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    "info": {
        "author": "John Volk",
        "author_email": "john.volk@dri.edu",
        "bugtrack_url": null,
        "classifiers": [
            "Development Status :: 4 - Beta",
            "Environment :: Console",
            "Intended Audience :: Science/Research",
            "License :: OSI Approved :: BSD License",
            "Programming Language :: Python :: 3.7",
            "Topic :: Scientific/Engineering"
        ],
        "description": "Rosely\n======\n\nInteractive windroses using pandas and plotly\n\n\n``Rosely`` leverages the polar bar char of `Plotly <https://plot.ly/python/>`__ and `pandas <https://pandas.pydata.org/>`__ to simplyfy the creation of beautiful and interactive windrose diagrams. This package was inspired by the Plotly polar bar chart with hoverable tooltips, zoom, pan, and other interactive features.``Rosely``'s main purpose is to make use of the Plotly polar bar chart more accessable and efficient for custom workflows using pandas and a simple object-oriented implementation.\n\nDocumentation \n-------------\n\nComing soon.\n\n\nInstallation\n------------\n\n``Rosely``'s dependencies are Python 3.4+, NumPy, pandas, and Plotly.\n\nYou may install the dependencies using the conda virtual environment (recommended), the environment file can be downloaded `here <https://raw.githubusercontent.com/JohnVolk/Rosely/master/environment.yml>`__ and installed and activated by\n\n.. code-block:: bash\n\n   conda env create -f environment.yml\n   conda activate rosely\n\nOnce activated install with PIP:\n\n.. code-block:: bash\n\n   pip install rosely\n\n\nQuick start\n-----------\n\nGiven arbitrary time series data that contains wind speed and direction (degrees) ``Rosely`` can quickly produce wind statistics and interactive windrose diagrams once the data is loaded into a `pandas.DataFrame <https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.html>`__.\n\nThis example uses the `provided example CSV <https://raw.githubusercontent.com/JohnVolk/Rosely/master/example/test_data.csv>`_ containing meterological data.\n\n    >>> import pandas as pd\n    >>> from rosely import WindRose\n    >>> df = pd.read_csv('path/to/example_data.csv')\n    >>> # make a WindRose object from the dataframe with \"ws\" and \"wd\" columns\n    >>> WR = WindRose(df)\n    >>> WR.plot(\n    >>>     template='seaborn', colors='Plotly3', \n    >>>     title='Twitchell Island, California'\n    >>> )\n\nThe resulting windrose diagram saved as a png (download `this file <https://raw.githubusercontent.com/JohnVolk/Rosely/master/docs/source/_static/quickstart.html>`_ for an interactive example):\n\n.. image:: https://raw.githubusercontent.com/JohnVolk/Rosely/master/docs/source/_static/quickstart.png\n   :align: center\n\nDetails and examples of plot customization, output options, and windrose calculation options can be found in the online documentation. \n\n\n\n",
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        "license": "BSD3",
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        "name": "Rosely",
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