Plotting data

ggplot, part 3

Roland Krause

MADS6

Wednesday, 25 February 2026

Contents

• Left over material from initial lectures

Left over material from initial lectures

Even better: beeswarm

ggplot extension ggbeeswarm

library(ggbeeswarm)
penguins |> 
  filter(!is.na(sex)) |>
  ggplot(aes(y = body_mass_g,
             x = species,
             colour = sex)) +
  geom_quasirandom(dodge.width = 1) #<<

Raincloud plots

library(ggdist)
ggplot(penguins, 
       aes(y = species, 
           x = bill_depth_mm / bill_length_mm, 
           color = species, fill = species)) +
  geom_violin(width = .5, fill = "white", alpha = 0.4,
              size = 1.1, trim = FALSE) +
  ggdist::stat_halfeye(
    adjust = .33, width = .67, 
    alpha = 0.6, trim = FALSE,
    position = position_nudge(y = .35)) +
  ggbeeswarm::geom_quasirandom(groupOnX = FALSE,
                               alpha = .5, size = 3, 
                               width = 0.25) +
  scale_color_brewer(palette = "Set1", type = "qual") +
  scale_fill_brewer(palette = "Set1", type = "qual") +
  labs(x = "Bill ratio", y = NULL) +
  theme(legend.position = "none",
        axis.line = element_blank(),
        panel.grid.major.x = element_line(colour = "grey90"),
        axis.ticks = element_blank())

Control the dots plotting order

ggplot2 outputs dots as they appear in the input data

tibble(x = LETTERS[1:3],
       y = x) |> 
  ggplot(aes(x, y)) +
  geom_point(aes(colour = x),
             show.legend = FALSE,
             size = 125) +
  scale_color_brewer(palette = "Dark2") +
  theme_classic(20)

tibble(x = LETTERS[1:3], y = x) |> 
  arrange(desc(x)) |> 
  ggplot(aes(x, y)) +
  geom_point(aes(colour = x),
             show.legend = FALSE,
             size = 125) +
  scale_color_brewer(palette = "Dark2") +
  theme_classic(20)