You can pass the read data directly to R. Probably the best way to
do this is to construct a python list containing one vector per
column. Call as.data.frame() on the list, and then proceed.
For example:
from rpy import *
set_default_mode(NO_CONVERSION)
data = [ [ 1, 2, 3], ["A","B","C"], [1.08, 1.334, 3.12] ]
df = r.as_data_frame(data)
r.print_(df)
-Greg
On Apr 1, 2008, at 5:40AM , Peter wrote:
> Hi Lukasz,
>
> If your data has all the elements of the same type, then you could try
> loading it into a NumPy matrix or array, and passing that to R.
>
> I personally would pass the filename to R, and use R's read.table()
> command to load it in R. You can work out the exact options you need
> for read.table() by experimenting in an R session, and then try the
> same from rpy. This assumes you do not need the actual data in python
> too.
>
> I don't know if you can pass the file pointer (handle) from python to
> R. I would be interested to know if this is possible.
>
> Peter
>
> On Tue, Apr 1, 2008 at 2:51 AM, Lukasz Szybalski
> <[EMAIL PROTECTED]> wrote:
>> Hello,
>> I am trying to read a 100mb+ csv file in python.
>> f=csv.DictReader(open(filename))
>> or
>> f=csv.Reader(open(filename))
>>
>> When I read it in I would like to pass it to R to do some work on
>> it.
>> How would I do that?
>>
>> Do I pass the file pointer or read file?
>> I think for speed purposes I would prefer passing read file.
>>
>> Lucas
>
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