onion diagram

R code of the ggplot2 example

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

## Four nested sets of countries in 2007, drawn as concentric circles whose
## areas are their populations: the data's 142 countries, their European
## countries, the European Union, the euro area.
## Membership on 1 January 2007: the EU had 27 members (Bulgaria and Romania
## joined that day), the euro area 13 (Slovenia joined that day). Gapminder
## lacks Cyprus, Estonia, Latvia, Lithuania, Luxembourg and Malta, about
## 9 million people: 21 EU members and 12 euro members remain.
eu <- c("Austria", "Belgium", "Bulgaria", "Czech Republic", "Denmark", "Finland",
        "France", "Germany", "Greece", "Hungary", "Ireland", "Italy", "Netherlands",
        "Poland", "Portugal", "Romania", "Slovak Republic", "Slovenia", "Spain",
        "Sweden", "United Kingdom")
euro <- c("Austria", "Belgium", "Finland", "France", "Germany", "Greece", "Ireland",
          "Italy", "Netherlands", "Portugal", "Slovenia", "Spain")
countries <- gapminder |>
  filter(year == 2007) |>
  mutate(pop = as.numeric(pop), country = as.character(country))
europe <- countries$country[countries$continent == "Europe"]
## Each set lies strictly inside the one around it.
stopifnot(all(euro %in% eu), all(eu %in% europe))

sets <- tibble(
  label = c("All 142 countries", paste(length(europe), "European countries"),
            "European Union, 21 of 27 members", "Euro area, 12 of 13 members"),
  pop = c(sum(countries$pop), sum(countries$pop[countries$country %in% europe]),
          sum(countries$pop[countries$country %in% eu]),
          sum(countries$pop[countries$country %in% euro]))
) |>
  mutate(r = sqrt(pop / 1e9 / pi),
         people = ifelse(pop >= 1e9, sprintf("%.2f billion people", pop / 1e9),
                         sprintf("%.0f million people", pop / 1e6)))
stopifnot(!is.unsorted(rev(sets$pop), strictly = TRUE))

## The three inner sets are named on the right, each by a segment that ends
## in the middle of its ring (or of the inner disc).
R <- sets$r[1]
inner <- sets[-1, ] |>
  mutate(r_mid = (r + c(r[-1], 0)) / 2,
         angle = c(40, 0, -40) * pi / 180,
         x = r_mid * cos(angle), y = r_mid * sin(angle),
         xend = R + 0.25, yend = c(0.75, 0, -0.75))

p <- ggplot() +
  geom_circle(data = sets, aes(x0 = 0, y0 = 0, r = r), colour = "#9b2367",
              fill = "#9b2367", alpha = 0.14, linewidth = 0.4) +
  annotate("text", x = 0, y = R * 0.68, size = 3, colour = "#535353", lineheight = 0.9,
           label = paste0(sets$label[1], "\n", sets$people[1])) +
  geom_segment(data = inner, aes(x = x, y = y, xend = xend, yend = yend),
               colour = "#535353", linewidth = 0.3) +
  geom_point(data = inner, aes(x = x, y = y), colour = "#535353", size = 0.6) +
  geom_text(data = inner, aes(x = xend + 0.06, y = yend, label = paste0(label, "\n", people)),
            hjust = 0, size = 2.8, colour = "#535353", lineheight = 0.9) +
  coord_equal(xlim = c(-R - 0.05, R + 2.6), clip = "off") +
  labs(title = "One person in twenty lived in the euro area in 2007",
       subtitle = "Population of the 142 countries in the data; areas drawn to scale",
       x = NULL, y = NULL,
       caption = "Data: Gapminder, via the gapminder R package; membership on 1 January 2007") +
  theme_lex_viz(grid = "", arrows = "") +
  theme(axis.text = element_blank())