Return int position of the largest value in the Index. If the maximum is achieved in multiple locations, the first row position is returned. Parameters ---------- axis : None Unused. Parameter needed for compatibility with DataFrame.
(
self, axis: AxisInt | None = None, skipna: bool = True, *args, **kwargs
)
| 7622 | return super().argmin(skipna=skipna) |
| 7623 | |
| 7624 | def argmax( |
| 7625 | self, axis: AxisInt | None = None, skipna: bool = True, *args, **kwargs |
| 7626 | ) -> int: |
| 7627 | """ |
| 7628 | Return int position of the largest value in the Index. |
| 7629 | |
| 7630 | If the maximum is achieved in multiple locations, |
| 7631 | the first row position is returned. |
| 7632 | |
| 7633 | Parameters |
| 7634 | ---------- |
| 7635 | axis : None |
| 7636 | Unused. Parameter needed for compatibility with DataFrame. |
| 7637 | skipna : bool, default True |
| 7638 | Exclude NA/null values. If the entire Series is NA, or if ``skipna=False`` |
| 7639 | and there is an NA value, this method will raise a ``ValueError``. |
| 7640 | *args, **kwargs |
| 7641 | Additional arguments and keywords for compatibility with NumPy. |
| 7642 | |
| 7643 | Returns |
| 7644 | ------- |
| 7645 | int |
| 7646 | Row position of the maximum value. |
| 7647 | |
| 7648 | See Also |
| 7649 | -------- |
| 7650 | Series.argmax : Return position of the maximum value. |
| 7651 | Series.argmin : Return position of the minimum value. |
| 7652 | numpy.ndarray.argmax : Equivalent method for numpy arrays. |
| 7653 | Series.idxmax : Return index label of the maximum values. |
| 7654 | Series.idxmin : Return index label of the minimum values. |
| 7655 | |
| 7656 | Examples |
| 7657 | -------- |
| 7658 | Consider dataset containing cereal calories |
| 7659 | |
| 7660 | >>> idx = pd.Index([100.0, 110.0, 120.0, 110.0]) |
| 7661 | >>> idx |
| 7662 | Index([100.0, 110.0, 120.0, 110.0], dtype='float64') |
| 7663 | |
| 7664 | >>> idx.argmax() |
| 7665 | np.int64(2) |
| 7666 | >>> idx.argmin() |
| 7667 | np.int64(0) |
| 7668 | |
| 7669 | The maximum cereal calories is the third element and |
| 7670 | the minimum cereal calories is the first element, |
| 7671 | since index is zero-indexed. |
| 7672 | """ |
| 7673 | nv.validate_argmax(args, kwargs) |
| 7674 | nv.validate_minmax_axis(axis) |
| 7675 | |
| 7676 | if not self._is_multi and self.hasnans: |
| 7677 | if not skipna: |
| 7678 | raise ValueError("Encountered an NA value with skipna=False") |
| 7679 | elif self._isnan.all(): |
| 7680 | raise ValueError("Encountered all NA values") |
| 7681 | return super().argmax(skipna=skipna) |