NBA Stats

Stats of the NBA and WNBA players related to the gender pay gap.

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.

Author

Jose Ignacio Bengoechea Isasa, ignacio.bengis@gmail.com

Quickstart

• 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

About this software

• 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

PDF Report

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

Dataset

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

License

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.