Hi,
If you truly have an array, this is option that should be much faster
than a loop:
index <- which(is.na(dat))
dat[index] <- dat[index - 1]
the only catch is that when there previous value is NA, you may have
to go through the process a few times to get them all. One way to
automate this would be:
index <- which(is.na(dat))
while (any(index)) {
dat[index] <- dat[index - 1]
index <- which(is.na(dat))
}
If your dataset has many adjacent missing values, then it would be
worth it to use a fancier technique that looks for the first previous
nonmissing value. There could even be a clever way with indexing that
I am missing.
HTH,
Josh
On Thu, Jun 16, 2011 at 5:13 AM, wuffmeister <hvemhva at gmail.com>
wrote:> I got an array similar to the one below, and want to replace all NAs with
the
> previous value.
> 99 8.2 b
> NA 8.3 x
> NA 7.9 x
> 98 8.1 b
> NA 7.7 x
> 99 9.3 b
> ...
>
> i.e. the first two NAs should be replaced to 99, whereas the last one
should
> be 98.
>
> I would like to apply a function to reach row, checking if the value in col
> 1 is NA, and if it is, set the value to the previous row's col 1 value.
>
> Haven't been able to do this without looping, which gets very slow for
large
> datasets...
>
> --
> View this message in context:
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> Sent from the R help mailing list archive at Nabble.com.
>
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>
--
Joshua Wiley
Ph.D. Student, Health Psychology
University of California, Los Angeles
http://www.joshuawiley.com/