Hi Alex, 2017-02-22 12:45 GMT+01:00 Alex Rogozhnikov <alex.rogozhni...@yandex.ru>:
> Hi Nathaniel, > > > pandas > > > yup, the idea was to have minimal pandas.DataFrame-like storage (which I > was using for a long time), > but without irritating problems with its row indexing and some other > problems like interaction with matplotlib. > > A dict of arrays? > > > that's what I've started from and implemented, but at some point I decided > that I'm reinventing the wheel and numpy has something already. In > principle, I can ignore this 'column-oriented' storage requirement, but > potentially it may turn out to be quite slow-ish if dtype's size is large. > > Suggestions are welcome. > You may want to try bcolz: https://github.com/Blosc/bcolz bcolz is a columnar storage, basically as you require, but data is compressed by default even when stored in-memory (although you can disable compression if you want to). > > Another strange question: > in general, it is considered that once numpy.array is created, it's shape > not changed. > But if i want to keep the same recarray and change it's dtype and/or > shape, is there a way to do this? > You can change shapes of numpy arrays, but that usually involves copies of the whole container. With bcolz you can change length and add/del columns without copies. If your containers are large, it is better to inform bcolz on its final estimated size. See: http://bcolz.blosc.org/en/latest/opt-tips.html Francesc > > Thanks, > Alex. > > > > 22 февр. 2017 г., в 3:53, Nathaniel Smith <n...@pobox.com> написал(а): > > On Feb 21, 2017 3:24 PM, "Alex Rogozhnikov" <alex.rogozhni...@yandex.ru> > wrote: > > Ah, got it. Thanks, Chris! > I thought recarray can be only one-dimensional (like tables with named > columns). > > Maybe it's better to ask directly what I was looking for: > something that works like a table with named columns (but no labelling for > rows), and keeps data (of different dtypes) in a column-by-column way (and > this is numpy, not pandas). > > Is there such a magic thing? > > > Well, that's what pandas is for... > > A dict of arrays? > > -n > _______________________________________________ > NumPy-Discussion mailing list > NumPy-Discussion@scipy.org > https://mail.scipy.org/mailman/listinfo/numpy-discussion > > > > _______________________________________________ > NumPy-Discussion mailing list > NumPy-Discussion@scipy.org > https://mail.scipy.org/mailman/listinfo/numpy-discussion > > -- Francesc Alted
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