pandas.Series.idxmin#

Series.idxmin(axis=0, skipna=True, *args, **kwargs)[source]#

Return the row label of the minimum value.

If multiple values equal the minimum, the first row label with that value is returned.

Parameters

axis{0 or ‘index’}: Unused. Parameter needed for compatibility with DataFrame.
skipnabool, default True: Exclude NA/null values. If the entire Series is NA, the result will be NA.
*args, **kwargs: Additional arguments and keywords have no effect but might be accepted for compatibility with NumPy.

Returns

Index: Label of the minimum value.

Raises

ValueError: If the Series is empty.

See also

numpy.argmin: Return indices of the minimum values along the given axis.
DataFrame.idxmin: Return index of first occurrence of minimum over requested axis.
Series.idxmax: Return index label of the first occurrence of maximum of values.

Notes

This method is the Series version of ndarray.argmin. This method returns the label of the minimum, while ndarray.argmin returns the position. To get the position, use series.values.argmin().

Examples

>>> s = pd.Series(data=[1, None, 4, 1],
...               index=['A', 'B', 'C', 'D'])
>>> s
A    1.0
B    NaN
C    4.0
D    1.0
dtype: float64

>>> s.idxmin()
'A'

If skipna is False and there is an NA value in the data, the function returns nan.

>>> s.idxmin(skipna=False)
nan