Merging DataFrames using join() on Index in Pandas
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.
 
Go to:
Previous: Merge Multiple DataFrames.
  Next: Merge with Indicator.
Python-Pandas Code Editor:
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