Efficient use of a list for filtering in `dplyr`

Question

My filter_list has a large number of elements. The filtering below works but how would one make the dplyr::filter more concise?

I couldn't make all_of work.

filter_list <- list(
  hair_color = c("blond", "brown"),
  skin_color = "light"
)

dplyr::starwars |> 
  dplyr::filter(
    hair_color %in% filter_list[["hair_color"]],
    skin_color %in% filter_list[["skin_color"]]
  )

Answer 1

We could use reduce2 to iteratively apply filter statements, e.g.:

library(purrr); library(dplyr)

out <- starwars |> 
  reduce2(
    .x = filter_list, .y = names(filter_list), .init = _,
    .f = \(df, x, y) filter(df, .data[[y]] %in% x)
  )

# A tibble: 8 × 14
  name     height  mass hair_color skin_color eye_color birth_year sex   gender homeworld species films vehicles
  <chr>     <int> <dbl> <chr>      <chr>      <chr>          <dbl> <chr> <chr>  <chr>     <chr>   <lis> <list>  
1 Leia Or…    150    49 brown      light      brown             19 fema… femin… Alderaan  Human   <chr> <chr>   
2 Beru Wh…    165    75 brown      light      blue              47 fema… femin… Tatooine  Human   <chr> <chr>   
3 Padmé A…    185    45 brown      light      brown             46 fema… femin… Naboo     Human   <chr> <chr>   
4 Cordé       157    NA brown      light      brown             NA NA    NA     Naboo     NA      <chr> <chr>   
5 Dormé       165    NA brown      light      brown             NA fema… femin… Naboo     Human   <chr> <chr>   
6 Raymus …    188    79 brown      light      brown             NA male  mascu… Alderaan  Human   <chr> <chr>   
7 Rey          NA    NA brown      light      hazel             NA fema… femin… NA        Human   <chr> <chr>   
8 Poe Dam…     NA    NA brown      light      brown             NA male  mascu… NA        Human   <chr> <chr>

Check if correct:

all.equal(
  out, 
  dplyr::starwars |> 
    dplyr::filter(
      hair_color %in% filter_list[["hair_color"]],
      skin_color %in% filter_list[["skin_color"]]
    )
)