I have a dataframe (df) that looks similar to this:

For persons whose last observation is a 0, I would like to remove the trailing 0s plus the last 1, so that the final df looks like this:

The last three 0s and last 1 were removed for A and C, but B was left alone because its last observation was a 1. Is there a way to do this, or does it have to be done by hand?

CodePudding user response：

May be this helps

library(dplyr)
df %>% 
   group_by(person) %>% 
   mutate(new = cumsum(outcome)) %>%
   filter(if(last(outcome) == 0) new <max(new) else TRUE) %>%
   ungroup %>%
   select(-new)

-output

# A tibble: 5 × 2
  person outcome
  <chr>    <int>
1 a            1
2 b            1
3 b            0
4 b            1
5 c            1

data

df <- structure(list(person = c("a", "a", "a", "a", "a", "b", "b", 
"b", "c", "c", "c", "c", "c"), outcome = c(1L, 1L, 0L, 0L, 0L, 
1L, 0L, 1L, 1L, 1L, 0L, 0L, 0L)), class = "data.frame", row.names = c(NA, 
-13L))