Introduction

MongoDB’s aggregation framework is a powerful tool for processing and analyzing data stored in collections. It allows us to perform complex data transformations and computations with ease. In this blog, we will explore how to use the aggregation framework to calculate the average age of people grouped by their city in a MongoDB collection.

Prerequisites

• A basic understanding of MongoDB and its query language.

• MongoDB installed on your machine or access to a cloud service like MongoDB Atlas.

Step 1: Create a MongoDB Collection and Insert Documents

To demonstrate the aggregation framework, we will create a collection called people and insert sample documents representing individuals with their respective ages and cities.

Inserting Sample Documents

db.people.insertMany([
    { name: "Alice", age: 28, city: "New York" },
    { name: "Bob", age: 34, city: "Los Angeles" },
    { name: "Charlie", age: 22, city: "Chicago" },
    { name: "Diana", age: 29, city: "New York" },
    { name: "Ethan", age: 42, city: "Los Angeles" },
    { name: "Frank", age: 30, city: "San Francisco" },
    { name: "George", age: 38, city: "Austin" },
    { name: "Hannah", age: 26, city: "Chicago" }
]);

Step 2: Using the Aggregation Framework

To calculate the average age of people grouped by their city, we will use the aggregate() method along with the $group stage.

Aggregation Pipeline

The aggregation pipeline consists of several stages, but for this task, we will primarily focus on the $group stage. The $group stage allows us to group documents by a specified field and perform operations on the grouped data.

Query to Calculate Average Age by City

db.people.aggregate([
    {
        $group: {
            _id: "$city",                     // Group by city
            averageAge: { $avg: "$age" }     // Calculate average age
        }
    }
]);

Step 3: Analyzing the Output

When you run the above aggregation query, you will receive an output showing the average age of individuals grouped by city.

Step 4: Understanding the Results

In the output:

• Each document represents a unique city (represented by _id).

• The averageAge field contains the average age of people residing in that city.

Conclusion

Using MongoDB’s aggregation framework allows for efficient data processing and analysis. In this blog post, we demonstrated how to calculate the average age of people grouped by city using the $group stage of the aggregation pipeline. This powerful feature can be utilized to derive insights from data in various real-world applications, such as reporting and data analytics.