Replacing values without looping

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

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...

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Joshua Wiley
Ph.D. Student, Health Psychology
University of California, Los Angeles
http://www.joshuawiley.com/