The same width of the bars in geom_bar(position = "dodge") - r

Question

I would like to draw plot with the same width of the bars. Here's my minimal example code:
data <- data.frame(A = letters[1:17],
B = sample(1:500, 17),
C = c(rep(1, 5), rep(2, 6), rep(c(3,4,5), each = 2)))
ggplot(data,
aes(x = C, y = B, label = A,
fill = A)) +
geom_bar(stat = "identity", position = "dodge") +
geom_text(position = position_dodge(width = 0.9), angle = 90)
The result is shown in the picture above:
The width of the bars is dependent on numbers of observation in group given in variable C. I want to have each bar to have the same width.
The facet_grid(~C) works (bars are the same width) it's not what I mean:
ggplot(data,
aes(x = C, y = B, label = A,
fill = A)) +
geom_bar(stat = "identity", position = "dodge") +
geom_text(position = position_dodge(width = 0.9), angle = 90) +
facet_grid(~C)
What I want is to have plot like in the first picture but with bars's width independent on number of observation in each level from column C. How can I do it?
[EDIT] geom_bar(width) changes width of the bars'group but still bars in fifth group are wider than in the first group, so it's not the answer to my question.

Answer 1

Update
Since ggplot2_3.0.0 version you are now be able to use position_dodge2 with preserve = c("total", "single")
ggplot(data,aes(x = C, y = B, label = A, fill = A)) +
geom_col(position = position_dodge2(width = 0.9, preserve = "single")) +
geom_text(position = position_dodge2(width = 0.9, preserve = "single"), angle = 90, vjust=0.25)
Original answer
As already commented you can do it like in this answer:
Transform A and C to factors and add unseen variables using tidyr's complete. Since the recent ggplot2 version it is recommended to use geom_col instead of geom_bar in cases of stat = "identity":
data %>%
as.tibble() %>%
mutate_at(c("A", "C"), as.factor) %>%
complete(A,C) %>%
ggplot(aes(x = C, y = B, fill = A)) +
geom_col(position = "dodge")
Or work with an interaction term:
data %>%
ggplot(aes(x = interaction(C, A), y = B, fill = A)) +
geom_col(position = "dodge")
And by finally transforming the interaction to numeric you can setup the x-axis according to your desired output. By grouping (group_by) you can calculate the matching breaks. The fancy stuff with the {} around the ggplot argument is neseccary to directly use the vaiables Breaks and C within the pipe.
data %>%
mutate(gr=as.numeric(interaction(C, A))) %>%
group_by(C) %>%
mutate(Breaks=mean(gr)) %>%
{ggplot(data=.,aes(x = gr, y = B, fill = A, label = A)) +
geom_col(position = "dodge") +
geom_text(position = position_dodge(width = 0.9), angle = 90 ) +
scale_x_continuous(breaks = unique(.$Breaks),
labels = unique(.$C))}
Edit:
Another approach would be to use facets. Using space = "free_x" allows to set the width proportional to the length of the x scale.
library(tidyverse)
data %>%
ggplot(aes(x = A, y = B, fill = A)) +
geom_col(position = "dodge") +
facet_grid(~C, scales = "free_x", space = "free_x")
You can also plot the facet labels on the bottom using switch and remove x axis labels
data %>%
ggplot(aes(x = A, y = B, fill = A)) +
geom_col(position = "dodge") +
facet_grid(~C, scales = "free_x", space = "free_x", switch = "x") +
theme(axis.text.x = element_blank(),
axis.ticks.x = element_blank(),
strip.background = element_blank())