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.duncan@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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