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        "author": "Open Knowledge Foundation",
        "author_email": "info@okfn.org",
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        "classifiers": [
            "Development Status :: 4 - Beta",
            "Intended Audience :: Developers",
            "Intended Audience :: Science/Research",
            "License :: OSI Approved :: GNU Lesser General Public License v3 or later (LGPLv3+)",
            "Operating System :: OS Independent",
            "Programming Language :: Python :: 2",
            "Programming Language :: Python :: 2.7",
            "Programming Language :: Python :: 3",
            "Programming Language :: Python :: 3.4",
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            "Topic :: Scientific/Engineering :: Information Analysis",
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        "description": "jsontableschema-pandas\n======================\n\n| |Travis|\n| |Coveralls|\n| |PyPi|\n| |SemVer|\n| |Gitter|\n\nGenerate and load Pandas data frames based on JSON Table Schema\ndescriptors.\n\n    Version ``v0.2`` contains breaking changes:\n\n-  removed ``Storage(prefix=)`` argument (was a stub)\n-  renamed ``Storage(tables=)`` to ``Storage(dataframes=)``\n-  renamed ``Storage.tables`` to ``Storage.buckets``\n-  changed ``Storage.read`` to read into memory\n-  added ``Storage.iter`` to yield row by row\n\nGetting Started\n---------------\n\nInstallation\n~~~~~~~~~~~~\n\n::\n\n    $ pip install datapackage\n    $ pip install jsontableschema-pandas\n\nExample\n~~~~~~~\n\nYou can easily load resources from a data package as Pandas data frames\nby simply using ``datapackage.push_datapackage`` function:\n\n.. code:: python\n\n    >>> import datapackage\n\n    >>> data_url = 'http://data.okfn.org/data/core/country-list/datapackage.json'\n    >>> storage = datapackage.push_datapackage(data_url, 'pandas')\n\n    >>> storage.buckets\n    ['data___data']\n\n    >>> type(storage['data___data'])\n    <class 'pandas.core.frame.DataFrame'>\n\n    >>> storage['data___data'].head()\n                 Name Code\n    0     Afghanistan   AF\n    1   \u00c5land Islands   AX\n    2         Albania   AL\n    3         Algeria   DZ\n    4  American Samoa   AS\n\nAlso it is possible to pull your existing data frame into a data\npackage:\n\n.. code:: python\n\n    >>> datapackage.pull_datapackage('/tmp/datapackage.json', 'country_list', 'pandas', tables={\n    ...     'data': storage['data___data'],\n    ... })\n    Storage\n\nStorage\n~~~~~~~\n\nPackage implements `Tabular\nStorage <https://github.com/frictionlessdata/jsontableschema-py#storage>`__\ninterface.\n\nWe can get storage this way:\n\n.. code:: python\n\n    >>> from jsontableschema_pandas import Storage\n\n    >>> storage = Storage()\n\nStorage works as a container for Pandas data frames. You can define new\ndata frame inside storage using ``storage.create`` method:\n\n.. code:: python\n\n    >>> storage.create('data', {\n    ...     'primaryKey': 'id',\n    ...     'fields': [\n    ...         {'name': 'id', 'type': 'integer'},\n    ...         {'name': 'comment', 'type': 'string'},\n    ...     ]\n    ... })\n\n    >>> storage.buckets\n    ['data']\n\n    >>> storage['data'].shape\n    (0, 0)\n\nUse ``storage.write`` to populate data frame with data:\n\n.. code:: python\n\n    >>> storage.write('data', [(1, 'a'), (2, 'b')])\n\n    >>> storage['data']\n    id comment\n    1        a\n    2        b\n\nAlso you can use\n`tabulator <https://github.com/frictionlessdata/tabulator-py>`__ to\npopulate data frame from external data file:\n\n.. code:: python\n\n    >>> import tabulator\n\n    >>> with tabulator.Stream('data/comments.csv', headers=1) as stream:\n    ...     storage.write('data', stream)\n\n    >>> storage['data']\n    id comment\n    1        a\n    2        b\n    1     good\n\nAs you see, subsequent writes simply appends new data on top of existing\nones.\n\nAPI Reference\n-------------\n\nSnapshot\n~~~~~~~~\n\nhttps://github.com/frictionlessdata/jsontableschema-py#snapshot\n\nDetailed\n~~~~~~~~\n\n-  `Docstrings <https://github.com/frictionlessdata/jsontableschema-py/tree/master/jsontableschema/storage.py>`__\n-  `Changelog <https://github.com/frictionlessdata/jsontableschema-pandas-py/commits/master>`__\n\nContributing\n------------\n\nPlease read the contribution guideline:\n\n`How to Contribute <CONTRIBUTING.md>`__\n\nThanks!\n\n.. |Travis| image:: https://img.shields.io/travis/frictionlessdata/jsontableschema-pandas-py/master.svg\n   :target: https://travis-ci.org/frictionlessdata/jsontableschema-pandas-py\n.. |Coveralls| image:: http://img.shields.io/coveralls/frictionlessdata/jsontableschema-pandas-py.svg?branch=master\n   :target: https://coveralls.io/r/frictionlessdata/jsontableschema-pandas-py?branch=master\n.. |PyPi| image:: https://img.shields.io/pypi/v/jsontableschema-pandas.svg\n   :target: https://pypi.python.org/pypi/jsontableschema-pandas\n.. |SemVer| image:: https://img.shields.io/badge/versions-SemVer-brightgreen.svg\n   :target: http://semver.org/\n.. |Gitter| image:: https://img.shields.io/gitter/room/frictionlessdata/chat.svg\n   :target: https://gitter.im/frictionlessdata/chat\n\n",
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