Try this:
data$score <- ave(data$score, data$group, FUN = prop.table)
On Sun, Aug 30, 2009 at 6:08 PM, Noah Silverman<n...@smartmediacorp.com> wrote:
> Hi,
>
> I need a bit of guidance with the sapply function. I've read the help page,
> but am still a bit unsure how to use it.
>
> I have a large data frame with about 100 columns and 30,000 rows. One of
> the columns is "group" of which there are about 2,000 distinct "groups".
>
> I want to normalize (sum to 1) one of my variables per-group.
>
> Normally, I would just write a huge "for each" loop, but have read that is
> hugely inefficient with R.
>
> The old way would be (just an example, syntax might not be perfect):
>
> for (group in data$group){
> for (score in data[data$group == group]){
> new_score <- score / sum(data$score[data$group==group])
> }
> }
>
> How would I simplify this with sapply?
>
> Thanks!
>
> --
> Noah
>
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