stickylabeller

The stickylabeller package helps you label the facets in your ggplot2 plots using glue.

Installation

Install stickylabeller from my R-Universe:

install.packages("stickylabeller", repos = c(
  "https://jimjam-slam.r-universe.dev",
  "https://cloud.r-project.org"))

Use

The package has just one function: label_glue. Give it a string template to be processed by glue, and it’ll return a labelling function that you can pass to facet_*:

library(ggplot2)
library(stickylabeller)

# here's some example data: some random points in groups
mydf <- data.frame(
  x = 1:90,
  y = rnorm(90),
  red = rep(letters[1:3], 30),
  blue = c(rep(1, 30), rep(2, 30), rep(3, 30)))

# and here's a labelled plot!
ggplot(mydf) +
  geom_point(aes(x = x, y = y)) +
  facet_wrap(
    vars(red, blue),
    labeller = label_glue("Red is {red}\nand blue is {blue}"))

ggplot(mydf) +
  geom_point(aes(x = x, y = y)) +
  facet_grid(
    vars(red), vars(blue),
    labeller = label_glue(
      "Red is {red}",
      "Blue is {blue}"))

Your label_glue labeller can refer to any of the data frame columns included in the facetting formula. It can also use those columns in expressions, like:

my_labeller <- label_glue("Red is {toupper(red)}\nand blue is {blue}")

Numbering sequential facets

As well as the columns you include in the facetting specification, stickylabeller includes a few helper columns:

• .n numbers the facets numerically: 1, 2, 3…
• .l numbers the facets using lowercase letters: a, b, c…
• .L numbers the facets using uppercase letters: A, B, C…
• .r numbers the facets using lowercase Roman numerals: i, ii, iii…
• .R numbers the facets using uppercase Roman numerals: I, II, III…

So you can automatically number your facets like:

ggplot(mydf) +
  geom_point(aes(x = x, y = y)) +
  facet_wrap(
    vars(red, blue),
    labeller = label_glue("({.l}) Red is {toupper(red)}\nand blue is {blue}"))

Limitations

• .n, .l and .L only work with facet_wrap for now. See Issue #1.

Including summary statistics in facet labels

As of stickylabeller 1.0, label_glue now accepts a summary_data argument. This accepts a data frame of pre-computed summary data for the facets; it should include the facet grouping columns, plus any other variables you’d like to reference in the templates.

For example:

library(magrittr)
library(dplyr)
#> 
#> Attaching package: 'dplyr'
#> The following objects are masked from 'package:stats':
#> 
#>     filter, lag
#> The following objects are masked from 'package:base':
#> 
#>     intersect, setdiff, setequal, union

# summarise the data
mydf_stats = mydf |>
  group_by(red, blue) |>
  summarise(
    mean_y = sprintf("%#.2f", mean(y)),
    sd_y = sprintf("%#.2f", sd(y))) |>
  ungroup()
#> `summarise()` has grouped output by 'red'. You can override using the `.groups`
#> argument.

# pass the summary data onto label_glue
ggplot(mydf) +
  geom_point(aes(x = x, y = y)) +
  facet_wrap(
    vars(red, blue),
    labeller = label_glue(
      "({.L}) Red = {red}, blue = {blue}\n(mean = {mean_y}, SD = {sd_y})",
      summary_data = mydf_stats))

Have fun! If you hit any snags, please feel free to file an issue here so that I can get on it! <3