Remove non-last rows with certain condition per group - r

Question

I have the following dataframe called df (dput below):
group indicator value
1 A FALSE 2
2 A FALSE 1
3 A FALSE 2
4 A TRUE 4
5 B FALSE 5
6 B FALSE 1
7 B TRUE 3
I would like to remove the non-last rows with indicator == FALSE per group. This means that in df the rows: 1,2 and 5 should be removed because they are not the last rows with FALSE per group. Here is the desired output:
group indicator value
1 A FALSE 2
2 A TRUE 4
3 B FALSE 1
4 B TRUE 3
So I was wondering if anyone knows how to remove non-last rows with certain condition per group in R?
dput of df:
df <- structure(list(group = c("A", "A", "A", "A", "B", "B", "B"),
indicator = c(FALSE, FALSE, FALSE, TRUE, FALSE, FALSE, TRUE
), value = c(2, 1, 2, 4, 5, 1, 3)), class = "data.frame", row.names = c(NA,
-7L))

Answer 1

Filter using last(which()) to find the row number of the last FALSE row per group:
library(dplyr)
df %>%
group_by(group) %>%
filter(indicator | row_number() == last(which(!indicator))) %>%
ungroup()
# A tibble: 4 × 3
group indicator value
<chr> <lgl> <dbl>
1 A FALSE 2
2 A TRUE 4
3 B FALSE 1
4 B TRUE 3

Answer 2

You can do this with lead and check if the following indicator is TRUE.
library(tidyverse)
df <- structure(list(group = c("A", "A", "A", "A", "B", "B", "B"),
indicator = c(FALSE, FALSE, FALSE, TRUE, FALSE, FALSE, TRUE
), value = c(2, 1, 2, 4, 5, 1, 3)), class = "data.frame", row.names = c(NA,
-7L))
df |>
group_by(group) |>
mutate(slicer = if_else(lead(indicator) ==F, 1, 0)) |>
mutate(slicer = if_else(is.na(slicer), 0 , slicer)) |>
filter(slicer == 0) |>
select(-slicer)
#> # A tibble: 4 × 3
#> # Groups: group [2]
#> group indicator value
#> <chr> <lgl> <dbl>
#> 1 A FALSE 2
#> 2 A TRUE 4
#> 3 B FALSE 1
#> 4 B TRUE 3

Answer 3

Another approach:
library(dplyr)
df %>%
group_by(group) %>%
slice_max(cumsum(!indicator))
Note: While this approach covers the example shown and OP's clarification that T always comes last, it will not work in sequences such as T, F, F, T in which you'd like to keep both Ts and not just the one following F.
Output:
# A tibble: 4 x 3
# Groups: group [2]
group indicator value
<chr> <lgl> <dbl>
1 A FALSE 2
2 A TRUE 4
3 B FALSE 1
4 B TRUE 3

Answer 4

Some alternatives one could come up with:
"Dumb" solution
should_be_kept <- logical(nrow(df))
for(row in 1:nrow(df)) {
if(df[row,"Indicator"]) {
should_be_kept[row] <- TRUE
} else if(row == max(which(!df[, "Indicator"] & df$Group == df[row, "Group"]))) {
should_be_kept[row] <- TRUE
} else {
should_be_kept[row] = FALSE
}
}
df[should_be_kept, ]
Solution using a custom function to find the last FALSE indicators from each group
rows_to_keep <- logical(nrow(df)) #We create a TRUE/FALSE vector with one entry for each row of df
rows_to_keep[df$Indicator] <- TRUE #If Indicator is TRUE, we mark that row as "selectable"
get_last_false_in_group <- function(df, group) {
return(max(which(df$Group == group & !df$Indicator))) #Gets the last time the condition inside of which() is met
}
#The following chunk does a group-by-group search of the last false indicator. There's probably some apply magic that simplifies this but I'm too dumb to come up with it.
groups <- levels(factor(df$Group))
for(current_group in groups) {
rows_to_keep[get_last_false_in_group(df, current_group)] <- TRUE
}
#Now that our rows_to_keep vector is ready, we can filter the corresponding rows and get the intended result:
df[rows_to_keep,]
With the data.table package, it's possible to replace the calls to max(which(...)) with calls to just the last function