Merging DataFrames and Selecting Specific Columns in Pandas

Last update on December 21 2024 07:41:29 (UTC/GMT +8 hours)

Pandas: Custom Function Exercise-20 with Solution

Write a Pandas program that merges DataFrames and select specific columns after merge.

This exercise demonstrates how to merge two DataFrames and then select specific columns from the resulting DataFrame.

Sample Solution :

Code :

import pandas as pd

# Create two sample DataFrames
df1 = pd.DataFrame({
    'ID': [1, 2, 3],
    'Name': ['David', 'Annabel', 'Charlie']
})

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

# Merge the DataFrames on the 'ID' column
merged_df = pd.merge(df1, df2, on='ID')

# Select specific columns from the merged DataFrame
selected_columns_df = merged_df[['Name', 'Salary']]

# Output the result
print(selected_columns_df)

Output:

      Name  Salary
0    David   50000
1  Annabel   60000
2  Charlie   70000

Explanation:

• Created two DataFrames df1 and df2.
• Merged them on the 'ID' column using pd.merge().
• Selected only the 'Name' and 'Salary' columns from the resulting DataFrame.

Python-Pandas Code Editor:

Have another way to solve this solution? Contribute your code (and comments) through Disqus.