Truth value of a Series is ambiguous. Use a.empty, a.bool(), a.item(), a.any() or a.all()

The truth value of a Series in pandas can be ambiguous, as it can contain multiple values. To check if a Series is empty, you can use the .empty attribute:

import pandas as pd

s = pd.Series([1, 2, 3])
print(s.empty) # False

s = pd.Series([])
print(s.empty) # True

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To check if any of the values in a Series are true, you can use the .any() method:

s = pd.Series([True, False, False])
print(s.any()) # True

s = pd.Series([False, False, False])
print(s.any()) # False

To check if all of the values in a Series are true, you can use the .all() method:

s = pd.Series([True, True, True])
print(s.all()) # True

s = pd.Series([True, False, True])
print(s.all()) # False

To check the single element of a series you can use .item() method:

s = pd.Series([1,2,3])
print(s.item()) # 1

To check the boolean value of a series you can use .bool() method:

s = pd.Series([1,2,3])
print(s.bool()) # True

It is also important to note that a series with at least one non-NaN value will return True while a series containing only NaN will return False.