Vikash B - 1 year ago 100

R 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.

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Answer Source

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()
```

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