{
    "info": {
        "author": "Abraham Lee",
        "author_email": "tisimst@gmail.com",
        "bugtrack_url": null,
        "classifiers": [
            "Development Status :: 5 - Production/Stable",
            "Intended Audience :: Customer Service",
            "Intended Audience :: Developers",
            "Intended Audience :: Education",
            "Intended Audience :: End Users/Desktop",
            "Intended Audience :: Financial and Insurance Industry",
            "Intended Audience :: Healthcare Industry",
            "Intended Audience :: Information Technology",
            "Intended Audience :: Manufacturing",
            "Intended Audience :: Other Audience",
            "Intended Audience :: Science/Research",
            "Intended Audience :: System Administrators",
            "Intended Audience :: Telecommunications Industry",
            "License :: OSI Approved :: BSD License",
            "Natural Language :: English",
            "Operating System :: MacOS",
            "Operating System :: Microsoft :: Windows",
            "Operating System :: OS Independent",
            "Operating System :: POSIX :: Linux",
            "Operating System :: Unix",
            "Programming Language :: Python",
            "Topic :: Multimedia",
            "Topic :: Multimedia :: Graphics",
            "Topic :: Multimedia :: Graphics :: Presentation",
            "Topic :: Office/Business",
            "Topic :: Scientific/Engineering",
            "Topic :: Scientific/Engineering :: Information Analysis",
            "Topic :: Scientific/Engineering :: Visualization"
        ],
        "description": "===========\nparetochart\n===========\n\n`Pareto chart`_ for python (similar to `Matlab`_, but much more flexible).\n\nFeatures\n--------\n\n- **Data labels** for the chart x-axis.\n- **Fully customizable** with unique ``arg`` and ``kwarg`` inputs:\n   - *Bar chart*: follows the inputs of the `matplotlib.pyplot.bar`_ \n     function (use ``bar_args=(...)`` and ``bar_kw={...}``).\n   - *Cumulative line*: follows the inputs of the `matplotlib.pyplot.plot`_ \n     function (use ``line_args=(...)`` and ``line_kw={...}``).\n   - *Limit line*: follows the inputs of the `matplotlib.axes.Axes.axhline`_ \n     function (use ``limit_kw={...}``).\n- Put the chart on **arbitrary axes**.\n\nExamples\n--------\nFirst, a simple import::\n     \n    from paretochart import pareto\n\nNow, let's create the numeric data (no pre-sorting necessary)::\n\n    data = [21, 2, 10, 4, 16]\n     \nWe can even assign x-axis labels (in the same order as the data)::\n\n    labels = ['tom', 'betty', 'alyson', 'john', 'bob']\n\nFor this example, we'll create 4 plots that show the customization \ncapabilities::\n\n    import matplotlib.pyplot as plt\n\n    # create a grid of subplots\n    fig, axes = plt.subplots(2, 2)\n    \nThe first plot will be the simplest usage, with just the data::\n    \n    pareto(data, axes=axes[0, 0])\n    plt.title('Basic chart without labels', fontsize=10)\n    \nIn the second plot, we'll add labels, put a cumulative limit at 0.75 (or 75%) \nand turn the cumulative line green::\n\n    pareto(data, labels, axes=axes[0, 1], limit=0.75, line_args=('g',))\n    plt.title('Data with labels, green cum. line, limit=0.75', fontsize=10)\n    \nIn the third plot, we'll remove the cumulative line and limit line, make the\nbars green and resize them to a width of 0.5::\n\n    pareto(data, labels, cumplot=False, axes=axes[1, 0], data_kw={'width': 0.5,\n        'color': 'g'})\n    plt.title('Data without cum. line, green bar width=0.5', fontsize=10)\n    \nIn the fourth plot, let's put the cumulative limit at 95% and make that line\nyellow::\n\n    pareto(data, labels, limit=0.95, axes=axes[1, 1], limit_kw={'color': 'y'})\n    plt.title('Data trimmed at 95%, yellow limit line', fontsize=10)\n\nAnd last, but not least, let's show the image::\n\n    fig.canvas.set_window_title('Pareto Plot Test Figure')\n    plt.show()\n\nThis should result in the following image (`click here`_ if the image doesn't \nshow up):\n\n.. image:: https://raw.github.com/tisimst/paretochart/master/pareto_plot_test_figure.png\n   :scale: 75%\n\nInstallation\n------------\n\nSince this is really a single python file, you can simply go to the \nGitHub_ page, simply download ``paretochart.py`` and put it in \na directory that python can find it.\n\nAlternatively, the file can be installed using::\n\n    $ pip install --upgrade paretochart\n\nor::\n    \n    $ easy_install --upgrade paretochart\n\nIf you are using Python3, download the compressed file from here, unzip and run::\n\n    $ 2to3 -w *.py\n    \nwhile in the unzipped directory, *then* run::\n\n    $ python3 setup.py install\n\n**NOTE:** *Administrative privileges may be required to perform any of \nthe above install methods.*\n\nContact\n-------\n\nPlease send **feature requests, bug reports, or feedback** to `Abraham Lee`_.\n\n.. _Pareto chart: http://en.wikipedia.org/wiki/Pareto_chart\n.. _Matlab: http://www.mathworks.com/help/matlab/ref/pareto.html\n.. _matplotlib.pyplot.bar: http://matplotlib.org/api/pyplot_api.html#matplotlib.pyplot.bar\n.. _matplotlib.pyplot.plot: http://matplotlib.org/api/pyplot_api.html#matplotlib.pyplot.plot\n.. _matplotlib.axes.Axes.axhline: http://matplotlib.org/api/axes_api.html#matplotlib.axes.Axes.axhline\n.. _Abraham Lee: mailto:tisimst@gmail.com\n.. _GitHub: https://github.com/tisimst/paretochart\n.. _click here: https://github.com/tisimst/paretochart/master/pareto_plot_test_figure.png",
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        "keywords": "matplotlib,pareto,chart,plot,quality,economics,manufacturing",
        "license": "BSD License",
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