On Sat, Sep 4, 2010 at 2:37 PM, Paul Johnson <[email protected]> wrote:
> I've been doing some consulting with students who seem to come to R
> from SAS. They are usually pre-occupied with do loops and it is tough
> to persuade them to trust R lists rather than keeping 100s of named
> matrices floating around.
>
> Often it happens that there is a list with lots of matrices or data
> frames in it and we need to "stack those together". I thought it
This has nothing specifically to do with do.call but note that
R is faster at handling matrices than data frames. Below
we see that rbind-ing 4 data frames takes over 100 times as
long as rbind-ing matrices with the same data:
> mylist <- list(iris[-5], iris[-5], iris[-5], iris[-5])
> L <- lapply(mylist, as.matrix)
>
> library(rbenchmark)
> benchmark(
+ df = do.call("rbind", mylist),
+ mat = do.call("rbind", L),
+ order = "relative", replications = 250
+ )
test replications elapsed relative user.self sys.self user.child sys.child
2 mat 250 0.01 1 0.02 0.00 NA NA
1 df 250 1.06 106 1.03 0.01 NA NA
--
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