# Chapter 5 Histogram

Quantitative variables often take so many values that a graph of the distribution is clearer if nearby values are group together. The most common graph of the distribution of one quantitative variable is a histogram. (Used for continious type of data)

Histogram can be used for continious type of random variables

• to find out the shape of the distribution of the variable of interest.

• to detect the outlier.

## 5.1 How to draw a histogram in base R?

Letâ€™s consider mtcars data set being available in R.

``hist(mtcars\$mpg)``

``hist(mtcars\$mpg, breaks=10)#Specify approximate number of bins with breaks``

## 5.2 How can we draw histogram in ggplot2?

``qplot(mtcars\$mpg)``
``## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.``

If the vector is in a data frame, you can use the following syntax:

``qplot(mpg, data=mtcars, binwidth=4)``

This is equivalent to:

``ggplot(mtcars, aes(x=mpg)) + geom_histogram(binwidth=4)#geom_histogram converts your plot into histogram``

``ggplot(mtcars,aes(x=mpg))+geom_histogram(binwidth = 4,colour="red",fill="yellow")#with color``

``````#fill fills inside of histogram
#colour defines the color of frame``````

This way is the better one.

## 5.3 Drawing Multiple Histogram

By using `facet_wrap` command, you can easily produce multiple histogram.

``ggplot(mtcars,aes(x=mpg))+geom_histogram(binwidth = 4,colour="red",fill="yellow")+facet_wrap("cyl")``