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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.

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