argmax(self, axis=None, skipna: 'bool' = True, *args, **kwargs) -> 'int'
If the maximum is achieved in multiple locations, the first row position is returned.
Dummy argument for consistency with Series.
Exclude NA/null values when showing the result.
Additional arguments and keywords for compatibility with NumPy.
Row position of the maximum value.
Return int position of the largest value in the Series.
Series.argmax
Return position of the maximum value.
Series.argmin
Return position of the minimum value.
Series.idxmax
Return index label of the maximum values.
Series.idxmin
Return index label of the minimum values.
numpy.ndarray.argmax
Equivalent method for numpy arrays.
Consider dataset containing cereal calories
This example is valid syntax, but we were not able to check execution>>> s = pd.Series({'Corn Flakes': 100.0, 'Almond Delight': 110.0,This example is valid syntax, but we were not able to check execution
... '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() 2This example is valid syntax, but we were not able to check execution
>>> 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.
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