Create multiple bar graphs in one bar graph

Question

I have a dataset which looks like the following:

my_DataSet <- {

#	Variable A	Variable B	Variable C	Control Group
1	1	0	0	1
2	1	1	0	1
3	0	0	1	0

}

Following Plot multiple boxplot in one graph , I did a transformation ( new_DataSet <- melt(my_DataSet, id.var = "Control_Group") ) so that the resulting data looks like this: I have a dataset which looks like the following:

new_DataSet <- {

#	Control Group	variable	value
1	1	Variable A	1
2	1	Variable B	0
3	1	Variable C	0
4	1	Variable A	1
5	1	Variable B	1
6	1	Variable C	0
7	0	Variable A	0
8	0	Variable B	0
9	0	Variable C	1

}

I want to produce a bar graph which shows the percentage of 1s in the control and intervention group along all 3 variables.

I imagine something like the following bar graph:

What I have done is the following:

p <- ggplot(data = my_DataSet)
p + geom_bar(mapping = aes(x = Variable_A, y = ..prop.., fill = Control_Group), position = "dodge")

This results in:

Which has two issues

• It only displays Variable A , not A , B and C
• I only want the percentage for the 1s, not for the zeroes. If I filter my data beforehand, the proportion becomes wrong, however.

Answer 1

You can get the proportions for each column and each control group and plot the bar graph.

library(tidyverse)

my_DataSet %>%
  pivot_longer(cols = -Control_group) %>%
  group_by(name, Control_group = recode(Control_group, 
                 '1' = 'control', '0' = 'intervention')) %>%
  summarise(value = mean(value)) %>%
  ggplot() + aes(name, value, fill = Control_group) + 
  geom_bar(stat = 'identity', position = 'dodge')