I tried searching but I couldn't quite find what I was looking for.
Here's a dummy data matrix (with row and column labels):
> y
0 1 2 3 4
21 3 4 8 5 5
22 3 6 8 6 NA
23 4 5 11 4 3
24 4 2 1 4 6
25 6 4 4 6 6
I can get cumulative row sums as follows:
> cy<-t(apply(y,1,cumsum))
> cy
0 1 2 3 4
21 3 7 15 20 25
22 3 9 17 23 NA
23 4 9 20 24 27
24 4 6 7 11 17
25 6 10 14 20 26
Which works, but this seems rather clumsy, especially the need for t().
Is there a better way? One that still retains row and/or column labels?
(that will also work for data frames, if possible - though of course one can
always as.data.frame() )
Row differences present a different problem. Here's one way to get back the
original data:
> cbind(cy[,1],cy[,-1]-cy[,-nrow(cy)])
1 2 3 4
21 3 4 8 5 5
22 3 6 8 6 NA
23 4 5 11 4 3
24 4 2 1 4 6
25 6 4 4 6 6
However, if I use that I lose the first column label. Is there a way to do
something like this without
losing that label? (again, if possible, that also works for data frames?)
thanks!
Glen_B.
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