I believe this will do what you want:
tmp1 <- split(xx, xx$a)
do.call(rbind, tmp1[ sample(length(unique(xx$a))) ])
The idea is to split the dataframe, and then reassemble in a random order.
Whether or not it will be faster for a large dataframe, I don't know.
There's probably also an indexing solution, perhaps using rle(), but
I thought of this first...
-Don
At 6:22 PM +0300 8/20/09, Tal Galili wrote:
Hello dear R-help group.
My task looks simple, but I can't seem to find a "smart" (e.g: non loop)
solution to it.
Task: I wish to randomize a data.frame by one column, while keeping the
inner-order in the second column as is.
So for example, let's say I have the following data.frame:
xx <-data.frame(a= c(1,2,2,3,3,3,4,4,4,4) ,
b = c(1,1,2,1,2,3,1,2,3,4) )
I would like to shuffle it by column "a", while keeping the order in column
"b".
Here is my "not-smart" way of doing it:
# R example
xx <-data.frame(a= c(1,2,2,3,3,3,4,4,4,4) ,
b = c(1,1,2,1,2,3,1,2,3,4) )
randomize.by.column.a <- function(xx)
{
new.a.order <- sample(unique(xx$a))
new.xx <- NULL
for(i in new.a.order)
{
xx.subset <- xx[ xx$a %in% i ,]
new.xx <- rbind(new.xx , xx.subset)
}
return(new.xx)
}
randomize.by.column.a(xx)
# END of - R example
I would love for a better, faster, way of doing it.
Thanks,
Tal
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--------------------------------------
Don MacQueen
Environmental Protection Department
Lawrence Livermore National Laboratory
Livermore, CA, USA
925-423-1062
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