Hello,
is it possible to do something like
DATA - read.table(file=blabla.dat,subset=(sex==male)),
i.e. make R read only a subset of a csv file ?
I think it would be useful in case of very big datasets,
but I can't find such a feature.
Thanks for an answer,
David Vonka
You can use pipe with read.table as in:
http://tolstoy.newcastle.edu.au/R/help/06/02/20379.html
Also note skip= and nrows= arguments to read.table.
On 7/12/06, David Vonka [EMAIL PROTECTED] wrote:
Hello,
is it possible to do something like
DATA -
It's not so straightforward as that, but you could construct something
with readLines().
-roger
On 7/12/06, David Vonka [EMAIL PROTECTED] wrote:
Hello,
is it possible to do something like
DATA - read.table(file=blabla.dat,subset=(sex==male)),
i.e. make R read only a subset of a csv file ?
On Wed, 12 Jul 2006, David Vonka wrote:
Hello,
is it possible to do something like
DATA - read.table(file=blabla.dat,subset=(sex==male)),
i.e. make R read only a subset of a csv file ?
I think it would be useful in case of very big datasets,
but I can't find such a feature.
No. It
It's possible and straightforward (just don't use R). IMHO the GNU
Core Utilities
http://www.gnu.org/software/coreutils/
plus a few other tools such as sed, awk, grep etc are much more
appropriate than R for processing massive text files. (Get a good book
about UNIX shell scripting. On Windows you
You could also use Perl/Python/Ruby to pipe the data to R, e.g. msci -
read.table(pipe(python /steve/python/msciintl.py),sep=,,header=T,
as.is=T)
This is a very reasonable way to exploit the data munging capabilities of
the agile languages. Of course, better still is to query the data into R
from
