pandas.Series.idxmax

Series.idxmax(self, axis=0, skipna=True, *args, **kwargs)

Return the row label of the maximum value.

If multiple values equal the maximum, the first row label with that value is returned.

Parameters

axisint, default 0

For compatibility with DataFrame.idxmax. Redundant for application on Series.

skipnabool, default True

Exclude NA/null values. If the entire Series is NA, the result will be NA.

*args, **kwargs

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

Returns

Index

Label of the maximum value.

Raises

ValueError

If the Series is empty.

See also

numpy.argmax

Return indices of the maximum values along the given axis.

DataFrame.idxmax

Return index of first occurrence of maximum over requested axis.

Series.idxmin

Return index label of the first occurrence of minimum of values.

Notes

This method is the Series version of ndarray.argmax. This method returns the label of the maximum, while ndarray.argmax returns the position. To get the position, use series.values.argmax().

Examples

>>> s = pd.Series(data=[1, None, 4, 3, 4],
...               index=['A', 'B', 'C', 'D', 'E'])
>>> s
A    1.0
B    NaN
C    4.0
D    3.0
E    4.0
dtype: float64

>>> s.idxmax()
'C'

If skipna is False and there is an NA value in the data, the function returns nan.

>>> s.idxmax(skipna=False)
nan

pandas.Series.hist pandas.Series.idxmin