How to Convert CSV Data to Multiple JSON Files by Grouping Categories in Python

Learn how to create multiple JSON files from CSV data by grouping products by year using Python. Follow our simple step-by-step guide with code examples!
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How to Convert CSV Data to Multiple JSON Files by Grouping Categories in Python

When working with data, it’s common to want to transform it into a more useful format. For instance, you might find yourself needing to convert a CSV file containing product information into multiple JSON files, with one file per year. The goal is to group products by year and structure the JSON output in a specific format that makes the data easy to consume. If you’ve ever struggled with this task, this guide is here to help you navigate through it with a practical solution.

The Problem: Converting CSV to JSON

Let's consider a CSV file that looks like this:

[[See Video to Reveal this Text or Code Snippet]]

From this file, we want to generate JSON files for each unique year, leading to a structure similar to this:

[[See Video to Reveal this Text or Code Snippet]]

However, the initial approach to parse this CSV can lead to a structure that is not quite what we expect. Let's take a look at the initial code and analyze why it doesn’t work as intended.

The Initial Attempt

Here is the code that was used to parse the CSV:

[[See Video to Reveal this Text or Code Snippet]]

The Result Obtained

This code generated the following output:

[[See Video to Reveal this Text or Code Snippet]]

As you can see, instead of getting a straightforward integer value for each product's price, we received a list containing that price, which isn't what we wanted.

The Solution: Achieving the Desired Structure

To achieve the desired JSON structure, the code needs to be slightly modified. Here’s how to approach it:

Refactor the Code Logic: Eliminate creating lists for prices and directly assign the integer values.

Create a Nested JSON Response: Group products correctly by year and ensure the values are integers rather than lists.

Updated Code

Below you’ll find an updated version of the code that fulfills our requirements:

[[See Video to Reveal this Text or Code Snippet]]

Important Adjustments Made

Price Parsing: Prices are directly stored as integers instead of lists.

Constructing Output: For each year, we construct a dictionary containing year, products, and processed before saving or printing them.

Conclusion

Using Python to transform a CSV into structured JSON data is a powerful method to organize and manipulate your data effectively. By ensuring that each product's price is handled correctly and grouping your data by year, you can generate a set of JSON documents that meet your needs for further processing or analysis. With the adjustments discussed, you can confidently convert your data formats and extract meaningful insights from them.

Have fun coding, and happy data manipulation!