G'day Ted,
On Sun, 18 Jul 2010 09:25:09 +0100 (BST)
(Ted Harding) <ted.hard...@manchester.ac.uk> wrote:
> On 18-Jul-10 05:47:03, Suresh Singh wrote:
> > I have a data file in which one of the columns is country code and
> > NA is the
> > code for Namibia.
> > When I read the data file using read.csv, NA for Namibia is being
> > treated as
> > null or "NA"
> >
> > How can I prevent this from happening?
> >
> > I tried the following but it didn't work
> > input <- read.csv("padded.csv",header = TRUE,as.is = c("code2"))
> >
> > thanks,
> > Suresh
>
> I suppose this was bound to happen, and in my view it represent
> a bit of a mess! With a test file temp.csv:
>
> Code,Country
> DE,Germany
> IT,Italy
> NA,Namibia
> FR,France
Thanks for providing an example.
> leads to exactly the same result. And I have tried every variation
> I can think of of "as.is" and "colClasses", still with exactly the
> same result!
Did you think of trying some variations of "na.strings"? ;-)
IMO, the simplest way of coding missing values in CSV files is to have
two consecutive commas; not some code (whether NA, 99, 999, -1, ...)
between them.
> Conclusion: If an entry in a data file is intended to become the
> character value "NA", there seems to be no way of reading it in
> directly. This should not be so: it should be preventable!
It is, through simple use of the "na.strings" argument:
R> X <- read.csv("temp.csv", na.strings="")
R> X
Code Country
1 DE Germany
2 IT Italy
3 NA Namibia
4 FR France
R> which(is.na(X))
integer(0)
HTH.
Cheers,
Berwin
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