r - calculate mean for geom_hline for mean within each facet - Stack Overflow

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I'm trying to add a horizontal line to each facet of my plot containing the mean value for solely the data in each facet. The only solutions I've found so far are to calculate the mean value in a separate dataframe and add that to the plot. Is there really no way to do this without that added step??

# plot with shared mean across facets
mutate(cars, grp = if_else(speed <15, "slow", "fast")) %>% 
  ggplot(aes(x = speed, y = dist)) +
  geom_point() +
  geom_hline(aes(yintercept = mean(dist))) +
  facet_grid(.~grp)

# I would have thought something like this would work, but it gives the same result
mutate(cars, grp = if_else(speed <15, "slow", "fast")) %>% 
  ggplot(aes(x = speed, y = dist)) +
  geom_point() +
  stat_summary(aes(yintercept = mean(dist)), fun = mean, geom = "hline") +
  facet_grid(.~grp)

I'm trying to add a horizontal line to each facet of my plot containing the mean value for solely the data in each facet. The only solutions I've found so far are to calculate the mean value in a separate dataframe and add that to the plot. Is there really no way to do this without that added step??

# plot with shared mean across facets
mutate(cars, grp = if_else(speed <15, "slow", "fast")) %>% 
  ggplot(aes(x = speed, y = dist)) +
  geom_point() +
  geom_hline(aes(yintercept = mean(dist))) +
  facet_grid(.~grp)

# I would have thought something like this would work, but it gives the same result
mutate(cars, grp = if_else(speed <15, "slow", "fast")) %>% 
  ggplot(aes(x = speed, y = dist)) +
  geom_point() +
  stat_summary(aes(yintercept = mean(dist)), fun = mean, geom = "hline") +
  facet_grid(.~grp)

• r
• ggplot2

Share Improve this question Follow asked Feb 3 at 21:05 tnttnt 1,4592020 silver badges3636 bronze badges

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1 Answer 1

Sorted by: Reset to default 3

You can achieve your desired result using after_stat() to map the mean computed by stat_summary on yintercept and by mapping a constant on x inside stat_summary:

library(ggplot2)
library(dplyr, warn = FALSE)

mutate(cars, grp = if_else(speed < 15, "slow", "fast")) %>%
  ggplot(aes(x = speed, y = dist)) +
  geom_point() +
  stat_summary(
    aes(yintercept = after_stat(y), x = 1),
    fun = mean, geom = "hline"
  ) +
  facet_grid(. ~ grp)

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