https://github.com/conorheffron/nba-stats

NBA Analytics (2015 - 2023): Player Statistics
https://github.com/conorheffron/nba-stats

basketball basketball-stats json-api mathplotlib pandas plotly python-3 seaborn sports sports-analytics

Last synced: 19 days ago
JSON representation

NBA Analytics (2015 - 2023): Player Statistics

• Host: GitHub
• URL: https://github.com/conorheffron/nba-stats
• Owner: conorheffron
• License: gpl-3.0
• Created: 2024-03-18T21:08:17.000Z (8 months ago)
• Default Branch: main
• Last Pushed: 2024-08-02T23:04:02.000Z (3 months ago)
• Last Synced: 2024-10-12T22:40:19.424Z (about 1 month ago)
• Topics: basketball, basketball-stats, json-api, mathplotlib, pandas, plotly, python-3, seaborn, sports, sports-analytics
• Language: Jupyter Notebook
• Homepage: https://conorheffron.github.io/nba-stats/
• Size: 13.9 MB
• Stars: 1
• Watchers: 1
• Forks: 0
• Open Issues: 2
• Metadata Files:
  • Readme: README.md
  • License: LICENSE
  • Security: SECURITY.md

Awesome Lists containing this project

README

        
![Proof HTML](https://github.com/cph33/nba-stats/actions/workflows/proof-html.yml/badge.svg)



  



Please see the inital version of this analysis in 2 parts (Jupyter notebooks using various Python 3 libraries).

This includes:

- [part1.ipynb](https://nbviewer.org/github/conorheffron/nba-stats/blob/main/part1.ipynb) (Part 1 Notebook - download data for analysis via sports API - NBA V2)

- [part2.ipynb](https://nbviewer.org/github/conorheffron/nba-stats/blob/main/part2.ipynb) (Part 2 Notebook - read, clean, analyse and visualise data stored on disk)

- Subset of the data used ( `/raw` dir with `Boston Celtics, Orlando Magic, & Atlanta Hawks` data), please contact me for more data samples or to collaborate on this analysis etc.