{
    "info": {
        "author": "CorrelAid",
        "author_email": "packages@correlaid.org",
        "bugtrack_url": null,
        "classifiers": [
            "Development Status :: 4 - Beta",
            "Intended Audience :: Developers",
            "Intended Audience :: Education",
            "Intended Audience :: Other Audience",
            "Intended Audience :: Science/Research",
            "License :: OSI Approved :: MIT License",
            "Natural Language :: English",
            "Natural Language :: German",
            "Operating System :: OS Independent",
            "Programming Language :: Python :: 3.6",
            "Programming Language :: Python :: 3.7",
            "Topic :: Education",
            "Topic :: Sociology"
        ],
        "description": "Datenguide Python\n=================\n\n.. image:: https://img.shields.io/pypi/v/datenguidepy.svg\n        :target: https://pypi.python.org/pypi/datenguidepy\n\n.. image:: https://img.shields.io/travis/CorrelAid/datenguide-python.svg\n        :target: https://travis-ci.org/CorrelAid/datenguide-python\n\n.. image:: https://readthedocs.org/projects/datenguidepy/badge/?version=latest\n        :target: https://datenguidepy.readthedocs.io/en/latest/readme/#quick-start\n\n.. image:: https://mybinder.org/badge_logo.svg\n :target: https://mybinder.org/v2/gh/CorrelAid/datenguide-python/master?filepath=use_case\n \n* Free software: MIT license\n* Documentation:  https://datenguidepy.readthedocs.io/\n\nThe package provides easy access to German publicly available `regional statistics`_.\nIt does so by providing a wrapper for the `GraphQL API of the Datenguide project`_.\n\n\nFeatures\n--------\n\n**Overview of available statistics and regions:**\n  The package provides DataFrames with the available statistics and regions, which\n  can be queried by the user without having to refer to expert knowledge on regional\n  statistics or the documentation of the underlying GraphQL API\n\n**Build and Execute Queries:**\n  The package provides the user an object oriented interface to build queries that\n  fetch certain statistics and return the results as a pandas DataFrame for\n  further analysis.\n  \n**Automatic inclusion of relevant meta data**\n  Queries automatically retrieve some meta data along with the actual data\n  to give the user more convenient access to the statistics without having to worry\n  about too many technichal details\n  \n**Full fidelity data**\n  The package provides full fidelity data access to the datenguide API.\n  This allows all use cases to use precicely the data that they need\n  if it is available. It also means that most data cleaning has to be done\n  by the user.\n\nQuick Start\n-----------\n\n============\nInstall\n============\nTo use the package install the package (command line): \n\n.. code-block:: python\n\n   pip install datenguidepy\n   \n===============\nMinimal example\n===============\nTo see the package work and obtain a DataFrame containing\nsome statistics, the followin constitutes a minimal example.\n\n.. code-block:: python\n\n    from datenguidepy import Query\n    \n    q = Query.region('01')\n    q.add_field('BEV001')\n    result_df = q.results()\n    \n    \n================\nComplex examples\n================\n\nThese examples is intendend to illustrate many\nof the package's features at the same time. The\nidea is to give an impression of some of the possibilities.\nA more detailed explanation of the functionality can be found\nin the the rest of the documentation.\n\n.. code-block:: python\n\n    q = Query.region(['02','11'])\n    stat = q.add_field('BEVSTD')\n    stat.add_args({'year' : [2011,2012]})\n    stat2 = q.add_field('AI1601')\n    stat2.add_args({'year' : [2011,2012]})\n    q.results(\n        verbose_statistics = True,\n        add_units = True,\n    ).iloc[:,:7]\n    \n====  ====  =======  ======  =============================================  =============  ============================  =============\n  ..    id  name       year    Verf\u00fcgbares Einkommen je Einwohner (AI1601)  AI1601_unit      Bev\u00f6lkerungsstand (BEVSTD)  BEVSTD_unit\n====  ====  =======  ======  =============================================  =============  ============================  =============\n   0    02  Hamburg    2011                                          22695  EUR                                 1718187  Anzahl\n   1    02  Hamburg    2012                                          22971  EUR                                 1734272  Anzahl\n   0    11  Berlin     2011                                          18183  EUR                                 3326002  Anzahl\n   1    11  Berlin     2012                                          18380  EUR                                 3375222  Anzahl\n====  ====  =======  ======  =============================================  =============  ============================  =============\n\n.. code-block:: python\n \n    q = Query.region('11')\n    stat = q.add_field('BEVSTD')\n    stat.add_args({\n        'GES' : 'GESW',\n        'statistics' : 'R12411',\n        'NAT' : 'ALL',\n        'year' : [1995,1996]\n    })\n    stat.add_field('GES')\n    stat.add_field('NAT')\n    q.results(verbose_enums = True).iloc[:,:6]\n    \n====  ====  ======  ========  ================  ======  ========\n  ..    id  name    GES       NAT                 year    BEVSTD\n====  ====  ======  ========  ================  ======  ========\n   0    11  Berlin  weiblich  Ausl\u00e4nder(innen)    1995    191378\n   1    11  Berlin  weiblich  Deutsche            1995   1605762\n   2    11  Berlin  weiblich  Gesamt              1995   1797140\n   3    11  Berlin  weiblich  Deutsche            1996   1590407\n   4    11  Berlin  weiblich  Ausl\u00e4nder(innen)    1996    195301\n   5    11  Berlin  weiblich  Gesamt              1996   1785708\n====  ====  ======  ========  ================  ======  ========\n\n\n\n\n=======================================\nGet information on fields and meta data\n=======================================\n\n**Get information on region ids**\n\n.. code-block:: python\n\n   # from datenguidepy import get_regions\n\n    get_regions()\n\nUse pandas *query()* functionality to get specific regions. E.g., if you want to get all IDs on \"Bundel\u00e4nder\" use.