The ever-wonderful pylab mode in matplotlib has a table function for plotting a table of text in a plot. If I remember correctly, what would happen is that matplotlib's table() function will simply obliterate the numpy's table function. This isn't a show-stopper, I just wanted to point that out.
Personally, while I wasn't a particular fan of "count_unique" because I wouldn't necessarially think of it when needing a contingency table, I do like that it is verb-ish. "table()", in this sense, is not a verb. That said, I am perfectly fine with it if you are fine with the name collision in pylab mode. On Wed, Aug 13, 2014 at 4:57 PM, Warren Weckesser < [email protected]> wrote: > > > > On Tue, Aug 12, 2014 at 12:51 PM, Eelco Hoogendoorn < > [email protected]> wrote: > >> ah yes, that's also an issue I was trying to deal with. the semantics I >> prefer in these type of operators, is (as a default), to have every array >> be treated as a sequence of keys, so if calling unique(arr_2d), youd get >> unique rows, unless you pass axis=None, in which case the array is >> flattened. >> >> I also agree that the extension you propose here is useful; but ideally, >> with a little more discussion on these subjects we can converge on an >> even more comprehensive overhaul >> >> >> On Tue, Aug 12, 2014 at 6:33 PM, Joe Kington <[email protected]> >> wrote: >> >>> >>> >>> >>> On Tue, Aug 12, 2014 at 11:17 AM, Eelco Hoogendoorn < >>> [email protected]> wrote: >>> >>>> Thanks. Prompted by that stackoverflow question, and similar problems I >>>> had to deal with myself, I started working on a much more general extension >>>> to numpy's functionality in this space. Like you noted, things get a little >>>> panda-y, but I think there is a lot of panda's functionality that could or >>>> should be part of the numpy core, a robust set of grouping operations in >>>> particular. >>>> >>>> see pastebin here: >>>> http://pastebin.com/c5WLWPbp >>>> >>> >>> On a side note, this is related to a pull request of mine from awhile >>> back: https://github.com/numpy/numpy/pull/3584 >>> >>> There was a lot of disagreement on the mailing list about what to call a >>> "unique slices along a given axis" function, so I wound up closing the pull >>> request pending more discussion. >>> >>> At any rate, I think it's a useful thing to have in "base" numpy. >>> >>> _______________________________________________ >>> NumPy-Discussion mailing list >>> [email protected] >>> http://mail.scipy.org/mailman/listinfo/numpy-discussion >>> >>> >> >> _______________________________________________ >> NumPy-Discussion mailing list >> [email protected] >> http://mail.scipy.org/mailman/listinfo/numpy-discussion >> >> > > Update: I renamed the function to `table` in the pull request: > https://github.com/numpy/numpy/pull/4958 > > > Warren > > _______________________________________________ > NumPy-Discussion mailing list > [email protected] > http://mail.scipy.org/mailman/listinfo/numpy-discussion > >
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