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

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())