Try read.csv("K:\\MerchantData\\RiskModel\\refund_distribution.csv",header =
TRUE)
--- On Fri, 9/19/08, Ted Byers <[EMAIL PROTECTED]> wrote:
> From: Ted Byers <[EMAIL PROTECTED]>
> Subject: [R] Novice question about getting data into R
> To: r-help@r-project.org
> Received: Friday, September 19, 2008, 1:01 PM
> I found it easy to use R when typing data manually into it.
> Now I need to
> read data from a file, and I get the following errors:
>
> > refdata =
> >
> read.table("K:\\MerchantData\\RiskModel\\refund_distribution.csv",
> header
> > = TRUE)
> Error in scan(file, what, nmax, sep, dec, quote, skip,
> nlines, na.strings,
> :
> line 1 did not have 42 elements
> > refdata =
> >
> read.table("K:\\MerchantData\\RiskModel\\refund_distribution.csv")
> Error in scan(file, what, nmax, sep, dec, quote, skip,
> nlines, na.strings,
> :
> line 2 did not have 42 elements
> >
>
> (I'd tried the first version above because the first
> record has column
> names.)
>
> First, I don't know why R expects 42 elements in a
> record.
> There is one column for a time variable (weeks since a
> given week of samples
> were taken) and one for each week of sampling in the data
> file (Week 18
> through Week 37 inclusive). And there is only 19 rows.
> The samples represented by the columns are independant, and
> the numbers in
> the columns are the fraction of events sampled that result
> in an event of
> another kind in the week since the sample was taken.
>
> The samples are not the same size, and starting with week
> 20, the number of
> values progressively gets smaller since there have been
> fewer than 37 weeks
> since the samples were taken.
>
> I can show you the contents of the data file if you wish.
> It is
> unremarkable, csv, with strings used for column names
> enclosed in double
> quotes.
>
> I don't have to manually separate the samples into
> their own files do I? I
> was hoping to write a function that estimates the density
> function that best
> fits each sample individually, and then iterate of the
> columns, applying
> that function to each in turn.
>
> What is the best way to handle this?
>
> Thanks
>
> Ted
>
>
> --
> View this message in context:
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> Sent from the R help mailing list archive at Nabble.com.
>
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