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One-to-Many and Many-to-Many Joins - Lab

Introduction

In this lab, you'll practice your knowledge of one-to-many and many-to-many relationships!

Objectives

You will be able to:

  • Explain one-to-many and many-to-many joins as well as implications for the size of query results
  • Query data using one-to-many and many-to-many joins

One-to-Many and Many-to-Many Joins

Connect to the Database

# Your code here

Employees and their Office (a One-to-One join)

Return a DataFrame with all of the employees including their first name and last name along with the city and state of the office that they work out of (if they have one). Include all employees and order them by their first name, then their last name.

# Your code here

Customers and their Orders (a One-to-Many join)

Return a DataFrame with all of the customer contacts (first and last names) along with details for each of the customers' order numbers, order dates, and statuses.

# Your code here

Customers and their Payments (another One-to-Many join)

Return a DataFrame with all of the customer contacts (first and last names) along with details for each of the customers' payment amounts and date of payment. Sort these results in descending order by the payment amount.

# Your code here

Orders, Order details, and Product Details (a Many-to-Many Join)

Return a DataFrame with all of the customer contacts (first and last names) along with the product names, quantities, and date ordered for each of the customers and each of their orders. Sort these in descending order by the order date.

Note: This will require joining 4 tables! This can be tricky! Give it a shot, and if you're still stuck, turn to the next section where you'll see how to write subqueries that can make complex queries such as this much simpler!

# Your code here

Summary

In this lab, you practiced your knowledge of one-to-many and many-to-many relationships!

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  • Jupyter Notebook 97.9%
  • Python 2.1%