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Calculate the {window_method} {aggregation_description}.
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Series or DataFrame
Return type is the same as the original object with ``np.float64`` dtype.
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pandas.Series.{window_method} : Calling {window_method} with Series data.
pandas.DataFrame.{window_method} : Calling {window_method} with DataFrames.
pandas.Series.{agg_method} : Aggregating {agg_method} for Series.
pandas.DataFrame.{agg_method} : Aggregating {agg_method} for DataFrame.
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numeric_only : bool, default False
Include only float, int, boolean columns.
.. versionadded:: 1.5.0
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**kwargs
Keyword arguments to configure the ``SciPy`` weighted window type.
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func : function
Must produce a single value from an ndarray input if ``raw=True``
or a single value from a Series if ``raw=False``. Can also accept a
Numba JIT function with ``engine='numba'`` specified.
raw : bool, default False
* ``False`` : passes each row or column as a Series to the
function.
* ``True`` : the passed function will receive ndarray
objects instead.
If you are just applying a NumPy reduction function this will
achieve much better performance.
engine : str, default None
* ``'cython'`` : Runs rolling apply through C-extensions from cython.
* ``'numba'`` : Runs rolling apply through JIT compiled code from numba.
Only available when ``raw`` is set to ``True``.
* ``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 ``nopython``, ``nogil``
and ``parallel`` dictionary keys. The values must either be ``True`` or
``False``. The default ``engine_kwargs`` for the ``'numba'`` engine is
``{{'nopython': True, 'nogil': False, 'parallel': False}}`` and will be
applied to both the ``func`` and the ``apply`` rolling aggregation.
args : tuple, default None
Positional arguments to be passed into func.
kwargs : dict, default None
Keyword arguments to be passed into func.
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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``
.. versionadded:: {version}.0
engine_kwargs : dict, default None
* 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``. The default ``engine_kwargs`` for the ``'numba'`` engine is
``{{'nopython': True, 'nogil': False, 'parallel': False}}``
.. versionadded:: {version}.0
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