CODEWITHSUNDEEP
rplotggplot2
kraussian
kraussian

Reputation: 279

Display percentage by column on a stacked bar graph

I'm trying to plot a stacked bar chart showing the relative percentages of each group within a column.

Here's an illustration of my problem, using the default mpg data set:

mpg %>%
  ggplot(aes(x=manufacturer, group=class)) +
  geom_bar(aes(fill=class), stat="count") +
  geom_text(aes(label=scales::percent(..prop..)),
    stat="count",
    position=position_stack(vjust=0.5))

And this is the output: enter image description here

My problem is that this output shows the percentage of each class against the grand total, not the relative percentage within each manufacturer.

For example, I want the first column (audi) to show 83.3% (15/18) for brown (compact) and 16.6% (3/18) for green (midsize).

I found a similar question here: How to draw stacked bars in ggplot2 that show percentages based on group?

But I wanted to know if there's an easier way to do this within ggplot2, especially since my actual dataset uses a bunch of dplyr pipes to massage the data before ultimately piping it into ggplot2.

Upvotes: 4

Views: 3613

Answers (2)

zx8754
zx8754

Reputation: 56249

If the plot is in need of numbers and percentages as text on top of the coloured barplots, to help us to see the differences, maybe it is better to present results as a simple table:

round(prop.table(table(mpg$class, mpg$manufacturer), margin = 2), 3) * 100

#             audi chevrolet dodge  ford honda hyundai  jeep land rover lincoln mercury nissan pontiac subaru toyota volkswagen
# 2seater      0.0      26.3   0.0   0.0   0.0     0.0   0.0        0.0     0.0     0.0    0.0     0.0    0.0    0.0        0.0
# compact     83.3       0.0   0.0   0.0   0.0     0.0   0.0        0.0     0.0     0.0   15.4     0.0   28.6   35.3       51.9
# midsize     16.7      26.3   0.0   0.0   0.0    50.0   0.0        0.0     0.0     0.0   53.8   100.0    0.0   20.6       25.9
# minivan      0.0       0.0  29.7   0.0   0.0     0.0   0.0        0.0     0.0     0.0    0.0     0.0    0.0    0.0        0.0
# pickup       0.0       0.0  51.4  28.0   0.0     0.0   0.0        0.0     0.0     0.0    0.0     0.0    0.0   20.6        0.0
# subcompact   0.0       0.0   0.0  36.0 100.0    50.0   0.0        0.0     0.0     0.0    0.0     0.0   28.6    0.0       22.2
# suv          0.0      47.4  18.9  36.0   0.0     0.0 100.0      100.0   100.0   100.0   30.8     0.0   42.9   23.5        0.0

Upvotes: 1

ricoderks
ricoderks

Reputation: 1619

If I compare your question to the link you gave than the difference is that the link "counted" them selves. That's what I did. I'am nor sure if this is than suitable for your real data.

library(ggplot2)
library(dplyr)

mpg %>%
  mutate(manufacturer = as.factor(manufacturer),
         class = as.factor(class)) %>%
  group_by(manufacturer, class) %>%
  summarise(count_class = n()) %>%
  group_by(manufacturer) %>%
  mutate(count_man = sum(count_class)) %>%
  mutate(percent = count_class / count_man * 100) %>%
  ggplot() +
  geom_bar(aes(x = manufacturer,
               y = count_man, 
               group = class,
               fill = class), 
           stat = "identity") +
  geom_text(aes(x = manufacturer,
                y = count_man,
                label = sprintf("%0.1f%%", percent)),
            position = position_stack(vjust = 0.5))

Edit, based on comment :

I made a mistake by selecting the wrong column for y

library(ggplot2)
library(dplyr)

mpg %>%
  mutate(manufacturer = as.factor(manufacturer),
         class = as.factor(class)) %>%
  group_by(manufacturer, class) %>%
  summarise(count_class = n()) %>%
  group_by(manufacturer) %>%
  mutate(count_man = sum(count_class)) %>%
  mutate(percent = count_class / count_man * 100) %>%
  ungroup() %>%
  ggplot(aes(x = manufacturer,
             y = count_class,
             group = class)) +
  geom_bar(aes(fill = class), 
           stat = "identity") +
  geom_text(aes(label = sprintf("%0.1f%%", percent)),
            position = position_stack(vjust = 0.5))

Upvotes: 4

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