DataFrame.sum

DataFrame.sum(numeric_only: bool | None = 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_api_docs:`pandas.DataFrame.sum`

Examples

>>> from tests import OPENSEARCH_TEST_CLIENT

>>> df = oml.DataFrame(OPENSEARCH_TEST_CLIENT, '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