Facets

Facetting

You can more easily compare subgroups of data if you place each subgroup in its own subplot, a process known as facetting.

facet_grid()

{ggplot2} provides two functions for facetting. facet_grid() divides the plot into a grid of subplots based on the values of one or two facetting variables. To use it, add facet_grid() to the end of your plot call.

The code chunks below show three ways to facet with facet_grid(). Spot the differences between the chunks, then run the code to learn what the differences do.

facet_grid() recap

As you saw in the code examples, you use facet_grid() by passing a rows and/or a cols argument, with the names of the variables inside a vars() function.

  • facet_grid() will split the plot into facets vertically by the values of the rows variable: each facet will contain the observations that have a common value of the variable.
  • facet_grid() will split the plot horizontally by values of the cols variable. The result is a grid of facets, where each specific subplot shows a specific combination of values.

facet_wrap()

facet_wrap() provides a more relaxed way to facet a plot on a single variable. It will split the plot into subplots and then reorganize the subplots into multiple rows so that each plot has a more or less square aspect ratio. In short, facet_wrap() wraps the single row of subplots that you would get with facet_grid() into multiple rows.

To use facet_wrap() pass it a variable name inside vars(), e.g. facet_wrap(vars(color)).

Add facet_wrap() to the code below to create the graph that appeared at the start of this section. Facet by cut.

ggplot(data = diamonds) +
  geom_bar(mapping = aes(x = color, fill = cut)) +
  facet_wrap(vars(cut))

scales

By default, each facet in your plot will share the same \(x\) and \(y\) ranges. You can change this by adding a scales argument to facet_wrap() or facet_grid().

  • scales = "free" will let the \(x\) and \(y\) range of each facet vary
  • scales = "free_x" will let the \(x\) range of each facet vary, but not the \(y\) range
  • scales = "free_y" will let the \(y\) range of each facet vary, but not the \(x\) range. This is a convenient way to compare the shapes of different distributions

Try changing the scales argument from free to free_x to free_y to see how it works:

Recap

In this tutorial, you learned how to make bar charts; but much of what you learned applies to other types of charts as well. Here’s what you should know:

  • Bar charts are the basis for histograms, which means that you can interpret histograms in a similar way.
  • Bars are not the only geom in {ggplot2} that use the fill aesthetic. You can use both fill and color aesthetics with any geom that has an “interior” region.
  • You can use the same position adjustments with any {ggplot2} geom: "identity", "stack", "dodge", "fill", "nudge", and "jitter" (we’ll learn about "nudge" and "jitter" later). Each geom comes with its own sensible default.
  • You can facet any {ggplot2} plot by adding facet_grid() or facet_wrap() to the plot call.

Bar charts are an excellent way to display the distribution of a categorical variable. In the next tutorial, we’ll meet a set of geoms that display the distribution of a continuous variable.

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