pandas.api.typing.Rolling.median#

Rolling.median(numeric_only=False, engine=None, engine_kwargs=None)[source]#

Calculate the rolling median.

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

Parameters:
numeric_onlybool, default False

Include only float, int, boolean columns.

enginestr, 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_kwargsdict, 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
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