Metadata-Version: 2.1
Name: mplsoccer
Version: 0.0.7
Summary: mplsoccer is a Python plotting library for drawing soccer / football pitches quickly in Matplotlib.
Home-page: https://github.com/andrewRowlinson/mplsoccer
Author: Andrew Rowlinson
Author-email: rowlinsonandy@gmail.com
License: MIT
Description: # mplsoccer
        
        mplsoccer is a Python library for drawing soccer/football pitches in Matplotlib and loading StatsBomb open-data.
        
        ## Installation
        
        Use the package manager [pip](https://pip.pypa.io/en/stable/) to install mplsoccer.
        
        ```bash
        pip install mplsoccer
        ```
        
        ## Docs
        
        Here are the [docs](https://mplsoccer.readthedocs.io/) for mplsoccer.
        
        ## Quick start
        
        Plot a StatsBomb pitch
        
        ```python
        from mplsoccer.pitch import Pitch
        pitch = Pitch(pitch_color='grass', line_color='white', stripe=True)
        fig, ax = pitch.draw()
        ```
        ![alt text](https://github.com/andrewRowlinson/mplsoccer/blob/master/docs/quick_start.png?raw=true "statsbomb pitch")
        
        ## Why mplsoccer exists
        
        mplsoccer shares some of the tools I built for the OptaPro Analytics Forum.
        At the time there werenâ€™t any open-sourced python tools. Now alternatives exist, such as [matplotsoccer](https://pypi.org/project/matplotsoccer/).
        
        By using mplsoccer, I hope that you can spend more time building insightful graphics rather than having to learn to draw pitches from scratch.
        
        
        ## Advantages of mplsoccer
        
        mplsoccer:
        
        1. draws 7 different pitch types by changing a single argument, which is useful as there isnâ€™t a standardised data format
        2. extends matplotlib to plot heatmaps, (comet) lines, footballs and rotated markers
        3. flips the data coordinates when in a vertical orientation so you donâ€™t need to remember to flip them
        4. creates tidy dataframes for StatsBomb data, which is useful as most of the alternatives produce nested dataframes
        
        ## License
        
        [MIT](https://choosealicense.com/licenses/mit)
        
        ## Contributions
        Contributions are welcome. It would be great to add the following functionality to mplsoccer:
        - pass maps
        - pass sonars
        - Voronoi diagrams
        
        Examples to help others are also welcome for a gallery.
        
        Please get in touch at rowlinsonandy@gmail.com or [@numberstorm](https://twitter.com/numberstorm) on Twitter.
        
        ## Inspiration
        
        mplsoccer was inspired by other people's work:
        - [Peter McKeever](http://petermckeever.com/2019/01/plotting-pitches-in-python/) inspired the API design
        - [ggsoccer](https://github.com/Torvaney/ggsoccer) - a library for plotting pitches in R
        - [lastrow](https://twitter.com/lastrowview) - often tweets animations from matches and the accompanying code
        - [fcrstats](http://fcrstats.com/) - tutorials for using football data
        - [fcpython](https://fcpython.com/) - Python tutorials for using football data
        - [Karun Singh](https://twitter.com/karun1710) - tweets some interesting football analytics and visuals
        - [StatsBomb](https://statsbomb.com/) - great visual design and free open-data
        - John Burn-Murdoch's [tweet](https://twitter.com/jburnmurdoch/status/1057907312030085120) got me interested in football analytics
        
        ## Recent changes
        
        mplsoccer's recent changes fixed several issues with the heatmap functionality
        - Pitch.label_heatmap(), now filters out labels outside of the pitch.
        - Pitch.bin_statistic(), now works for a statistic argument other than 'count'.
        - Pitch.heatmap(), now returns a mesh in horizontal orientation.
        
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3 :: Only
Classifier: Topic :: Scientific/Engineering :: Visualization
Requires-Python: >=3.6
Description-Content-Type: text/markdown
