Filter different variables based on different conditions

Question

I have a deep nested data and a function that runs on it through purrr. Here is a mock data & analysis that resembles my case:

df <- tibble::tribble(
     ~A, ~B, ~C,
    "e", 2L, 6L,
    "e", 5L, 8L,
    "e", 5L, 3L,
    "f", 3L, 8L,
    "f", 4L, 1L,
    "f", 5L, 6L,
    "g", 3L, 9L,
    "g", 4L, 2L,
    "g", 5L, 7L,
    "h", 5L, 4L
    )

I need to filter different variables based on different conditions. I need to do something like this:

df1 <- df %>% group_by(A) %>% 
              nest() %>% 
              case_when(A == "e" ~filter(B<4),
              A == "f" ~filter(C<=6),
              A == "g" ~filter(B<5, C<7))

My desired output should be:

desired_output <- tibble::tribble(
                     ~A, ~B, ~C,
                    "e", 2L, 6L,
                    "f", 4L, 1L,
                    "f", 5L, 6L,
                    "g", 4L, 2L
                    )

Answer 1

We can do the following to filter for different conditions.

library(tidyverse)

df %>%
  filter((A %in% "e" & B < 4)  | 
           (A %in% "f" & C <= 6) |
           (A %in% "g" & B < 5 & C < 7))  
# # A tibble: 4 x 3
#   A         B     C
#   <chr> <int> <int>
# 1 e         2     6
# 2 f         4     1
# 3 f         5     6
# 4 g         4     2