Aggregating data (with more than one function)

Robin Tori Schroeder
International Institute for Sustainability 
P.O. Box 873211
Arizona State University
Tempe, Arizona 85287-3211
Phone: (480) 727-7290

dat <- read.table("clipboard", header=T, row=1)
do.call("rbind",by(dat$Salary, dat$Department, function(x) c(mean=mean(x),

From: Sivakumaran Raman

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