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(), ...)
data | A data.frame |
---|---|
replace | A named list given the NA to replace values for each column |
... | additional arguments for methods. Currently unused |
Dataframe with values replaced by NA.
replace_with_na()
replace_with_na_all()
replace_with_na_at()
replace_with_na_if()
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#> # 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#> # 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