R help - Nov 2002 - read.table: colClasses when num. of columns is unknown

Hi,

I am looking for a way to read tables that have general structure of

characterTag num1 num2 ...

i.e. one character column followed by an unknown to the caller (but fixed
throughout the file) number of numeric columns. I wanted to improve the
speed of read.table by using colClasses, but that seemed to require
knowledge of the actual number of columns in the file. For example I tried
colClasses=c("character", rep("numeric", 100)), here 100 is
an upper
boundary on the number of columns, and hoped read.table() would just ignore
the unused entries. But read.table failed and printed an error message
(proving once again that R is a production-strength software).
Is there any way around? Note that my files do have headers so the number of
columns should be known to read.table once it parses the header.

Thanks,
Vadim

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On Wed, 27 Nov 2002, Vadim Ogranovich wrote:
> Hi,
>
> I am looking for a way to read tables that have general structure of
>
> characterTag num1 num2 ...
>
> i.e. one character column followed by an unknown to the caller (but fixed
> throughout the file) number of numeric columns. I wanted to improve the
> speed of read.table by using colClasses, but that seemed to require
> knowledge of the actual number of columns in the file. For example I tried
> colClasses=c("character", rep("numeric", 100)), here
100 is an upper
> boundary on the number of columns, and hoped read.table() would just ignore
> the unused entries. But read.table failed and printed an error message
> (proving once again that R is a production-strength software).
> Is there any way around? Note that my files do have headers so the number
of
> columns should be known to read.table once it parses the header.
So read it yourself with readLines and push the header back.

-- 
Brian D. Ripley,                  ripley at stats.ox.ac.uk
Professor of Applied Statistics,  http://www.stats.ox.ac.uk/~ripley/
University of Oxford,             Tel:  +44 1865 272861 (self)
1 South Parks Road,                     +44 1865 272860 (secr)
Oxford OX1 3TG, UK                Fax:  +44 1865 272595

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