Merging DataFrames on their Indexes in Pandas

Last update on December 21 2024 07:41:30 (UTC/GMT +8 hours)

Pandas: Custom Function Exercise-7 with Solution

Write a Pandas program to merge two DataFrames on their indexes.

This exercise demonstrates how to merge two DataFrames on their indexes using the left_index and right_index options.

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])

# Merge the DataFrames on their indexes
merged_df = pd.merge(df1, df2, left_index=True, right_index=True)

# Output the result
print(merged_df)

Output:

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

Explanation:

• Created two DataFrames df1 and df2, both with an index column.
• Used pd.merge() with left_index=True and right_index=True to merge on the index.
• The result is a DataFrame that merges rows based on their index values.

Python-Pandas Code Editor:

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