Pandas Series: idxmax() function

Last update on September 15 2022 12:56:33 (UTC/GMT +8 hours)

Get the row label of the maximum value in Pandas series

The idxmax() function is used to get the row label of the maximum value.

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

Syntax:

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

Parameters:

Name	Description	Type/Default Value	Required / Optional
skipna	Exclude NA/null values. If the entire Series is NA, the result will be NA.	bool Default Value: True	Required
axis	For compatibility with DataFrame.idxmax. Redundant for application on Series.	bool Default Value: 0	Required
args, *kwargs	Additional keywords have no effect but might be accepted for compatibility with NumPy.		Required

Returns: Index
Label of the maximum value.

Raises: ValueError
If the Series is empty.

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().

Example:

Python-Pandas Code:

import numpy as np
import pandas as pd
s = pd.Series(data=[2, None, 5, 4, 5],
              index=['P', 'Q', 'R', 'S', 'T'])
s

Output:

P    2.0
Q    NaN
R    5.0
S    4.0
T    5.0
dtype: float64

Python-Pandas Code:

import numpy as np
import pandas as pd
s = pd.Series(data=[2, None, 5, 4, 5],
              index=['P', 'Q', 'R', 'S', 'T'])
s.idxmax()

Output:

'R'

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

Python-Pandas Code:

import numpy as np
import pandas as pd
s = pd.Series(data=[2, None, 5, 4, 5],
              index=['P', 'Q', 'R', 'S', 'T'])
s.idxmax(skipna=False)

Output:

nan

Previous: Get the first n rows in Pandas series
Next: Row label of the minimum value in Pandas series