Tidy up coefficient plot

Question

In the below coefficient plot, I would like to decrease the white space under "Roads" and "Timing" as highlighted in red:

How can I make this look tidier? Below is my current code, using ggplot2:

plotdata <- structure(
  list(
    term = c("Category 1_a","Category 1_b","Category 1_c","Category 1_d","Category 2",
      "Category 3_a","Category 3_b"),
    estimate = c(-0.033882004,0.001508041,0.122957935,-0.033882004,0.001508041,-0.033882004,0.001508041),
    ymin = c(
      -0.13278953,-0.007547426,0.025116265,-0.13278953,-0.007547426,-0.13278953,-0.007547426), ymax = c(0.065025521,0.010563508,0.220799605,0.065025521,0.010563508,0.065025521,0.010563508)
  ), row.names = c(NA,-7L),
  spec = structure(list(cols = list(
      term = structure(list(), class = c("collector_character",
                                         "collector")),
      estimate = structure(list(), class = c("collector_double",
                                             "collector")),
      ymin = structure(list(), class = c("collector_double",
                                         "collector")),
      ymax = structure(list(), class = c("collector_double",
                                         "collector"))
    ),
    default = structure(list(), class = c("collector_guess",
                                          "collector")),
    delim = ","), class = "col_spec"),class = c("spec_tbl_df","tbl_df", "tbl", "data.frame"))

# Libraries
library(dplyr)
library(broom)
library(ggplot2)

# Plot
plotdata %>%
  mutate(category = rep(c("Pollution", "Roads", "Timing"), times = c(4, 1, 2))) %>%
  mutate(term = factor(term, levels = rev(term))) %>%
  ggplot(aes(x = term, y = estimate)) + 
  geom_hline(yintercept = 0, color="black", size = 0.5, linetype = "dashed") +
  geom_pointrange(aes(ymin = ymin, ymax = ymax), size = 0.5, 
                  fill="#0202fe", color="#b5b5b5", shape=21, stroke = 1) +
  labs(x = NULL, y = "Coefficient Estimate") +
  scale_x_discrete(expand = c(0.4, 0.1)) +
  coord_flip() +
  facet_grid(category~., switch = 'y', scales = 'free_y') +
  theme_classic(base_size = 13) +
  theme(strip.placement = 'outside',
        strip.background = element_blank(),
        strip.text.y.left = element_text(face = 'bold', angle = 0, vjust = 1, hjust = 1),
        panel.spacing.y = unit(0, 'mm'))

Answer 1

This could be achieved via the space argument of facet_grid . Setting space="free_y" will set the panel size according to the "proportional to the length of the y scale", ie the number of categories:

Note: I also dropped the scale_x_discrete .

library(dplyr)
library(broom)
library(ggplot2)

# Plot
plotdata %>%
  mutate(category = rep(c("Pollution", "Roads", "Timing"), times = c(4, 1, 2))) %>%
  mutate(term = factor(term, levels = rev(term))) %>%
  ggplot(aes(x = term, y = estimate)) + 
  geom_hline(yintercept = 0, color="black", size = 0.5, linetype = "dashed") +
  geom_pointrange(aes(ymin = ymin, ymax = ymax), size = 0.5, 
                  fill="#0202fe", color="#b5b5b5", shape=21, stroke = 1) +
  labs(x = NULL, y = "Coefficient Estimate") +
  coord_flip() +
  facet_grid(category~., switch = 'y', scales = 'free_y', space = "free_y") +
  theme_classic(base_size = 13) +
  theme(strip.placement = 'outside',
        strip.background = element_blank(),
        strip.text.y.left = element_text(face = 'bold', angle = 0, vjust = 1, hjust = 1),
        panel.spacing.y = unit(0, 'mm'))