Why aggregation operators matter in MongoDB - See It in Action

Why aggregation operators matter

📖 Scenario: You work at a small bookstore that keeps track of sales in a MongoDB database. You want to learn how to use aggregation operators to find useful information like total sales and average price per book.

🎯 Goal: Build a MongoDB aggregation pipeline step-by-step to calculate the total number of books sold and the average price of books sold.

📋 What You'll Learn

Create a collection called sales with documents containing book, price, and quantity fields.

Add a variable to hold the aggregation pipeline stages.

Use the $group aggregation operator to calculate total quantity sold and average price.

Complete the aggregation pipeline and assign it to a variable.

💡 Why This Matters

🌍 Real World

Aggregation operators help summarize and analyze data in databases, like calculating total sales or average prices in a bookstore.

💼 Career

Database developers and analysts use aggregation pipelines to generate reports and insights from large data collections efficiently.

1

DATA SETUP: Create the sales collection with sample documents

Create a variable called sales that is a list of three documents with these exact entries: { book: "MongoDB Basics", price: 20, quantity: 5 }, { book: "Advanced MongoDB", price: 35, quantity: 3 }, and { book: "MongoDB Aggregation", price: 25, quantity: 7 }.

MongoDB

# Create the sales list with three documents
# Your code here

Need a hint?

Use a Python list of dictionaries to represent the sales documents.

2

CONFIGURATION: Define the aggregation pipeline variable

Create a variable called pipeline and set it to an empty list [] to hold the aggregation stages.

MongoDB

sales = [
    {"book": "MongoDB Basics", "price": 20, "quantity": 5},
    {"book": "Advanced MongoDB", "price": 35, "quantity": 3},
    {"book": "MongoDB Aggregation", "price": 25, "quantity": 7}
]
# Create an empty pipeline list
# Your code here

Need a hint?

Just create an empty list called pipeline.

3

CORE LOGIC: Add a $group stage to calculate total quantity and average price

Add a dictionary to the pipeline list with a $group stage that groups all documents together (_id: null) and calculates totalQuantity as the sum of quantity and averagePrice as the average of price.

MongoDB

sales = [
    {"book": "MongoDB Basics", "price": 20, "quantity": 5},
    {"book": "Advanced MongoDB", "price": 35, "quantity": 3},
    {"book": "MongoDB Aggregation", "price": 25, "quantity": 7}
]
pipeline = []
# Add a $group stage to pipeline
# Your code here

Need a hint?

Use $group with _id: null to aggregate all documents together.

4

COMPLETION: Assign the aggregation pipeline to a variable called aggregation_pipeline

Create a variable called aggregation_pipeline and assign it the value of the pipeline list.

MongoDB

sales = [
    {"book": "MongoDB Basics", "price": 20, "quantity": 5},
    {"book": "Advanced MongoDB", "price": 35, "quantity": 3},
    {"book": "MongoDB Aggregation", "price": 25, "quantity": 7}
]
pipeline = [
    {
        "$group": {
            "_id": null,
            "totalQuantity": {"$sum": "$quantity"},
            "averagePrice": {"$avg": "$price"}
        }
    }
]
# Assign pipeline to aggregation_pipeline
# Your code here

Need a hint?

Just assign the existing pipeline list to aggregation_pipeline.