First, I regenerate random data with a seed for reproducibility:
set.seed(42)
ltrs <- sample(letters)
ltrs
# [1] "q" "e" "a" "j" "d" "r" "z" "o" "g" "v" "i" "y" "n" "t" "w" "b" "c" "p" "x"
# [20] "l" "m" "s" "u" "h" "f" "k"
Use -2:2
and then (cautionarily) remove those below 1 or above the length of the vector:
ind <- -2:2 + which(ltrs == "m")
ind <- ind[0 < ind & ind < length(ltrs)]
ltrs[ind]
# [1] "x" "l" "m" "s" "u"
If your target is more than one (not just "m"
), then we can use a different approach.
ind <- which(ltrs %in% c("m", "f"))
ind <- lapply(ind, function(z) { z <- z + -2:2; z[0 < z & z <= length(ltrs)]; })
ind
# [[1]]
# [1] 19 20 21 22 23
# [[2]]
# [1] 23 24 25 26
lapply(ind, function(z) ltrs[z])
# [[1]]
# [1] "x" "l" "m" "s" "u"
# [[2]]
# [1] "u" "h" "f" "k"
Or, if you don't care about keeping them grouped, we can try this:
ind <- which(ltrs %in% c("m", "f"))
ind <- unique(sort(outer(-2:2, ind, `+`)))
ind <- ind[0 < ind & ind <= length(ltrs)]
ltrs[ind]
# [1] "x" "l" "m" "s" "u" "h" "f" "k"