For Loops And R

John Mount has a couple of tips around using for loops in R.  First up, pre-allocate lists to make certain types of iterative processing faster:

Another R tip. Use vector(mode = "list") to pre-allocate lists.

result <- vector(mode = "list", 3)
print(result)
#> [[1]]
#> NULL
#> 
#> [[2]]
#> NULL
#> 
#> [[3]]
#> NULL

The above used to be critical for writing performant R code (R seems to have greatly improved incremental list growth over the years). It remains a convenient thing to know.

Also, use loop indices when iterating through for loops:

Below is an R annoyance that occurs again and again: vectors lose class attributes when you iterate over them in a for()-loop.

d <- c(Sys.time(), Sys.time())
print(d)
#> [1] "2018-02-18 10:16:16 PST" "2018-02-18 10:16:16 PST"

for(di in d) {
  print(di)
}
#> [1] 1518977777
#> [1] 1518977777

Notice we printed numbers, not dates/times.

Very useful information.