Specify variables and their values that you want to convert to missing values. This is a complement to tidyr::replace_na.

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

Value

Dataframe with values replaced by NA.

See also

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 x 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 = -98))
#> # A tibble: 5 x 3 #> x y z #> <dbl> <chr> <dbl> #> 1 1 A -100 #> 2 3 N/A -99 #> 3 NA <NA> -98 #> 4 -99 E -101 #> 5 NA F -1
replace_with_na(dat_ms, replace = list(x = c(-99, -98)))
#> # A tibble: 5 x 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")))
#> # A tibble: 5 x 3 #> x y z #> <dbl> <chr> <dbl> #> 1 1 A -100 #> 2 3 <NA> -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 x 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