Try this:
read.table('don.5.clusters.txt', header = TRUE, comment.char = '', quote =
'')
On Tue, Oct 26, 2010 at 1:15 PM, Donald Braman <dbra...@law.gwu.edu> wrote:
> That's one of the things I tried, but which didn't work. I get the
> following
> error when I do that:
>
> Error in read.table(file = "don.5.clusters.txt", header = TRUE,
> comment.char
> = "", :
> more columns than column names
>
> If I remove the hashes by other means, I don't get that error.
>
>
> On Tue, Oct 26, 2010 at 10:49 AM, Duncan Murdoch
> <murdoch.dun...@gmail.com>wrote:
>
> > On 26/10/2010 10:33 AM, Donald Braman wrote:
> >
> >> I'm importing a lot of text tables of data (from Latent Gold) that
> >> includes
> >> hashes in some of the column names ("Cluster#1", "Cluster#2", etc.). Is
> >> there an easy way to strip the offending hashes out before pushing the
> >> text
> >> into a table or data frame? I thought I'd use gsub, e.g., but can't
> >> figure
> >> out how to read in a text file without reading it into a table or data
> >> frame
> >> (which would be ill structured, given the hashes). I could do it in
> >> another
> >> scripting language or shell script, but would like to try to do it in R.
> >>
> >
> > readLines() will read it, but you may not need to do that. Set
> > comment.char="" to turn off the special meaning of # in read.table() and
> > related functions.
> >
> > Duncan
> >
>
>
>
> --
> Donald Braman
> phone: 971-645-0607
> http://www.culturalcognition.net/braman/
> http://ssrn.com/author=286206
> http://www.law.gwu.edu/Faculty/profile.aspx?id=10123
>
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>
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--
Henrique Dallazuanna
Curitiba-Paraná-Brasil
25° 25' 40" S 49° 16' 22" O
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