How to Convert a Pandas DataFrame to JSON Format: Column Names with Values as Lists

Описание: Learn how to easily convert a Pandas DataFrame to a JSON format with column names mapping to lists of values. This guide provides step-by-step instructions for beginners.
---
This video is based on the question https://stackoverflow.com/q/65814417/ asked by the user 'Leonel Garcia' ( https://stackoverflow.com/u/10938467/ ) and on the answer https://stackoverflow.com/a/65814497/ provided by the user 'Mayank Porwal' ( https://stackoverflow.com/u/5820814/ ) at 'Stack Overflow' website. Thanks to these great users and Stackexchange community for their contributions.

Visit these links for original content and any more details, such as alternate solutions, latest updates/developments on topic, comments, revision history etc. For example, the original title of the Question was: Pandas dataframe to json with format {column1 name : [Values], column2 name: [values], Column3 name... }

Also, Content (except music) licensed under CC BY-SA https://meta.stackexchange.com/help/l...
The original Question post is licensed under the 'CC BY-SA 4.0' ( https://creativecommons.org/licenses/... ) license, and the original Answer post is licensed under the 'CC BY-SA 4.0' ( https://creativecommons.org/licenses/... ) license.

If anything seems off to you, please feel free to write me at vlogize [AT] gmail [DOT] com.
---
How to Convert a Pandas DataFrame to JSON Format: Column Names with Values as Lists

If you're working with Python and Pandas, you might encounter the need to convert a DataFrame to JSON format. Specifically, you may want the JSON structure to reflect your DataFrame in a way that aligns column names with their corresponding values in lists. This is particularly useful for data interchange or API usage. In this guide, we will guide you through the process to achieve this format effortlessly.

Understanding the Problem

The goal is to transform a DataFrame like this:

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

into a JSON format that looks like this:

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

Using df.to_json(orient='columns') will not yield the desired output, as it introduces row keys which are unnecessary for our case. Instead, let's explore the correct method to achieve our objective.

The Solution: Converting DataFrame to JSON

Step 1: Use the Appropriate Method

To convert the DataFrame to the desired JSON format, we need to use the to_dict() method in combination with the orient='list' parameter. This approach collects the values of each column into a list, effectively formatting the DataFrame exactly how we want it.

Step 2: Example Code

Here’s a concise code snippet to demonstrate this conversion:

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

Step 3: Analyzing the Output

When you run the code above, it should yield the following output:

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

This output matches your expectations, with each column name linked to an array of its values, which can now be utilized in various applications such as REST APIs or data storage formats.

Summary

Converting a DataFrame to JSON in the desired format can be easily achieved using the Pandas library. By employing the to_dict() method with the orient='list' parameter, you can transform your DataFrame without introducing unwanted row keys. This method not only simplifies data handling but also enhances data interoperability for your projects. If you're new to Python and Pandas, this is an essential tool in your data manipulation skillset!