Something like this should work:
num <- apply(yourData, 2, function(x) sum(is.na(x)) < 375)
yourData <- youData[, num]
On Sun, Jan 18, 2009 at 9:55 AM, Josh B <josh...@yahoo.com> wrote:
> Hello,
>
> I have a dataset (named "x") with many (966) columns. What I would like to do
> is delete any columns that do not have at least 375 non-blank observations
> (i.e., the cells have some value in them besides NA).
>
> How can I do this? I have come up with the following code to _count_ the
> non-blank observations in each column, but how would I adapt this code to
> _delete_ columns from the dataset if they do not have at least 375 non-blank
> observations?
>
>
>
> lapply(x, function(d)
> {
> d.2<- na.omit(d)
> count<- length(d.2)
> }
> )
>
> Many thanks in advance,
> Josh B.
>
>
>
> [[alternative HTML version deleted]]
>
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>
--
Jim Holtman
Cincinnati, OH
+1 513 646 9390
What is the problem that you are trying to solve?
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