ggpattern-fake-ggdist.md

library(tidyverse)
library(ggdist)
library(ggpattern)

# Just look at a few categories
diamonds_small <- diamonds %>% 
  filter(cut %in% c("Fair", "Good", "Very Good"))

# Manually calculate summary statistics since we can't use stat_pointinterval()
# and instead have to use geom_pointinterval()
diamonds_summary <- diamonds_small %>% 
  group_by(cut) %>% 
  median_qi(price, .width = c(0.5, 0.8, 0.95))

# Plot!
diamonds_small %>% 
  ggplot(aes(x = price, fill = cut, pattern_fill = cut)) +
  geom_density_pattern(
    aes(y = after_stat(density * 1e5)),  # Scale this up so that the pointinterval fits on the plot
    pattern = "stripe",  # Stripes
    pattern_density = 0.5,  # Take up 50% of the pattern (i.e. stripes equally sized)
    pattern_spacing = 0.2,  # Thicker stripes
    pattern_size = 0,  # No border on the stripes
    trim = TRUE,  # Trim the ends of the distributions
    linewidth = 0  # No border on the distributions
  ) +
  # Add 50%, 80%, and 95% intervals + median
  geom_pointinterval(data = diamonds_summary, aes(x = price, xmin = .lower, xmax = .upper)) +
  # Set colors for fills and pattern fills
  scale_fill_manual(values = c("red", "blue", "orange")) +
  scale_pattern_fill_manual(values = colorspace::lighten(c("red", "blue", "orange"), 0.1)) +
  # Turn off legends
  guides(fill = "none", pattern_fill = "none") +
  labs(y = NULL) +
  # Need to facet because the y-axis doesn't use categories like stat_halfeye() or ggridges
  facet_wrap(vars(cut), ncol = 1) +
  # Turn off the y-axis and make some other theme tweaks
  theme_minimal() +
  theme(axis.text.y = element_blank(),
        axis.ticks.y = element_blank(),
        strip.text = element_text(face = "bold", hjust = 0))

^{Created on 2023-05-11 with reprex v2.0.2}