pandas.Index.argmin#
- Index.argmin(axis=None, skipna=True, *args, **kwargs)[source]#
Return int position of the smallest value in the Series.
If the minimum is achieved in multiple locations, the first row position is returned.
- Parameters
- axis{None}
Unused. Parameter needed for compatibility with DataFrame.
- skipnabool, default True
Exclude NA/null values when showing the result.
- *args, **kwargs
Additional arguments and keywords for compatibility with NumPy.
- Returns
- int
Row position of the minimum value.
See also
Series.argmin
Return position of the minimum value.
Series.argmax
Return position of the maximum value.
numpy.ndarray.argmin
Equivalent method for numpy arrays.
Series.idxmax
Return index label of the maximum values.
Series.idxmin
Return index label of the minimum values.
Examples
Consider dataset containing cereal calories
>>> s = pd.Series({'Corn Flakes': 100.0, 'Almond Delight': 110.0, ... 'Cinnamon Toast Crunch': 120.0, 'Cocoa Puff': 110.0}) >>> s Corn Flakes 100.0 Almond Delight 110.0 Cinnamon Toast Crunch 120.0 Cocoa Puff 110.0 dtype: float64
>>> s.argmax() 2 >>> s.argmin() 0
The maximum cereal calories is the third element and the minimum cereal calories is the first element, since series is zero-indexed.