Use purrr::when to conditionally operate in a pipe (for example, to only filter if an argument is given a defined value) #rstatstips

conditional-filter.md

library(tidyverse)
#> Warning: package 'ggplot2' was built under R version 3.6.1

conditional_filter <- function(l_disp = NULL, u_disp = NULL, l_hp = NULL, u_hp = NULL) {
  mtcars %>%
    # tidy up mtcars
    rownames_to_column() %>%
    as_tibble() %>%
    select(rowname, disp, hp) %>%
    # only filter on arguments that are defined
    when(!is_empty(l_disp) ~ filter(., disp > l_disp), TRUE ~ .) %>%
    when(!is_empty(u_disp) ~ filter(., disp < u_disp), TRUE ~ .) %>%
    when(!is_empty(l_hp)   ~ filter(., hp > l_hp),     TRUE ~ .) %>%
    when(!is_empty(u_hp)   ~ filter(., hp < u_hp),     TRUE ~ .) %>%
    str()
}

conditional_filter()
#> Classes 'tbl_df', 'tbl' and 'data.frame':    32 obs. of  3 variables:
#>  $ rowname: chr  "Mazda RX4" "Mazda RX4 Wag" "Datsun 710" "Hornet 4 Drive" ...
#>  $ disp   : num  160 160 108 258 360 ...
#>  $ hp     : num  110 110 93 110 175 105 245 62 95 123 ...
  
conditional_filter(u_disp = 170)
#> Classes 'tbl_df', 'tbl' and 'data.frame':    16 obs. of  3 variables:
#>  $ rowname: chr  "Mazda RX4" "Mazda RX4 Wag" "Datsun 710" "Merc 240D" ...
#>  $ disp   : num  160 160 108 147 141 ...
#>  $ hp     : num  110 110 93 62 95 123 123 66 52 65 ...
  
conditional_filter(u_disp = 170, l_hp = 120)
#> Classes 'tbl_df', 'tbl' and 'data.frame':    3 obs. of  3 variables:
#>  $ rowname: chr  "Merc 280" "Merc 280C" "Ferrari Dino"
#>  $ disp   : num  168 168 145
#>  $ hp     : num  123 123 175

^{Created on 2019-09-20 by the reprex package (v0.3.0)}

Note: !is_empty() should probably be wrapped in parentheses—I think the formula operator ~ is lower precedence, but this is dangerous...