Try this:

split(as.data.frame(DF), is.na(DF$x))


On Fri, Oct 15, 2010 at 9:45 AM, Jumlong Vongprasert <jumlong.u...@gmail.com
> wrote:

> Dear all
> I have data like this:
>              x          y
>  [1,] 59.74889  3.1317081
>  [2,] 38.77629  1.7102589
>  [3,]       NA  2.2312962
>  [4,] 32.35268  1.3889621
>  [5,] 74.01394  1.5361227
>  [6,] 34.82584  1.1665412
>  [7,] 42.72262  2.7870875
>  [8,] 70.54999  3.3917257
>  [9,] 59.37573  2.6763249
>  [10,] 68.87422  1.9697770
>  [11,] 19.00898  2.0584415
>  [12,] 60.27915  2.5365194
>  [13,] 50.76850  2.3943836
>  [14,]       NA  2.2862790
>  [15,] 39.01229  1.7924957
>
> and I want to spit data into two set of data,  data set of nonmising and
> data set of missing.
> How I can do this.
> Many Thanks.
> Jumlong
>
>
> --
> Jumlong Vongprasert
> Institute of Research and Development
> Ubon Ratchathani Rajabhat University
> Ubon Ratchathani
> THAILAND
> 34000
>
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>
> ______________________________________________
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> PLEASE do read the posting guide
> http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
>



-- 
Henrique Dallazuanna
Curitiba-Paraná-Brasil
25° 25' 40" S 49° 16' 22" O

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