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Populate a Pandas DataFrame using a nested JSON file.

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Jupyter-df

Purpose

This repository was created to help navigate through a nested JSON file and successfully populate a Pandas DataFrame. It introduces an alternative solution to pandas.json_normalize using Jupyter Notebook.

Prerequisites

  :ballot_box_with_check: Python Version: 2.7.16

  :ballot_box_with_check: Pandas Version: 1.2.4

  :ballot_box_with_check: Jupyter Notebook: 6.1.3

Dataset

The dataset used in this example spans from March 1, 2019 - March 1, 2021 and consists of 11,522 sessions. The JSON file was extracted from ACN-Data.

Testing

In order to test this repository you will need an environment that supports Jupyter Notebook.

  • Step 1: Clone project to your local machine
git clone https://github.com/jguev/nested-dataframe.git
  • Step 2: Install Jupyter Lab

If you use pip, you can install it with:

pip install jupyterlab

  For additional methods or detailed instructions reference the installation guide.

  • Step 3: In order to launch the notebook on your web browser, navigate to the cloned project through your terminal and run the command:
jupyter-notebook
  • Step 4: After the notebook opens on your browser, click on the Nested.ipynb file

Now you are free to run, edit and test the project using Jupyter-Notebook. Happy coding! ✨

Documentation

Read more about it on Geek Culture article

nested-c

Contributing

If you would like to submit a bug report, question, or documentation suggestion, please submit the issue through GitHub.

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