pandas 1.4.2

NotesParametersReturns
sum(self, *args, engine=None, engine_kwargs=None, **kwargs)

Notes

See window.numba_engine and enhancingperf.numba for extended documentation and performance considerations for the Numba engine.

Parameters

*args :

For NumPy compatibility and will not have an effect on the result.

engine : str, default None
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
**kwargs :

For NumPy compatibility and will not have an effect on the result.

Returns

Series or DataFrame

Return type is the same as the original object with np.float64 dtype.

Calculate the ewm (exponential weighted moment) sum.

See Also

pandas.DataFrame.ewm

Calling ewm with DataFrames.

pandas.DataFrame.sum

Aggregating sum for DataFrame.

pandas.Series.ewm

Calling ewm with Series data.

pandas.Series.sum

Aggregating sum for Series.

Examples

See :

Local connectivity graph

Hover to see nodes names; edges to Self not shown, Caped at 50 nodes.

Using a canvas is more power efficient and can get hundred of nodes ; but does not allow hyperlinks; , arrows or text (beyond on hover)

SVG is more flexible but power hungry; and does not scale well to 50 + nodes.

All aboves nodes referred to, (or are referred from) current nodes; Edges from Self to other have been omitted (or all nodes would be connected to the central node "self" which is not useful). Nodes are colored by the library they belong to, and scaled with the number of references pointing them


File: /pandas/core/window/ewm.py#564
type: <class 'function'>
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