I have two datasets: A with columns Open and Name (and many others, irrelevant to the merge) B with columns Time and Name (and many others, irrelevant to the merge)
I want the dataset AB with all these columns Open from A - a difftime (time of day) Time from B - a difftime (time of day) Name (same in A & B) - a factor, does NOT index rows, i.e., there are _many_ rows in both A & B with the same Name. all the other columns from A & B. Each row in AB must come from exactly one row in A. (i.e., dim(AB)[1] == dim(A)[1]). For each row in AB, Open>=Time, and "as small as possible". The above conditions uniquely define AB. The "obvious algorithm" is: for each row in A search B for a row with the same Name and the largest Time <= Open. However, I don't see an easy way to do it in R. The obvious intermediary step is AB1 <- merge(A, B, all.x = TRUE, all.y = FALSE, by = 'Name') Now, AB1 has many rows with the same Name and Open. I need to drop all of them except for the one with the largest Time <= Open. I can do AB2 <- AB1[which(AB1$Time <= AB1$Open),] Now I need to keep just _one_ row with the same Name & Open - and the largest Time. How do I do that? unique() seems to have the right name, but I don't see how it can help me... tia. -- Sam Steingold (http://sds.podval.org/) on CentOS release 5.6 (Final) X 11.0.60900031 http://jihadwatch.org http://honestreporting.com http://ffii.org http://camera.org http://thereligionofpeace.com UNIX is a way of thinking. Windows is a way of not thinking. ______________________________________________ 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.
