Philipp Pagel wrote:
Dear R experts,
Suppose I have a data frame of three variables:
foo <- data.frame(row=1:5, col=1:3, val=rnorm(15))
foo
row col val
1 1 1 -1.00631642
2 2 2 0.77715344
3 3 3 0.17358793
4 4 1 -1.67226988
5 5 2 1.08218836
6 1 3 1.32961329
7 2 1 -0.51186267
8 3 2 -1.20990127
9 4 3 -0.57786899
10 5 1 0.67102887
11 1 2 0.05646411
12 2 3 0.01146612
13 3 1 -3.12094409
14 4 2 -1.01932191
15 5 3 0.76736702
I want to turn this into a matrix of val according to row and col. Let's also
assume that some combinations of row and col are missing - i.e. there will be
NAs in the resulting Matrix. My current approach is simple and works but is
slow for large datasets:
mat <- matrix(nrow=max(foo$row), ncol=max(foo$col))
for (line in 1:dim(foo)[1]) {
mat[foo[line, 'row'], foo[line, 'col']] <- foo[line, 'val']
}
mat
[,1] [,2] [,3]
[1,] -1.0063164 0.05646411 1.32961329
[2,] -0.5118627 0.77715344 0.01146612
[3,] -3.1209441 -1.20990127 0.17358793
[4,] -1.6722699 -1.01932191 -0.57786899
[5,] 0.6710289 1.08218836 0.76736702
Can anyone think of a more efficient way?
Here's one.
> d <- read.table("clipboard")
> with(d,tapply(val,list(row,col),"[[",1))
1 2 3
1 -1.0063164 0.05646411 1.32961329
2 -0.5118627 0.77715344 0.01146612
3 -3.1209441 -1.20990127 0.17358793
4 -1.6722699 -1.01932191 -0.57786899
5 0.6710289 1.08218836 0.76736702
or use mean, min, max etc instead of "[[", 1.
Also, there's matrix indexing
> M <- matrix(,5,3)
> attach(d)
> M[cbind(row,col)]<-val
> M
[,1] [,2] [,3]
[1,] -1.0063164 0.05646411 1.32961329
[2,] -0.5118627 0.77715344 0.01146612
[3,] -3.1209441 -1.20990127 0.17358793
[4,] -1.6722699 -1.01932191 -0.57786899
[5,] 0.6710289 1.08218836 0.76736702
--
O__ ---- Peter Dalgaard Øster Farimagsgade 5, Entr.B
c/ /'_ --- Dept. of Biostatistics PO Box 2099, 1014 Cph. K
(*) \(*) -- University of Copenhagen Denmark Ph: (+45) 35327918
~~~~~~~~~~ - ([EMAIL PROTECTED]) FAX: (+45) 35327907
______________________________________________
R-help@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
