numpy maximum reduce error for pandas series and int

np.maximum.reduce(lst) has different behavior from functools.reduce(np.maximum, lst) and also different behavior from np.maximum itself, when one of the elements in the list is a number (e.g. int) instead of an array/pandas Series.

np.maximum.reduce

on one hand,

import pandas as pd
import numpy as np

df = pd.DataFrame({'a': [1, 3, 2]})

np.maximum.reduce([df['a'], 2])

The last line gives the following error:

ValueError: The truth value of a Series is ambiguous. Use a.empty, a.bool(), a.item(), a.any() or a.all().

np.maximum

on the other hand,

np.maximum(df['a'], 2)

yields the expected output

0    2
1    3
2    2
Name: a, dtype: int64

reduce(np.maximum)

on a third hand,

reduce(np.maximum, [df['a'], 2])

also yields the expected output

0    2
1    3
2    2
Name: a, dtype: int64

Versions used

pandas version: 1.2.5
numpy version: 1.19.5
python: 3.7.9