Set last N values of dataframe to NA in R - r

Question

I am trying to group my dataframe and set the last N values of a column in each group to NA. I can do it for N = 1 like so:
df %>% group_by(ID) %>% mutate(target = c(target[-n()], NA))
But am struggling to get it to work for any N
This is my current attempt:
df %>% group_by(ID) %>% mutate(target = c(target[1:(abs(n()-1))], NA))
But this seems to fail for groups of size 1
I also tried:
df %>% group_by(ID) %>% mutate(target = ifelse(n()==1, target, c(target[1:(abs(n()-1))], NA)))
But the else clause never takes effect.
Any advice would be appreciated, thanks.

Answer 1

We could use
library(dplyr)
df %>%
group_by(ID) %>%
mutate(target = replace(target, tail(row_number(), N), NA))

Answer 2

You can use case_when() for a vectorized solution in dplyr.
library(dplyr)
df %>%
group_by(ID) %>%
mutate(target = case_when(row_number() <= n() - N ~ target))
My thanks to #akrun for pointing out that case_when() defaults to an NA of the proper type, so case_when() automatically fills the last N with NAs.
Update
The solution by #akrun is more performant: when benchmarked at times = 50 repetitions apiece
library(microbenchmark)
big_df <- tibble(ID = rep(letters, 100000)) %>%
mutate(target = row_number()) %>%
group_by(ID)
microbenchmark(
times = 50,
Greg = {
big_df %>%
mutate(target = case_when(row_number() <= n() - N ~ target))
},
akrun = {
big_df %>%
mutate(target = replace(target, tail(row_number(), N), NA))
}
)
it is about 35% faster than mine at scale (2600000 rows):
Unit: milliseconds
expr min lq mean median uq max neval
Greg 82.6337 90.9669 128.93278 96.35760 213.3593 258.8570 50
akrun 52.4519 55.8314 63.40997 61.43945 64.1082 196.4069 50

Answer 3

Here is an alternative suggestion:
We could define the top N after using arrange in descending order (with -x), apply our ifelse statement and rearrange:
library(dplyr)
N = 2
df %>%
group_by(id) %>%
arrange(-x, .by_group = TRUE) %>%
mutate(x = ifelse(row_number()== 1:N, NA, x)) %>%
arrange(x, .by_group = TRUE)
df <- structure(list(x = c(2, 4, 6, 1, 2, 5, 6, 7, 3, 4, 5, 6), id = c(1L,
1L, 1L, 1L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L)), class = c("tbl_df",
"tbl", "data.frame"), row.names = c(NA, -12L))