GL wrote:
If I have a column with 2 levels, but one level has no remaining
observations. Can I remove the level?
What is a 'column'? An element of a data.frame?
Does the following help?
f1 <- factor("L1", levels = c("L1", "L2"))
levels(f1)
f1 <- factor(f1)
levels(f1)
In absence of a reproducible example, as the posting guide requests, I
cannot tell exactly what you're after here.
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.
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