Specify variables and their values that you want to convert to missing values.
This is a complement to tidyr::replace_na.
Usage
replace_with_na(data, replace = list(), ...)Arguments
- data
A data.frame
- replace
A named list given the NA to replace values for each column
- ...
additional arguments for methods. Currently unused
See also
replace_with_na() replace_with_na_all() replace_with_na_at() replace_with_na_if()
Examples
dat_ms <- tibble::tribble(~x, ~y, ~z,
1, "A", -100,
3, "N/A", -99,
NA, NA, -98,
-99, "E", -101,
-98, "F", -1)
replace_with_na(dat_ms,
replace = list(x = -99))
#> # A tibble: 5 × 3
#> x y z
#> <dbl> <chr> <dbl>
#> 1 1 A -100
#> 2 3 N/A -99
#> 3 NA NA -98
#> 4 NA E -101
#> 5 -98 F -1
replace_with_na(dat_ms,
replace = list(x = c(-99, -98)))
#> # A tibble: 5 × 3
#> x y z
#> <dbl> <chr> <dbl>
#> 1 1 A -100
#> 2 3 N/A -99
#> 3 NA NA -98
#> 4 NA E -101
#> 5 NA F -1
replace_with_na(dat_ms,
replace = list(x = c(-99, -98),
y = c("N/A"),
z = c(-101)))
#> # A tibble: 5 × 3
#> x y z
#> <dbl> <chr> <dbl>
#> 1 1 A -100
#> 2 3 NA -99
#> 3 NA NA -98
#> 4 NA E NA
#> 5 NA F -1