Hi Adam,
I don't think there is a faster alternative to plyr, without doing it in
nested for loops, with a lot of book-keeping of variables  (but if someone
here were to correct me, I'd be happy to know).

Two things to consider:
1) See if you can optimizing your function.  (there is a lot of material on
R code optimization online)
2) plyr has a parallel processing backend.
Here is a post I wrote about how to use it for windows users (as myself) :
http://www.r-statistics.com/2010/09/using-the-plyr-1-2-package-parallel-processing-backend-with-windows/

Good luck,
Tal



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On Wed, Aug 24, 2011 at 7:25 PM, AdamMarczak <adam.marczak@gmail.com> wrote:

> Hello everyone,
> I was asked to repost this again, sorry for any inconvenience.
>
> I'm looking replacement for ddply function from plyr package.
> Function allows to apply function by category stored in any column/columns.
>
> Regular loops or lapplys slow down greatly because my unique combination
> count exceeds 9000. Is there any available solution which allow me to apply
> function by category?
>
> currently my code looks like snippet below
>
> ddply(myData, c("country_name", "product_name"), myFunction)
>
> Please note that I'm looking for decently performing resolution.
>
> Thanks in advance!
>
> With regards,
> Adam.
>
> --
> View this message in context:
> http://r.789695.n4.nabble.com/ddply-from-plyr-package-any-alternatives-tp3765936p3765936.html
> Sent from the R help mailing list archive at Nabble.com.
>
> ______________________________________________
> R-help@r-project.org mailing list
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> PLEASE do read the posting guide
> http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
>

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