Dear Payam, Here is a suggestion: index <- apply(yourdata, 1, function(x) any( is.na(x) ) ) yourdata[ !index, ]
Above creates an index (TRUE) when any row of the data contains a missing value. Then it filters up (extract) the rows that have complete observations. See ?any, ?is.na, ?"!" and ?apply for more information. HTH, Jorge On Wed, Sep 2, 2009 at 1:09 PM, Payam Minoofar <payam.minoo...@meissner.com>wrote: > Hello everyone, > > I am trying to prune a data frame for partial least squares analysis. > I need to delete an entire row if one cell in the row contains a NA. > > Presently, I am running a loop that is supposed to extract the rows > that are full of numbers into a second data frame and skips the rows > that contain a single NA value. > > I want to know if there is a simple way to determine if a row (about > 20 columns) contains a single NA value without running a loop that > checks each individual cell. > > Thanks in advance. > > __________________ > Payam Minoofar, Ph.D. > Scientist > Meissner Filtration Products > 4181 Calle Tesoro > Camarillo, CA 93012 > +1 805 388 9911 ext. 159 > +1 805 388 5948 fax > payam.minoo...@meissner.com > > ______________________________________________ > 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. > > [[alternative HTML version deleted]] ______________________________________________ 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.
