On 03/08/10 21:50, GL wrote:
If I have a column with 2 levels, but one level has no remaining
observations. Can I remove the level?
Like this?
d <- data.frame(a = factor(rep("A", 3), levels = c("A", "B")))
levels(d$a)
# [1] "A" "B"
d$a <- d$a[,drop=TRUE]
levels(d$a)
# [1] "A"
Hope this h
Ended up working as follows:
dbs3.train.sans.influential.obs <-
drop.levels(dbs3.train.sans.influential.obs)
drop.list <- NULL
for (i in 4:ncol(dbs3.train.sans.influential.obs)) {
if (nlevels(dbs3.train.sans.influential.obs[,i]) < 2) {drop.list <-
cbind(drop.list,i)}}
dbs3.train.san
Actually, you probably want to remove the remaining level -- that is,
remove the variable altogether, since if it has only a single value
its effect is indistinguishable from the overall mean.
Again, complying with the posting guide would be advisable.
Bert Gunter
Genentech Nonclinical Biostatist
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 repr
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)
yie
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