>From an email suggestion, here are two sample datasets, and my ideal output:
dataA <- data.frame(unique.id=c("A","B","C","B"),x=11:14,y=5:2) dataB <- data.frame(unique.id=c("A","B","A","B","A","C","D","A"),x=27:20,y=22:29) ## mystery operation(s) happen here.... ## ideal output would be: dataA <- data.frame(unique.id=c("A","B","C","B"),x=11:14,y=5:2,countA=c(1,2,1,2),countB=c(4,2,1,2)) so my mystery operation(s) would count the number of times the unique id shows up in a given dataset. my ideal outputs are as follows: countA is the "mystery operation" applied to dataA (counting occurrences within the same dataset) countB is applied to dataB (counting occurrences within a second dataset). My best try so far is to do: tempA <- aggregate(dataA$unique.id,list(dataA$unique.id),length) which gives me a matrix with ONE instance of each unique.id and the counts... (and which I thought was kinda cute) but it only works for within a single dataset! tathta wrote: > > I have two dataframes, the first column of each dataframe is a unique id > number (the rest of the columns are data variables). > I would like to figure out how many times each id number appears in each > dataframe. > > So far I can use: > length( match (dataframeA$unique.id[1], dataframeB$unique.id) ) > > but this only works on each row of dataframe A one-at-a-time. > > I would like to do this for all of the rows in dataframe A, and then put > the results in a new variable: dataframeA$count > > > I'm new to R, so please be patient with me! > > > > thx > -- View this message in context: http://www.nabble.com/matching-each-row-tp24393051p24395711.html Sent from the R help mailing list archive at Nabble.com. ______________________________________________ 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.