Metadata-Version: 1.0
Name: Fantasy-Basketball
Version: 0.2
Summary: A package that fetches, processes and visualizes fantasy basketball statistics
Home-page: https://github.com/dwwkelly/fantasy_basketball
Author: Devin Kelly
Author-email: dwwkelly@fastmail.fm
License: GPL3
Description: fantasy_basketball
        ==================
        
        This package will fetch NBA stas from basketball-reference.com, parse 
        the statistics into pandas dataframes, then visualize the statistics.
        
        Installation
        ============
        
        This package can be installed with either pip,::
        
           $ pip install Fantasy_Basketball
        
        Or with directly from the source code::
        
           $ git checkout https://github.com/dwwkelly/fantasy_basketball
           $ cd fantasy_basketball
           $ python setup.py install
        
        
        Dependencies
        ============
        
         * Click
         * numpy
         * matplotlib
         * pandas
         * jinja2
         * pycurl',
         * beautifulsoup4
         * lxml
         
        Usage
        =====
        
        A library and a user application are provided, you can use
        the user application like this::
        
           $ FB_Manager download --year 2013 --teams --draft
           $ FB_Manager process --year 2013 --teams
           $ FB_Manager plot --year 2013
        
        Data Storage
        ============
        
        The fantasy_basketball library creates several directories::
        
           ~/.fantasy_basketball/plots
           ~/.fantasy_basketball/processed_data
           ~/.fantasy_basketball/raw_data
        
        Each directory contains directories that are either the data type or
        the year for the data, *e.g.*::
        
           ~/.fantasy_basketball/processed_data/2013
           ~/.fantasy_basketball/raw_data/teams/2013
        
        The raw data is all HTML files, the processed data is pickle files
        that contain pandas dataframes, the plots directory contains either
        eps images or png images.
        
        You can import the dataframes yourself for your own analysis with ipython::
        
           In [1]: import pandas as pd
        
           In [2]: import os
        
           In [3]: data_dir = os.path.expanduser('~/.fantasy_basketball/processed_data/2013/team_data.pkl')
        
           In [4]: df = pd.read_pickle(data_dir)
        
           In [5]: df.shape
           Out[5]: (347, 55)
        
        
        
        TODO
        ====
        
        * Config file.
        * Generate HTML from data.
        * Download and process more statistics.
        * Deal with infer_types warning for pandas > 0.14
        
Keywords: fantasy basketball pandas
Platform: UNKNOWN
