How to define common y-axis limits when using facet_grid() in ggplot2

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My third post here. I am leading the plot design using lines and areas in ggplot2 with facet_grid(). The code works well. Here is the data I used:

#My data
df <- structure(list(Var = structure(c(1L, 2L, 3L, 4L, 5L, 6L, 7L, 
8L, 9L, 10L, 11L, 12L, 1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 
11L, 12L), .Label = c("1", "2", "3", "4", "5", "6", "7", "8", 
"9", "10", "11", "12"), class = c("ordered", "factor")), Val = c(46.0233614780009, 
85.6471698498353, 83.8100037071854, 98.6977939726785, 94.0682111307979, 
92.1834012959152, 79.1579962009564, 62.9422475816682, 2.36891501117498, 
25.3718703053892, 87.2779565863311, 32.0944497128949, 444.363995105959, 
337.84707041923, 93.2718054391444, 171.342949266545, 81.6757546272129, 
135.7353850035, 286.496924120001, 450.293861329556, 339.913251576945, 
80.7274857070297, 122.17661133036, 370.043645612895), Group = c("Up", 
"Up", "Up", "Up", "Up", "Up", "Up", "Up", "Up", "Up", "Up", "Up", 
"Down", "Down", "Down", "Down", "Down", "Down", "Down", "Down", 
"Down", "Down", "Down", "Down")), row.names = c(NA, -24L), class = "data.frame")

Now this is my plot:

library(ggplot2)
library(dplyr)
#Code for the plot
df %>%
  mutate(Val=ifelse(Group=='Down',-Val,Val),
         Group=factor(Group,levels = c('Up','Down'),ordered = T)) %>%
  ggplot(aes(x=Var,y=Val,color=Group,fill=Group,group=Group))+
  geom_line(size=1)+geom_area(alpha=0.75)+
  facet_grid(Group~.,scales = 'free')+
  scale_y_continuous(labels = function(x) abs(x),
                     expand = c(0,0.1))+
  scale_fill_manual(values=c('cyan','tomato'))+
  scale_color_manual(values=c('cyan','tomato'))+
  theme_bw()

Which produces this baby:

enter image description here

Until here everything is fine. I would like if it is possible to modify two elements:

  1. How can I reduce the vertical space between both facets so that visually there would be only one x-axis (align in the same axis both zeroes and reduce that space).

  2. I would like to have the same scale in both y-axis, so the code is designed to have a mirror effect. My issue is that when I set a scale in y-axis like this:

scale_y_continuous(labels = function(x) abs(x),expand = c(0,0.1),limits = c(NA,800))

Everything changes:

enter image description here

I would like if possible that both y-axis have the same scale starting in 0 to 800 but respecting the magnitude. In this case upper would go from 0 to 800 and down from 0 to -800 but masked according to labels to have the mirror effect.

Many thanks for the help.

1 Answers

This looks like an ideal job for the old "invisible dots" trick to set the facet limits where you want them:

library(ggplot2)
library(dplyr)

df %>%
  mutate(Val = ifelse(Group == 'Down', -Val, Val),
         Group = factor(Group, levels = c('Up', 'Down'), ordered = TRUE)) %>%
  ggplot(aes(Var, Val, color = Group, fill = Group, group = Group)) +
  geom_line(size = 1) +
  geom_area(alpha = 0.75) +
  geom_point(data = data.frame(Group = factor(c("Down", "Up"), c('Up', 'Down')),
                               Var = c(1, 1),
                               Val = c(-800, 800)), alpha = 0) +
  facet_grid(Group~., scales = 'free') +
  scale_y_continuous(labels = function(x) abs(x),
                     expand = c(0, 0.1)) +
  scale_fill_manual(values = c('cyan', 'tomato')) +
  scale_color_manual(values = c('cyan', 'tomato')) +
  theme_bw() +
  theme(panel.spacing = unit(0, "points"))

enter image description here

Though, it's only fair to point out you don't really need facets here and you get a very similar effect by doing:

df %>%
  mutate(Val = ifelse(Group == 'Down', -Val, Val),
         Group = factor(Group, levels = c('Up', 'Down'), ordered = TRUE)) %>%
  ggplot(aes(Var, Val, color = Group, fill = Group, group = Group)) +
  geom_line(size = 1) +
  geom_area(alpha = 0.75) +
  geom_hline(yintercept = 0) +
  scale_y_continuous(labels = function(x) abs(x),
                     expand = c(0, 0.1),
                     limits = c(-800, 800)) +
  scale_fill_manual(values = c('cyan', 'tomato')) +
  scale_color_manual(values = c('cyan', 'tomato')) +
  theme_bw() +
  theme(panel.spacing = unit(0, "points"))

enter image description here

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