<html><head><meta http-equiv="Content-Type" content="text/html charset=utf-8"></head><body style="word-wrap: break-word; -webkit-nbsp-mode: space; -webkit-line-break: after-white-space;" class=""><div class="">Hi Nathaniel, </div><div class=""><br class=""></div><div class=""><br class=""></div><div class=""><blockquote type="cite" class=""><div dir="auto" class=""><div dir="auto" class="">pandas</div></div></blockquote><br class=""></div><div class="">yup, the idea was to have minimal pandas.DataFrame-like storage (which I was using for a long time), </div><div class="">but without irritating problems with its row indexing and some other problems like interaction with matplotlib.</div><div class=""><br class=""></div><div class=""><div class=""><blockquote type="cite" class=""><div dir="auto" class=""><div dir="auto" class="">A dict of arrays?</div></div></blockquote></div><div class=""><br class=""></div><div class="">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.</div></div><div class=""><br class=""></div><div class="">Suggestions are welcome.</div><div class=""><br class=""></div><div class="">Another strange question:</div><div class="">in general, it is considered that once numpy.array is created, it's shape not changed. </div><div class="">But if i want to keep the same recarray and change it's dtype and/or shape, is there a way to do this?</div><div class=""><br class=""></div><div class="">Thanks, </div><div class="">Alex.</div><div class=""><br class=""></div><div class=""><br class=""></div><div class=""><br class=""></div><div><blockquote type="cite" class=""><div class="">22 февр. 2017 г., в 3:53, Nathaniel Smith <<a href="mailto:njs@pobox.com" class="">njs@pobox.com</a>> написал(а):</div><br class="Apple-interchange-newline"><div class=""><div dir="auto" class=""><div class=""><div class="gmail_extra"><div class="gmail_quote">On Feb 21, 2017 3:24 PM, "Alex Rogozhnikov" <<a href="mailto:alex.rogozhnikov@yandex.ru" class="">alex.rogozhnikov@yandex.ru</a>> wrote:<br type="attribution" class=""><blockquote class="quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex"><div style="word-wrap:break-word" class=""><div class="">Ah, got it. Thanks, Chris!</div><div class="">I thought recarray can be only one-dimensional (like tables with named columns).</div><div class=""><br class=""></div><div class="">Maybe it's better to ask directly what I was looking for: </div><div class="">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). </div><div class=""><br class=""></div><div class="">Is there such a magic thing?</div></div></blockquote></div></div></div><div dir="auto" class=""><br class=""></div><div dir="auto" class="">Well, that's what pandas is for...</div><div dir="auto" class=""><br class=""></div><div dir="auto" class="">A dict of arrays?</div><div dir="auto" class=""><br class=""></div><div dir="auto" class="">-n</div></div>
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