sounds like plyr although I have never used it... If you want help with code you need to provide reproducible examples.
On Wed, Nov 5, 2008 at 5:11 AM, Bert Jacobs <[EMAIL PROTECTED]> wrote: > > > > > Hi, > > I've written the following line of code to make a summary of some data: > > > > Final.Data.Short <- as.data.frame(aggregate(Merge.FinalSubset[,8:167], > list(Location = Merge.FinalSubset $Location,Measure = Merge.FinalSubset > $Measure,Site = Merge.FinalSubset $Site, Label= Merge.FinalSubset $Label), > FUN=sum)) > > > > Where "Merge.FinalSubset" is a dataframe of 2640 rows and 167 columns > > The result "Final.Data.Short" is a dataframe of 890 rows and 164 columns > > > > This operation takes at the moment more than a minute. Now I was wondering > if their exist ways to reduce this operation time by using other code or by > splitting the original dataframe in smaller bits, make several different > aggregations, and recompose the dataframe again? > > > > Thx for helping me out > > Bert > > > > > > > > > [[alternative HTML version deleted]] > > ______________________________________________ > R-help@r-project.org mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. > -- Stephen Sefick Research Scientist Southeastern Natural Sciences Academy Let's not spend our time and resources thinking about things that are so little or so large that all they really do for us is puff us up and make us feel like gods. We are mammals, and have not exhausted the annoying little problems of being mammals. -K. Mullis ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.