If I have a column with 2 levels, but one level has no remaining observations. Can I remove the level?
Had intended to do it as listed below, but soon realized that even though there are no observations, the level is still there. For instance summary(dbs3.train.sans.influential.obs$HAC) yields 0 ,1 4685,0 nlevels(dbs3.train.sans.influential.obs$HAC) yields [1] 2 drop.list <- NULL for (i in 1:ncol(dbs3.train.sans.influential.obs)) { if (nlevels(dbs3.train.sans.influential.obs[,i]) < 2) {drop.list <- cbind(drop.list,i)}} yields nothing because HAC still has two levels, even though there aren't any observations in on of the levels. What I want to do is loop through all columns that are factors and create a list of items to drop because there will subsequently be < 2 levels when I try to run a linear model. -- View this message in context: http://r.789695.n4.nabble.com/REmove-level-with-zero-observations-tp2312553p2312553.html Sent from the R help mailing list archive at Nabble.com. ______________________________________________ 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.