YNBA

An awesome Python project that we had to do in Master 1 at Junia ISEN

Table of Contents

1. About The Project
   • Built With
2. Getting Started
   • Prerequisites
   • Installation
3. License
4. Contact

About The Project

The idea of the project is simple. We had to use our knowledge in data scrapping, AI and data handling to scrap the NBA's website stats and make some meaningful plots about them. As a bonus, we could create an AI that predicts a value from another.

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Built With

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Getting Started

The project is in multiple parts. Be sure to have everything listed below before trying to launch the project

Prerequisites

You need to have Node.js installed and run the command in your directory

• npm

  npm install

You will also need to have installed pip and our libraries like so:

• pip

  pip install nba_api

  pip install matplotlib

  pip install pandas

  pip install plotly

  pip install -U kaleido

  pip install scikit-learn

Installation

1. Clone the repo

   git clone https://github.com/JambonPasFrais/python-project-M1.git

2. Make sure every package is installed as listed on top of this category

Website

1. In the main directory, run:

   node index.js

2. Click on the link in the console and go to http://localhost:4444

Data analysis and visualization

1. Execute the show_plots.py

AI

1. Open the decision_tree.ipynb file in the AI directory on Jupyter or PyCharm
2. Run each step

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License

Distributed under the MIT License. See LICENSE for more information.

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Contact

• Jambon : @LinkedIn
• Corow : @LinkedIn
• Marie : @LinkedIn
• Thayo : @LinkedIn

Project Link: https://github.com/github_username/repo_name

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