you can do the following:
mat <- cbind(x = runif(15, 50, 70), y = rnorm(15, 2))
mat[sample(15, 2), "x"] <- NA
na.x <- is.na(mat[, 1])
mat[na.x, ]
mat[!na.x, ]
I hope it helps.
Best,
Dimitris
On 10/15/2010 2:45 PM, Jumlong Vongprasert 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
--
Dimitris Rizopoulos
Assistant Professor
Department of Biostatistics
Erasmus University Medical Center
Address: PO Box 2040, 3000 CA Rotterdam, the Netherlands
Tel: +31/(0)10/7043478
Fax: +31/(0)10/7043014
Web: http://www.erasmusmc.nl/biostatistiek/
______________________________________________
R-help@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
