With melt and rep you are close. If you combine them it works: library(reshape) # your data: df1 <- data.frame(area=c(1,2),group1=c(2,3),group2=c(1,5),group3=c(4,0)) df2<-data.frame(person_id=seq(1:15),area=c(rep(1,7),rep(2,8)),group_num=c(1,1,2,3,3,3,3,1,1,1,2,2,2,2,2)) # first melt d <- melt(df1,"area",2:4) # then repeat each row by 'counts' d <- d[rep(seq(nrow(d)), times=d$value),] # then order (if order of id's is not arbitrary), and add ids d <- d[order(d$area,d$variable),] d$value <- seq(nrow(d)) # compare cbind(df2,"---",d)
Best, Sven. On 22 October 2014 17:48, Gavin Rudge <g.ru...@bham.ac.uk> wrote: > I've got data frame containing a simple frequency distribution of numbers of > people in three age groups by area. > > df1<-data.frame(area=c(1,2),group1=c(2,3),group2=c(1,5),group3=c(4,0)) > df1 > > I want to get a data frame with one record per person (in my case 15 of them) > which would look like this, with variables indicating the area and age group > to which each belongs > > df2<-data.frame(person_id=seq(1:15),area=c(rep(1,7),rep(2,8)),group_num=c(1,1,2,3,3,3,3,1,1,1,2,2,2,2,2)) > df2 > > This is not the same as melting wide to long data as in reshape2, as I'm > melting from aggregated data. I can get vectors of columns values using the > rep command, but sewing them together and allowing for zeros looks a bit > cumbersome. I'm assuming there is a simple command that does this sort of > thing. > > Any help gratefully received, > > GavinR > > [[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. ______________________________________________ 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.
