cfanalytics: Downloading, analyzing and visualizing CrossFit data

.. image:: https://travis-ci.org/raybellwaves/cfanalytics.svg?branch=master :target: https://travis-ci.org/raybellwaves/cfanalytics .. .. image:: https://ci.appveyor.com/api/projects/status/github/raybellwaves/cfanalytics?svg=true&passingText=passing&failingText=failing&pendingText=pending .. .. :target: https://ci.appveyor.com/project/raybellwaves/cfanalytics .. .. image:: https://coveralls.io/repos/github/raybellwaves/cfanalytics/badge.svg?branch=master .. .. :target: https://coveralls.io/github/raybellwaves/cfanalytics?branch=master .. image:: https://img.shields.io/pypi/v/cfanalytics.svg :target: https://pypi.python.org/pypi/cfanalytics .. image:: https://zenodo.org/badge/DOI/10.5281/zenodo.1208106.svg :target: https://doi.org/10.5281/zenodo.1208106

cfanalytics is an open source project and Python package that aims to provide analyzes to CrossFit workouts. The goal is to enhance data-driven performance of athletes.

.. image:: https://github.com/raybellwaves/cfanalytics/blob/master/Plots/Men_Rx_2018_Overall_rank_P0.1.png .. image:: https://github.com/raybellwaves/cfanalytics/blob/master/Plots/Women_Rx_2018_Miami_Overall_rankP0.png

Installing

The version numbers 0.1.X are all development versions as I chip away at the project on here in my spare time. I occasionally build the package if i've finished something large. But you can grab the least-buggy version of this package by typing:

pip install git+https://github.com/raybellwaves/cfanalytics

Make sure you have the optional dependencies installed below for this to work.

The psudo-stable packages are here.

conda install -c conda-forge cfanalytics

pip install cfanalytics

As a precautionary note, it has been developed entirely on Mac OSX using Python installed with anaconda <https://anaconda.org/anaconda/python>__. Therefore, use in Windows and Linux at your own peril.

As good practice, I recommend installing with anaconda/miniconda and in a new enviroment:

.. parsed-literal::

$ conda create -n cfa python=3.6
$ source activate cfa
$ conda install -c matplotlib cartopy joblib netcdf4
$ pip install motionless
$ pip install git+https://github.com/fmaussion/salem.git
$ pip install git+https://github.com/raybellwaves/cfanalytics
$ # eventually: conda install -c conda-forge cfanalytics matplotlib cartopy

You can type source deactivate when finished. You can also check which environments you have created by typing conda info --envs. To remove an environment type conda remove --name cfa --all.

Optional dependencies (for plotting)

matplotlib <https://github.com/matplotlib/matplotlib>__
cartopy <https://github.com/SciTools/cartopy>__
salem <https://github.com/fmaussion/salem>__ and its dependencies

Examples

See examples here <https://github.com/raybellwaves/cfanalytics/tree/master/Examples>__.

Documentation

The documentation is hosted at http://cfanalytics.readthedocs.io/

Projects using this data

Unofficial 2018 Open Results <http://www.rpresidente.com.br/Open2018/Index>__
View a map of the results <https://app.powerbi.com/view?r=eyJrIjoiNmJmODk0MGUtNjVmNi00ZWYxLTg3NjgtOTQ5ZWFlYzFmYjJiIiwidCI6IjQ2YzUxNzhlLWEwZjQtNGY0ZC04YzQwLTk1OThlM2QxMTg2MCIsImMiOjN9>__

Contributing

See my TODO list here <https://github.com/raybellwaves/cfanalytics/blob/master/TODO.rst>__.

Acknowledgements

Thanks to posts on r/crossfit <https://www.reddit.com/r/crossfit/>. e.g. here <https://www.reddit.com/r/crossfit/comments/5uikq8/2017_open_data_analysis/>, I worked out how to download data from the CrossFit open <https://games.crossfit.com/leaderboard/open/2017?division=1&region=0&scaled=0&sort=0&occupation=0&page=1>__.
Cfopendata is a very minor adaptation from captamericadevs/CFOpenData <https://github.com/captamericadevs/CFOpenData>. Who smartly developed code to download CrossFit open data using aiohttp <https://github.com/aio-libs/aiohttp>.
Affliatelist used this answer <https://stackoverflow.com/questions/33618324/web-scraping-google-map-website-is-it-possible-to-scrape>__ as well as this answer <https://stackoverflow.com/questions/49211863/scrape-latitude-and-longitude-of-address-obtained-from-mapbox>__ on SO.
Cfplot().regionplot() was made possible by the work of the cartopy <https://github.com/SciTools/cartopy>__ developers and developers of Natural Earth <http://www.naturalearthdata.com/>__.
Cfplot().cityplot() was made possible by the work by fmaussion <https://github.com/fmaussion>__ in salem <https://github.com/fmaussion/salem>__
xarray <https://github.com/pydata/xarray>__ developers. Whose package template I used for this package as well as the package itself.