Randomly dividing a dataset in R

Steve Simon


Categories: Blog post Tags: R software

I'm working with someone who wants to do a simple cross-validation of a statistcal procedure. One simple way to do this is to randomly divide a data set into two piece. Assume that you have a matrix or data frame (x) that has n rows and you want to split the data set into a group that has proportion p of the rows and a group that has the remaining proportion (1-p). You want to do this randomly. Here is the code in R to do this.

m <- trunc(n*p) a <- sample(1:n,m) b <- x[a,] c <- x[-a,]

The sample function randomly selects m values from the vector 1:n. The use of the negative sign in the last line tells R that you wish to select all the rows EXCEPT the rows listed in a. The matrices (or data frames) b and c represent a random split of the data in x.