CODEWITHSUNDEEP
rggplot2data-visualization
ethancav
ethancav

Reputation: 23

Create a side-by-side bar chart using ggplot2

I have a df that looks like:

> bank
Groups:   Income_Category [5]
  Income_Category `Attrited Customer` `Existing Customer`
  <chr>                         <int>               <int>
1 $120K +                         126                 601
2 $40K - $60K                     271                1519
3 $60K - $80K                     189                1213
4 $80K - $120K                    242                1293
5 Less than $40K                  612                29

I'm looking to create a side-by-side bar chart that's grouped by income level on the X-axis, simply showing counts on the y-axis. To further describe, it should be 5 groupings of 2 bars for numbers of attrited/existing customers.

I'm just really lost as to how I can set the y and fill args in ggplot. The following code does not work but this is how I understand ggplot to work:

ggplot(bank, aes(x = Income_Category, y = stat(count),fill = c(`Attrited Customer`, `Existing Customer`))) +
  geom_col(position = "dodge")

I've searched for similar situations through google/stackOF, documentations, etc but nothing thus far has elucidated how to alter y = and fill = to generate a working plot. Any help or pointers in the right direction are greatly appreciated!!

Upvotes: 0

Views: 188

Answers (1)

Ronak Shah
Ronak Shah

Reputation: 389265

It is easier to plot once you get the data in long format.

library(ggplot2)

long_data <- tidyr::pivot_longer(bank, cols = -Income_Category)
long_data$Income_Category <- factor(long_data$Income_Category, 
            c('Less than $40K', '$40K - $60K', '$60K - $80K', '$80K - $120K', '$120K +'))

Here are some options for plotting.

1.

ggplot(long_data) + aes(name, value, fill = Income_Category) + geom_col()

enter image description here

2.

ggplot(long_data) + aes(Income_Category, value, fill = name) + geom_col()

enter image description here

3.

ggplot(long_data) + aes(Income_Category, value, fill = name) + geom_col(position = 'dodge')

enter image description here

4.

ggplot(long_data) + aes(Income_Category, value) + geom_col() + facet_wrap(~name)

enter image description here

data

It is easier to help if you share data in a format which is easier to copy.

bank <- data.frame(Income_Category = c('$120K +', '$40K - $60K', '$60K - $80K', '$80K - $120K', 'Less than $40K'), 
                   "Attrited Customer" = c(126, 271, 189, 242, 612), 
                   "Existing Customer" = c(601, 1519, 1213, 1293, 29))

Upvotes: 1

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