ggplot stacked bar graph with bars relating to two different variables with percentages

Question

I would like to create a stacked bar graph with ggplot where the heights of the bars depend on the values of one variable (voter turnout in %) and the stacks of the bars individually add up to 100% of another variable (voteshare in %). So for the year 1990 there was a voter turnout of 96.7 and the bar should be filled with the individual voteshares of each party, which add up to 100% (of the 96.7%). I look at the data of 3 parties and 3 years.

Here is my data:

party <- c("a", "b", "c", "a", "b", "c", "a", "b", "c") 
year <- c(1990, 1990, 1990, 1991, 1991, 1991, 1992,1992, 1992)
voteshare <- c(0,33.5, 66.5, 40.5, 39.0, 20.5, 33.6, 33.4, 33)
turnout = c(96.7,96.7,96.7, 85.05,85.05,85.05, 76.41, 76.41, 76.41)
df<- data.frame(parties, year, voteshare, turnout)

In addition, I would like to put the numbers of the individual voteshares and the total turnout inside the graph.

My approach so far:

ggplot(df, aes(x=year, y=interaction(turnout, voteshare), fill=party)) + 
    geom_bar(stat="identity", position=position_stack()) +
    geom_text(aes(label=Voteshare), vjust=0.5)

It's a mess.

Thanks a ton in advance!

Answer 1

I used a dplyr pipeline to:

• create a column for adjusted vote total which is the product of each party's share and total turnout.
• get rid of the zero rows so no zeros appear on the final output
• calculate the y value where the vote total should be displayed by taking the cumsum() of vote share by party, grouped by year. I had to use rev() because the default of position_stack() is to put the low number in alphabetical order at the top of the stack.

Code

library(dplyr)
library(ggplot2)

df <- df %>%
  mutate(adj_vote = turnout * voteshare / 100) %>%
  filter(adj_vote > 0) %>%
  group_by(year) %>% 
  mutate(cum_vote = cumsum(rev(adj_vote)),
         vote_label = rev(voteshare))


ggplot(df, aes(x=year, y=adj_vote, fill=party)) + 
  geom_bar(stat="identity", position=position_stack()) +
  geom_text(aes(label=vote_label, y = cum_vote), vjust=0.5)

Output