I am working with a matrix (x), where rows are non-overlapping geographical areas (postcodes; here denoted with letter row names), and columns are income bands with a central value (e.g. ?7.5k, here denoted x1,x2, etc.). The data are counts (how many households with 0-5k pa, 5-10k pa?, etc.) I would like to summarise this data set. First row-wise as suggested by Henrik Bengtsson (www.maths.lth.se/help/R/R.classes/ <http://www.maths.lth.se/help/R/R.classes/> ), example: library (R.basic) x<-cbind(x1=3,x2=c(4:1,2:5)) dimnames(x)[[1]]<-letters[1:8] w<-c(1,2) wm <- apply(x, MARGIN=1, FUN=weighted.median, w=w, na.rm=TRUE) wm QUESTION Secondly, I would like to aggregate rows (postcodes) into bigger units according additional factor vectors (higher administrative order or environmental attributes). I would be grateful for ideas to how I can achieve this in our R. Jakob Software: R ver 2.01 (Windows) R.basic ver 0.59 Jakob Petersen GISc student (MSc) Birkbeck, University of London