This method worked perfectly! The rle() function was key and I was
completely unfamiliar with it. Thanks so much,
Max
On Thu, May 24, 2012 at 8:52 AM, Rui Barradas <ruipbarra...@sapo.pt> wrote:
> Hello,
>
> Assuming that 'd' is your original data.frame and that you've set entire
> rows to NA, try this
>
>
> d$leak_num <- NA
> ix <- !is.na(d[, 1]) # any column will do, entire row is NA
> ## alternative, if other rows may have NAs, due to something else
> #ix <- apply(d, 1, function(x) all(!is.na(x)))
> r <- rle(ix)
> v <- cumsum(r$values)
> d$leak_num[ix] <- rep(v[r$values], r$lengths[r$values])
> d
>
>
> Hope this helps,
>
> Rui Barradas
>
> Em 24-05-2012 11:00, Max Brondfield <mbro...@post.harvard.edu> escreveu:
>
>> Date: Wed, 23 May 2012 16:42:02 -0400
>> From: Max Brondfield<mbrondf@post.**harvard.edu<mbro...@post.harvard.edu>
>> >
>> To:r-help@r-project.org
>> Subject: [R] Using NA as a break point for indicator variable?
>> Message-ID:
>> <CADu+jDpcJUHZTXxrsxyQvjaEmw_**N0iLbL6ZJjHZC-rSBCMneiw@mail.**
>> gmail.com<cadu%2bjdpcjuhztxxrsxyqvjaemw_n0ilbl6zjjhzc-rsbcmn...@mail.gmail.com>
>> >
>> Content-Type: text/plain
>>
>>
>> Hi all,
>> I am working with a spatial data set for which I am only interested in
>> high
>> concentration values ("leaks"). The low values (< 90th percentile) have
>> already been turned into NA's, leaving me with a matrix like this:
>>
>> < CH4_leak
>>
>> lon lat CH4
>> 1 -71.11954 42.35068 2.595834
>> 2 -71.11954 42.35068 2.595688
>> 3 NA NA NA
>> 4 NA NA NA
>> 5 NA NA NA
>> 6 -71.11948 42.35068 2.435762
>> 7 -71.11948 42.35068 2.491003
>> 8 NA NA NA
>> 9 -71.11930 42.35068 2.464475
>> 10 -71.11932 42.35068 2.470865
>>
>> Every time an NA comes up, it means the "leak" is gone, and the next valid
>> value would represent a different leak (at a different location). My goal
>> is to tag all of the remaining values with an indicator variable to
>> spatially distinguish the leaks. I am envisioning a simple numeric
>> indicator such as:
>>
>> lon lat CH4 leak_num
>> 1 -71.11954 42.35068 2.595834 1
>> 2 -71.11954 42.35068 2.595688 1
>> 3 NA NA NA NA
>> 4 NA NA NA NA
>> 5 NA NA NA NA
>> 6 -71.11948 42.35068 2.435762 2
>> 7 -71.11948 42.35068 2.491003 2
>> 8 NA NA NA NA
>> 9 -71.11930 42.35068 2.064475 3
>> 10 -71.11932 42.35068 2.070865 3
>>
>> Does anyone have any thoughts on how to code this, perhaps using the NA
>> values as a "break point"? The data set is far too large to do this
>> manually, and I must admit I'm completely at a loss. Any help would be
>> much
>> appreciated! Best,
>>
>> Max
>>
>> [[alternative HTML version deleted]]
>>
>>
>>
--
Max Brondfield
Research Assistant
Department of Geography & Environment
Boston University
[[alternative HTML version deleted]]
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