eland.DataFrame.sum#

DataFrame.sum(numeric_only: Optional[bool] = None) Series#

Return sum for each numeric column

TODO - implement remainder of pandas arguments, currently non-numerics are not supported

Parameters#

numeric_only: {True, False, None} Default is None

Which datatype to be returned - True: Returns all values as float64, NaN/NaT values are removed - None: Returns all values as the same dtype where possible, NaN/NaT are removed - False: Returns all values as the same dtype where possible, NaN/NaT are preserved

Returns#

pandas.Series

sum for each numeric column

See Also#

pandas.DataFrame.sum

Examples#

>>> df = ed.DataFrame('http://localhost:9200', 'flights', columns=["AvgTicketPrice", "Cancelled", "dayOfWeek", "timestamp", "DestCountry"])
>>> df.sum()  
AvgTicketPrice    8.20436e+06
Cancelled                1678
dayOfWeek               37035
dtype: object
>>> df.sum(numeric_only=True)
AvgTicketPrice    8.204365e+06
Cancelled         1.678000e+03
dayOfWeek         3.703500e+04
dtype: float64
>>> df.sum(numeric_only=False)  
AvgTicketPrice    8.20436e+06
Cancelled                1678
dayOfWeek               37035
timestamp                 NaT
DestCountry               NaN
dtype: object