Quickly Exploring Data - R Graphics - page 7

Chapter2.Quickly Exploring Data
Although I've used the ggplot2 package for most of the graphics in this topic, it is not the only
way to make graphs. For very quick exploration of data, it's sometimes useful to use the plot-
ting 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, are straightforward to use in simple cases, and
run very quickly.
If you want to do anything beyond very simple graphs, 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 qplot() function in ggplot2, which has a syntax
similar to the base graphics functions. For each qplot() graph, there is also an equivalent using
the more powerful ggplot() function.
If you already know how to use base graphics, having these examples side by side will help you
transition to using ggplot2 for when you want to make more sophisticated graphics.
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 xvalues followed by a
vector of yvalues:
plot(mtcars$wt, mtcars$mpg)