On Feb 8, 2010, at 11:39 AM, Jonathan wrote:
Hi all,
I'm feeling a little guilty to ask this question, since I've
written a solution using a rather clunky for loop that gets the job
done. But I'm convinced there must be a faster (and probably more
elegant) way to accomplish what I'm looking to do (perhaps using the
"merge" function?). I figured somebody out there might've already
figured this out:
I have a dataframe with two columns (let's call them V1 and V2). All
rows are unique, although column V1 has several redundant entries.
Ex:
V1 V2
1 a 3
2 a 2
3 b 9
4 c 4
5 a 7
6 b 11
What I'd like is to return a dataframe cut down to have only unique
entires in V1. V2 should contain a vector, for each V1, that is the
minimum of all the possible choices from the set of redundant V1's.
> rd.txt
function(txt, header=TRUE,...) {
rd<-read.table(textConnection(txt), header=header, ...)
closeAllConnections()
rd}
> DF <- rd.txt(" V1 V2
+ 1 a 3
+ 2 a 2
+ 3 b 9
+ 4 c 4
+ 5 a 7
+ 6 b 11
+ ")
> tapply(DF$V2, DF$V1, min)
a b c
2 9 4
> as.data.frame.table(tapply(DF$V2, DF$V1, min))
Var1 Freq
1 a 2
2 b 9
3 c 4
> DF2 <- as.data.frame.table(tapply(DF$V2, DF$V1, min))
> names(DF2) <- names(DF)
> DF2
V1 V2
1 a 2
2 b 9
3 c 4
Example output:
V1 V2
1 a 2
2 b 9
3 c 4
If somebody could (relatively easily) figure out how to get closer to
a solution, I'd appreciate hearing how. Also, I'd be interested to
hear how you came upon the answer (so I can get better at searching
the R resources myself).
Regards,
Jonathan
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PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
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David Winsemius, MD
Heritage Laboratories
West Hartford, CT
______________________________________________
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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.
