or without plyr you could do, e.g.,

aggregate(df2aggregate[,-1], df2aggregate["id"], function(..)
if(is.numeric(..)) mean(..) else if(is.character(..)) ..[1])

Kenn


On Mon, May 13, 2013 at 1:30 AM, Spencer Graves <
spencer.graves@structuremonitoring.com> wrote:

> Hi, Arun:  Thanks.  That's exactly what I need.  Spencer
>
>
>  fortune(298)
>
> Don't do as I say, do as Hadley does.
>    -- Barry Rowlingson (in a discussion about the workflow for writing R
>       packages, see also fortune(128))
>       R-devel (September 2011)
>
>
>
> On 5/12/2013 2:25 PM, arun wrote:
>
>>
>> HI,
>>
>> Try:
>> library(plyr)
>> res1<-ddply(df2aggregate,.(id)**,summarize,x=sum(x),y=mean(y),**
>> a=head(a,1))
>> res1
>> #  id  x   y    a
>> #1  a  3  NA <NA>
>> #2  b  7 2.5    A
>> #3  c 11 4.5    C
>> #4  d NA  NA    E
>>   res1$x<- as.numeric(res1$x)
>>   identical(ag1.2,res1)
>> #[1] TRUE
>> A.K.
>>
>>
>> ----- Original Message -----
>> From: Spencer Graves <spencer.graves@**structuremonitoring.com<spencer.graves@structuremonitoring.com>
>> >
>> To: R list <R-help@r-project.org>
>> Cc:
>> Sent: Sunday, May 12, 2013 4:54 PM
>> Subject: [R] aggregate.data.frame with NAs and different types
>>
>> Hello:
>>
>>
>>         Do you have suggestions for how to aggregate a data.frame using
>> different functions on different columns?
>>
>>
>>         Consider the following example:
>>
>>
>> df2aggregate <- data.frame(id=rep(letters[1:4]**, each=2),
>>                              x =c(1:6, NA, NA),
>>                              y =c(NA, 1:6, NA),
>>                              a =c(NA, NA, LETTERS[1:6]),
>>                              stringsAsFactors=FALSE)
>>
>> # Desired output:
>>
>> ag1.2 <- data.frame(id=letters[1:4],
>>                       x =c(3, 7, 11, NA),
>>                       y =c(NA, 2.5, 4.5, NA),
>>                       a =c(NA, 'A', 'C', 'E'),
>>                       stringsAsFactors=FALSE)
>>
>>
>>         I'm thinking of writing a function Aggregate(x, by, FUN, ...),
>> where x = data.frame, by = vector of names of columns of x, and FUN =
>> function that would accept as input a data.frame subset of x and would
>> return a data.frame FUNout, which would be combined using cbind(x[, by],
>> FUNout), then rbind over all such subset data.frames.  However, before I
>> write this, I'd like to make sure it doesn't already exist.  My current
>> plan is to add it to the Ecdat package.
>>
>>
>>         Suggestions?  Should I study "plyr"?  fortune(298) ;-)
>>
>>
>>         Thanks,
>>         Spencer
>>
>>
>> p.s.  library(sos); findFn('aggregate.data.frame') returned 4 matches,
>> none of which seemed to solve this problem. findFn('aggregate
>> data.frame') returned 133 matches in 71 package. findFn('aggregate')
>> returned 734 matches in 282 packages.  I failed to find anything useful
>> in the latter two and with other attempts using RSiteSearch, except for
>> a reference to plyr.
>>
>
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