You can read chunks of it at a time and store it in sparse matrix form using the packages SparseM or Matrix, but then you need to think about what you want to do with it.... least squares sorts of things are ok, but other options are somewhat limited...
url: www.econ.uiuc.edu/~roger Roger Koenker email [EMAIL PROTECTED] Department of Economics vox: 217-333-4558 University of Illinois fax: 217-244-6678 Champaign, IL 61820 On Apr 24, 2006, at 12:41 PM, Sachin J wrote: > Hi, > > I have a dataset consisting of 350,000 rows and 266 columns. Out > of 266 columns 250 are dummy variable columns. I am trying to read > this data set into R dataframe object but unable to do it due to > memory size limitations (object size created is too large to handle > in R). Is there a way to handle such a large dataset in R. > > My PC has 1GB of RAM, and 55 GB harddisk space running windows XP. > > Any pointers would be of great help. > > TIA > Sachin > > > --------------------------------- > > [[alternative HTML version deleted]] > > ______________________________________________ > R-help@stat.math.ethz.ch mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide! http://www.R-project.org/posting- > guide.html ______________________________________________ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html