Did you know that the salary gap between NBA and WNBA is one of the biggest in the sports?
NBA Stats is a scrapping tool that gives the following stats for all the NBA and WNBA players:
- Points and salary/points.
- Rebounds and salary/rebounds.
- Assists and salary/assists.
- Steals and salary/steals.
- Blocks and salary/blocs.
Jose Ignacio Bengoechea Isasa, ignacio.bengis@gmail.com
- Language: Python 3.6.2.
- Requires urllib, lxml, requests, csv, selenium and PhantomJS.
Assuming git, python and pip installed:
git clone https://github.com/Bengis/nba-stats.git
cd nba-stats/code
python nba-gap.py
- This software is part of the Practice 1 of the class: "Tipologia y ciclo de vida de los datos".
- Class: Tipologia y ciclo de vida de los datos.
- Master of Data Science.
- Universitat Oberta of Catalunya.
- Tutored by: Laia Subirats Maté
You can check the report of this proyect in this link. The report is in spanish:
https://github.com/Bengis/nba-wnba-salary-gap/blob/master/doc/informe-nba-wnba-salary-gap.pdf
You can check the dataset of this proyect in this folder:
https://github.com/Bengis/nba-wnba-salary-gap/tree/master/data
The dataset related to NBA players:
https://github.com/Bengis/nba-wnba-salary-gap/blob/master/data/nba-stats_out.csv
The dataset related to WNBA players:
https://github.com/Bengis/nba-wnba-salary-gap/blob/master/data/wnba-stats_out.csv
The content of this project itself is licensed under the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International, and the underlying source code used to format and display that content is licensed under the MIT license.