Below my clunky way to seek what I'm looking for, just to know if someone has a nicer, shorter method. Relatively concerned with performance. Ideally I'd try to avoid creating another object in the environment.

``` r
library(dplyr)

## making some dummy data
set.seed(42)
df <- esoph[sample(nrow(esoph), 50), ] %>%
  group_by(agegp, alcgp) %>%
  filter(n() > 1) %>%
  slice(1:2) %>%
  mutate(group_id = cur_group_id()) %>%
  arrange(agegp, alcgp) %>%
  head(14) %>%
  ungroup() %>%
  select(-agegp, -alcgp)

### to the actual problem

## only if group has both tobgp = "20-29" and "10-19", remove row "10-19".
df_im <- df %>%
  group_by(group_id) %>%
  filter(
    any(tobgp == "20-29") & any(tobgp == "10-19"),
    # remove then row "10-19"
    tobgp != "10-19"
  ) %>%
  ungroup()

## Now I'm removing all groups that I have found out to contain both values, just to add the data without the "10-19" rows back... 

df %>%
  anti_join(df_im, by = "group_id") %>%
  bind_rows(df_im)
#> # A tibble: 13 × 4
#>    tobgp    ncases ncontrols group_id
#>                  
#>  1 20-29         0         6        1
#>  2 30+           0         5        1
#>  3 0-9g/day      0        27        2
#>  4 30+           0         7        2
#>  5 0-9g/day      0        35        3
#>  6 20-29         1        13        3
#>  7 10-19         0         6        4
#>  8 0-9g/day      0        11        4
#>  9 20-29         2         2        5
#> 10 0-9g/day      2         1        5
#> 11 20-29         1         4        7
#> 12 30+           2         2        7
#> 13 20-29         5        10        6

## expected result: Group 6 has no "10-19"

^{Created on 2025-12-15 with reprex v2.1.1}