# dask.dataframe.api.Rolling.median

#### Rolling.median(\*args, \*\*kwargs)

Calculate the rolling median.

This docstring was copied from pandas.api.typing.Rolling.median.

Some inconsistencies with the Dask version may exist.

* **Parameters:**
  **numeric_only**
  : Include only float, int, boolean columns.

  **engine**
  : * `'cython'` : Runs the operation through C-extensions from cython.
    * `'numba'` : Runs the operation through JIT compiled code from numba.
    * `None` : Defaults to `'cython'` or
      globally setting `compute.use_numba`

  **engine_kwargs**
  : * For `'cython'` engine, there are no accepted `engine_kwargs`
    * For `'numba'` engine, the engine can accept `nopython`, `nogil`
      and `parallel` dictionary keys. The values must either be `True` or
      `False`.
    <br/>
    The default `engine_kwargs` for the `'numba'` engine is
    `{'nopython': True, 'nogil': False, 'parallel': False}`.
* **Returns:**
  Series or DataFrame
  : Return type is the same as the original object with `np.float64` dtype.

#### SEE ALSO
`Series.rolling`
: Calling rolling with Series data.

`DataFrame.rolling`
: Calling rolling with DataFrames.

`Series.median`
: Aggregating median for Series.

`DataFrame.median`
: Aggregating median for DataFrame.

### Notes

See [Numba engine](https://pandas.pydata.org/pandas-docs/stable/user_guide/window.html#window-numba-engine) and [Numba (JIT compilation)](https://pandas.pydata.org/pandas-docs/stable/user_guide/enhancingperf.html#enhancingperf-numba)
for extended documentation and performance considerations
for the Numba engine.

### Examples

Compute the rolling median of a series with a window size of 3.

```pycon
>>> s = pd.Series([0, 1, 2, 3, 4])
>>> s.rolling(3).median()
0    NaN
1    NaN
2    1.0
3    2.0
4    3.0
dtype: float64
```

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