case_when {dplyr} | R Documentation |
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
... |
< 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.
|
.default |
The value used when all of the LHS inputs return either
If |
.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
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)