Hello, I have two dataframes DF1 and DF2 that should be identical but are not (DF1 has some rows that aren't in DF2, and vice versa). I would like to produce a new dataframe DF3 containing rows in DF1 that aren't in DF2 (and similarly DF4 would contain rows in DF2 that aren't in DF1).
I have a solution for this problem (see self contained example below) but it's awkward and requires making a new "ID" column by pasting together all of the columns in each DF and them comparing the two DFs based on this unique ID. Is there a better way? Many thanks for your help, Mark #compare two dataframes and extract uncommon rows #MAKE SOME DATA cars$id<-paste(cars$speed,cars$dist,sep="") $create unique ID field by pasting all columns together cars1<-cars[1:35,] cars2<-cars[16:50,] #EXTRACT UNIQUE ROWS cars1_unique<-cars1[cars1$id %in% setdiff(cars1$id,cars2$id),] #rows unique to cars1 (i.e., not in cars2) cars2_unique<-cars2[cars2$id %in% setdiff(cars2$id,cars1$id),] #rows unique to cars2 ______________________________________________ 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.
