Summarized Data Distributions

This chapter explores how to visualize summarized distributions of data.

# 6.1 Making a Basic Histogram

## Problem

You want to make a histogram.

## Solution

Use `geom_histogram()` and map a continuous variable to `x` (Figure 6-1):

````ggplot``(``faithful``,` `aes``(``x` `=` `waiting``))` `+`
`geom_histogram``()````

## Discussion

All `geom_histogram()` requires is one column from a data frame or a single vector of data. For this example we’ll use the `faithful` data set, which contains two columns with data about the Old Faithful geyser: `eruptions`, which is the length of each eruption, and `waiting`, which is the length of time to the next eruption. We’ll only use the `waiting` variable in this example:

````faithful`
`#>     eruptions waiting`
`#> 1       3.600      79`
`#> 2       1.800      54`
`#> 3       3.333      74`
`#>  ...<266 more rows>...`
`#> 270     4.417      90`
`#> 271     1.817      46`
`#> 272     4.467      74````

If you just want to get a quick look at some data that isn’t in a data frame, you can get the same result by passing in `NULL` for the data frame and giving `ggplot()` a vector of values. This would have the same result as the previous code:

````# Store the values in a simple vector`
`w` `<-` `faithful``\$``waiting`

`ggplot``(``NULL``,` `aes``(``x` `=` `w``))` `+`
`geom_histogram``()````

By default, the data is grouped into 30 bins. This number of bins is an arbitrary default value, and may be too fine or too coarse for your data. You can change the size of the ...

Get R Graphics Cookbook, 2nd Edition now with the O’Reilly learning platform.

O’Reilly members experience live online training, plus books, videos, and digital content from nearly 200 publishers.