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        "author": "Ran Aroussi",
        "author_email": "ran@aroussi.com",
        "bugtrack_url": null,
        "classifiers": [
            "Development Status :: 3 - Alpha",
            "Intended Audience :: Developers",
            "License :: OSI Approved :: GNU Lesser General Public License v3 (LGPLv3)",
            "Operating System :: OS Independent",
            "Programming Language :: Python :: 3.4",
            "Programming Language :: Python :: 3.5",
            "Programming Language :: Python :: 3.6",
            "Topic :: Office/Business :: Financial",
            "Topic :: Office/Business :: Financial :: Investment",
            "Topic :: Scientific/Engineering :: Interface Engine/Protocol Translator",
            "Topic :: Software Development :: Libraries",
            "Topic :: Software Development :: Libraries :: Python Modules"
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        "description": "Monte Carlo Simulator for Pandas Series\n=======================================\n\n.. image:: https://img.shields.io/pypi/pyversions/pandas-montecarlo.svg?maxAge=60\n    :target: https://pypi.python.org/pypi/pandas-montecarlo\n    :alt: Python version\n\n.. image:: https://img.shields.io/travis/ranaroussi/pandas-montecarlo/master.svg?\n    :target: https://travis-ci.org/ranaroussi/pandas-montecarlo\n    :alt: Travis-CI build status\n\n.. image:: https://img.shields.io/pypi/v/pandas-montecarlo.svg?maxAge=60\n    :target: https://pypi.python.org/pypi/pandas-montecarlo\n    :alt: PyPi version\n\n.. image:: https://img.shields.io/pypi/status/pandas-montecarlo.svg?maxAge=60\n    :target: https://pypi.python.org/pypi/pandas-montecarlo\n    :alt: PyPi status\n\n.. image:: https://img.shields.io/github/stars/ranaroussi/pandas-montecarlo.svg?style=social&label=Star&maxAge=60\n    :target: https://github.com/ranaroussi/pandas-montecarlo\n    :alt: Star this repo\n\n.. image:: https://img.shields.io/twitter/follow/aroussi.svg?style=social&label=Follow%20Me&maxAge=60\n    :target: https://twitter.com/aroussi\n    :alt: Follow me on twitter\n\n\\\n\n**pandas-montecarlo** is a lightweight Python library for running simple\n`Monte Carlo Simulations <https://en.wikipedia.org/wiki/Monte_Carlo_method>`_ on Pandas Series data.\n\n`Changelog \u00bb <./CHANGELOG.rst>`__\n\n-----\n\nQuick Start\n-----------\n\nLet's run a monte carlo simulation on the returns of `SPY <https://finance.yahoo.com/quote/SPY>`_ (S&P 500 Spider ETF).\n\nFirst, let's download SPY's data and calculate the daily returns.\n\n.. code:: python\n\n    from pandas_datareader import data\n\n    df = data.get_data_yahoo(\"SPY\")\n    df['return'] = df['Adj Close'].pct_change().fillna(0)\n\nNext, we'll import ``pandas_montecarlo`` and run monte carlo simulation\nwith 10 simulations (for demo simplifications) and bust/max drawdown set to ``-10.0%``\nand goal threshhold set to ``+100.0%`` (defaults is ``>=0%``):\n\n.. code:: python\n\n    import pandas_montecarlo\n    mc = df['return'].montecarlo(sims=10, bust=-0.1, goal=1)\n\n\n**Plot simulations**\n\n.. code:: python\n\n    mc.plot(title=\"SPY Returns Monte Carlo Simulations\")  # optional: , figsize=(x, y)\n\n.. image:: https://raw.githubusercontent.com/ranaroussi/pandas-montecarlo/master/demo.png\n   :width: 640 px\n   :height: 360 px\n   :alt: demo\n\n\n**Show test stats**\n\n.. code:: python\n\n    print(mc.stats)\n\n    # prints\n    {\n        'min':    0.98088401987146789,\n        'max':    0.98088401987146934,\n        'mean':   0.98088401987146911,\n        'median': 0.98088401987146911,\n        'std':    4.0792198665315552e-16,\n        'maxdd': -0.17221175099828012,  # max drawdown\n        'bust':   0.2,  # probability of going bust\n        'goal':   0.0   # probability of reaching 100% goal\n    }\n\n**Show bust / max drawdown stats**\n\n.. code:: python\n\n    print(mc.maxdd)\n\n    # prints\n    {\n        'min':    -0.27743285515585991,\n        'max':    -0.00031922711279186444,\n        'mean':   -0.07888087155686732,\n        'median': -0.06010335858432081,\n        'std':     0.062172124557467685\n    }\n\n**Access raw simulations' DataFrame**\n\n.. code:: python\n\n    print(mc.data.head())\n\n.. code:: text\n\n        original          1          2          3          4  ...       10\n    0   0.000000   0.017745  -0.002586  -0.005346  -0.042107  ...  0.00139\n    1   0.002647   0.000050   0.000188   0.010141   0.007443  ...  0.00108\n    2   0.000704   0.002916   0.005324   0.000073  -0.003238  ...  0.00071\n    3   0.004221   0.008564   0.001397   0.007950  -0.006392  ...  0.00902\n    4   0.003328  -0.000511   0.005123   0.013491  -0.005105  ...  0.00252\n\n\nInstallation\n------------\n\nInstall ``pandas_montecarlo`` using ``pip``:\n\n.. code:: bash\n\n    $ pip install pandas_montecarlo --upgrade --no-cache-dir\n\nRequirements\n------------\n\n* `Python <https://www.python.org>`_ >=3.4\n* `Pandas <https://github.com/pydata/pandas>`_ (tested to work with >=0.18.1)\n* `Matplotlib <https://matplotlib.org>`_ (tested to work with >=1.5.3)\n\n\nLegal Stuff\n------------\n\n**pandas-montecarlo** is distributed under the **GNU Lesser General Public License v3.0**. See the `LICENSE.txt <./LICENSE.txt>`_ file in the release for details.\n\n\nP.S.\n------------\n\nPlease drop me an note with any feedback you have.\n\n**Ran Aroussi**\n",
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