Pandas - Detecting duplicate rows in a DataFrame using duplicated()

Last update on May 05 2025 13:05:17 (UTC/GMT +8 hours)

3. Data Cleaning Techniques

Write a Pandas program to detect duplicates using duplicated() method.

In this exercise, you will identify duplicate rows in a DataFrame using the duplicated() method.

Sample Solution :

Code :

import pandas as pd

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

# Detect duplicates in the DataFrame
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 detect which rows are duplicates.
Outputted a Boolean Series indicating whether each row is a duplicate.

For more Practice: Solve these Related Problems:

Write a Pandas program to detect and remove rows with outliers using the IQR method.
Write a Pandas program to normalize a numeric column using Z-score scaling.
Write a Pandas program to apply a function to clean a text column.
Write a Pandas program to convert categorical data into numerical values.

Go to:

Previous: Handling Duplicates in Pandas.
Next: String Manipulation in Pandas.

Python-Pandas Code Editor:

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