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# pandas.api.typing.Rolling.median

Rolling.median(numeric_only=False, engine=None, engine_kwargs=None)

  Calculate the rolling median.

  This is equivalent to applying `numpy.median` over each rolling window.

  Parameters:
    numeric_only bool, default False

      Include only float, int, boolean columns.

    engine str, default None

      - `'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 dict, default None

      - For `'cython'` engine, there are no accepted `engine_kwargs`

      - For `'numba'` engine, the engine can accept `nogil` and `parallel` dictionary keys. The values must either be `True` or `False`.

      The default `engine_kwargs` for the `'numba'` engine is `{'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 and Numba (JIT compilation) for extended documentation and performance considerations for the Numba engine.

  Examples

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

      >>> 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