[.data.table `which` argument could accept integer
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Assessment
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Newbie friendliness
- 35/100
Research direction
Start by tracing how the data.table which argument and missing(i) are handled, then review issue #3735 and its benchmark. Done means integer row indices such as which=2:3 subset rows efficiently while existing logical values and validation continue to work.
Written by the indexing model from the issue text.
Description
Currently which is guaranteed to be logical length 1.
if (!is.logical(which) || length(which)>1L) stop("which= must be a logical vector length 1. Either FALSE, TRUE or NA.")
If we will accept integer to be supplied to which argument (AND missing(i)) we could easily invert its functionality to subset data.table by integer row index. That would efficiently address #3735, see benchmark there (12.7s vs 3.5s).
Example usage
d = data.table(a=6:10, b=11:15)
d[which=2:3]
# faster equivalent to
d[2:3]
# a b
#1: 7 12
#2: 8 13
I am aware it is better to optimise i=2:3 but because of NSE processing it is very tricky to optimise that, and probably will never be as fast as non-NSE which argument.
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