fan chart

R code of the ggplot2 example

library(ggplot2)
library(dplyr)
library(HistData)
library(forecast)

## Yearly christenings in London, 1629-1710, projected 20 years ahead.
## auto.arima settles on a random walk: a flat projection, whose
## uncertainty grows with the square root of the horizon.
christenings <- ts(Arbuthnot$Total, start = 1629)
f <- forecast(auto.arima(christenings), h = 20, level = c(50, 80, 95))
bands <- bind_rows(lapply(seq_along(f$level), function(i) {
  tibble(year = as.numeric(time(f$mean)), low = f$lower[, i], high = f$upper[, i],
         level = paste0(f$level[i], "%"))
})) |>
  mutate(level = factor(level, levels = c("95%", "80%", "50%"), ordered = TRUE))
observed <- tibble(year = Arbuthnot$Year, total = Arbuthnot$Total)
projected <- tibble(year = c(1710, as.numeric(time(f$mean))),
                    total = c(tail(Arbuthnot$Total, 1), as.numeric(f$mean)))

p <- ggplot() +
  geom_ribbon(data = bands, aes(x = year, ymin = low, ymax = high, fill = level)) +
  geom_line(data = observed, aes(x = year, y = total), colour = "#535353", linewidth = 0.5) +
  geom_line(data = projected, aes(x = year, y = total), colour = "white", linewidth = 0.5,
            linetype = "dashed") +
  scale_fill_ordinal(type = idest_seq[c(2, 4, 6)], name = "Projection interval") +
  scale_y_continuous(labels = lex_number, breaks = lex_break_breaks, expand = lex_break_expand) +
  labs(title = "By 1730, yearly christenings could number 7 to 23 thousand\n(95% interval)",
       subtitle = "Christenings in London, 1629–1710, and a random-walk projection to 1730",
       x = NULL, y = "Christenings (thousands)",
       caption = "Data: Arbuthnot 1710, via the HistData R package") +
  theme_lex_viz(grid = "y", arrows = "y", break_not_zero = "y") +
  theme(legend.position = "right")