Hi Fred, 

Pandas has a nice interface to PyTable if you still need it:

http://pandas.sourceforge.net/io.html#hdf5-pytables

However, my intention was just to point you to pandas because it
is really a powerful tool if you need to deal with tabular heterogenic
data. It is also important to notice that there are plans in the numpy 
community to include/port "part" of this package directly in the codebase.
This says a lot about how good it is... 

Best, 
Eraldo 
 
On Tue, Dec 13, 2011 at 9:01 PM, ferreirafm <ferreirafm@lim12.fm.usp.br> wrote:

Hi Eraldo,
Thanks for your suggestion. I was using pytables but give up after known
that some very useful capabilities are sold as a professional package.
However, it still useful to many printing and data manipulation and, also,
it can handle extremely large datasets (which is not my case.).
Regards,
Fred


Eraldo Pomponi wrote:
>
> I would suggest you to have a look at pandas
> (http://pandas.sourceforge.net/)
> . It was
> really helpful for me. It seems well suited for the type of data that you
> are working
> with. It has nice "brodcasting" capabilities to apply numpy functions to a
> set column.
> http://pandas.sourceforge.net/basics.html#descriptive-statistics
> http://pandas.sourceforge.net/basics.html#function-application
>
> Cheers,
> Eraldo
>

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