# Chapter 8 Presenting distributions

Table 8.1 shows the geometric objects we will be working with below. In addition to the name of the object, you will also find a link where you can find more illustrations and examples on how they work.

Table 8.1: Selected geometric objects with ggplot2
Name Function Cookbook for R
Bar plot geom_bar() Bar and line graphs
Histogram geom_histogram() Plotting distributions
Density plot geom_density() Plotting distributions

## 8.1 Bar plot

The first plot we will do is a bar plot. To do this we use a variable on the number of restrictions on abortion (abortlaw10) and geom_bar().

ggplot(states, aes(x=abortlaw10)) +
geom_bar() 

## 8.2 Histograms

The next figure we will work with is the histogram. Here we will plot the distribution of Obama’s vote share in 2012 (the obama2012 variable) and use geom_histogram().

ggplot(states, aes(x=obama2012)) +
geom_histogram() 
stat_bin() using bins = 30. Pick better value with binwidth.

As you can see, we get a message about the use of a default binwidth. This is to emphasize the importance of specifying the binwidth yourself. We can change the bin width by adding binwidth to geom_histogram().

ggplot(states, aes(x=obama2012)) +
geom_histogram(binwidth = 5)

Play around with different binwidths to see how it affects the distribution in the figure.

## 8.3 Density plots

The histogram is not the only way to show the distribution of a variable. To make a density plot, you can use geom_density(). We use the obama2012 variable again.

ggplot(states, aes(x=obama2012)) +
geom_density() 

Do compare the density plot to the histograms above.