Vectorised if else that if true returns first possibility otherwise returns
second possibility (even if the condition is a missing value).
When searching character vectors an alternative solution is to use
str_detect2().
if_else2(condition, true, false)A logical vector
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.
Where condition is TRUE, the matching value from true, where it's FALSE or NA, the matching value from false.
ifelse() and dplyr::if_else().
# consider the following data frame
data <- tibble::tibble(
x = c(TRUE, FALSE, NA),
y = c("x is false", NA, "hello"))
# with a single vector if_else2() behaves the same as the default call to if_else().
dplyr::mutate(data,
y1 = dplyr::if_else(y != "x is false", "x is true", y),
y2 = if_else2(y != "x is false", "x is true", y))
#> # A tibble: 3 × 4
#> x y y1 y2
#> <lgl> <chr> <chr> <chr>
#> 1 TRUE x is false x is false x is false
#> 2 FALSE NA NA NA
#> 3 NA hello x is true x is true
# however in the case of a second vector the use of
# if_else2() does not introduce missing values
dplyr::mutate(data,
x1 = dplyr::if_else(stringr::str_detect(y, "x is false"), FALSE, x),
x2 = if_else2(stringr::str_detect(y, "x is false"), FALSE, x))
#> # A tibble: 3 × 4
#> x y x1 x2
#> <lgl> <chr> <lgl> <lgl>
#> 1 TRUE x is false FALSE FALSE
#> 2 FALSE NA NA FALSE
#> 3 NA hello NA NA
# in the case of regular expression matching an alternative is to use
# str_detect2()
dplyr::mutate(data,
x3 = dplyr::if_else(str_detect2(y, "x is false"), FALSE, x))
#> # A tibble: 3 × 3
#> x y x3
#> <lgl> <chr> <lgl>
#> 1 TRUE x is false FALSE
#> 2 FALSE NA FALSE
#> 3 NA hello NA