Checking for Duplicate Rows in a Pandas DataFrame

Last update on April 09 2025 12:55:09 (UTC/GMT +8 hours)

4. Checking Duplicate Rows in a DataFrame

Write a Pandas program to check duplicate rows in a DataFrame.

This exercise shows how to check duplicate rows in a DataFrame using duplicated().

Sample Solution :

Code :

import pandas as pd

# Create a sample DataFrame with duplicate rows
df = pd.DataFrame({
    'Name': ['Orville', 'Arturo', 'Ruth', 'Orville'],
    'Age': [25, 30, 22, 25],
    'Salary': [50000, 60000, 70000, 50000]
})

# Check for duplicate rows
duplicates = df.duplicated()

# Output the result
print(duplicates)

Output:

0    False
1    False
2    False
3     True
dtype: bool

Explanation:

• Created a DataFrame with some duplicate rows.
• Used duplicated() to check for duplicate rows.
• Outputted a Boolean Series indicating which rows are duplicates.

For more Practice: Solve these Related Problems:

• Write a Pandas program to check for duplicate rows in a DataFrame and list the indices of the duplicates.
• Write a Pandas program to identify duplicate rows based on a subset of columns and output a summary of duplicates.
• Write a Pandas program to count duplicate rows and visualize the frequency of duplicates per unique row.
• Write a Pandas program to detect duplicate rows and generate a DataFrame that includes an additional column marking duplicate status.

Python-Pandas Code Editor:

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