In article <800acfc0-2c3c-41f1-af18-3b52f7e43...@jhsph.edu>,
bcarv...@jhsph.edu says...
> aves = aggregate(df1$score, by=list(col1=df1$col1, col2=df1$col2), mean)
> results = merge(df1, aves)
Or, with the 'plyr' package, which has a very nice syntax:
library(plyr)
ddply(df1, .(col1, col2), transform, Average=mean(score))
It may be a bit slow for very large datasets, though.
Here's an alternative, which will be as fast as the aggregate solution.
within(df1, { Average=ave(score, col1, col2, FUN=mean) } )
Which one you use is a matter of taste.
And of course, the 'within' function is not the important part here;
'ave' is. For example, if you have attached your data frame, you just
have to type
Average=ave(score, col1, col2, FUN=mean)
--
Karl Ove Hufthammer
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