Series.
idxmax
Return the row label of the maximum value.
If multiple values equal the maximum, the first row label with that value is returned.
Exclude NA/null values. If the entire Series is NA, the result will be NA.
Label of the maximum value.
If the Series is empty.
See also
Series.idxmin
Return index label of the first occurrence of minimum of values.
Examples
>>> s = ps.Series(data=[1, None, 4, 3, 5], ... index=['A', 'B', 'C', 'D', 'E']) >>> s A 1.0 B NaN C 4.0 D 3.0 E 5.0 dtype: float64
>>> s.idxmax() 'E'
If skipna is False and there is an NA value in the data, the function returns nan.
nan
>>> s.idxmax(skipna=False) nan
In case of multi-index, you get a tuple:
>>> index = pd.MultiIndex.from_arrays([ ... ['a', 'a', 'b', 'b'], ['c', 'd', 'e', 'f']], names=('first', 'second')) >>> s = ps.Series(data=[1, None, 4, 5], index=index) >>> s first second a c 1.0 d NaN b e 4.0 f 5.0 dtype: float64
>>> s.idxmax() ('b', 'f')
>>> s = ps.Series([1, 100, 1, 100, 1, 100], index=[10, 3, 5, 2, 1, 8]) >>> s 10 1 3 100 5 1 2 100 1 1 8 100 dtype: int64
>>> s.idxmax() 3