# otp.qcut

### qcut(column, q, labels=None)

Quantile-based discretization function (mimics [pandas.qcut](https://pandas.pydata.org/docs/reference/api/pandas.qcut.html)).

* **Parameters:**
  * **column** ([`Column`](../operation/root.md#onetick.py.Column)) -- Column with numeric data used to build bins.
  * **q** ([*int*](https://docs.python.org/3/library/functions.html#int) *or* *List* *[*[*float*](https://docs.python.org/3/library/functions.html#float) *]*) -- 

    When List[float] - array of quantiles, e.g. [0, .25, .5, .75, 1.] for quartiles.

    When int - Number of quantiles. 10 for deciles, 4 for quartiles, etc.
  * **labels** (*List* *[*[*str*](https://docs.python.org/3/library/stdtypes.html#str) *]*) -- Labels used to name resulting bins.
    If not set, bins are numeric intervals like (5.0000000000, 7.5000000000].
* **Return type:**
  object that can be set to [`Column`](../operation/root.md#onetick.py.Column) via [`__setitem__()`](../source/__setitem__.md#onetick.py.Source.__setitem__)

### Examples

```pycon
>>> data = otp.Ticks({"X": [10, 3, 5, 6, 7, 1]})
>>> data['bin'] = otp.qcut(data['X'], q=3, labels=['a', 'b', 'c'])
>>> otp.run(data)[['X', 'bin']]
    X bin
0  10   c
1   3   a
2   5   b
3   6   b
4   7   c
5   1   a
```