How to Use case_when() in dplyr

The case_when() function from the dplyr package in R can be used to create new variables from existing variables.

This function uses the following basic syntax:

library(dplyr)

df %>%
  mutate(new_var = case_when(var1 low',
                             var2 med',
                             TRUE ~ 'high'))

Note that TRUE is equivalent to an “else” statement.

The following examples show how to use this function in practice with the following data frame:

#create data frame
df frame(player = c('AJ', 'Bob', 'Chad', 'Dan', 'Eric', 'Frank'),
                 position = c('G', 'F', 'F', 'G', 'C', NA),
                 points = c(12, 15, 19, 22, 32, NA),
                 assists = c(5, 7, 7, 12, 11, NA))

#view data frame
df

  player position points assists
1     AJ        G     12       5
2    Bob        F     15       7
3   Chad        F     19       7
4    Dan        G     22      12
5   Eric        C     32      11
6  Frank       NA     NA      NA

Example 1: Create New Variable from One Existing Variable

The following code shows how to create a new variable called quality whose values are derived from the points column:

df %>%
  mutate(quality = case_when(points > 20 ~ 'high',
                             points > 15 ~ 'med',
                             TRUE ~ 'low' ))

  player position points assists quality
1     AJ        G     12       5     low
2    Bob        F     15       7     low
3   Chad        F     19       7     med
4    Dan        G     22      12    high
5   Eric        C     32      11    high
6  Frank       NA     NA      NA     low

Here is exactly how the case_when() function created the values for the new column:

• If the value in the points column is greater than 20, then the value in the quality column is “high”
• Else, if the value in the points column is greater than 15, then the value in the quality column is “med”
• Else, if the value in the points column is less than or equal to 15 (or a missing value like NA), then the value in the quality column is “low”

Example 2: Create New Variable from Multiple Variables

The following code shows how to create a new variable called quality whose values are derived from both the points and assists column:

df %>%
  mutate(quality = case_when(points > 15 & assists > 10 ~ 'great',
                             points > 15 & assists > 5 ~ 'good',
                             TRUE ~ 'average' ))

  player position points assists quality
1     AJ        G     12       5 average
2    Bob        F     15       7 average
3   Chad        F     19       7    good
4    Dan        G     22      12   great
5   Eric        C     32      11   great
6  Frank       NA     NA      NA average

Note that we can also use the is.na() function to explicitly assign strings to NA values:

df %>%
  mutate(quality = case_when(is.na(points) ~ 'missing',
                             points > 15 & assists > 10 ~ 'great',
                             points > 15 & assists > 5 ~ 'good',
                             TRUE ~ 'average' ))

  player position points assists quality
1     AJ        G     12       5 average
2    Bob        F     15       7 average
3   Chad        F     19       7    good
4    Dan        G     22      12   great
5   Eric        C     32      11   great
6  Frank       NA     NA      NA missing

Additional Resources

How to Arrange Rows in R
How to Count Observations by Group in R
How to Filter Rows that Contain a Certain String in R