In the Arguments section of help(aggregate), you will find : FUN: a scalar function to compute the summary statistics which can be applied to all data subsets.
a) So you can try the 'by' function : > by( df[ , 3], df$Department, function(x) c(mean(x), sum(x)) ) INDICES: Finance [1] 83925.67 251777.00 ------------------------------------------------------------ INDICES: HR [1] 63333.33 190000.00 ------------------------------------------------------------ INDICES: IT [1] 59928.67 179786.00 ------------------------------------------------------------ INDICES: Sales [1] 62481.67 187445.00 b) or use tapply more directly : > tmp <- tapply(df$Salary, df$Department, function(x) c( mean(x), sum(x) ) ) $Finance [1] 83925.67 251777.00 $HR [1] 63333.33 190000.00 $IT [1] 59928.67 179786.00 $Sales [1] 62481.67 187445.00 And using the 'sapply( tmp, c )' gives you a slightly more compact output as Finance HR IT Sales [1,] 83925.67 63333.33 59928.67 62481.67 [2,] 251777.00 190000.00 179786.00 187445.00 Regards, Adai On Mon, 2005-03-28 at 19:15 -0600, Sivakumaran Raman wrote: > I have the data similar to the following in a data frame: > LastName Department Salary > 1 Johnson IT 56000 > 2 James HR 54223 > 3 Howe Finance 80000 > 4 Jones Finance 82000 > 5 Norwood IT 67000 > 6 Benson Sales 76000 > 7 Smith Sales 65778 > 8 Baker HR 56778 > 9 Dempsey HR 78999 > 10 Nolan Sales 45667 > 11 Garth Finance 89777 > 12 Jameson IT 56786 > > I want to calculate both the mean salary broken down by Department and > also the > total amount paid out per department i.e. I want both sum(Salary) and > mean(Salary) for each Department. Right now, I am using aggregate.data.frame > twice, creating two data frames, and then combining them using data.frame. > However, this seems to be very memory and processor intensive and is > taking a > very long time on my data set. Is there a quicker way to do this? > > Thanks in advance, > Siv Raman > > ______________________________________________ > R-help@stat.math.ethz.ch mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html > ______________________________________________ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html