Merging DataFrames using join() on Index in Pandas

Last update on April 09 2025 12:52:10 (UTC/GMT +8 hours)

11. Join on Index

Write a Pandas program to merge DataFrames using join() on Index.

In this exercise, we have used join() to merge two DataFrames on their index, which is a more concise alternative to merge() for index-based joining.

Sample Solution :

Code :

import pandas as pd

# Create two sample DataFrames with indexes
df1 = pd.DataFrame({
    'Name': ['Selena', 'Annabel', 'Caeso'],
    'Age': [25, 30, 22]
}, index=[1, 2, 3])

df2 = pd.DataFrame({
    'Salary': [50000, 60000, 70000]
}, index=[1, 2, 3])

# Perform a join on the indexes
joined_df = df1.join(df2)

# Output the result
print(joined_df)

Output:

      Name  Age  Salary
1   Selena   25   50000
2  Annabel   30   60000
3    Caeso   22   70000        

Explanation:

• Created two DataFrames df1 and df2 with a shared index.
• Used the join() method to merge based on the index.
• The result merges both DataFrames based on their index.

For more Practice: Solve these Related Problems:

• Write a Pandas program to join two DataFrames using join() on their indexes and then sort the result by a specified column.
• Write a Pandas program to join DataFrames using join() on indexes and fill missing values with zeros.
• Write a Pandas program to join two DataFrames using join() on indexes and then compute the difference between similarly named columns.
• Write a Pandas program to join two DataFrames using join() on their indexes and then reindex the resulting DataFrame to a given range.

Python-Pandas Code Editor:

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