This is good news, although I have recently encountered what I consider excessive memory usage in the addition of key columns that don't affect the number of groups. For example, grouping by Year and Month, if I add MonthBegin, a POSIXct column from which the Year and Month columns were derived, I run out of memory.
hadley wickham <h.wick...@gmail.com> wrote: >On Thu, Apr 15, 2010 at 1:16 AM, Chuck <vijay.n...@gmail.com> wrote: >> Depending on the size of the dataframe and the operations you are >> trying to perform, aggregate or ddply may be better. In the function >> below, df has the same structure as your dataframe. > >Current version of plyr: > > agg ddply >X10 0.005 0.007 >X100 0.007 0.026 >X1000 0.086 0.248 >X10000 0.577 3.136 >X1e.05 4.493 44.147 > >Development version of plyr: > > agg ddply >X10 0.003 0.005 >X100 0.007 0.007 >X1000 0.042 0.044 >X10000 0.410 0.443 >X1e.05 4.479 4.237 > >So there are some big speed improvements in the works. > >Hadley > > >-- >Assistant Professor / Dobelman Family Junior Chair >Department of Statistics / Rice University >http://had.co.nz/ > >______________________________________________ >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.
