[R] Dataframes of marginal summaries

[Andrew Robinson]

Hi dear R-community,

I wonder if anyone has written code that will post-process the results of a 
tapply to create a dataframe that includes the outcome, the factor by which 
the function has been applied, and, if the factor is also an interaction, 
then also the levels of contributing factors?

>From this

outcome <- tapply(data, A.B, function)

I'd like to arrange something like this:

    A     B     A.B     outcome
1
2
3
4

I have the following example solution, which seems clumsy, relying on 
dissecting the labels of the tapply result.  I don't think I've harvested 
this from anyone else, but I apologize if I have.

=======================================================================

x <- factor(c(rep("B",4), rep("A",4)))
y <- factor(c(1,2,1,2,1,2,1,2))
z <- rnorm(8)
data <- as.data.frame(cbind(x, y, z))
data$x.y <- interaction(x,y)

my.test <- tapply(data$z, data$x.y, mean)

test <- as.data.frame(as.numeric(my.test))
names(test) <- "Mean"
nList <- function(list, n) list[[n]]
test$x <- factor(as.character(lapply(strsplit(row.names(my.test),
                                               "\\."), nList, n=1)))
test$y <- factor(as.character(lapply(strsplit(row.names(my.test),
                                               "\\."), nList, n=2)))
test$x.y <- factor(row.names(my.test))

test[,c(2:4,1)]

=======================================================================

Any suggestions to simplify would be much appreciated.

Andrew
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