Retrieve Sports data in Python
Project description
sportsdataverse-py
See CHANGELOG.md for details.
The goal of sportsdataverse-py is to provide the community with a python package for working with sports data as a companion to the cfbfastR, hoopR, and wehoop R packages. Beyond data aggregation and tidying ease, one of the multitude of services that sportsdataverse-py provides is for benchmarking open-source expected points and win probability metrics for American Football.
Installation
sportsdataverse-py can be installed via pip:
pip install sportsdataverse
or from the repo (which may at times be more up to date):
git clone https://github.com/saiemgilani/sportsdataverse-py
cd sportsdataverse-py
pip install -e .
Our Authors
Citations
To cite the sportsdataverse-py
Python package in publications, use:
BibTex Citation
@misc{gilani_sdvpy_2021,
author = {Gilani, Saiem},
title = {sportsdataverse-py: The SportsDataverse's Python Package for Sports Data.},
url = {https://sportsdataverse-py.sportsdataverse.org},
season = {2021}
}
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
sportsdataverse-0.0.6.tar.gz
(69.3 kB
view hashes)
Built Distribution
Close
Hashes for sportsdataverse-0.0.6-py3-none-any.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 7227a74a9b450b7cbcf37b0afe680ef985823f8427ae885eb93f5008d1792787 |
|
MD5 | 6746cfedeef68ab3450c4c95067824d3 |
|
BLAKE2b-256 | 97b2c1fc9e9790290ff0174c2706eb2527a6015a5089f06d7b3479ba79b6d65b |