[Numpy-discussion] adding a cut function to numpy

Tony Yu tsyu80@gmail....
Mon Apr 16 16:51:24 CDT 2012

```On Mon, Apr 16, 2012 at 5:27 PM, Skipper Seabold <jsseabold@gmail.com>wrote:

> Hi,
>
> I have a pull request here [1] to add a cut function similar to R's
> [2]. It seems there are often requests for similar functionality. It's
> something I'm making use of for my own work and would like to use in
> statstmodels and in generating instances of pandas' Factor class, but
> is this generally something people would find useful to warrant its
> inclusion in numpy? It will be even more useful I think with an enum
> dtype in numpy.
>
> If you aren't familiar with cut, here's a potential use case. Going
> from a continuous to a categorical variable.
>
> Given a continuous variable
>
> [~/]
> [8]: age = np.random.randint(15,70, size=100)
>
> [~/]
> [9]: age
> [9]:
> array([58, 32, 20, 25, 34, 69, 52, 27, 20, 23, 51, 61, 39, 54, 39, 44, 27,
>       17, 29, 18, 66, 25, 44, 21, 54, 32, 50, 60, 25, 41, 68, 25, 42, 69,
>       50, 69, 24, 69, 69, 48, 30, 20, 18, 15, 50, 48, 44, 27, 57, 52, 40,
>       27, 58, 45, 44, 32, 54, 19, 36, 32, 55, 17, 55, 15, 19, 29, 22, 25,
>       36, 44, 29, 53, 37, 31, 51, 39, 21, 66, 25, 26, 20, 17, 41, 50, 27,
>       23, 62, 69, 65, 34, 38, 61, 39, 34, 38, 35, 18, 36, 29, 26])
>
> Give me a variable where people are in age groups (lower bound is not
> inclusive)
>
> [~/]
> [10]: groups = [14, 25, 35, 45, 55, 70]
>
> [~/]
> [11]: age_cat = np.cut(age, groups)
>
> [~/]
> [12]: age_cat
> [12]:
> array([5, 2, 1, 1, 2, 5, 4, 2, 1, 1, 4, 5, 3, 4, 3, 3, 2, 1, 2, 1, 5, 1, 3,
>       1, 4, 2, 4, 5, 1, 3, 5, 1, 3, 5, 4, 5, 1, 5, 5, 4, 2, 1, 1, 1, 4, 4,
>       3, 2, 5, 4, 3, 2, 5, 3, 3, 2, 4, 1, 3, 2, 4, 1, 4, 1, 1, 2, 1, 1, 3,
>       3, 2, 4, 3, 2, 4, 3, 1, 5, 1, 2, 1, 1, 3, 4, 2, 1, 5, 5, 5, 2, 3, 5,
>       3, 2, 3, 2, 1, 3, 2, 2])
>
> Skipper
>
> [1] https://github.com/numpy/numpy/pull/248
> [2] http://stat.ethz.ch/R-manual/R-devel/library/base/html/cut.html
>

Is this the same as `np.searchsorted` (with reversed arguments)?

In [292]: np.searchsorted(groups, age)
Out[292]:
array([5, 2, 1, 1, 2, 5, 4, 2, 1, 1, 4, 5, 3, 4, 3, 3, 2, 1, 2, 1, 5, 1, 3,
1, 4, 2, 4, 5, 1, 3, 5, 1, 3, 5, 4, 5, 1, 5, 5, 4, 2, 1, 1, 1, 4, 4,
3, 2, 5, 4, 3, 2, 5, 3, 3, 2, 4, 1, 3, 2, 4, 1, 4, 1, 1, 2, 1, 1, 3,
3, 2, 4, 3, 2, 4, 3, 1, 5, 1, 2, 1, 1, 3, 4, 2, 1, 5, 5, 5, 2, 3, 5,
3, 2, 3, 2, 1, 3, 2, 2])
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