Outer join in Data Analysis Python - Mini Project: Build & Apply

Outer Join with Python Data Analysis

📖 Scenario: You work in a small company that keeps customer and order information in separate tables. You want to combine these tables to see all customers and their orders, including customers who have not placed any orders yet.

🎯 Goal: Build a Python script that performs an outer join on two data tables (dictionaries) to combine customer and order data, showing all customers and their orders, including those without orders.

📋 What You'll Learn

Create two dictionaries: customers and orders with given data

Create a list all_customer_ids that contains all unique customer IDs from both dictionaries

Use a for loop to perform an outer join by iterating over all_customer_ids

Create a final dictionary customer_orders that maps each customer ID to their order or None if no order exists

💡 Why This Matters

🌍 Real World

Combining customer and order data is common in business to understand sales and customer activity.

💼 Career

Data analysts and database professionals often perform joins to merge data from different sources for reporting and analysis.

1

Create customer and order data dictionaries

Create a dictionary called customers with these exact entries: 1: 'Alice', 2: 'Bob', 3: 'Charlie'. Also create a dictionary called orders with these exact entries: 2: 'Order1001', 3: 'Order1002', 4: 'Order1003'.

Data Analysis Python

# Create the customers and orders dictionaries
# Your code here

Hint

Use curly braces {} to create dictionaries with the exact keys and values given.

2

Create a list of all unique customer IDs

Create a list called all_customer_ids that contains all unique keys from both customers and orders dictionaries combined. Use the set() function and union() method to combine keys.

Data Analysis Python

customers = {1: 'Alice', 2: 'Bob', 3: 'Charlie'}
orders = {2: 'Order1001', 3: 'Order1002', 4: 'Order1003'}
# Create all_customer_ids list with unique keys from both dictionaries
# Your code here

Hint

Use set(customers.keys()) and set(orders.keys()) to get keys, then combine with union().

3

Perform the outer join using a for loop

Create an empty dictionary called customer_orders. Use a for loop with variable customer_id to iterate over all_customer_ids. Inside the loop, add an entry to customer_orders with key customer_id and value as a tuple of the customer name from customers (or None if missing) and the order from orders (or None if missing). Use the get() method for safe access.

Data Analysis Python

customers = {1: 'Alice', 2: 'Bob', 3: 'Charlie'}
orders = {2: 'Order1001', 3: 'Order1002', 4: 'Order1003'}
all_customer_ids = list(set(customers.keys()).union(orders.keys()))
# Create customer_orders dictionary and fill it with outer join results
# Your code here

Hint

Use dict.get(key) to get values safely, returning None if the key is missing.

4

Complete the outer join dictionary

Add a final line that assigns the customer_orders dictionary to a variable called final_result. This completes the data structure for further use.

Data Analysis Python

customers = {1: 'Alice', 2: 'Bob', 3: 'Charlie'}
orders = {2: 'Order1001', 3: 'Order1002', 4: 'Order1003'}
all_customer_ids = list(set(customers.keys()).union(orders.keys()))
customer_orders = {}
for customer_id in all_customer_ids:
    customer_orders[customer_id] = (customers.get(customer_id), orders.get(customer_id))
# Assign customer_orders to final_result
# Your code here

Hint

Simply assign the dictionary customer_orders to final_result.