Lesson 27: The ggplot2 Graphics Package

Now, on to ggplot2.

The ggplot2 package was written by Hadley Wickham, who later became Chief Scientist at RStudio. It’s highly complex, with well over 400 functions, and rather abstract, but quite powerful. We will touch on it at various points in this tutorial, while staying with base-R graphics when it is easier to go that route.

Now to build up to using ggplot2, let’s do a bit more with base-R graphics first, continuing with our weight/age investigation of the ballplayers. To begin, let’s do a scatter plot of weight against age, color-coded by position. We could type

> plot(mlb$Age,mlb$Weight,col=mlb$PosCategory)

but to save some typing, let’s use R’s with function (we’ll change the point size while we are at it):

> with(mlb,plot(Age,Weight,col=PosCategory,cex=0.6))

By writing with, we tell R to take Age, Weight and PosCategory in the context of mlb.

Here is how we can do it in ggplot2:

First, I make an empty plot, based on the data frame mlb:

> p <- ggplot(mlb)

Nothing will appear on the screen. The package displays only when you “print” the plot:

> p

This will just display an empty plot. (Try it.) By the way, recall that any expression you type, even 1 + 1, will be evaluated and printed to the screen. Here the plot (albeit) empty is printed to the screen.

Now let’s do something useful:

> p + geom_point(aes(x = Age, y = Weight, col = PosCategory),cex=0.6)

What happened here? Quite a bit, actually, so let’s take this slowly.

• We took our existing (blank) plot, p, and by writing the’+’ sign, directed ggplot2 to add to the plot p.

• Now, WHAT do we want added? We are saying, ggplot2, please add to the plot p whatever geom_point() returns.”

• Note that geom_point() is a ggplot2 function. Its task is to produce scatter plots.

• Here are the details on the arguments to geom_point:

  • We want to plot weight against height. We do not need to specify what data frame these two variables are from, as we already stated that the plot p is for the data frame mlb.

  • We are also specifying that the color coding will be according to the player position, again from mlb.

• When R evaluates that entire expression, p + geom_point(aes(x = Age, y = Weight, col = PosCategory),cex=0.6), the result will be another ggplot2 graph object. Since we typed that expression at the > prompt, it was then printed to the screen as seen above.

• There is one mystery left, though: What does the function aes (‘aesthetic”) do? And why is the expression cex=0.6 NOT an argument to aes? Unfortunately, there are no easy answers to these questions, and in a rare exception to our rule of explaining all, we will just have to leave this as something that must be done.

One nice thing is that we automatically got a legend printed to the right of the graph, so we know which color corresponds to which position. We can do this in base-R graphics too, but need to set an argument for it in plot.