The question was about matrices, not data frames or data tables. While faster
than Reduce, the conversions still make it over twice as slow as Rui's answer.
On June 10, 2018 12:18:39 PM HST, Benjamin Christoffersen
wrote:
>You may be able to speed it up further by using `data.table`'s
>`rbindli
You may be able to speed it up further by using `data.table`'s
`rbindlist` or a similar function as shown here
https://stackoverflow.com/a/49772719/5861244.
2018-06-10 21:20 GMT+02:00 Christofer Bogaso :
> Using do.call() reduces my calculation time significantly.
>
> On Sun, Jun 10, 2018 at 10:45
Using do.call() reduces my calculation time significantly.
On Sun, Jun 10, 2018 at 10:45 PM ruipbarradas wrote:
> Hello,
>
> Instead of Reduce try do.call.
>
> do.call ('rbind', list)
>
> But with such a long list it will still take time.
>
> Hope this helps,
>
> Rui Barradas
>
>
>
> Enviado a p
Hello,
Instead of Reduce try do.call.
do.call ('rbind', list)
But with such a long list it will still take time.
Hope this helps,
Rui Barradas
Enviado a partir do meu smartphone Samsung Galaxy. Mensagem original
De: Christofer Bogaso Data: 10/06/2018
16:33 (GMT+00:00) Para:
Sorry typos
Try this. Suppose your list of matrices is in the list locL.
nc <- 3
locL2 <- list()
for ( i in 1:length(locL) )
locL2[[i]] <- as.numeric( t( locL[[i]] ) )
bigMat <- matrix(unlist(locL2), ncol=nc, byrow=TRUE)
HTH,
Eric
On Sun, Jun 10, 2018 at 7:10 PM, Eric Berger wrote:
> Try
Try this. Suppose your list of matrices is in the list locL.
nc <- 3
locL2 <- list()
for ( i in 1:length(locL )
locL2[[i]] <- as.numeric(t(locL[[i]]))
bigMat <- matrix(unlist(locL3), ncol=nc, byrow=TRUE)
HTH,
Eric
On Sun, Jun 10, 2018 at 6:33 PM, Christofer Bogaso <
bogaso.christo...@gmail.
Hi,
I have a list of length 10,000, and each element of that list is a matrix
with 3 columns and 2,000 rows.
Now when I tried to make a Matrix object with that list using
Reduce('rbind', list), my code is taking a considerable amount of time.
Is there any way to implement same above task in more
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