[Rd] Incorrect Import by Data for CSV File

[peter dalgaard]

> On 25 Sep 2017, at 14:27 , Prof Brian Ripley <ripley at stats.ox.ac.uk> wrote:
> 
> On 25/09/2017 08:00, Dario Strbenac wrote:
>> Good day,
>> The data function can import a variety of file formats, one of them being C.S.V. 
> 
> That isn't its documented purpose.  It was the original way for packages to provide datasets as needed (before lazy data was added).
> 
> Problematically, all of the table columns are collapsed into a single data frame column. This occurs because "files ending .csv or .CSV are read using read.table(..., header = TRUE, sep = ";", as.is=FALSE)". I suggest that the semi-colon used as the column separator be changed to a comma.
> 
> We suggest you read the documentation ... the (non-English-locales) version with a semicolon separator is one of four documented formats, and the English-language one is not.  Even if it were desirable it would not be possible to make a backwards-incompatible change after almost 20 years.
> 
> It really isn't clear why anyone would want to use anything other than the second option (.rda) for data() unless other manipulations are needed (e.g. to attach a package).  But that option was not part of the original implementation.
> 

It can be handy to have raw ascii data included in a package for people to see, but then you can use the .R mechanism to read the data. It is done for a couple of cases in the ISwR package, see e.g. the stroke.R and stroke.csv pair. This also allows you to fix up other things that you have no chcance of specifying directly in the file:

stroke <-  read.csv2("stroke.csv", na.strings=".")
names(stroke) <- tolower(names(stroke))
stroke <-  within(stroke,{
    sex <- factor(sex,levels=0:1,labels=c("Female","Male"))
    dgn <- factor(dgn)
    coma <- factor(coma, levels=0:1, labels=c("No","Yes"))
    minf <- factor(minf, levels=0:1, labels=c("No","Yes"))
    diab <- factor(diab, levels=0:1, labels=c("No","Yes"))
    han <- factor(han, levels=0:1, labels=c("No","Yes"))
    died <- as.Date(died, format="%d.%m.%Y")
    end <- pmin(died, as.Date("1996-01-01"), na.rm=TRUE)
    dstr <- as.Date(dstr,format="%d.%m.%Y")
    obsmonths <- as.numeric(end-dstr, "days")/30.6
    obsmonths[obsmonths==0] <- 0.1
    dead <- !is.na(died) & died < as.Date("1996-01-01")
    died[!dead] <- NA
    rm(end)
})


-pd


> -- 
> Brian D. Ripley,                  ripley at stats.ox.ac.uk
> Emeritus Professor of Applied Statistics, University of Oxford
> 
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-- 
Peter Dalgaard, Professor,
Center for Statistics, Copenhagen Business School
Solbjerg Plads 3, 2000 Frederiksberg, Denmark
Phone: (+45)38153501
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Email: pd.mes at cbs.dk  Priv: PDalgd at gmail.com