Metadata-Version: 2.1
Name: pandas-fpl
Version: 0.3.0
Summary: Pandas wrapper for Fantasy Premier League API based on the FPL package: https://github.com/amosbastian/fpl
Home-page: https://github.com/177arc/pandas-fpl
Author: Marc Maier
Author-email: py@177arc.net
License: MIT
Description: [![PyPi Downloads](https://pepy.tech/badge/pandas-fpl)](https://pepy.tech/project/pandas-fpl)
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        [![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/177arc/pandas-fpl/master?filepath=usage.ipynb)
        
        # Pandas wrapper for Fantasy Premier League API
        
        The `FPLPandas` class in this package uses the excellent [FPL](https://github.com/amosbastian/fpl) library to retrieve data from the [Fantasy Premier League API](https://fantasy.premierleague.com/api/bootstrap-static/). It maps the results to the pandas data frames so that the data can be analysed interactively, e.g. in a Jupyter notebook.
        
        [FPL](https://github.com/amosbastian/fpl) library is an asynchronous wrapper for the [Fantasy Premier League API](https://fantasy.premierleague.com/api/bootstrap-static/) But the Jupyter notebook work better with synchronous code, the methods exposed by the `FPLPandas` class are synchronous.
        
        ## Installation
        
        ### Using pip
        
        You can install using the pip package manager by running
        
            pip install pandas-fpl
        
        ### From source
        
        Download the source code by cloning the repository or by pressing [Download ZIP](https://github.com/177arc/pandas-fpl/archive/master.zip) on this page.
        Install by navigating to the proper directory and running
        
            python setup.py install
        
        ## Usage
        
        For usage guidance and testing the package interactively, hit the [Usage Jupyter Notebook](https://mybinder.org/v2/gh/177arc/pandas-fpl/master?filepath=usage.ipynb).
        
        ## Documentation
        
        For the code documentation, please visit the [Documentation Github Pages](https://177arc.github.io/pandas-fpl/docs/fplpandas/).
        
        ## Contributing
        
        1. Fork the repository on GitHub.
        2. Run the tests with `python -m pytest tests/` to confirm they all pass on your system.
           If the tests fail, then try and find out why this is happening. If you aren't
           able to do this yourself, then don't hesitate to either create an issue on
           GitHub, contact me on Discord or send an email to [py@177arc.net](mailto:py@177arc.net>).
        3. Either create your feature and then write tests for it, or do this the other
           way around.
        4. Run all tests again with with `python -m pytest tests/` to confirm that everything
           still passes, including your newly added test(s).
        5. Create a pull request for the main repository's ``master`` branch.
Platform: UNKNOWN
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Description-Content-Type: text/markdown
