Replaces missing values with the given value, or optionally conditions the
replacement on the expressions given in ..., which are applied to the
inputs in the same way as filter.
if_na(.x, ..., then = default_value(.x), otherwise = NULL)
| .x | Input vector of values |
|---|---|
| ... | Additional expressions to condition replacement. NA values are only replaced when the additional expression matches. |
| then | Replacement value. Defaults to a value based on the input type
and favors |
| otherwise | If given, provides a secondary replacement value to be
subsituted for missing values when the conditions in |
library(dplyr)#> #>#> #> #>#> #> #>storms <- storms %>% filter(name == "Erika", year == 2003) %>% select(name, year, status, wind, contains("diameter")) # Default is replacement with appropriate default (0, FALSE, "", etc.) storms %>% mutate(hu_diameter = if_na(hu_diameter))#> # A tibble: 11 x 6 #> name year status wind ts_diameter hu_diameter #> <chr> <dbl> <chr> <int> <dbl> <dbl> #> 1 Erika 2003 tropical storm 35 NA 0 #> 2 Erika 2003 tropical storm 40 NA 0 #> 3 Erika 2003 tropical storm 40 NA 0 #> 4 Erika 2003 tropical storm 45 NA 0 #> 5 Erika 2003 tropical storm 50 NA 0 #> 6 Erika 2003 tropical storm 55 NA 0 #> 7 Erika 2003 tropical storm 60 NA 0 #> 8 Erika 2003 hurricane 65 NA 0 #> 9 Erika 2003 hurricane 65 NA 0 #> 10 Erika 2003 tropical storm 35 NA 0 #> 11 Erika 2003 tropical depression 25 NA 0# Replacement can be single value or vector of values storms %>% mutate( ts_diameter = if_na(ts_diameter, then = 30), hu_diameter = if_na(hu_diameter, then = rnorm(11, 100)) )#> # A tibble: 11 x 6 #> name year status wind ts_diameter hu_diameter #> <chr> <dbl> <chr> <int> <dbl> <dbl> #> 1 Erika 2003 tropical storm 35 30 98.6 #> 2 Erika 2003 tropical storm 40 30 100. #> 3 Erika 2003 tropical storm 40 30 97.6 #> 4 Erika 2003 tropical storm 45 30 100. #> 5 Erika 2003 tropical storm 50 30 101. #> 6 Erika 2003 tropical storm 55 30 101. #> 7 Erika 2003 tropical storm 60 30 98.2 #> 8 Erika 2003 hurricane 65 30 99.8 #> 9 Erika 2003 hurricane 65 30 99.8 #> 10 Erika 2003 tropical storm 35 30 99.7 #> 11 Erika 2003 tropical depression 25 30 99.4# Replacement can be predicated on other conditions in addition to missingness storms %>% mutate( hu_diameter = if_na(hu_diameter, then = 30, status == "hurricane") )#> # A tibble: 11 x 6 #> name year status wind ts_diameter hu_diameter #> <chr> <dbl> <chr> <int> <dbl> <dbl> #> 1 Erika 2003 tropical storm 35 NA NA #> 2 Erika 2003 tropical storm 40 NA NA #> 3 Erika 2003 tropical storm 40 NA NA #> 4 Erika 2003 tropical storm 45 NA NA #> 5 Erika 2003 tropical storm 50 NA NA #> 6 Erika 2003 tropical storm 55 NA NA #> 7 Erika 2003 tropical storm 60 NA NA #> 8 Erika 2003 hurricane 65 NA 30 #> 9 Erika 2003 hurricane 65 NA 30 #> 10 Erika 2003 tropical storm 35 NA NA #> 11 Erika 2003 tropical depression 25 NA NA# Can provide a secondary value for missing values when the conditions # are not met storms %>% mutate( ts_diameter = if_na(ts_diameter, then = wind, status == "tropical storm", otherwise = 0) )#> # A tibble: 11 x 6 #> name year status wind ts_diameter hu_diameter #> <chr> <dbl> <chr> <int> <dbl> <dbl> #> 1 Erika 2003 tropical storm 35 35 NA #> 2 Erika 2003 tropical storm 40 40 NA #> 3 Erika 2003 tropical storm 40 40 NA #> 4 Erika 2003 tropical storm 45 45 NA #> 5 Erika 2003 tropical storm 50 50 NA #> 6 Erika 2003 tropical storm 55 55 NA #> 7 Erika 2003 tropical storm 60 60 NA #> 8 Erika 2003 hurricane 65 0 NA #> 9 Erika 2003 hurricane 65 0 NA #> 10 Erika 2003 tropical storm 35 35 NA #> 11 Erika 2003 tropical depression 25 0 NA