{
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        "author": "Michael Vilim",
        "author_email": "michael.vilim@gmail.com",
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        "description": "<!--\nCopyright (c) 2019 Michael Vilim\n\nThis file is part of the bamboo library. It is currently hosted at\nhttps://github.com/mvilim/bamboo\n\nLicensed under the Apache License, Version 2.0 (the \"License\");\nyou may not use this file except in compliance with the License.\nYou may obtain a copy of the License at\n\n   http://www.apache.org/licenses/LICENSE-2.0\n\nUnless required by applicable law or agreed to in writing, software\ndistributed under the License is distributed on an \"AS IS\" BASIS,\nWITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\nSee the License for the specific language governing permissions and\nlimitations under the License.\n-->\n\n## bamboo\n\n[![PyPI Release](https://img.shields.io/pypi/v/bamboo-nested.svg)](https://pypi.org/project/bamboo-nested/)\n[![Build Status](https://travis-ci.org/mvilim/bamboo.svg?branch=master)](https://travis-ci.org/mvilim/bamboo)\n\nbamboo is a library for feeding nested data formats into pandas. The space of data representable in nested formats is larger than the space covered by pandas. pandas supports only data representable in a flat table (though things like multi-indexs allows certain types of tree formats to be efficiently projected into a table). Data which supports arbitrary nesting is not in general convertible to a pandas dataframe. In particular, data which contains multiple repetition structures (e.g. JSON arrays) that are not nested within each other will not be flattenable into a table.\n\nThe current data formats supported are:\n* JSON\n* Apache Avro\n* Apache Arrow\n* Profobuf (via [PBD](https://github.com/mvilim/pbd))\n\nbamboo works by projecting a flattenable portion (a subset of the nested columns) of the data into a pandas dataframe. By projecting various combinations of columns, one can make use of all the relationships implied by the nested structure of the data.\n\n### Installation\n\nTo install from PyPI:\n\n```\npip install bamboo-nested\n```\n\n### Example\n\nA minimal example of flattening a JSON string:\n\n```\nfrom bamboo import from_json\n\nobj = [{'a': None, 'b': [1, 2], 'c': [5, 6]}, {'a': -1.0, 'b': [3, 4], 'c': [7, 8]}]\nnode = from_json(json.dumps(obj))\n    > - a float64\n    > - b []uint64\n    > - c []uint64\n```\n\nFlattening just the values of column `a`:\n\n```\ndf_a = node.flatten(include=['a'])\n    >      a\n    > 0  NaN\n    > 1 -1.0\n```\n\nFlattening columns `a` and `b` (note that column `a` is repeated to match the corresponding elements of column `b`):\n\n```\ndf_ab = node.flatten(include=['a', 'b'])\n    >      a  b\n    > 0  NaN  1\n    > 1  NaN  2\n    > 2 -1.0  3\n    > 3 -1.0  4\n```\n\nTrying to flatten two repetition lists at the same level will lead to an error (as this structure is unflattenable without taking a Cartesian product):\n\n```\ndf_bc = node.flatten(include=['b', 'c'])\n    > ValueError: Attempted to flatten conflicting lists\n```\n\n### Building\n\nTo build this project:\n\nBuilding from source requires cmake (`pip install cmake`) and Boost.\n\n```\npython setup.py\n```\n\n### Unit tests\n\nTo run the unit tests:\n\n```\npython setup.py test\n```\n\nor use nose:\n\n```\nnosetests python/bamboo/tests\n```\n\n### Licensing\n\nThis project is licensed under the [Apache 2.0 License](https://github.com/mvilim/bamboo/blob/master/LICENSE). It uses the pybind11, Arrow, Avro, nlohmann JSON, and PBD projects. The licenses can be found in those [projects' directories](https://github.com/mvilim/bamboo/blob/master/cpp/thirdparty).\n\n\n",
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