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

Assume you have a series and the result for Boolean operations,

And operation is: 0 True 1 True 2 False dtype: bool Or operation is: 0 True 1 True 2 True dtype: bool Xor operation is: 0 False 1 False 2 True dtype: bool

## Solution

To solve this, we will follow the below approach.

Define a Series

Create a series with boolean and nan values

Perform boolean True against bitwise & operation to each element in the series defined below,

series_and = pd.Series([True, np.nan, False], dtype="bool") & True

Perform boolean True against bitwise | operation to each element in the series defined below,

series_or = pd.Series([True, np.nan, False], dtype="bool") | True

Perform boolean True against bitwise ^ operation to each element in the series defined below,

series_xor = pd.Series([True, np.nan, False], dtype="bool") ^ True

### Example

Let us see the complete implementation to get a better understanding −

import pandas as pd import numpy as np series_and = pd.Series([True, np.nan, False], dtype="bool") & True print("And operation is: \n",series_and) series_or = pd.Series([True, np.nan, False], dtype="bool") | True print("Or operation is: \n", series_or) series_xor = pd.Series([True, np.nan, False], dtype="bool") ^ True print("Xor operation is: \n", series_xor)

### Output

And operation is: 0 True 1 True 2 False dtype: bool Or operation is: 0 True 1 True 2 True dtype: bool Xor operation is: 0 False 1 False 2 True dtype: bool

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