# 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.**