Close, but not quite what I need.
That very nicely gives me sums by group.
I need to take each value of X and divide it by the sum of the group it belongs
to.
With your example, I have 100,000 X and only 10,000 group. The "by" command
gives me 10,000 sums. I still have to loop over all 100,000 entries, and find
the group sum they belong to.
On Nov 29, 2012, at 11:05 AM, MikoÅaj Hnatiuk <mikolaj.hnat...@gmail.com>
wrote:
> Yes, type in:
> ?by
>
> for example:
> data <- data.frame(fac=factor(c("A","A","B","B")), vec=c(1:4) )
> by(data$vec,data$fac, FUN=sum)
>
> Best,
> MikoÅaj Hnatiuk
>
> 2012/11/29 Noah Silverman <noahsilver...@ucla.edu>
> Hi,
>
> I have a very large data set (aprox. 100,000 rows.)
>
> The data comes from around 10,000 "groups" with about 10 entered per group.
>
> The values are in one column, the group ID is an integer in the second column.
>
> I want to normalize the values by group:
>
> for(g in unique(groups){
> x[group==g] / sum(x[group==g])
> }
>
> This works find in a loop, but is slow. Is there a faster way to do this?
>
> Thanks!
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