pandas.Series.argmax#
- Series.argmax(axis=None, skipna=True, *args, **kwargs)[source]#
Return int position of the largest value in the Series.
If the maximum 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 maximum value.
See also
Series.argmax
Return position of the maximum value.
Series.argmin
Return position of the minimum value.
numpy.ndarray.argmax
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.