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case_when with factor levels

Source: R/case_when_fct.R
case_when_fct.Rd

Recode a variable using the dplyr::case_when() syntax

Usage

case_when_fct(..., .default = NULL)

Arguments

...

<dynamic-dots> A sequence of two-sided formulas. The left hand side (LHS) determines which values match this case. The right hand side (RHS) provides the replacement value.

The LHS inputs must evaluate to logical vectors.

The RHS inputs will be coerced to their common type.

All inputs will be recycled to their common size. That said, we encourage all LHS inputs to be the same size. Recycling is mainly useful for RHS inputs, where you might supply a size 1 input that will be recycled to the size of the LHS inputs.

NULL inputs are ignored.

.default

A string. The value used when all of the LHS inputs return either FALSE or NA. If NULL, the default, a NA will be used.

Examples

# load the dplyr library so we can use `mutate()`
library(dplyr)

# let's use the `test_data` data set and convert `edu` to a dichotomous factor
# of college degree vs no degree. I'll demonstrate this a few different ways
new_data <- test_data %>%
  mutate(
    edu_f2 = case_when_fct(
      edu %in% c(1:3) ~ "No degree",
      # we can specify the other values explicitly like this
      edu %in% c(4:5) ~ "College degree"
    )
  )

# we can see that the `edu_f2` has two levels and they are in the correct
# and it attached the transformation metadata
str(new_data$edu_f2)
#>  Factor w/ 2 levels "No degree","College degree": 1 1 2 1 1 2 2 2 1 1 ...

# another way of doing this is to indicate that when edu is less than 4 it
# means no degree and when edu is above 3  it means college degree, like this
new_data <- test_data %>%
  mutate(
    edu_f2 = case_when_fct(
      edu < 4 ~ "No degree",
      # we can specify the other values explicitly like this
      edu > 3 ~ "College degree"
    )
  )

# let's check it again
str(new_data$edu_f2)
#>  Factor w/ 2 levels "No degree","College degree": 1 1 2 1 1 2 2 2 1 1 ...

# yet another way to do it, is to use the `.default =` argument to specify
# ALL other values not listed in the prior arguments
new_data <- test_data %>%
  mutate(
    edu_f2 = case_when_fct(
      edu < 4 ~ "No degree",
      # we can specify the other values explicitly like this
      .default = "College degree"
    )
  )

# let's check it again
str(new_data$edu_f2)
#>  Factor w/ 2 levels "No degree","College degree": 1 1 2 1 1 2 2 2 1 1 ...