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. 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 ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.