ggplot2 - Equal x-axis distances across faceted plots

Question

Assume three datasets (A, B, and C), each representing a data.frame with four columns. The data in each dataset are paired, with the first half of all rows representing state "bf", and the second half of all row representing the state "after". The number of rows in each dataset is different, with set C containing equal to or more rows than A and B together.

A = structure(list(marker = c("a", "b", "c", "d", "a", "b", "c", "d", "a", "b", "c", "d", "a", "b", "c", "d"), value = c("0.962", "0.923", "0.921", "0.938", "0.949", "0.898", "0.811", "1", "0.967", "0.944", "0.946", "0.96", "0.889", "0.923", "0.864", "1"), metric = c("rc", "rc", "rc", "rc", "ci", "ci", "ci", "ci", "rc", "rc", "rc", "rc", "ci", "ci", "ci", "ci"), treatment = c("b4", "b4", "b4", "b4", "b4", "b4", "b4", "b4", "after", "after", "after", "after", "after", "after", "after", "after")), row.names = c(NA, -16L), class = "data.frame")
B = structure(list(marker = c("a", "b", "a", "b", "a", "b", "a", "b"), value = c("1", "0.967", "0.966", "0.962", "1", "1", "0.967", "0.965"), metric = c("rc", "rc", "ci", "ci", "rc", "rc", "ci", "ci"), treatment = c("b4", "b4", "b4", "b4", "after", "after", "after", "after")), row.names = c(NA, -8L), class = "data.frame")
C = structure(list(marker = c("a", "b", "c", "d", "e", "f", "a", "b", "c", "d", "e", "f", "a", "b", "c", "d", "e", "f", "a", "b", "c", "d", "e", "f"), value = c("0.944", "0.934", "0.947", "0.944", "0.949", "0.922", "0.909", "0.923", "0.958", "0.857", "0.9", "0.914", "0.944", "0.934", "0.947", "0.944", "0.949", "0.922", "0.909", "0.923", "0.958", "0.857", "0.9", "0.914"), metric = c("rc", "rc", "rc", "rc", "rc", "rc", "ci", "ci", "ci", "ci", "ci", "ci", "rc", "rc", "rc", "rc", "rc", "rc", "ci", "ci", "ci", "ci", "ci", "ci"), treatment = c("b4", "b4", "b4", "b4", "b4", "b4", "b4", "b4", "b4", "b4", "b4", "b4", "after", "after", "after", "after", "after", "after", "after", "after", "after", "after", "after", "after")), row.names = c(NA, -24L), class = "data.frame")

Assume further that we wish to visualize the variability of column value between the different classes.

library(ggplot2)
library(ggpubr)

Plot_A = ggplot(data=data.frame(A), aes(x=marker, y=as.numeric(value), group=treatment, color=metric)) +
    facet_grid(metric ~ .) + 
    geom_line(aes(linetype=treatment)) + 
    theme(axis.text.x=element_text(angle=45, hjust=1),
          legend.position="none",
          axis.title.x=element_blank()) +
    ylab("")

Plot_B = ggplot(data=data.frame(B), aes(x=marker, y=as.numeric(value), group=treatment, color=metric)) +
    facet_grid(metric ~ .) + 
    geom_line(aes(linetype=treatment)) + 
    theme(axis.text.x=element_text(angle=45, hjust=1),
          legend.position="none",
          axis.title.x=element_blank()) +
    ylab("")

Plot_C = ggplot(data=data.frame(C), aes(x=marker, y=as.numeric(value), group=treatment, color=metric)) +
    facet_grid(metric ~ .) + 
    geom_line(aes(linetype=treatment)) + 
    theme(axis.text.x=element_text(angle=45, hjust=1),
          legend.position="bottom") + 
    xlab("Marker") +
    ylab("Value")
ggarrange(Plot_A, Plot_B, Plot_C, nrow=3,  ncol=1)

How can I ensure that the x-axis distances between the individual markers in both, plots A and B, are the same as in plot C?

This what I want to achieve (without having to edit the individual plot widths manually):

Answer 1

Maybe this approach can help you. You can add scale_x_discrete(limits=unique(C$marker)) to the A and B plots, so that you keep same levels across all plots. Here the code. Also you can create a independent vector for the levels in x-axis and use it directly as vec=c("a", "b", "c", "d", "e", "f") and then scale_x_discrete(limits=vec). The key is fixing this element in all the required plots:

library(ggplot2)
library(ggpubr)

Plot_A = ggplot(data=data.frame(A), aes(x=marker, y=as.numeric(value), group=treatment, color=metric)) +
  facet_grid(metric ~ .) + 
  geom_line(aes(linetype=treatment)) + 
  scale_x_discrete(limits=unique(C$marker))+
  theme(axis.text.x=element_text(angle=45, hjust=1),
        legend.position="none",
        axis.title.x=element_blank()) +
  ylab("")

Plot_B = ggplot(data=data.frame(B), aes(x=marker, y=as.numeric(value), group=treatment, color=metric)) +
  facet_grid(metric ~ .) + 
  geom_line(aes(linetype=treatment)) + 
  scale_x_discrete(limits=unique(C$marker))+
  theme(axis.text.x=element_text(angle=45, hjust=1),
        legend.position="none",
        axis.title.x=element_blank()) +
  ylab("")

Plot_C = ggplot(data=data.frame(C), aes(x=marker, y=as.numeric(value), group=treatment, color=metric)) +
  facet_grid(metric ~ .) + 
  geom_line(aes(linetype=treatment)) + 
  scale_x_discrete(limits=unique(C$marker))+
  theme(axis.text.x=element_text(angle=45, hjust=1),
        legend.position="bottom") + 
  xlab("Marker") +
  ylab("Value")

ggarrange(Plot_A, Plot_B, Plot_C, nrow=3,  ncol=1)

Output: