Metadata-Version: 2.1
Name: ptplot
Version: 0.2.0
Summary: Make beautiful plots of player tracking data
Home-page: https://github.com/AndrewRook/ptplot
Author: Andrew Schechtman-Rook
Author-email: footballastronomer@gmail.com
License: GNU General Public License v3
Description: # ptplot
        `ptplot` makes it easy to turn player-tracking data into beautiful,
        interactive visualizations — including animations! These visualizations can be used to guide
        data exploration/analysis work, or to embed in webpages to share with
        the world. 
        
        ![example animation](ptplot.gif)
        
        ## Installation
        
        `ptplot` can be installed via pip:
        
        ```bash
        $ pip install ptplot
        ```
        
        It is strongly recommended that you install `ptplot` into a virtual
        environment, such as with [`conda`](https://docs.conda.io/en/latest/):
        
        ```bash
        [After installing conda]
        $ conda create -n player_tracking python=3
        $ conda activate player_tracking
        $ pip install ptplot
        ```
        
        You may wish to install some of `ptplot`'s dependencies
        via conda, specifically `pandas` and `bokeh`:
        
        ```bash
        [After installing conda]
        $ conda create -n player_tracking python=3 pandas bokeh
        $ conda activate player_tracking
        $ pip install ptplot
        ```
        
        ## Getting Started
        
        Making your first plot can be as simple as
        
        ```python
        import pandas as pd
        
        from bokeh.plotting import show
        
        from ptplot import PTPlot
        from ptplot.nfl import Field
        from ptplot.plot import Positions
        
        data = pd.read_csv("YOUR PLAYER TRACKING DATA")
        plot = PTPlot(data) + Field() + Positions("X_COORDINATE_COLUMN", "Y_COORDINATE_COLUMN")
        show(plot.draw())
        ```
        
        For additional documentation and examples, check out the
        notebooks in the `notebooks/` directory, which can be viewed
        online with all of the plots correctly rendered via nbviewer:
        1. [Basic Plots](https://nbviewer.jupyter.org/github/AndrewRook/ptplot/blob/main/notebooks/1-Basic_Plots.ipynb)
        2. [Animations](https://nbviewer.jupyter.org/github/AndrewRook/ptplot/blob/main/notebooks/2-Animations.ipynb)
        3. [Faceting](https://nbviewer.jupyter.org/github/AndrewRook/ptplot/blob/main/notebooks/3-Faceting.ipynb)
        4. [Tips and Tricks](https://nbviewer.jupyter.org/github/AndrewRook/ptplot/blob/main/notebooks/4-Tips_and_Tricks.ipynb)
        
        Additionally, layers within `ptplot` have docstrings with
        more usage details. Those can be accessed either by reading the
        source code or running `help([FUNCTION])` inside of Python. 
        
        ## Development Docs
        
        See [here](development.md)
Keywords: ptplot
Platform: UNKNOWN
Classifier: Development Status :: 2 - Pre-Alpha
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: GNU General Public License v3 (GPLv3)
Classifier: Natural Language :: English
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Requires-Python: >=3.7
Description-Content-Type: text/markdown
Provides-Extra: dev
