Manual breaks of facet_wrap() in ggplot2

Question

Problem

I am trying to understand how to provide y-axis breaks manually to facets, generated by the facet_wrap() function in ggplot2 in R .

Minimal reproducible example

Disclaimer: I have borrowed the following example from the R studio community

With the following code, you can specify the y-axis breaks based on the y-axis values in de dataset.

library(ggplot2)
diamonds2 <- subset(diamonds, !(cut == "Fair" & price > 5000))

my_breaks <- function(x) { if (max(x) < 6000) seq(0, 5000, 1000) else seq(0, 15000, 5000) }

ggplot(data = diamonds2, aes(x = carat, y = price)) +
  facet_wrap(~ cut, scales = "free_y") +
  geom_point() +
  scale_y_continuous(breaks = my_breaks)

Question

I would like to be able to specify the breaks manually, based on the facet (in this case: based on the 'cut' of the diamonds). For example, I would like to set the breaks for the 'Fair' cut to seq(1000, 2500, 5000) , the breaks for the 'Good' cut to seq(1500, 3000, 4500, 6000, ..., 15000) and the rest to seq(0,15000, 5000) .

Attempt

I thought that adapting the my_breaks function with an if-else-ladder, specifying the 'cut' would solve the problem, however, it doesn't:

my_breaks <- function(x) { 
  if (cut == "Fair") {seq(0, 5000, 1000) }
  else if (cut == "Good") {seq(1500,15000, 1500)}
  else { seq(0, 15000, 5000) }
}

It provides the error:

Error in cut == "Fair" : comparison (1) is possible only for atomic and list types

Is there another approach to manually provide the breaks to different facets?

Answer 1

Try defining each facet manually by filtering the data and then "patch" the plot up using patchwork package

library(ggplot2)
library(patchwork)

my_plot <- function(df, var, sc) {
  ggplot(data = df, aes(x = carat, y = price)) +
  facet_grid(~ {{var}}) +
  geom_point() +
  coord_cartesian(ylim = {{sc}})
}

diamonds2 <- subset(diamonds, !(cut == "Fair" & price > 5000))

p1 <- diamonds2 %>% filter(cut == "Fair") %>% my_plot(var = "Fair",  sc = c(0, 5000))
p2 <- diamonds2 %>% filter(cut == "Good") %>% my_plot(var = "Good",  sc = c(0, 15000))
p3 <- diamonds2 %>% filter(cut == "Very Good") %>% my_plot(var = "Very Good",  sc = c(0, 1000))
p4 <- diamonds2 %>% filter(cut == "Premium") %>% my_plot(var = "Premium",  sc = c(0, 500))
p5 <- diamonds2 %>% filter(cut == "Ideal") %>% my_plot(var = "Ideal",  sc = c(0, 20000))

p1+p2+p3+p3+p4+plot_layout(ncol = 3)

edit: I realized it was the y-axis breaks to be set pr. facet. In that case

my_plot <- function(df, var, my_breaks) {
  ggplot(data = df, aes(x = carat, y = price)) +
  facet_grid(~ {{var}}) +
  geom_point() +
  scale_y_continuous(breaks = {{my_breaks}})
}

library(ggplot2)
diamonds2 <- subset(diamonds, !(cut == "Fair" & price > 5000))

p1 <- diamonds2 %>% filter(cut == "Fair") %>% my_plot(var = "Fair",  my_breaks = seq(0, 5000, 1000))
p2 <- diamonds2 %>% filter(cut == "Good") %>% my_plot(var = "Good",  my_breaks = seq(1500,15000, 1500))
p3 <- diamonds2 %>% filter(cut == "Very Good") %>% my_plot(var = "Very Good",  my_breaks =seq(1500,15000, 5000))
p4 <- diamonds2 %>% filter(cut == "Premium") %>% my_plot(var = "Premium",  my_breaks = seq(1500,15000, 5000))
p5 <- diamonds2 %>% filter(cut == "Ideal") %>% my_plot(var = "Ideal",  my_breaks = seq(1500,15000, 5000))

p1+p2+p3+p3+p4+plot_layout(ncol = 3)

Edit2: A leaner way to do this using purrr

library(ggplot2)
library(patchwork)
library(purrr)
facets = diamonds2 %>% distinct(cut) %>% pull()
my_breaks = list(seq(0, 5000, 1000), seq(1500,15000, 1500), seq(1500,15000, 5000),
                 seq(1500,15000, 5000), seq(1500,15000, 5000))

plt_list <- purrr::map2(facets, my_breaks, ~my_plot(diamonds2, .x, .y))

Reduce('+', plt_list) + plot_layout(ncol = 3)