pandas.DataFrame.idxmin

DataFrame.idxmin(axis=0, skipna=True, numeric_only=False)

Return index of first occurrence of minimum over requested axis.

NA/null values are excluded.

Parameters:

axis{{0 or ‘index’, 1 or ‘columns’}}, default 0

The axis to use. 0 or ‘index’ for row-wise, 1 or ‘columns’ for column-wise.

skipnabool, default True

Exclude NA/null values. If the entire DataFrame is NA, or if skipna=False and there is an NA value, this method will raise a ValueError.

numeric_onlybool, default False

Include only float, int or boolean data.

Added in version 1.5.0.

Returns:

Series

Indexes of minima along the specified axis.

Raises:

ValueError

• If the row/column is empty

See also

Series.idxmin

Return index of the minimum element.

Notes

This method is the DataFrame version of ndarray.argmin.

Examples

Consider a dataset containing food consumption in Argentina.

>>> 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

By default, it returns the index for the minimum value in each column.

>>> df.idxmin()
consumption                Pork
co2_emissions    Wheat Products
dtype: object

To return the index for the minimum value in each row, use axis="columns".

>>> df.idxmin(axis="columns")
Pork                consumption
Wheat Products    co2_emissions
Beef                consumption
dtype: object