try this:
> myData = data.frame(Name = c('a', 'a', 'b', 'b'), length = c(1,2,3,4), type
+ = c('x','x','y','z'))
>
> result <- do.call(rbind, lapply(split(myData, myData$Name), function(.name){
+ data.frame(Name = .name$Name[1L]
+ , length = mean(.name$length)
+ , type = if (all(.name$type[1L] == .name$type)) .name$type[1L] else NA
+ )
+ })
+ )
> result
Name length type
a a 1.5 x
b b 3.5 <NA>
>
On Tue, Jul 3, 2012 at 12:04 PM, Filoche <pmassico...@hotmail.com> wrote:
> Hi everyone.
>
> I have these data :
>
> myData = data.frame(Name = c('a', 'a', 'b', 'b'), length = c(1,2,3,4), type
> = c('x','x','y','z'))
>
> which gives me:
>
> Name length type
> 1 a 1 x
> 2 a 2 x
> 3 b 3 y
> 4 b 4 z
>
> I would group (mean) this DF using 'Name' as grouping factor. However, I
> have a field ('type') which is a string. I would like to use the unique
> value of this field when possible (i.e. when all the 'type' values are the
> same for each group) or replace with NA when 'type' has multiple values.
>
> In fact, I would like to obtain this:
>
> Name length type
> 1 a 1.5 x
> 2 b 3.5 NA
>
> For instance, I was using this command:
>
> aggregate(list(myData$length, myData$type), list(myData$Name), FUN = mean)
>
> But it can't deal with string data.
>
> I hope I have been clear enough.
>
> With regards,
> Phil
>
> --
> View this message in context:
> http://r.789695.n4.nabble.com/Data-manipulation-with-aggregate-tp4635298.html
> Sent from the R help mailing list archive at Nabble.com.
>
> ______________________________________________
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> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
--
Jim Holtman
Data Munger Guru
What is the problem that you are trying to solve?
Tell me what you want to do, not how you want to do it.
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