Advanced Boolean indexing in Pandas DataFrame

Last update on September 06 2025 12:48:25 (UTC/GMT +8 hours)

13. Boolean Indexing: Conditions on 'X' and 'Y'

Write a Pandas program to select rows where column 'X' > 5 and column 'Y' < 5.

Sample Solution :

Python Code :

import pandas as pd

# Create a DataFrame
df = pd.DataFrame({
    'X': [1, 6, 8, 3, 7],
    'Y': [5, 2, 9, 4, 1]
})

# Advanced Boolean indexing
result = df[(df['X'] > 5) & (df['Y'] < 5)]
print(result)

Output:

   X  Y
1  6  2
4  7  1

Explanation:

Import pandas library.
Create a DataFrame.
Apply advanced Boolean indexing to select rows where column 'X' > 5 and column 'Y' < 5.
Print the results.

For more Practice: Solve these Related Problems:

Write a Pandas program to select rows where column 'X' > 5 and column 'Y' < 5 using a combined condition.
Write a Pandas program to filter a DataFrame with multiple conditions on 'X' and 'Y' and then display the resulting subset.
Write a Pandas program to use boolean indexing to extract rows that satisfy conditions on two columns and compute the mean of another column.
Write a Pandas program to combine conditions on 'X' and 'Y' using & operator and then visualize the filtered data.

Go to:

PREV : .loc Slicing Based on Row and Column Labels.
NEXT : .loc Slicing of a MultiIndex DataFrame.

Python-Pandas Code Editor:

Have another way to solve this solution? Contribute your code (and comments) through Disqus.