{
    "info": {
        "author": "Jeffrey McLarty",
        "author_email": "jeffrey.mclarty@gmail.com",
        "bugtrack_url": null,
        "classifiers": [
            "Development Status :: 1 - Planning",
            "Intended Audience :: Developers",
            "Intended Audience :: Education",
            "Intended Audience :: Financial and Insurance Industry",
            "Intended Audience :: Healthcare Industry",
            "Intended Audience :: Science/Research",
            "License :: OSI Approved :: MIT License",
            "Operating System :: OS Independent",
            "Programming Language :: Python :: 2.7",
            "Topic :: Scientific/Engineering",
            "Topic :: Scientific/Engineering :: Mathematics"
        ],
        "description": "Sympa\n=====\n\n*Symbolic math for pandas.*\n\nDescription\n===========\n\nLinks symbolic expressions created using sympy to columns of data in pandas DataFrames.\nAny expression created with sympy, which can be \"lambdified\", will/should/might work. \n\nWarning\n=======\n\nThe API design for sympa is subject to change, depending on feedback, if any.\n\nUsage\n=====\n\n.. code:: python\n\n   from pandas import DataFrame\n   from sympy import symbols\n   from sympa import domath\n   \n   df = pd.DataFrame({'x' : [1,2,3,4] * 2, 'y' : [0.1, 0.2] * 4)\n   \n   # Notice x_-1 and x_-2 are used to reference x @ t=-1, and x @ t=-2.\n   x, xn1, xn2, y = symbols('x x_-1 x_-2 y')\n   \n   f = 3.0 * x ** 3 + 2.0 * xn1 ** 2 + xn2 + (y * 2) / 2\n   \n   df['f'] = domath(df,f)\n\nDocs\n====\n\nFor now, there isn't much documentation.  I think it's pretty straightforward.\nCheck out the /doc folder of the repo on github for more examples.\n\nRequirements\n============\n\n* Sympy >= 0.7.6 but should work with much older versions (untested).\n* Pandas >= 0.15 but should work with much older versions (untested).\n\nPython\n------\nWorks on 2.7, untested on all other versions.\nIt is expected to be ported to 3.4 soon, and likely 2.6 as well.\n\nInstall\n=======\n\n    pip install sympa",
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        "keywords": "symbolic,symbol,sympa,sympy,pandas,math",
        "license": "UNKNOWN",
        "maintainer": null,
        "maintainer_email": null,
        "name": "sympa",
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        "summary": "Symbolic math for pandas",
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