Joel, try this:
# sample matrix m <- matrix(sample(c(1:10, NA),150,replace=T),byrow=T,ncol=15) # nr of missing values per row nacounts <- apply(m, 1, function(x)length(x[is.na(x)])) # new matrix newm <- m[nacounts/ncol(m) < 0.1,] greetings, Remko ------------------------------------------------- Remko Duursma Post-Doctoral Fellow Centre for Plants and the Environment University of Western Sydney Hawkesbury Campus Richmond NSW 2753 Dept of Biological Science Macquarie University North Ryde NSW 2109 Australia Mobile: +61 (0)422 096908 www.remkoduursma.com 2010/1/15 Joel Fürstenberg-Hägg <joel_furstenberg_h...@hotmail.com>: > > Hi all, > > > > I would like to remove rows from a matrix, based on the frequency of missing > values. If there are more than 10 % missing values, the row should be deleted. > > > > I use the following to calculate the frequencies, thereby getting a new > matrix with the frequencies: > > > > freqNA=rowMeans(is.na(exprdata)) > > > > But is there a shorter way to remove the rows based on "(1-freqNA)>0.1" than > looping through the whole matrix using a for loop? > > > > > > All the best, > > > > Joel > > _________________________________________________________________ > Hitta kärleken i vinter! > http://dejting.se.msn.com/channel/index.aspx?trackingid=1002952 > [[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. > > ______________________________________________ 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.
