case_when() function in R is part of the
dplyr package and is an elegant way to perform multiple if-else statements within a
summarise() function, or even stand-alone. In this article, we will dive into how to write and understand the
case_when() function in R, including its syntax, examples, and best practices.
Table of Contents
- Introduction to
- Basic Syntax
- Practical Examples
- 4.1 Basic Usage
- 4.2 Using with
- 4.3 Using with
- 4.4 Stand-alone Use
- 4.5 Nested
- Advanced Tips
- Common Pitfalls and How to Avoid Them
Before diving into the
case_when() function, you should have install the
dplyr package, which can be done using the following code:
Load the package using:
2. Introduction to case_when( )
case_when() function allows you to vectorize multiple
if_else() conditions. It operates in a way similar to SQL’s
CASE WHEN statement, helping you avoid a lengthy series of nested
3. Basic Syntax
The basic syntax of
case_when() is as follows:
case_when( condition1 ~ value1, condition2 ~ value2, ... TRUE ~ value_default )
condition2, …: These are logical conditions that will be checked.
value2, …: These are the values that will be returned if the condition is TRUE.
TRUE ~ value_default: A default value if none of the conditions are met.
4. Practical Examples
4.1 Basic Usage
Here’s a basic example using a vector of numbers:
nums <- c(1, 2, 3, 4, 5) result <- case_when( nums <= 2 ~ "small", nums <= 4 ~ "medium", TRUE ~ "large" ) print(result)
 "small" "small" "medium" "medium" "large"
4.2 Using with mutate( )
You can use
case_when() within the
mutate() function to create a new column based on some conditions.
data <- tibble( age = c(22, 45, 67, 34, 29) ) data <- data %>% mutate( age_group = case_when( age < 30 ~ "young", age < 50 ~ "middle-aged", TRUE ~ "old" ) )
4.3 Using with summarise( )
Similarly, you can use
summarise() to aggregate data conditionally.
data %>% summarise( num_young = sum(case_when( age < 30 ~ 1, TRUE ~ 0 )) )
4.4 Stand-alone Use
You can use
case_when() as a stand-alone function to perform calculations based on conditions.
result <- case_when( nums %% 2 == 0 ~ "even", TRUE ~ "odd" )
4.5 Nested case_when( )
You can also nest
case_when() functions for more complex logic.
result <- case_when( nums %% 2 == 0 ~ case_when( nums > 3 ~ "even and large", TRUE ~ "even and small" ), TRUE ~ "odd" )
5. Advanced Tips
case_when()in combination with other
dplyrfunctions for cleaner and more efficient code.
- You can use other R functions within
case_when()for complex calculations.
6. Common Pitfalls and How to Avoid Them
- Order Matters: Conditions are checked in order. Once a TRUE condition is found,
case_when()will stop checking subsequent conditions.
- Missing Default Case: Always include a default case (
TRUE ~ value_default) to catch cases that don’t meet any condition.
- Type Consistency: Make sure all the return values are of the same type.
case_when() function in R, a part of the
dplyr package, provides a clean and efficient way to perform multiple conditional statements. Its usage can be diverse, ranging from stand-alone cases to being embedded in other
dplyr functions like
summarise(). It is essential to remember the order of conditions, include a default case, and maintain type consistency while using
With this comprehensive guide, you should now be able to employ
case_when() effectively in your R programming.