For completeness: with dplyr v0.2 ddply with colwise will also do this:
> ddply(df, .(grp), colwise(mean))
grp a b c d
1 1 4.333333 4.00 1.000000 2.000000
2 2 2.000000 2.75 2.750000 2.750000
3 3 3.000000 4.00 4.333333 3.666667
but it is slower, at least in this case:
> microbenchmark(ddply(df, .(grp), colwise(mean)),
df %>% group_by(grp) %>% summarise_each(funs(mean)))
Unit: milliseconds
expr min lq mean
ddply(df, .(grp), colwise(mean)) 3.278002 3.331744 3.533835
df %>% group_by(grp) %>% summarise_each(funs(mean)) 1.001789 1.031528 1.109337
median uq max neval
3.353633 3.378089 7.592209 100
1.121954 1.133428 2.292216 100
