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free online bettingWed, 22 Feb 2017 03:46:30 -0800

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.

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?

Thanks, 
Alex.



> 22 ֧ӧ. 2017 .,  3:53, Nathaniel Smith <n...@pobox.com> ߧѧڧѧ():
> 
> On Feb 21, 2017 3:24 PM, "Alex Rogozhnikov" <alex.rogozhni...@yandex.ru 
> <mailto: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
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