This is a translation of the SQL command NULLIF. It is useful if you want to convert an annoying value to NA.

na_if(x, y)

Arguments

x

Vector to modify

y

Value to replace with NA

Value

A modified version of x that replaces any values that are equal to y with NA.

See also

coalesce() to replace missing values with a specified value.

tidyr::replace_na() to replace NA with a value.

recode() to more generally replace values.

Examples

na_if(1:5, 5:1)
#> [1]  1  2 NA  4  5

x <- c(1, -1, 0, 10)
100 / x
#> [1]  100 -100  Inf   10
100 / na_if(x, 0)
#> [1]  100 -100   NA   10

y <- c("abc", "def", "", "ghi")
na_if(y, "")
#> [1] "abc" "def" NA    "ghi"

# na_if() is particularly useful inside mutate(),
# and is meant for use with vectors rather than entire data frames
starwars %>%
  select(name, eye_color) %>%
  mutate(eye_color = na_if(eye_color, "unknown"))
#> # A tibble: 87 x 2
#>    name               eye_color
#>    <chr>              <chr>    
#>  1 Luke Skywalker     blue     
#>  2 C-3PO              yellow   
#>  3 R2-D2              red      
#>  4 Darth Vader        yellow   
#>  5 Leia Organa        brown    
#>  6 Owen Lars          blue     
#>  7 Beru Whitesun lars blue     
#>  8 R5-D4              red      
#>  9 Biggs Darklighter  brown    
#> 10 Obi-Wan Kenobi     blue-gray
#> # … with 77 more rows

# na_if() can also be used with mutate() and across()
# to mutate multiple columns
starwars %>%
   mutate(across(where(is.character), ~na_if(., "unknown")))
#> # A tibble: 87 x 14
#>    name    height  mass hair_color  skin_color eye_color birth_year sex   gender
#>    <chr>    <int> <dbl> <chr>       <chr>      <chr>          <dbl> <chr> <chr> 
#>  1 Luke S…    172    77 blond       fair       blue            19   male  mascu…
#>  2 C-3PO      167    75 NA          gold       yellow         112   none  mascu…
#>  3 R2-D2       96    32 NA          white, bl… red             33   none  mascu…
#>  4 Darth …    202   136 none        white      yellow          41.9 male  mascu…
#>  5 Leia O…    150    49 brown       light      brown           19   fema… femin…
#>  6 Owen L…    178   120 brown, grey light      blue            52   male  mascu…
#>  7 Beru W…    165    75 brown       light      blue            47   fema… femin…
#>  8 R5-D4       97    32 NA          white, red red             NA   none  mascu…
#>  9 Biggs …    183    84 black       light      brown           24   male  mascu…
#> 10 Obi-Wa…    182    77 auburn, wh… fair       blue-gray       57   male  mascu…
#> # … with 77 more rows, and 5 more variables: homeworld <chr>, species <chr>,
#> #   films <list>, vehicles <list>, starships <list>