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Vectorized if-else

Source: R/if-else.R
vec_if_else.Rd

vec_if_else() is a vectorized if-else. Compared to the base R equivalent, ifelse(), this function allows you to handle missing values in the condition with missing and always takes true, false, and missing into account when determining what the output type should be.

Usage

vec_if_else(
  condition,
  true,
  false,
  ...,
  missing = NULL,
  ptype = NULL,
  condition_arg = "condition",
  true_arg = "true",
  false_arg = "false",
  missing_arg = "missing",
  error_call = current_env()
)

Arguments

condition

A logical vector.

true, false

Vectors to use for TRUE and FALSE values of condition.

Both true and false will be recycled to the size of condition.

true, false, and missing (if used) will be cast to their common type.

...

These dots are for future extensions and must be empty.

missing

If not NULL, will be used as the value for NA values of condition. Follows the same size and type rules as true and false.

ptype

An optional prototype declaring the desired output type. If supplied, this overrides the common type of true, false, and missing.

condition_arg, true_arg, false_arg, missing_arg

Argument names used in error messages.

error_call

The execution environment of a currently running function, e.g. caller_env(). The function will be mentioned in error messages as the source of the error. See the call argument of abort() for more information.

Value

A vector with the same size as condition and the same type as the common type of true, false, and missing.

Where condition is TRUE, the matching values from true, where it is FALSE, the matching values from false, and where it is NA, the matching values from missing, if provided, otherwise a missing value will be used.

Examples

x <- c(-5:5, NA)
vec_if_else(x < 0, NA, x)
#>  [1] NA NA NA NA NA  0  1  2  3  4  5 NA

# Explicitly handle `NA` values in the `condition` with `missing`
vec_if_else(x < 0, "negative", "positive", missing = "missing")
#>  [1] "negative" "negative" "negative" "negative" "negative" "positive"
#>  [7] "positive" "positive" "positive" "positive" "positive" "missing" 

# Unlike `ifelse()`, `vec_if_else()` preserves types
x <- factor(sample(letters[1:5], 10, replace = TRUE))
ifelse(x %in% c("a", "b", "c"), x, NA)
#>  [1]  2 NA  2 NA NA  3 NA  1  1 NA
vec_if_else(x %in% c("a", "b", "c"), x, NA)
#>  [1] b    <NA> b    <NA> <NA> c    <NA> a    a    <NA>
#> Levels: a b c d e

# `vec_if_else()` also works with data frames
condition <- c(TRUE, FALSE, NA, TRUE)
true <- data_frame(x = 1:4, y = 5:8)
false <- data_frame(x = 9:12, y = 13:16)
vec_if_else(condition, true, false)
#> # A tibble: 4 × 2
#>       x     y
#>   <int> <int>
#> 1     1     5
#> 2    10    14
#> 3    NA    NA
#> 4     4     8