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        "author": "Quantopian Inc.",
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            "Development Status :: 5 - Production/Stable",
            "Intended Audience :: Developers",
            "License :: OSI Approved :: Apache Software License",
            "Natural Language :: English",
            "Operating System :: OS Independent",
            "Programming Language :: Python",
            "Programming Language :: Python :: 2.7",
            "Programming Language :: Python :: 3.4",
            "Programming Language :: Python :: 3.5",
            "Topic :: Office/Business :: Financial",
            "Topic :: Scientific/Engineering :: Information Analysis",
            "Topic :: Utilities"
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        "description": ".. image:: https://media.quantopian.com/logos/open_source/alphalens-logo-03.png\n    :align: center\n\nAlphalens\n=========\n.. image:: https://travis-ci.org/quantopian/alphalens.svg?branch=master\n    :target: https://travis-ci.org/quantopian/alphalens\n   \n    \nAlphalens is a Python Library for performance analysis of predictive\n(alpha) stock factors. Alphalens works great with the\n`Zipline <http://zipline.io/>`__ open source backtesting library, and\n`Pyfolio <https://github.com/quantopian/pyfolio>`__ which provides\nperformance and risk analysis of financial portfolios.\n\nThe main function of Alphalens is to surface the most relevant statistics\nand plots about an alpha factor, including:\n\n-  Returns Analysis\n-  Information Coefficient Analysis\n-  Turnover Analysis\n-  Grouped Analysis\n\nGetting started\n---------------\n\nWith a signal and pricing data creating a factor \"tear sheet\" is a two step process:\n\n.. code:: python\n\n    import alphalens\n    \n    # Ingest and format data\n    factor_data = alphalens.utils.get_clean_factor_and_forward_returns(my_factor, \n                                                                       pricing, \n                                                                       quantiles=5,\n                                                                       groupby=ticker_sector,\n                                                                       groupby_labels=sector_names)\n\n    # Run analysis\n    alphalens.tears.create_full_tear_sheet(factor_data)\n\n\nLearn more\n----------\n\nCheck out the `example notebooks <https://github.com/quantopian/alphalens/tree/master/alphalens/examples>`__ for more on how to read and use\nthe factor tear sheet.\n\nInstallation\n------------\n\nInstall with pip:\n\n::\n\n    pip install alphalens\n\nInstall with conda: \n\n::\n\n    conda install -c conda-forge alphalens\n\nInstall from the master branch of Alphalens repository (development code):\n\n::\n\n    pip install git+https://github.com/quantopian/alphalens\n\nAlphalens depends on:\n\n-  `matplotlib <https://github.com/matplotlib/matplotlib>`__\n-  `numpy <https://github.com/numpy/numpy>`__\n-  `pandas <https://github.com/pydata/pandas>`__\n-  `scipy <https://github.com/scipy/scipy>`__\n-  `seaborn <https://github.com/mwaskom/seaborn>`__\n-  `statsmodels <https://github.com/statsmodels/statsmodels>`__\n\nUsage\n-----\n\nA good way to get started is to run the examples in a `Jupyter\nnotebook <http://jupyter.org/>`__.\n\nTo get set up with an example, you can:\n\nRun a Jupyter notebook server via:\n\n.. code:: bash\n\n    jupyter notebook\n\nFrom the notebook list page(usually found at\n``http://localhost:8888/``), navigate over to the examples directory,\nand open any file with a .ipynb extension.\n\nExecute the code in a notebook cell by clicking on it and hitting\nShift+Enter.\n\nQuestions?\n----------\n\nIf you find a bug, feel free to open an issue on our `github\ntracker <https://github.com/quantopian/alphalens/issues>`__.\n\nContribute\n----------\n\nIf you want to contribute, a great place to start would be the\n`help-wanted\nissues <https://github.com/quantopian/alphalens/issues?q=is%3Aopen+is%3Aissue+label%3A%22help+wanted%22>`__.\n\nCredits\n-------\n\n-  `Andrew Campbell <https://github.com/a-campbell>`__\n-  `James Christopher <https://github.com/jameschristopher>`__\n-  `Thomas Wiecki <https://github.com/twiecki>`__\n-  `Jonathan Larkin <https://github.com/marketneutral>`__\n-  Jessica Stauth (jstauth@quantopian.com)\n-  `Taso Petridis <https://github.com/tasopetridis>`_\n\nFor a full list of contributors see the `contributors page. <https://github.com/quantopian/alphalens/graphs/contributors>`_\n\nExample Tear Sheet\n------------------\n\nExample factor courtesy of `ExtractAlpha <http://extractalpha.com/>`_\n\n.. image:: https://github.com/quantopian/alphalens/raw/master/alphalens/examples/table_tear.png\n.. image:: https://github.com/quantopian/alphalens/raw/master/alphalens/examples/returns_tear.png\n.. image:: https://github.com/quantopian/alphalens/raw/master/alphalens/examples/ic_tear.png\n.. image:: https://github.com/quantopian/alphalens/raw/master/alphalens/examples/sector_tear.png\n    :alt:",
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