ggpk_tukey_ribbons <- function(...) {
  tukey_whisker_min <- function(x) {
    x[head(which(x > quantile(x, 0.25, names = FALSE) - 1.5 * IQR(x)), 1)]
  }
  tukey_whisker_max <- function(x) {
    x[tail(which(x < quantile(x, 0.75, names = FALSE) + 1.5 * IQR(x)), 1)]
  }
  ggpacket(...) %+%
    # Tukey Box Edges
    geom_ribbon(
      .id = "box",
      mapping = aes(fill = ..color..),
      stat = "summary",
      fun = median,
      fun.min = ~quantile(., 0.25, names = FALSE),
      fun.max = ~quantile(., 0.75, names = FALSE),
      alpha = 0.15,
      ...,
      color = NA
    ) %+%
    # Tukey Whiskers
    geom_ribbon(
      .id = "whisker",
      mapping = aes(fill = ..color..),
      stat = "summary",
      fun = median,
      fun.min = tukey_whisker_min,
      fun.max = tukey_whisker_max,
      alpha = 0.15,
      ...,
      color = NA
    ) %+%
    # Median Line
    geom_line(
      .id = list(NULL, "line"),
      stat = "summary",
      fun = median,
      alpha = 0.8,
      ...
    )
}
library(dplyr)
economics_long %>%
  filter(variable %in% c("pop", "unemploy")) %>%
  mutate(
    year = as.integer(format(as.Date(date, format = "%Y-%m-%d"), "%Y"))
  ) %>%
  ggplot() +
  aes(x = year, y = value, color = variable) +
  ggpk_tukey_ribbons() +
  scale_y_log10()