Write a Pyton program to perform Boolean logical AND, OR, Ex-OR operations for a given series

Boolean logical operations on Pandas Series allow you to perform element-wise AND, OR, and XOR operations using bitwise operators &, |, and ^. These operations are useful for filtering data and creating conditional logic.

Creating a Boolean Series

First, let's create a Pandas Series with boolean values including np.nan ?

import pandas as pd
import numpy as np

# Create a boolean series with True, NaN, and False
series = pd.Series([True, np.nan, False], dtype="bool")
print("Original series:")
print(series)

Original series:
0     True
1     True
2    False
dtype: bool

Boolean AND Operation

The AND operation using & returns True only when both operands are True ?

import pandas as pd
import numpy as np

series = pd.Series([True, np.nan, False], dtype="bool")
series_and = series & True
print("AND operation result:")
print(series_and)

AND operation result:
0     True
1     True
2    False
dtype: bool

Boolean OR Operation

The OR operation using | returns True if at least one operand is True ?

import pandas as pd
import numpy as np

series = pd.Series([True, np.nan, False], dtype="bool")
series_or = series | True
print("OR operation result:")
print(series_or)

OR operation result:
0    True
1    True
2    True
dtype: bool

Boolean XOR Operation

The XOR (exclusive OR) operation using ^ returns True when operands have different boolean values ?

import pandas as pd
import numpy as np

series = pd.Series([True, np.nan, False], dtype="bool")
series_xor = series ^ True
print("XOR operation result:")
print(series_xor)

XOR operation result:
0    False
1    False
2     True
dtype: bool

Complete Example

Here's a complete program demonstrating all three boolean operations ?

import pandas as pd
import numpy as np

# Create boolean series
series = pd.Series([True, np.nan, False], dtype="bool")

# Perform boolean operations
series_and = series & True
series_or = series | True
series_xor = series ^ True

print("AND operation:")
print(series_and)
print("\nOR operation:")
print(series_or)
print("\nXOR operation:")
print(series_xor)

AND operation:
0     True
1     True
2    False
dtype: bool

OR operation:
0    True
1    True
2    True
dtype: bool

XOR operation:
0    False
1    False
2     True
dtype: bool

Key Points

• np.nan values are converted to True when cast to boolean dtype
• Use &, |, and ^ for element-wise boolean operations
• These operations work with scalars or other Series of the same length

Conclusion

Boolean operations on Pandas Series provide powerful tools for data filtering and conditional logic. Use & for AND, | for OR, and ^ for XOR operations on boolean data.