Hi r-help-boun...@r-project.org napsal dne 17.02.2010 09:36:45:
> Hi, > > > > I'm having a dataframe 'Subset1' with a number of factor variables and 160 > numerical variables > > Now I want to make sums for all rows that have the same values for the > different factor variables, except for the factor variables: VAR1,VAR2,VAR3 > who may have the same values. > > With the formula given below this works great, but in a situation with 15000 > rows and 13 factor variables the calculation takes more than 2 minutes. > > So my question is: Does anyone knows if there exists a faster alternative? I believe plyr package has optimised code for such aggregations. But I do not use it myself much often so I am not sure. You probably could speed things by avoiding ncol(Subset1) in aggregate. Either use numbers or do selection <- Subset1[,(ncol(Subset1)-159):ncol(Subset1)] and avoiding unnecessary coercion to data.frame. Aggregate perform it for you :-) Subset1.AGG <- aggregate(selection, list(VAR1 = Subset1$VAR1,VAR2=Subset1$VAR2,VAR3 = Subset1$VAR3), FUN=sum) Regards Petr > > > > Subset1.AGG <- > as.data.frame(aggregate(Subset1[,(ncol(Subset1)-159):ncol(Subset1)], > list(VAR1 = Subset1$VAR1,VAR2=Subset1$VAR2,VAR3 = Subset1$VAR3), FUN=sum) ) > > > > Thank you very much 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. ______________________________________________ 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.
