If d is your data frame
i1 <- sapply(d,function(x)is.factor(x)&&length(levels(x))>31)
## a vector of length ncol(d) that is TRUE only for factor columns
with >31 levels
i2 >- sapply(d,function(x)any(is.na(x)))
## You can figure it out.
-- Bert
On Thu, Aug 30, 2012 at 8:38 AM, Lopez, Dan <lopez...@llnl.gov> wrote:
> Hi,
>
> How do you subset a dataframe so that you only have columns:
>
> 1. that contain one or more NAs?
>
> 2. that contain factors with greater than or equal to 32 levels?
>
> How do you remove from a dataframe columns**
>
> 3. with one or more NA's?
>
> 4. that contain factors with greater than or equal to 32 levels?
>
> ** I know how to remove columns at a basic level but I am trying to figure
> out a more efficient way of performing these particular tasks (my data set
> has 60 columns).
> For NA's I essentially used summary(mtcars) and manually made a note of where
> NA's appeared than used:
> mtcars1<-mtcars1[,!(names(mtcars1)%in% c("hp","wt","vs"))]
> I did something similar for factors with greater than x levels only I used
> str(mtcars) to help me identify them.
> BTW I know mtcars doesn't have any of these issues. I just used it as a quick
> reference.
>
>
> Dan
>
>
> [[alternative HTML version deleted]]
>
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--
Bert Gunter
Genentech Nonclinical Biostatistics
Internal Contact Info:
Phone: 467-7374
Website:
http://pharmadevelopment.roche.com/index/pdb/pdb-functional-groups/pdb-biostatistics/pdb-ncb-home.htm
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