Question

I have a table that looks like this

uid gid score
1   a   5
1   a   8
1   a   9
1   b   2
1   b   7
2   a   5
2   a   9
.
.
.

But with many more entries for each user and group.

I want to get a table that has a row for each uid/gid pairing that is the mean of their bottom 5 scores.

This was trivial in Excel using pivot tables, but I need to do some analysis that R is much better for.

So I want my result to look like

uid gid top5avg
1   a   4.3
1   b   5.7
2   a   3.5
2   b   6.8
.
.
.

with one row for each uid gid pair and then the average of the top five scores for that uid/gid pair.

Answer 1

If your data was called dat this would work:

aggregate(score~uid+gid, data=dat, function(x) mean(sort(x)[1:5]))

EDIT:
If you meant the opposite (bottom 5) than what I had, as indicated by Joran (I was confused too), then use rev as in:

aggregate(score~uid+gid, data=dat, function(x) mean(rev(sort(x))[1:5]))

Or use the tail suggestion Joran made.