Thank you Pikal and Bert. My apology for posting parts of my previous
email in HTML. Bert's suggestion will work but i am wondering if there
is an alternative
especially in the case where the data frames are big; that is the
difference in lengths among them is large. Below is a list of sample
date frames and desired result.
EK
dput(df1<-data.frame(col1=c(1,2,3,4,5),col2=c("aa","aa","bb","cc","dd")))
dput(df2<-data.frame(col1=c(1,2,4,5),col2=c("bb","bb","cc","bb")))
dput(df3<-data.frame(col1=c(1,3),col2=c("aa","aa")))
# desired result
dput(dfn<-data.frame(col1=c(2,2,1,1),col2=c(0,3,1,0),col3=c(2,0,0,0),row.names
= c("aa","bb","cc","dd")))
On Fri, Feb 23, 2018 at 7:45 AM, PIKAL Petr <petr.pi...@precheza.cz> wrote:
> Hi
>
> Your example is rather confusing - partly because HTML formating, partly
> because weird coding.
>
> You probably could concatenate your data frames e.g. by rbind or merge and
> after that you could try to aggregate them somehow.
>
> I could construct example data.frames myself but most probably they would be
> different from yours and also the result would not be necessary the same as
> you expect.
>
> You should post those data frames as output from dput(data) and show us real
> desired result from those example data frames.
>
> Cheers
> Petr
>
>> -----Original Message-----
>> From: R-help [mailto:r-help-boun...@r-project.org] On Behalf Of Ek Esawi
>> Sent: Wednesday, February 21, 2018 3:34 AM
>> To: r-help@r-project.org
>> Subject: [R] Aggregate over multiple and unequal column length data frames
>>
>> Hi All--
>>
>> I have generated several 2 column data frames with variable length. The data
>> frames have the same column names and variable types. I was trying to
>> aggregate over the 2nd column for all the date frames, but could not figure
>> out
>> how.
>>
>> I thought i could make them all of equal length then combine them in 1 data
>> frame where i can use aggregate, the formula version Or to put them in a list
>> and loop use lapply but did not know how to do that and thought there might
>> be a simpler way.
>>
>> Below is an example of 3 data frames and the desired result; note that some
>> levels don't appear in all and may be null over all variable, like the case
>> of dd
>> on the desired result which i would like to list all levels even if some are
>> all null.
>>
>> Thanks in advance,
>>
>> EK
>>
>> df1 df2 df3
>>
>> c1 c2 c1 c2 c1 c2
>> 1 aa 1 bb 1 aa
>> 2 aa 2 bb 2 aa
>> 3 bb 3 cc
>> 4 cc 4 bb
>> 5 bb
>>
>> desired result
>>
>> c1 c2 c2 c2
>> aa 2 2
>> bb 1 2 2
>> cc 1 1
>> dd
>>
>> [[alternative HTML version deleted]]
>>
>> ______________________________________________
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