... okay, I found a solution: set.seed(1) x <- data.frame(group = c(rep("A", 4), rep("B", 3)), year = c(2001, 2003, 2004, 2005, 2003, 2004, 2005), value = rexp(7))
tply <- as.data.frame(as.table(tapply(x$value, list(x$group, x$year), FUN=length)), nm=colnames(x)) # => 2002 missing names(tply) <- c("group", "year", "num") grid <- expand.grid(group = LETTERS[1:2], year=2001:2005) # all variable combinations tply <- merge(grid, tply, by=c("group", "year"), all=TRUE) # merge the two data.frames tply$num[is.na(tply$num)] <- 0 tply Marius Hofert <> writes: > Dear expeRts, > > I have a data.frame with certain covariate combinations ('group' and 'year') > and corresponding values: > > set.seed(1) > x <- data.frame(group = c(rep("A", 4), rep("B", 3)), > year = c(2001, 2003, 2004, 2005, > 2003, 2004, 2005), > value = rexp(7)) > > My goal is essentially to construct a data.frame which contains all (group, > year) > combinations with corresponding number of values. This can easily be done > with tapply(): > > as.data.frame(as.table(tapply(x$value, list(x$group, x$year), FUN=length))) # > => 2002 missing > > However, the tricky part is now that I would like to have *all* years in > between 2001 and 2005. > Although tapply() sees the missing year 2001 for group "B" (since group "A" > has a value there), > tapply() does not 'see' the missing year 2002. > > How can such a data.frame be constructed [ideally without using additional R > packages]? > > Here is a straightforward way (hopelessly inefficient for the application in > mind): > > num <- cbind(expand.grid(group = LETTERS[1:2], year=2001:2005), num=0) > covar <- c("group", "year") > for(i in seq_len(nrow(num))) > num[i,"num"] <- sum(apply(x[,covar], 1, function(z) all(z == > num[i,covar]))) > num > > Cheers, > > Marius ______________________________________________ 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.