DataFrame.min

DataFrame.min(numeric_only: bool | None = None) → Series

Return the minimum value 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: min value for each numeric column

See Also

:pandas_api_docs:`pandas.DataFrame.min`

Examples

>>> from tests import OPENSEARCH_TEST_CLIENT

>>> df = oml.DataFrame(OPENSEARCH_TEST_CLIENT, 'flights', columns=["AvgTicketPrice", "Cancelled", "dayOfWeek", "timestamp", "DestCountry"])
>>> df.min()  
AvgTicketPrice                100.021
Cancelled                       False
dayOfWeek                           0
timestamp         2018-01-01 00:00:00
dtype: object

>>> df.min(numeric_only=True)
AvgTicketPrice    100.020531
Cancelled           0.000000
dayOfWeek           0.000000
dtype: float64

>>> df.min(numeric_only=False)  
AvgTicketPrice                100.021
Cancelled                       False
dayOfWeek                           0
timestamp         2018-01-01 00:00:00
DestCountry                       NaN
dtype: object