Hi Sam, How about this?
test[apply(test, 1, function(x) !any(x == '#DIV/0!')), ] HTH, Jorge On Wed, Mar 9, 2011 at 3:29 PM, Sam Albers <> wrote: > Hello Venerable List, > > I am trying to loop (I think) an operation through a list of columns in a > dataframe to remove set of #DIV/0! values. I am trying to do this like so: > > #Data.frame > test <- read.csv("http://dl.dropbox.com/u/1574243/sample_data.csv", > header=TRUE, sep=",") > > > #This removes all the rows with #DIV/0! values in the mean column. > only.mean <- test[!test$mean=="#DIV/0!",] > > #This removes the majority of #DIV/0! values as there is a large block of > these values that extends over every column. > #However, it doesn't remove then all. Can any recommend a way where I can > cycle through all the columns and remove these values other than manually > like so: > mean.median <- only.mean[!only.mean$median=="#DIV/0!",] # and so on through > each column? > > Can anyone recommend a better way of doing this? > > Thanks in advance! > > Sam > > [[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. > [[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.