Never mind, I find a generic solution:
require(reshape)
melted<-melt(dataframe, id=c("id","f1","f2"))
averaged=cast(melted,id+f1~variable,mean)
which collapses away "f2", and it's easy to generalize this to collapse
any factors.
Thanks anyway
Gordon
On 4/25/11 6:14 AM, Kenneth Roy Cabrera Torres wrote:
> Hi Junquian:
>
> I try your code (there is a typo, I believe)
>
> a<-rnorm(6)
> b<-rnorm(9)
> f1<-c("x1","x2","x3")
> f2<-c("y1","y2")
> id<-c(1:6)
> a_df<-data.frame(cbind(id,f1,"y1",a))
> id<-c(1:9)
> b_df<-data.frame(cbind(id,f1,"y2",b))
>
> But I don't understand the "nested" databases.
> I see that both have f1 variable but I do not see f2 variable in any of
> them. So, what do you mean with "collapse f2"?
>
> Maybe you need to first "merge()" de databases and then "aggregate()"
> them.
>
> Have a nice day!
>
> El dom, 24-04-2011 a las 23:42 -0500, Junqian Gordon Xu escribió:
>> I have two nested data frames:
>>
>> a<-rnorm(6)
>> b<-rnorm(9)
>> f1<-c("x1","x2","x3"))
>> f2<-c("y1","y2")
>> id<-c(1:6)
>> a_df<-data.frame(cbind(id,f1,"y1",a))
>> id<-c(1:9)
>> b_df<-data.frame(cbind(id,f1,"y2",b))
>>
>> I want to preserve id and f1, but want to collapse f2 and take the
>> corresponding mean values of a and b. Missing value in either dataframe
>> should be handled properly (i.e., just take the non-missing number
>> without dividing by 2).
>>
>> I had a look at rowSum/Means and s/l/tapply, but couldn't figure out how
>> to handle this case cleanly. Any suggestions?
>>
>> Thanks
>> Gordon
>>
>> ______________________________________________
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>> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
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>
>
>
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