Merging DataFrames and applying custom sorting by column in Pandas

Last update on April 09 2025 12:52:08 (UTC/GMT +8 hours)

15. Merge with Custom Sorting

Write a Pandas program to merge DataFrames with custom sorting.

This exercise demonstrates how to merge two DataFrames and sort the result by a specific column.

Sample Solution :

Code :

import pandas as pd
# Create two sample DataFrames
df1 = pd.DataFrame({
    'ID': [1, 2, 3],
    'Name': ['Selena', 'Annabel', 'Caeso']
})

df2 = pd.DataFrame({
    'ID': [2, 3, 1],
    'Age': [30, 22, 25]
})

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

# Sort the result by 'Age' column
sorted_df = merged_df.sort_values(by='Age')

# Output the result
print(sorted_df)

Output:

   ID     Name  Age
2   3    Caeso   22
0   1   Selena   25
1   2  Annabel   30 

Explanation:

• Created two DataFrames df1 and df2.
• Merged them on the 'ID' column using pd.merge().
• Sorted the resulting DataFrame by the 'Age' column using sort_values().

For more Practice: Solve these Related Problems:

• Write a Pandas program to merge two DataFrames and then sort the merged DataFrame based on a custom list of column priorities.
• Write a Pandas program to merge two DataFrames and then apply custom sorting based on a date column in descending order.
• Write a Pandas program to merge two DataFrames and then sort the result by multiple columns with different sort orders.
• Write a Pandas program to merge two DataFrames with custom sorting that first groups by a categorical column then sorts each group by a numeric column.

Python-Pandas Code Editor:

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