Metadata-Version: 1.1
Name: py-goldsberry
Version: 0.6.3
Summary: API interface for stats.nba.com
Home-page: http://github.com/bradleyfay/py-goldsberry
Author: Bradley Fay
Author-email: bradley.fay@gmail.com
License: MIT
Description: py-Goldsberry
        =============
        
        A Python Package for easily acquiring NBA Data for analysis
        
        What is ``py-Goldsberry``?
        --------------------------
        
        ``py-Goldsberry`` is designed to give the user easy access to data
        available from stats.nba.com in a form that facilitates innovative
        analysis. With a few simple commands, you can have access to virtually
        any data available on the site in an easy to analyze format. In fact,
        some of the data is in a less summarize form giving you the opportunity
        to work with the most raw data possible when you are attempting to
        answer questions that interest you.
        
        Why was it built?
        -----------------
        
        I attended the 2015 Sloan Sports Analytics conference and had the
        fortunate opportunity to listen to `Kirk Goldsberry`_ address the crowd
        regarding the state of analytics in sports (You can watch the talk
        `here`_). One of the questions he addressed at the end was related to
        the availability of data (or lack thereof in some instances). Basically,
        he concluded that the lack of availability of some of the newest data is
        actually hindering the progression of analytics in sports. Innovation is
        now restricted to those with access to data instead of to the entire
        community of interested parties. I wrote (am writing) this package in an
        attempt to help address this issue in whatever small way I can.
        
        This package is a work in progress. As the NBA continues to make more
        data available, I will do my best to update ``py-Goldsberry`` to reflect
        these additions. Currently, there is almost a cumbersome amount of data
        available from the NBA so dealing with what is there is a bit of a
        challenge.
        
        Getting started
        ---------------
        
        To get started with ``py-Goldsberry``, you need to install and load the
        package. From your terminal, run the following command:
        
        ::
        
            pip install py-goldsberry
        
        Once you have the package installed, you can load it into a Python
        session with the following command:
        
        .. code:: python
        
            import goldsberry
            import pandas as pd
        
        The package is designed to work with `pandas`_ in that the output of
        each API call to the NBA website it returned in a format that is easily
        converted into a pandas dataframe.
        
        Getting a List of Players
        ~~~~~~~~~~~~~~~~~~~~~~~~~
        
        One of the key variables necessary to fully utilize ``py-Goldsberry`` is
        ``playerid``. This is the unique id number assigned to each player by
        the NBA. ``py-Goldsberry`` has a top-level function ``PlayerList()``
        built-in to give you quick access to a list of players and numbers. When
        you run the function, you should specify the year of the season from
        which you want the list of available players.
        
        .. code:: python
        
        
            playersCurrent = pd.DataFrame(goldsberry.PlayerList(2014))
            playersCurrent.head()
        
        If you want a list of every player in the history of the NBA, you can
        pass the ``AllTime=True`` argument:
        
        .. code:: python
        
            playersAllTime = pd.DataFrame(goldsberry.PlayerList(AllTime=True))
            playersAllTime.head()
        
        .. _Kirk Goldsberry: http://twitter.com/kirkgoldsberry
        .. _here: https://www.youtube.com/watch?v=wLf2hLHlFI8
        .. _pandas: http://pandas.pydata.org/
Keywords: sports NBA basketball
Platform: any
Classifier: Development Status :: 3 - Alpha
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 2
Classifier: Programming Language :: Python :: 2.6
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.2
Classifier: Programming Language :: Python :: 3.3
Classifier: Programming Language :: Python :: 3.4
