Joining aggregated values back to the original data frame [duplicate]

Answer 1

I think ave() is more useful here than the plyr call you show (I'm not familiar enough with plyr to know if you can do what you want with plyr directly or not, I would be surprised if you can't!) or the other base R alternatives (aggregate(), tapply()).:

> with(df, ave(values, group1, FUN = mean))
 [1] -0.121033381  0.004803931  0.758597929 -0.121033381  0.004803931
 [6]  0.758597929 -0.121033381  0.004803931  0.758597929 -0.121033381
[11]  0.004803931  0.758597929

You can use within() or transform() to embed this result directly into df:

> df2 <- within(df, meanValue <- ave(values, group1, FUN = mean))
> head(df2)
  group1 group2     values    meanValue
1      1      A  0.4874291 -0.121033381
2      2      B  0.7383247  0.004803931
3      3      B  0.5757814  0.758597929
4      1      C -0.3053884 -0.121033381
5      2      A  1.5117812  0.004803931
6      3      C  0.3898432  0.758597929
> df3 <- transform(df, meanValue = ave(values, group1, FUN = mean))
> all.equal(df2,df3)
[1] TRUE

And if the ordering is important:

> head(df2[order(df2$group1, df2$group2), ])
   group1 group2      values    meanValue
1       1      A  0.48742905 -0.121033381
10      1      A -0.04493361 -0.121033381
4       1      C -0.30538839 -0.121033381
7       1      C -0.62124058 -0.121033381
5       2      A  1.51178117  0.004803931
11      2      A -0.01619026  0.004803931