[R] packaged datasets in .csv format (David Firth)
david.firth at nuffield.oxford.ac.uk
Thu Jul 10 15:44:22 CEST 2003
Many thanks to those who replied to my question.
Dirk's suggestion, to use a .R file in the "data" directory of the
package, specifying how the .csv should be read, works fine as an
answer to the question about making comma-separated files available.
Uwe's answer to my other question (; vs ,), ie compatibility with
existing R packages, is well taken!
On Thursday, Jul 10, 2003, at 12:25 Europe/London, Uwe Ligges wrote:
> Andreas Christmann wrote:
>>> Message: 1
>>> Date: Wed, 9 Jul 2003 10:53:27 +0100
>>> From: David Firth <david.firth at nuffield.oxford.ac.uk>
>>> Subject: [R] packaged datasets in .csv format
>>> To: r-help at stat.math.ethz.ch
>>> <307D34CE-B1F3-11D7-A8D2-0050E4C03977 at nuffield.oxford.ac.uk>
>>> Content-Type: text/plain; charset=US-ASCII; format=flowed
>>> A couple of questions in connection with using .csv format to
>>> include data in a package:
>>> First, the background. The data() function loads data from .csv
>>> ("comma-separated values") files using
>>> read.table(..., header = TRUE, sep = ";")
>>> But ?read.table says
>>> ## To write a CSV file for input to Excel one might use
>>> write.table(x, file = "foo.csv", sep = ",", col.names = NA)
>>> ## and to read this file back into R one needs
>>> read.table("file.csv", header = TRUE, sep = ",", row.names=1)
>>> As a result, .csv files created by write.table() as above are not
>>> read in by data() in the way that might be expected [that is,
>>> expected by someone who had not read help(data)!]
>>> Two questions, then:
>>> -- is there some compelling reason for the use of `sep = ";"' in
>>> place of `sep = ",", row.names=1'?
> Do you really want an answer?
> Today, one reason is compatibility to all the other packages on CRAN.
>> I prefer ";" instead of "," , because in text variables there are
>> often ",".
> That's why text variables can be quoted.
>>> -- if I want to maintain a dataset in .csv format, for use both in R
>>> and in other systems such as Excel, SPSS, etc, what is the best way
>>> to go about it?
> When regularly using that many systems on the same data sets, it might
> be worth using a database system, e.g. MySQL.
> BTW: R *and* Excel *and* (for sure, but I haven't tested) also SPSS
> can read a couple of different ASCII formatted files, so there are
> quite a lot possible formats.
> Uwe Ligges
>> Depends. Perhaps it is best to check it out for the software packages
>> and the versions of the software packages you are using.
>> Andreas Christmann
>>> Any advice would be much appreciated.
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