sum(self, *args, engine=None, engine_kwargs=None, **kwargs)
See window.numba_engine
and enhancingperf.numba
for extended documentation and performance considerations for the Numba engine.
For NumPy compatibility and will not have an effect on the result.
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}
For NumPy compatibility and will not have an effect on the result.
Return type is the same as the original object with np.float64
dtype.
Calculate the ewm (exponential weighted moment) sum.
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.
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