geom_map(
  mapping = NULL,
  data = NULL,
  stat = "identity",
  ...,
  map,
  na.rm = FALSE,
  show.legend = NA,
  inherit.aes = TRUE
)

# When using geom_polygon, you will typically need two data frames:
# one contains the coordinates of each polygon (positions),  and the
# other the values associated with each polygon (values).  An id
# variable links the two together

ids <- factor(c("1.1", "2.1", "1.2", "2.2", "1.3", "2.3"))

values <- data.frame(
  id = ids,
  value = c(3, 3.1, 3.1, 3.2, 3.15, 3.5)
)

positions <- data.frame(
  id = rep(ids, each = 4),
  x = c(2, 1, 1.1, 2.2, 1, 0, 0.3, 1.1, 2.2, 1.1, 1.2, 2.5, 1.1, 0.3,
  0.5, 1.2, 2.5, 1.2, 1.3, 2.7, 1.2, 0.5, 0.6, 1.3),
  y = c(-0.5, 0, 1, 0.5, 0, 0.5, 1.5, 1, 0.5, 1, 2.1, 1.7, 1, 1.5,
  2.2, 2.1, 1.7, 2.1, 3.2, 2.8, 2.1, 2.2, 3.3, 3.2)
)

ggplot(values) +
  geom_map(aes(map_id = id), map = positions) +
  expand_limits(positions)
ggplot(values, aes(fill = value)) +
  geom_map(aes(map_id = id), map = positions) +
  expand_limits(positions)
ggplot(values, aes(fill = value)) +
  geom_map(aes(map_id = id), map = positions) +
  expand_limits(positions) + ylim(0, 3)

# Better example
if (require(maps)) {

  crimes <- data.frame(state = tolower(rownames(USArrests)), USArrests)

  # Equivalent to crimes %>% tidyr::pivot_longer(Murder:Rape)
  vars <- lapply(names(crimes)[-1], function(j) {
    data.frame(state = crimes$state, variable = j, value = crimes[[j]])
  })
  crimes_long <- do.call("rbind", vars)

  states_map <- map_data("state")
  ggplot(crimes, aes(map_id = state)) +
    geom_map(aes(fill = Murder), map = states_map) +
    expand_limits(x = states_map$long, y = states_map$lat)

  last_plot() + coord_map()
  ggplot(crimes_long, aes(map_id = state)) +
    geom_map(aes(fill = value), map = states_map) +
    expand_limits(x = states_map$long, y = states_map$lat) +
    facet_wrap( ~ variable)
}