Lorenz curve

R code of the ggplot2 example

library(ggplot2)
library(dplyr)
library(gapminder)

## Countries ranked from the lowest to the highest GDP per capita; each
## person counts at their country's average, so the curve ignores the
## inequality inside each country.
lorenz <- gapminder |>
  filter(year == 2007) |>
  mutate(pop = as.numeric(pop), gdp = gdpPercap * pop) |>
  arrange(gdpPercap) |>
  mutate(people = cumsum(pop) / sum(pop), wealth = cumsum(gdp) / sum(gdp))
lorenz <- bind_rows(tibble(people = 0, wealth = 0), lorenz)

half <- approx(lorenz$people, lorenz$wealth, xout = 0.5)$y

p <- ggplot(lorenz, aes(x = people, y = wealth)) +
  geom_abline(slope = 1, intercept = 0, linetype = "dashed", colour = "grey55", linewidth = 0.4) +
  geom_ribbon(aes(ymin = wealth, ymax = people), fill = lex_colors[["plum"]], alpha = 0.25) +
  geom_line(colour = lex_colors[["plum"]], linewidth = 0.8) +
  annotate("segment", x = 0.5, xend = 0.5, y = 0, yend = half, colour = "grey35", linewidth = 0.3) +
  annotate("segment", x = 0, xend = 0.5, y = half, yend = half, colour = "grey35", linewidth = 0.3) +
  annotate("text", x = 0.52, y = half, label = "13% of GDP", hjust = 0, vjust = 1.3, size = 3.3) +
  annotate("text", x = 0.62, y = 0.66, label = "Perfect equality", angle = 45, size = 3.2,
           colour = "grey45", vjust = -0.5) +
  scale_x_continuous(labels = scales::label_percent(), expand = expansion(mult = c(0, 0.02))) +
  scale_y_continuous(labels = scales::label_percent(), expand = expansion(mult = c(0, 0.02))) +
  labs(title = "In 2007, the poorer half of the world accounted\nfor 13% of its GDP",
       subtitle = "Cumulative shares of people and of GDP, each person counted at their\ncountry's average; between-country Gini index 0.57",
       x = "People, poorest country first", y = "GDP",
       caption = "Data: gapminder (Bryan 2025), 142 countries") +
  theme_lex_viz()