waterfall chart

R code of the ggplot2 example

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

## From the 1952 total to the 2007 total, one step per continent's growth.
totals <- gapminder |>
  filter(year %in% c(1952, 2007)) |>
  group_by(continent, year) |>
  summarise(pop = sum(as.numeric(pop)) / 1e6, .groups = "drop") |>
  tidyr::pivot_wider(names_from = year, values_from = pop, names_prefix = "y")
steps <- totals |>
  transmute(step = as.character(continent), change = y2007 - y1952) |>
  arrange(desc(change)) |>
  mutate(end = sum(totals$y1952) + cumsum(change), start = end - change, kind = "Growth")
bars <- bind_rows(
  tibble(step = "1952", start = 0, end = sum(totals$y1952), kind = "Total"),
  steps,
  tibble(step = "2007", start = 0, end = sum(totals$y2007), kind = "Total")
) |>
  mutate(x = row_number())

p <- ggplot(bars, aes(xmin = x - 0.4, xmax = x + 0.4, ymin = start, ymax = end, fill = kind)) +
  geom_rect() +
  geom_segment(data = head(bars, -1), aes(x = x + 0.4, xend = x + 0.6, y = end, yend = end),
               colour = "#a6a6a6", linewidth = 0.3, inherit.aes = FALSE) +
  scale_fill_manual(values = c(Total = "#a6a6a6", Growth = "#9b2367")) +
  scale_x_continuous(breaks = bars$x, labels = bars$step, expand = expansion(add = 0.3)) +
  scale_y_continuous(labels = lex_number, expand = expansion(mult = c(0, 0.05))) +
  labs(title = "Asia accounts for 63% of the population growth",
       subtitle = "Population of the 142 Gapminder countries, 1952 to 2007, by continent",
       x = NULL, y = "Population (millions)",
       caption = "Data: Gapminder, via the gapminder R package") +
  theme_lex_viz(grid = "y", arrows = "y") +
  theme(legend.position = "none")