[Numpy-discussion] New function `count_unique` to generate contingency tables.

[Benjamin Root]

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 <
warren.weckesser at gmail.com> wrote:

>
>
>
> On Tue, Aug 12, 2014 at 12:51 PM, Eelco Hoogendoorn <
> hoogendoorn.eelco at gmail.com> 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 <joferkington at gmail.com>
>> wrote:
>>
>>>
>>>
>>>
>>> On Tue, Aug 12, 2014 at 11:17 AM, Eelco Hoogendoorn <
>>> hoogendoorn.eelco at gmail.com> 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.
>>>
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>>>
>>
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>>
>
> Update: I renamed the function to `table` in the pull request:
> https://github.com/numpy/numpy/pull/4958
>
>
> Warren
>
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