Array of objects - how to group items by property and squash data from each of grouped items into 1

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05-10-2024

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Grouping and Squashing Data in Arrays of Objects: A Comprehensive Guide

Working with large datasets often requires organizing information into meaningful groups. When dealing with an array of objects, you might need to group items based on a specific property and then combine the data from each group into a single, condensed representation. This process, commonly known as "grouping and squashing," is essential for tasks like generating reports, creating summaries, or visualizing data.

This article will guide you through the process of grouping and squashing data in arrays of objects using JavaScript. We'll explore a practical example, understand the logic behind the solution, and offer insights for adapting this technique to various scenarios.

The Scenario: Grouping Customers by Region and Summarizing their Orders

Imagine you have an array of customer objects, each containing information about their region and order history. We want to group these customers by region and then calculate the total order value for each region.

Here's an example of our data:

const customers = [
  { name: "Alice", region: "North", orders: [{ amount: 100 }, { amount: 50 }] },
  { name: "Bob", region: "South", orders: [{ amount: 75 }] },
  { name: "Charlie", region: "North", orders: [{ amount: 120 }, { amount: 80 }] },
  { name: "David", region: "West", orders: [{ amount: 150 }, { amount: 200 }] },
  { name: "Eve", region: "South", orders: [{ amount: 100 }, { amount: 100 }] }
];

Our goal is to transform this data into a structure like this:

const groupedCustomers = [
  { region: "North", totalOrderValue: 250 },
  { region: "South", totalOrderValue: 275 },
  { region: "West", totalOrderValue: 350 }
];

The Solution: Grouping and Squashing with reduce and map

JavaScript provides powerful array manipulation methods that can simplify this task. We'll use a combination of reduce and map to achieve our goal.

1. Grouping with reduce:

   We start by using reduce to group the customers based on their region. The reduce function iterates through the array, accumulating the results into a new object.

   const groupedByRegion = customers.reduce((acc, customer) => {
       const { region } = customer;
       if (!acc[region]) {
           acc[region] = { region, totalOrderValue: 0 };
       }
       acc[region].totalOrderValue += customer.orders.reduce((sum, order) => sum + order.amount, 0);
       return acc;
   }, {});
   

   This code creates an object where each key represents a region and the value is an object containing the region name and the total order value.

2. Transforming to an Array with map:

   We then use map to transform the object created by reduce into an array of objects, mirroring the desired output format.

   const groupedCustomers = Object.entries(groupedByRegion).map(([region, data]) => ({
       region,
       totalOrderValue: data.totalOrderValue
   }));
   

   This code iterates over the key-value pairs of the groupedByRegion object and creates a new object for each region, extracting the relevant data.

Understanding the Process

Let's break down the code to understand the steps involved:

• Grouping: reduce iterates through the customers array and builds a new object (acc) to hold the grouped data. For each customer, it checks if the customer's region already exists in the acc object. If it does, it adds the customer's total order value to the existing region's total. If not, it creates a new entry in the acc object for the region.
• Squashing: map iterates over the key-value pairs of the groupedByRegion object (created by reduce). For each region, it creates a new object containing the region name and the total order value from the grouped data.

Adapting the Solution

The code we've provided is a starting point. You can modify it to:

• Group by different properties: Change the property used in the reduce function to group by different criteria.
• Calculate different aggregates: Modify the reduce function to calculate various statistics for each group, such as average order value, maximum order value, or number of orders.
• Handle complex objects: Adapt the squashing process using map or other array methods to extract specific data from more complex objects.

Conclusion

Grouping and squashing data in arrays of objects is a common task in data processing and analysis. By understanding the principles of using reduce and map to group and manipulate data, you can efficiently organize and summarize information from large datasets. This empowers you to extract valuable insights and make informed decisions based on the data.