[Rd] Improve aggregate.default ...?

[Gavin Simpson]

Hi,

I find it a bit annoying that aggregate.default forces the returned
object to loose the 'name' of the variable aggregated, replacing it with
'x'.

A brief example:

> dat <- data.frame(A = runif(100), B = rnorm(100), 
+                   Group = gl(4, 25))
> with(dat, aggregate(A, by = list(Group = Group), FUN = mean))
  Group         x
1     1 0.6523228
2     2 0.4544317
3     3 0.4619624
4     4 0.4703156

This arises because aggregate default has:

function (x, ...) 
{
    if (is.ts(x)) 
        aggregate.ts(as.ts(x), ...)
    else aggregate.data.frame(as.data.frame(x), ...)
}

which recasts x as a data frame, but doesn't make any effort to supply a
name. Can we do a better job of supplying a useful name?

My first attempt is:

aggregate.default <- function(x, ...) {
    if (is.ts(x))
        aggregate.ts(as.ts(x), ...)
    else {
        nam <- deparse(substitute(x))
        x <- as.data.frame(x)
        names(x) <- nam
        aggregate.data.frame(x, ...)
    }
}

Which works for the brief example above:

> with(dat, aggregate(A, by = list(Group = Group), FUN = mean))
  Group         A
1     1 0.4269715
2     2 0.5479352
3     3 0.5091543
4     4 0.4926412

However, it fails make check-all because examples have relied on
returned object having 'x'. I also note that this might have the
annoying side effect of producing odd names if we use the following
incantation:

> res <- aggregate(dat$A, by = list(Group = dat$Group), FUN = mean)
> str(res)
'data.frame':	4 obs. of  2 variables:
 $ Group: Factor w/ 4 levels "1","2","3","4": 1 2 3 4
 $ dat$A: num  0.427 0.548 0.509 0.493
> res$dat$A
Error in res$dat$A : $ operator is invalid for atomic vectors
> res$`dat$A`
[1] 0.4269715 0.5479352 0.5091543 0.4926412

Is there a way of coming up with a better way to name the aggregated
variable? Would a change of this kind be something R Core would consider
making to aggregate.default if a good solution is found?

Thanks in advance,

G
-- 
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 Dr. Gavin Simpson             [t] +44 (0)20 7679 0522
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