MongoDB $avg Operator

Posted in mongoDB Tutorial

Updated on Oct 30, 2024

By Mari Selvan

👁️ 27 - Views

⏳ 4 mins

💬 1 Comment

Photo Credit to CodeToFun

🙋 Introduction

In MongoDB's aggregation framework, the $avg operator emerges as a fundamental tool for computing the average of numerical values within a dataset. This operator facilitates various statistical analyses and provides valuable insights into the central tendency of the data.

Let's explore how the $avg operator can be effectively utilized within MongoDB's aggregation pipelines.

💡 Syntax

The syntax for the $avg method is straightforward:

syntax.js

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{ $avg: <expression> }

$avg: This operator signifies that the subsequent operation will compute the average value.
<expression>: This represents the expression that evaluates to the values for which the average will be computed. It could be a field reference, a mathematical expression, or a value.

📝 Example

⌨️ Input

Consider a collection named scores containing documents with fields student and score, representing student scores. Here are sample documents from the scores collection:

Input

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[
  { "_id": ObjectId("609c26812e9274a86871bc6a"), "student": "Alice", "score": 85 },
  { "_id": ObjectId("609c26812e9274a86871bc6b"), "student": "Bob", "score": 75 },
  { "_id": ObjectId("609c26812e9274a86871bc6c"), "student": "Charlie", "score": 90 }
]

🔄 Aggregation

Suppose we want to calculate the average score of all students. Here's how you can achieve this using the $avg operator:

example.js

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db.scores.aggregate([
  {
    $group: {
      _id: null,
      averageScore: { $avg: "$score" }
    }
  }
])

🧩 Explanation

$group: This stage groups all documents into a single group (since _id: null) and computes the average score within that group.
$avg: Calculates the average value of the specified field, which in this case is the score.

When discussing how the above aggregation works:

_id: null: Since we are grouping all documents into a single group, there is no specific grouping key, hence _id is represented as null.
averageScore: 83.33333333333333: The average score is calculated by adding up all the scores (85 + 75 + 90 = 250) and dividing by the total number of documents (3). So, the average score is approximately 83.33.

💻 Output

Now, let's take a look at the output generated by the aggregation pipeline:

Output

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{ "_id": null, "averageScore": 83.33333333333333 }

📚 Use Cases

Performance Evaluation:

The $avg operator is useful for calculating average performance metrics, such as exam scores, sales figures, or website traffic.
Data Comparison:

Averaging values allows for comparison across different groups or time periods, aiding in identifying trends or disparities.
Quality Control:

In manufacturing or production environments, computing averages helps monitor product quality or process efficiency over time.

🎉 Conclusion

The $avg operator in MongoDB's aggregation framework provides a powerful mechanism for computing average values within datasets, enabling users to gain insights into the central tendency of their data. Whether you're analyzing student scores, sales data, or production metrics, mastering the usage of $avg empowers you to efficiently compute averages and derive meaningful insights from your datasets.

With its intuitive syntax and diverse applications, the $avg operator proves to be an invaluable asset for handling numerical data effectively within MongoDB. Incorporate it into your aggregation pipelines to unlock new dimensions of data analysis and gain deeper insights into your datasets.