Percentage labels on grouped column chart with percentage summing up to 100% per group-CodePudding

I have been breaking my head on this one, but have not succeeded to figure it out yet.

What I am trying to do is quite simple; Instead of placing percentages on the chart totaling 100%, I would like to put percentages totaling to 100% PER GROUP. So e.g. all_other should sum up to 100% and the other groups as well.

Is there any easy way to do this, or would you have to calculate these percentages and add them as a separate column?

The chart shown above is coded this way;

loans %>% 
  count(purpose = factor(purpose), not.fully.paid = factor(not.fully.paid)) %>% 
  mutate(pct = prop.table(n)) %>%
  ggplot(aes(x=purpose,y=pct, fill =not.fully.paid,label = scales::percent(pct)))   geom_col(position="dodge")  scale_y_continuous(labels=scales::percent)  geom_text(position = position_dodge(width = .9),vjust = -0.5,size = 3)

This way, I tried to get a table showing the numbers as shown in the graph above. However, I still needed to convert the count to a percentage of that specific group and here I got stuck yet again :/ e.g. 1944/(1944 387) as shown below. I am not sure if this substep is the right approach. Hope someone can help!

loans$Count <- 1
df <- loans %>% group_by(purpose,not.fully.paid)
df <- df %>% summarise(sum(Count))`

 purpose            not.fully.paid `sum(Count)`
  <chr>              <fct>                 <dbl>
1 all_other          0                      1944
2 all_other          1                       387
3 credit_card        0                      1116
4 credit_card        1                       146
5 debt_consolidation 0                      3354
6 debt_consolidation 1                       603

CodePudding user response：

You could get your percentages using ... %>% group_by(purpose) %>% mutate(pct = n / sum(n)) after count:

library(dplyr)
library(ggplot2)

loans_count %>%
  group_by(purpose) %>%
  mutate(pct = n / sum(n)) %>%
  ggplot(aes(x = purpose, y = pct, fill = not.fully.paid, label = scales::percent(pct)))  
  geom_col(position = "dodge")  
  scale_y_continuous(labels = scales::percent)  
  geom_text(position = position_dodge(width = .9), vjust = -0.5, size = 3)

DATA

structure(list(purpose = c("all_other", "all_other", "credit_card", 
"credit_card", "debt_consolidation", "debt_consolidation"), not.fully.paid = structure(c(1L, 
2L, 1L, 2L, 1L, 2L), levels = c("0", "1"), class = "factor"), 
    n = c(1944L, 387L, 1116L, 146L, 3354L, 603L)), row.names = c("1", 
"2", "3", "4", "5", "6"), class = "data.frame")