R barplot of two categorical variables

Question

I have a dataframe, i am interested in the relationship between two categorical variables Type and Location, Type has 5 levels and the Location has 20 levels.

I want to plot the percentage of Types for each location. I wanted to know if there was a concise way of doing it using ggplot2 ?

In my case the variable in the x axis has 20 levels so i am also running into spacing issues, any help would be appreciated

EDIT: A more concrete example:

df
   gender beverage
1  Female     coke
2    Male     bear
3    Male     coke
4  Female     bear
5    Male      tea
6    Male     bear
7  Female    water
8  Female      tea
9  Female     bear
10   Male      tea

I want to plot the gender wise percentage of each beverage, eg: There are 3 tea drinkers of which 2 are male and 1 is female so male % would be 66.67 and female percentage would be 33.33 So in the x axis corresponding to tea there should be two bars male with y = 66.67 and female with y = 33.33.

Answer 1

The easiest way is to pre-process, since we have to calculate the percentages separately by gender. I use complete to make sure we have the zero percent bars explicitly in the data.frame, otherwise ggplot will ignore that bar and widen the other gender's bar.

library(dplyr)
library(tidyr)
df2 <- df %>% 
  group_by(gender, beverage) %>% 
  tally() %>% 
  complete(beverage, fill = list(n = 0)) %>% 
  mutate(percentage = n / sum(n) * 100)

ggplot(df2, aes(beverage, percentage, fill = gender)) + 
  geom_bar(stat = 'identity', position = 'dodge') +
  theme_bw()

Or the other way around:

df3 <- df %>% 
  group_by(beverage, gender) %>% 
  tally() %>% 
  complete(gender, fill = list(n = 0)) %>% 
  mutate(percentage = n / sum(n) * 100)

ggplot(df3, aes(beverage, percentage, fill = gender)) + 
  geom_bar(stat = 'identity', position = 'dodge') +
  theme_bw()