On Mon, 18 Jul 2005, Peter Dalgaard wrote:
> Chuck Cleland <[EMAIL PROTECTED]> writes:
>
>>> data <- as.data.frame(cbind(X1,X2,X3,X4,X5))
>>>
>>> So only X1, X3 and X5 are vars without any NAs and there are some vars (X2
>>> and
>>> X4 stacked in between that have NAs). Now, how can I extract those former
>>> vars
>>> in a new dataset or remove all those latter vars in between that have NAs
>>> (without missing a single row)?
>>> ...
>>
>> Someone else will probably suggest something more elegant, but how
>> about this:
>>
>> newdata <- data[,-which(apply(data, 2, function(x){all(is.na(x))}))]
>
> (I think that's supposed to be any(), not all(), and which() is
> crossing the creek to fetch water.)
>
> This should do it:
>
> data[,apply(!is.na(data),2,all)]
If `data' is a data frame, apply will coerce it to a matrix. I would do
something like
keep <- sapply(data, function(x) all(!is.na(x)))
data[keep]
to use the list-like structure of a data frame and make the fewest
possible copies.
--
Brian D. Ripley, [EMAIL PROTECTED]
Professor of Applied Statistics, http://www.stats.ox.ac.uk/~ripley/
University of Oxford, Tel: +44 1865 272861 (self)
1 South Parks Road, +44 1865 272866 (PA)
Oxford OX1 3TG, UK Fax: +44 1865 272595
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