Python sample code for merge or join data frames using pandas| S-Logix

How to Merge or Join DataFrame in Python Using Pandas

Merging DataFrames

Condition for Merging or Joining DataFrames

Description:
In Pandas, merging or joining DataFrames is a process of combining two or more datasets based on a common column or index.

Merge: Combines DataFrames using one or more common columns or indices.

Join: Combines DataFrames on their indices or on a specified column.

Step-by-Step Process

Import Pandas Library:
Import the necessary Pandas library.
Create DataFrames:
Create sample data using pd.DataFrame().
Merge or Join DataFrames:
Use pd.merge() or df.join() to combine DataFrames.
Specify Merge Keys:
Define the columns or indices to merge on.

Sample Source Code

# Code for Merging DataFrames

import pandas as pd

df1 = pd.DataFrame({
'ID': [1, 2, 3, 4],
'Name': ['Alice', 'Bob', 'Charlie', 'David'],
'Age': [25, 30, 35, 40]
})

df2 = pd.DataFrame({
'ID': [1, 2, 4, 5],
'Salary': [50000, 60000, 70000, 80000],
'Department': ['HR', 'IT', 'Finance', 'Marketing']
})

print("DataFrame 1:")
print(df1)

print("\nDataFrame 2:")
print(df2)

# Merge DataFrames using 'ID' as the common column (Inner Join by default)
merged_inner = pd.merge(df1, df2, on='ID', how='inner')

print("\nInner Merge (Common 'ID' values):")
print(merged_inner)

# Left Join DataFrames using 'ID'
merged_left = pd.merge(df1, df2, on='ID', how='left')

print("\nLeft Merge (All rows from df1):")
print(merged_left)

# Right Join DataFrames using 'ID'
merged_right = pd.merge(df1, df2, on='ID', how='right')

print("\nRight Merge (All rows from df2):")
print(merged_right)

# Outer Join DataFrames using 'ID'
merged_outer = pd.merge(df1, df2, on='ID', how='outer')

print("\nOuter Merge (All rows from both df1 and df2):")
print(merged_outer)

Screenshots

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