Hi all, I'm having a problem restructuring my data the way I'd like it. I have data that look like this:
Candidate.ID Specialty Office Score 110002 C London 47 110002 C East 48 110003 RM West 45 110003 RM Southwest 39 110003 C Southwest 38 110004 H South 42 110006 G East 47 110006 G London 45 Candidates can apply for the same job specialty in up to 2 offices (never more). They can apply for different specialties in further centres. I would like to look at score differences when candidates apply for the same specialty in two different offices. With the help of the archives I have tried various stack/unstack and reshape/melt/cast combinations, and I've managed to get a huge matrix where the columns are all possible combinations of Specialties & Offices - and there are many. This leaves a very sparse matrix with mainly null values, and this is not what I want. I'd like the scores from the two attempts in two columns so I can do scatterplots, calculate differences by specialty etc. In SPSS I'd use 'restructure' to get what I want. I'm working to order with specific requests here so I have to do it this way (as opposed to a modelling approach). I would like it restructured to look something like this: Candidate.ID Specialty Office.1 Score.1 Office.2 Score.2 110002 C London 47 East 48 110003 RM West 45 Southwest 39 110003 C Southwest 38 110004 H South 42 110006 G East 47 London 45 110006 G London 45 So one row per candidate/specialty combination, with 2 sets of offices/scores and null values in the second set if they've only applied once for that specialty. Can anyone help me out with this? Is it possible using stack or reshape? Many thanks for reading, Jan PS Closest I've come to what I need is the sparse matrix produced by this: recast(spec.scores, Candidate.ID ~ Specialty + Office, measure.var="Score") [[alternative HTML version deleted]] ______________________________________________ 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.