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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.

Pre-allocation is particularly useful when using for-loops.

for(i in seq_along(result)) {
result[[i]] <- i
}
print(result)
# [[1]]
# [1] 1
#
# [[2]]
# [1] 2
#
# [[3]]
# [1] 3


seq_along() is a handy function similar to what we discussed in R Tip: Use seq_len() to Avoid The Backwards List Trap. For “[[ ]]” please see R Tip: Use [[ ]] Wherever You Can.

Note: for-loops are not in fact a always a bad thing (even in R). for-loops can be easier to debug, are the right solution when you are carrying state from iteration to iteration, and with proper pre-allocation can be as performant as map/apply methods. Mostly one should not use them where better vectorized operations can be used. For example: in R it is usually wrong to try to iterate over rows in a data.frame, as usually thare are vectorized operators that can more efficiently write the same process in terms of column operations.