Using position_nudge() to make the comparison to a background distribution a little nicer.

position_nudge.r

## Using position_nudge() to make showing a background 
## distribution a little nicer, by pushing it very slightly
## to the right. Most of the work is getting the penguins
## data to the point where I can demonstrate position_nudge()

library(tidyverse)
library(palmerpenguins)

# Classify every penguin's flipper length into 
# bins with widths of 10mm; then sum up
# the n in each bin and calculate a proportion.
df_all <- penguins |> 
  mutate(flip_f = cut_width(flipper_length_mm, 
                           width = 10,
                           boundary = 10)) |> 
  group_by(flip_f) |> 
  summarize(all_n = n()) |> 
  mutate(all_prop = all_n/sum(all_n)) |> 
  drop_na()

# Do the same again (every individual penguin classified 
# into the 10mm bins), but now calculate the 
# sums and proportions within species. Ungroup and 
# complete to restore any zero-count category rows within 
# species
df_species <- penguins |> 
  mutate(flip_f = cut_width(flipper_length_mm, 
                           width = 10,
                           boundary = 10)) |> 
  group_by(species, flip_f) |> 
  summarize(species_n = n()) |> 
  ungroup() |> 
  complete(species, flip_f, 
           fill = list(species_n = 0)) |> 
  group_by(species) |> 
  mutate(species_prop = species_n/sum(species_n))
  
# Join the two tables
df <- left_join(df_species, df_all, by = "flip_f")


# Now we have a binned measure of flipper width, 
# with proportions calculated by Species and also 
# overall, using the same bins. After the join, 
# the values for all species are repeated within
# every species. This means that when we draw it
# below and facet by species, it just repeats the 
# same in every panel.

df

# Put the overall distribution in the background, facet on 
# species, and nudge the overall one a tiny bit to make the 
# comparison look nicer.
df |> 
  drop_na() |> 
  ggplot() + 
  # Add the background layer, nudged with position_nudge()
  geom_col(mapping = aes(x = flip_f, y = all_prop),
           color = "black", size = 0.1, fill = "gray50",
           alpha = 0.7, position = position_nudge(x = 0.05)) +
  # Then add the species layer we'll also end up faceting by
  geom_col(mapping = aes(x = flip_f, y = species_prop, 
                         fill = species),
           color = "black", size = 0.1,
           alpha = 0.8) + 
  ggokabeito::scale_fill_okabe_ito() + 
  scale_y_continuous(labels = scales::label_percent()) + 
  guides(fill = "none") + 
  facet_wrap(~ species, ncol = 1) + 
  labs(x = "Flipper width in mm", y = "Percent of Penguins", 
       title = "Flipper Width Distribution by Species", 
       subtitle = "Distribution for all penguins shown in grey", 
       caption = "Data: palmerpenguins. Graph: Kieran Healy / @kjhealy.",
       fill = "Species") + 
  theme(axis.text.x = element_text(size = rel(0.6)))