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Скачать или смотреть Convert Your Pandas DataFrame into a Nested Dictionary or JSON Format

  • vlogize
  • 2025-04-01
  • 1
Convert Your Pandas DataFrame into a Nested Dictionary or JSON Format
How to convert pandas dataframe into nested dictionary or json?pythonpandasdataframedictionary
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Описание к видео Convert Your Pandas DataFrame into a Nested Dictionary or JSON Format

Learn how to effectively convert your `Pandas DataFrame` into a nested `dictionary` or `JSON` format with easy-to-follow steps and code examples.
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This video is based on the question https://stackoverflow.com/q/70163975/ asked by the user 'Asinha' ( https://stackoverflow.com/u/16286075/ ) and on the answer https://stackoverflow.com/a/70164374/ provided by the user 'Derek O' ( https://stackoverflow.com/u/5327068/ ) at 'Stack Overflow' website. Thanks to these great users and Stackexchange community for their contributions.

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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.

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How to Convert a Pandas DataFrame into a Nested Dictionary or JSON

If you're working with Python's Pandas library, there’s a good chance you’ll encounter situations where you need to convert a DataFrame into a structured format like a nested dictionary or JSON. This can be particularly useful when preparing data for APIs or when you want to organize your data more hierarchically.

The Problem

Imagine you have a DataFrame that looks like this:

id_numbernameamountaddenda1234ABCD$100Car-wash-$301234ABCD$100Maintenance-$70You wish to transform it into a nested structure similar to this:

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

However, you might find that using simple methods like groupby and to_dict doesn’t quite achieve the result you want. Fear not! This post will guide you through the steps to get from your original DataFrame to the desired nested structure.

The Solution

Understanding Your Data

To achieve the desired result, you need to change the addenda column in such a way that all related addenda entries are grouped together before converting the DataFrame into a dictionary.

Steps to Convert the DataFrame

Group Your Data:

Use the groupby() function on the columns that you want to remain singular (like id_number, name, and amount).

Collapse Rows:

Create a custom function that consolidates the addenda entries into a list of dictionaries.

Convert to Dictionary:

Finally, use the to_dict() method with the appropriate orientation to create the nested dictionary format.

Example Code

Here’s a step-by-step implementation:

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

Expected Result

When you run the code, you should see an output like this:

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

Conclusion

Converting your Pandas DataFrame into a nested dictionary or JSON format might seem complex, but by utilizing groupby and a custom function, you can efficiently structure the data as needed. This approach not only organizes your data for better readability but also prepares it for further processing, such as sending it to APIs or saving it in JSON files.

Now you're equipped to transform your DataFrames into a nested dictionary with ease!

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