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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