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Suppose I have create a list in R and append to it as follows:
x = list(10) x[[2]] = 20 Is this equivalent to
x = list(10) x = list(10, 20) ? I'm not so experienced with the particular details of how R handles lists in memory, but my limited understanding is that it tends to be copy-happy; what would be ideal for me would be that the first option doesn't involve essentially creating another list in memory, but just results in setting aside a new place in memory for the appended value. Essentially, if I have a big list, I don't want R to make another copy of it if I just want to append something to it.
If the behaviour I want is not what is given here, is there any other way I can get the desired effect?
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💡 Tips: When you use . append() the original list is modified. The method does not create a copy of the list – it mutates the original list in memory.
To append an element in the R List, use the append() function. You can use the concatenate approach to add components to a list. While concatenate does a great job of adding elements to the R list, the append() function operates faster.
To add an item to a list in R programming, call append() function and pass the list and item as arguments in the function call.
I'm fairly confident the answer is "no". I used the following code to double check:
Rprof(tmp <- tempfile(), memory.profiling = TRUE) x <- list() for (i in 1:100) x[[i]] <- runif(10000) Rprof() summaryRprof(tmp, memory = "stats") unlink(tmp) The output:
# index: runif # vsize.small max.vsize.small vsize.large max.vsize.large # 76411 381781 424523 1504387 # nodes max.nodes duplications tot.duplications # 2725878 13583136 0 0 # samples # 5 The relevant part being duplications = 0.
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