[R] read data into R with some constraints (Just out of curiosity)
Prof Brian Ripley
ripley at stats.ox.ac.uk
Thu Jan 11 22:13:32 CET 2001
On Thu, 11 Jan 2001, Yves Gauvreau wrote:
> Hi Brian
> I'm not sure about this but could this kind of selective records reading be
> done (at least under Windoze) using RODBC since there is a driver for ASCII
> file sources?
Yes, it could.
> Assuming the answer is Yes. I would then ask if RODBC could also be used to
> do the same for a file residing on a Linux (Ext2fs) drive or any other file
> system for that matter?
Don't think so.
Had the request been 100x larger, I would have suggested that.
> (I think not because RODBC is just an interface that call upon the existing
> drivers on the system.)
> Yves Gauvreau
> B.E.F.P. Universite du Quebec a Montreal
> cyg at sympatico.ca
> > -----Message d'origine-----
> > De : owner-r-help at stat.math.ethz.ch
> > [mailto:owner-r-help at stat.math.ethz.ch]De la part de Prof Brian D Ripley
> > Envoye : Thursday, January 11, 2001 1:45 PM
> > A : Yu-Ling Wu
> > Cc : R-help at stat.math.ethz.ch
> > Objet : Re: [R] read data into R with some constraints
> > On Thu, 11 Jan 2001, Yu-Ling Wu wrote:
> > > Hi,
> > >
> > > I have a big data file (over 30,000 records) looks
> > > like this:
> > >
> > > 100, 20, 46, 70
> > > 103, 0, 22, 45
> > > 117, -1, 34, 65
> > > 120, 15, 0, 25
> > > 113, 0, -1, 32
> > > 142, -1, -1, 55
> > > .....
> > >
> > > I want to read only those records having positive
> > > values in all of the four
> > > columns. That is, I don't want to read record # 3, 5,
> > > and 6 into R. However,
> > > when I type:
> > >
> > > read.csv("data.csv", sep=",") -> rawdata
> > Um, read.csv uses sep =",", and you need header=FALSE.
> > > it reads the whole thing into R including those
> > > records I don't want.
> > > Could anyone tell me how I can read only those records
> > > I want?
> > You can't! Until you have read the record, you cannot tell if all the
> > entries are positive.
> > Is this really a problem? You only have around 120k numbers, and I just
> > did it very easily.
> > rawdata <- read.csv("data.csv", header=F)
> > Perhaps better is to use a matrix and scan():
> > rawdata <- matrix(scan("data.csv", sep=","), , 4, byrow=TRUE)
> > keep <- (rawdata <= 0) %*% rep(1,4) == 0
> > rawdata[keep, ]
> > Takes a few seconds and a few Mb.
> > --
> > Brian D. Ripley, ripley at stats.ox.ac.uk
> > Professor of Applied Statistics, http://www.stats.ox.ac.uk/~ripley/
> > University of Oxford, Tel: +44 1865 272861 (self)
> > 1 South Parks Road, +44 1865 272860 (secr)
> > Oxford OX1 3TG, UK Fax: +44 1865 272595
> > -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.
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Brian D. Ripley, ripley at stats.ox.ac.uk
Professor of Applied Statistics, http://www.stats.ox.ac.uk/~ripley/
University of Oxford, Tel: +44 1865 272861 (self)
1 South Parks Road, +44 1865 272860 (secr)
Oxford OX1 3TG, UK Fax: +44 1865 272595
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