Boolean indexing in Pandas DataFrame

Last update on April 09 2025 12:51:38 (UTC/GMT +8 hours)

8. Boolean Indexing: Column 'x' > 6

Write a Pandas program to use Boolean indexing to select rows where column 'x' > 6.

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]
})

# Boolean indexing to select rows
result = df[df['X'] > 6]
print(result)

Output:

   X  Y
2  8  9
4  7  1

Explanation:

• Import pandas library.
• Create a DataFrame.
• Apply Boolean indexing to select rows where column 'X' > 6.
• Print the results.

For more Practice: Solve these Related Problems:

• Write a Pandas program to filter rows where column 'x' is greater than 6 using boolean indexing and display the result.
• Write a Pandas program to apply a boolean condition on column 'x' to extract rows with values exceeding 6 and then sort by another column.
• Write a Pandas program to create a boolean mask for rows where 'x' > 6 and use it to compute summary statistics on the filtered DataFrame.
• Write a Pandas program to use boolean indexing to select rows where 'x' is greater than 6 and then plot these rows against another variable.

Python-Pandas Code Editor:

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