modin.pandas.DataFrame.idxmin

DataFrame.idxmin(axis=0, skipna=True, numeric_only=False)[source] (https://github.com/snowflakedb/snowpark-python/blob/v1.26.0/snowpark-python/src/snowflake/snowpark/modin/plugin/extensions/base_overrides.py#L2270-L2294)

Return index of first occurrence of minimum over requested axis.

Parameters:

  • axis ({0 or 1}, default 0) – The axis to use. 0 for row-wise, 1 for column-wise.

  • skipna (bool, default True) – Exclude NA/null values. If an entire row/column is NA, the result will be NA.

  • numeric_only (bool, default False:) – Include only float, int or boolean data.

Return type:

Series if DataFrame input, Index if Series input

Examples

>>> df = pd.DataFrame({'consumption': [10.51, 103.11, 55.48],
...                     'co2_emissions': [37.2, 19.66, 1712]},
...                   index=['Pork', 'Wheat Products', 'Beef'])
>>> df
                consumption  co2_emissions
Pork                  10.51          37.20
Wheat Products       103.11          19.66
Beef                  55.48        1712.00
>>> df.idxmin()
consumption                Pork
co2_emissions    Wheat Products
dtype: object
>>> df.idxmin(axis=1)
Pork                consumption
Wheat Products    co2_emissions
Beef                consumption
dtype: object
>>> s = pd.Series(data=[1, None, 4, 3, 4],
...               index=['A', 'B', 'C', 'D', 'E'])
>>> s.idxmin()
'A'
>>> s.idxmin(skipna=False)  
nan
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