How we teach ggplot (in the Insights book)

In our book Insights we help readers learn how to use the amazing ggplot2 package to make visualisations. If you have some experience with ggplot2, you may think our method of teaching it, and of using it in the book are a bit odd. Here we explain our reason for teaching it the way we teach it.

For example, here is the code for the first graph we make:

bats_Age_Sex %>%
  ggplot() +
    geom_col(mapping = aes(x=Sex, y=num_bat_IDs, fill=Age))

And if we had not piped the dataset into ggplot then we would have done this:

ggplot() +
  geom_col(data = bats_Age_Sex,
           mapping = aes(x=Sex, y=num_bat_IDs, fill=Age))

Generally speaking, we first teach students to put all the arguments into the geom. We believe this is a valuable didactic tool/approach (and also not bad to do in any case). This is because we believe that it’s important to know how the geoms work and what they need, and that this is best seen by specifying the necessary information in the geom.

After we’ve explained and practiced this approach numerous times with different geoms, we explain how inheritance from the ggplot function works, and when it is useful.

Owen Petchey
Professor of Integrative Ecology

Interested in ecology, diversity, prediction, quantitative methods, a bit of programming, and making beer.