https://github.com/tobrun/jupyter-playground

The Jupyter Notebook Playground is a repository designed to showcase experiments in data science and visualization. Using Jupyter notebooks as the primary tool, this repository serves for sharing knowledge and exploring data science.
https://github.com/tobrun/jupyter-playground

Last synced: 2 months ago
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The Jupyter Notebook Playground is a repository designed to showcase experiments in data science and visualization. Using Jupyter notebooks as the primary tool, this repository serves for sharing knowledge and exploring data science.

• Host: GitHub
• URL: https://github.com/tobrun/jupyter-playground
• Owner: tobrun
• License: apache-2.0
• Created: 2023-04-21T08:16:57.000Z (about 2 years ago)
• Default Branch: main
• Last Pushed: 2023-10-02T14:44:18.000Z (over 1 year ago)
• Last Synced: 2025-02-01T14:16:17.991Z (4 months ago)
• Language: Jupyter Notebook
• Size: 1.06 MB
• Stars: 0
• Watchers: 2
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# Jupyter Playground

The Jupyter Notebook Playground is a repository created to showcase my personal exploration in a variety of experiments in data science and visualization. 

## How to Use Jupyter Notebook Playground?

To get started with Jupyter Notebook Playground, you will need to have [Jupyter Notebook environement installed](https://code.visualstudio.com/docs/datascience/jupyter-notebooks) on your computer. Once you have installed your notebook environemnt, you can clone this repository to your local machine, install dependencies and start exploring the various notebooks available.

> git clone [email protected]:tobrun/jupyter-playground.git

> cd jupyter-playground

> pip3 install .

You can now open this project directory in VSCode.

## Env. variables

A variety of notebooks integrate in services that require access tokens for authentication. Depending on which you execute you will need to have the following env. variables provided:

> OPENAI_API_KEY

## Static code analysis

Install tools with

> pip3 install -e '.[lint]'

Run tooling with

> isort --check-only . -v

> black --check --diff . -v

> flake8 . -v