xorbits.pandas.Series.idxmin#

Series.idxmin(axis: Axis = 0, skipna: bool = True, *args, **kwargs) → Hashable[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.

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

  • *args – Additional arguments and keywords have no effect but might be accepted for compatibility with NumPy.

  • **kwargs – Additional arguments and keywords have no effect but might be accepted for compatibility with NumPy.

Returns

Label of the minimum value.

Return type

Index

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

Warning

This method has not been implemented yet. Xorbits will try to execute it with pandas.

This docstring was copied from pandas.core.series.Series.