case_when: A general vectorised if-else

In dplyr: A Grammar of Data Manipulation

A general vectorised if-else

Description

This function allows you to vectorise multiple if_else() statements. Each case is evaluated sequentially and the first match for each element determines the corresponding value in the output vector. If no cases match, the .default is used as a final "else" statment.

case_when() is an R equivalent of the SQL "searched" ⁠CASE WHEN⁠ statement.

Usage

case_when(..., .default = NULL, .ptype = NULL, .size = 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	The value used when all of the LHS inputs return either FALSE or NA. .default must be size 1 or the same size as the common size computed from .... .default participates in the computation of the common type with the RHS inputs. NA values in the LHS conditions are treated like FALSE, meaning that the result at those locations will be assigned the .default value. To handle missing values in the conditions differently, you must explicitly catch them with another condition before they fall through to the .default. This typically involves some variation of is.na(x) ~ value tailored to your usage of case_when(). If NULL, the default, a missing value will be used.
.ptype	An optional prototype declaring the desired output type. If supplied, this overrides the common type of the RHS inputs.
.size	An optional size declaring the desired output size. If supplied, this overrides the common size computed from ....

Value

A vector with the same size as the common size computed from the inputs in ... and the same type as the common type of the RHS inputs in ....

See Also

case_match()

Examples

x <- 1:70
case_when(
  x %% 35 == 0 ~ "fizz buzz",
  x %% 5 == 0 ~ "fizz",
  x %% 7 == 0 ~ "buzz",
  .default = as.character(x)
)

# Like an if statement, the arguments are evaluated in order, so you must
# proceed from the most specific to the most general. This won't work:
case_when(
  x %%  5 == 0 ~ "fizz",
  x %%  7 == 0 ~ "buzz",
  x %% 35 == 0 ~ "fizz buzz",
  .default = as.character(x)
)

# If none of the cases match and no `.default` is supplied, NA is used:
case_when(
  x %% 35 == 0 ~ "fizz buzz",
  x %% 5 == 0 ~ "fizz",
  x %% 7 == 0 ~ "buzz",
)

# Note that `NA` values on the LHS are treated like `FALSE` and will be
# assigned the `.default` value. You must handle them explicitly if you
# want to use a different value. The exact way to handle missing values is
# dependent on the set of LHS conditions you use.
x[2:4] <- NA_real_
case_when(
  x %% 35 == 0 ~ "fizz buzz",
  x %% 5 == 0 ~ "fizz",
  x %% 7 == 0 ~ "buzz",
  is.na(x) ~ "nope",
  .default = as.character(x)
)

# `case_when()` evaluates all RHS expressions, and then constructs its
# result by extracting the selected (via the LHS expressions) parts.
# In particular `NaN`s are produced in this case:
y <- seq(-2, 2, by = .5)
case_when(
  y >= 0 ~ sqrt(y),
  .default = y
)

# `case_when()` is particularly useful inside `mutate()` when you want to
# create a new variable that relies on a complex combination of existing
# variables
starwars %>%
  select(name:mass, gender, species) %>%
  mutate(
    type = case_when(
      height > 200 | mass > 200 ~ "large",
      species == "Droid" ~ "robot",
      .default = "other"
    )
  )


# `case_when()` is not a tidy eval function. If you'd like to reuse
# the same patterns, extract the `case_when()` call in a normal
# function:
case_character_type <- function(height, mass, species) {
  case_when(
    height > 200 | mass > 200 ~ "large",
    species == "Droid" ~ "robot",
    .default = "other"
  )
}

case_character_type(150, 250, "Droid")
case_character_type(150, 150, "Droid")

# Such functions can be used inside `mutate()` as well:
starwars %>%
  mutate(type = case_character_type(height, mass, species)) %>%
  pull(type)

# `case_when()` ignores `NULL` inputs. This is useful when you'd
# like to use a pattern only under certain conditions. Here we'll
# take advantage of the fact that `if` returns `NULL` when there is
# no `else` clause:
case_character_type <- function(height, mass, species, robots = TRUE) {
  case_when(
    height > 200 | mass > 200 ~ "large",
    if (robots) species == "Droid" ~ "robot",
    .default = "other"
  )
}

starwars %>%
  mutate(type = case_character_type(height, mass, species, robots = FALSE)) %>%
  pull(type)

dplyr documentation built on Nov. 17, 2023, 5:08 p.m.