R Graphics Cookbook, 2nd Edition

Chapter 2. Quickly Exploring Data

Although I’ve used the ggplot2 package for most of the graphics in this book, it is not the only way to plot data. For very quick exploration of data, it’s sometimes useful to use the plotting functions in base R. These are installed by default with R and do not require any additional packages to be installed. They’re quick to type, straightforward to use in simple cases, and run very quickly.

If you want to do anything beyond very simple plots, though, it’s generally better to switch to ggplot2. This is in part because ggplot2 provides a unified interface and set of options, instead of the grab bag of modifiers and special cases required in base graphics. Once you learn how ggplot2 works, you can use that knowledge for everything from scatter plots and histograms to violin plots and maps.

Each recipe in this section shows how to make a graph with base graphics. Each recipe also shows how to make a similar graph with the ggplot() function in ggplot2. The previous edition of this book also gave examples using the qplot() function from the ggplot2 package, but now it is recommended to just use ggplot() instead.

If you already know how to use R’s base graphics, having these examples side by side will help you transition to using ggplot2 for when you want to make more sophisticated graphics.

2.1 Creating a Scatter Plot

Problem

You want to create a scatter plot.

Solution

To make a scatter plot (Figure 2-1), use plot() and pass it a vector of