I have a data set of many rows and many columns in which both the rows and the columns have associated grouping factors.
Is there a way to do what 'aggregate' does but in the other dimension? The way I have been doing this is to use 'aggregate' on the data in the usual way and then rotate the result and apply 'aggregate' again. This works but is a little messy and I was wondering if there is some built-in way to do this easier. An example of what I have been doing is below. #Four observations of four variables v1 <- c(1, 8, 5, 3) v2 <- c(5, 5, 6, 5) v3 <- c(3, 2, 9, 4) v4 <- c(4, 1, 1, 1) myData <- data.frame(v1=v1, v2=v2, v3=v3, v4=v4) myData #The observations have either property 1 or property 2 rowFactor <- data.frame(RowTraits=factor(c(1, 2, 1, 2))) rowFactor #The variables have a property that is either present or absent colFactor <- data.frame(ColTraits=factor(c(1, 1, 0, 0))) colFactor #Getting the means for the columns by row groups is easy MeanByRowTraits <- aggregate (myData, rowFactor[1], mean) MeanByRowTraits #But now to get the means for the rows by column groups is awkward rotateData <- data.frame(t(MeanByRowTraits[2:5])) colnames(rotateData) <- c(levels(rowFactor[,1])) rotateData #This is the kind of result I want in the end aggregate (rotateData, colFactor[1], mean) -- Jack Siegrist Graduate Program in Ecology & Evolution, and Department of Ecology, Evolution, & Natural Resources, Rutgers University, New Brunswick, NJ 08901 ______________________________________________ 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.