\nFor more information on \"nuts\" levels see Wikipedia_.\n\n.. code-block:: python\n\n    get_regions().query(\"level == 'nuts1'\")\n\n\n\n**Get information on statistic shortnames**\n\n.. code-block:: python\n\n  #  from datenguidepy import get_statistics\n\n    get_statistics()\n    # return statistical descriptions in English\n    get_statistics(target_language = 'en')\n\n**Get information on single fields**\n\nYou can further information about description, possible arguments, fields and enum values on a field you added to a query.\n\n.. code-block:: python\n\n    q = Query.region(\"01\")\n    stat = q.add_field(\"BEV001\")\n    stat.get_info()\n\n===================\nFurther information\n===================\n\nFor detailed examples see the notebooks within the use_case_ folder.\n\nFor a detailed documentation of all statistics and fields see the Datenguide API.\n\n\n\nCredits\n-------\nAll this builds on the great work of Datenguide_ and their GraphQL API `datenguide/datenguide-api`_ \n\nThe data is retrieved via the Datenguide API from the \"Statistische \u00c4mter des Bundes und der L\u00e4nder\". \nData being used via this package has to be `credited according to the \"Datenlizenz Deutschland \u2013 Namensnennung \u2013 Version 2.0\"`_.\n\nThis package was created with Cookiecutter_ and the `audreyr/cookiecutter-pypackage`_ project template.\n\n.. _Cookiecutter: https://github.com/audreyr/cookiecutter\n.. _`audreyr/cookiecutter-pypackage`: https://github.com/audreyr/cookiecutter-pypackage\n.. _`datenguide/datenguide-api`: https://github.com/datenguide/datenguide-api\n.. _Datenguide: https://datengui.de/\n.. _`GraphQL API of the Datenguide project`: https://github.com/datenguide/datenguide-api\n.. _`regional statistics`: https://www.regionalstatistik.de/genesis/online/logon\n.. _use_case: https://github.com/CorrelAid/datenguide-python/tree/master/use_case\n.. _`credited according to the \"Datenlizenz Deutschland \u2013 Namensnennung \u2013 Version 2.0\"`: https://www.regionalstatistik.de/genesis/online;sid=C636A83329D19AF20E3A4F9E767576A9.reg2?Menu=Impressum\n.. _Wikipedia: https://de.wikipedia.org/wiki/NUTS:DE#Liste_der_NUTS-Regionen_in_Deutschland_(NUTS_2016)\n\n\n=======\nHistory\n=======\n\n0.1.0 (2019-10-07)\n------------------\n\n* First release on PyPI.\n\n0.1.1 (2019-10-09)\n------------------\n\n* Cleanup of the first release regarding naming, authors and docs.\n\n0.2.0 (2020-11-30)\n------------------\n\n* Added functionality to use meta data for displaying descriptive statistics names and enum values\n\n0.2.1 (2020-05-17)\n------------------\n* Added functionality to display the units of a statistic along with the numerical value.\n* Internally split the meta data extraction into technical meta data and meta data about the statistics. Implemented new defaults for the statistics meta data in order to account for changes in the datenguide API.\n\n0.2.2 (2020-05-24)\n------------------\n* Fixed a critical bug in the package data perventing the pypi version to essentially stop working completely.\n* Fixed a bug related to incorrectly displayed version number of the package.\n\n0.3.0 (2020-06-24)\n------------------\n* renamed get_all_regions to get_regions in accordance with get_statistics \n* changed the index column name of the DataFrame returnd by all_regions from id to region_id\n* made the statstics column name the index in the DataFrame returned by get_statistics and renamed it to statistic\n* added functionality to obtain a stored auto-translated version of the get_statistics descriptions (default is German, now machine translation is available in English)\n* introduced a new helper function get_availability_summary containing a (pre-calculated) summary of available data for region_id, statistic pairs down to nut3 level.\n\n0.3.1 (2020-07-14)\n------------------\n* Introduced a better error messages for queries that are run without a statistic\n* Bug fixes related to enums and auto join functionality\n\n0.4.0 (2021-01-23)\n------------------\n* Introduced better error messages in case of invalid regions\n* Introduced duplicate removal as an option for standard query results\n  * New default is to remove duplicates but can be turned of with an argument\n  * Auto-joining of multiple statistics should work better now as duplicates are removed before the joining.\n  * Purpouse is only to remove duplicates that that may exist for technichal API reasons. The Purpouse is not to filter the data for content.\n  * Rows are only counted as duplaces if everything, including the data source is identical\n\n0.4.1 (2021-08-01)\n------------------\n* Bugfixe",
        "description_content_type": "",
        "docs_url": null,
        "download_url": "",
        "downloads": {
            "last_day": -1,
            "last_month": -1,
            "last_week": -1
        },
        "home_page": "https://github.com/CorrelAid/datenguide-python",
        "keywords": "datenguidepy",
        "license": "MIT license",
        "maintainer": "",
        "maintainer_email": "",
        "name": "datenguidepy",
        "package_url": "https://pypi.org/project/datenguidepy/",
        "platform": "",
        "project_url": "https://pypi.org/project/datenguidepy/",
        "project_urls": {
            "Homepage": "https://github.com/CorrelAid/datenguide-python"
        },
        "release_url": "https://pypi.org/project/datenguidepy/0.4.1/",
        "requires_dist": null,
        "requires_python": "",
        "summary": "Provids easy access to German publically availible regional statistics",
        "version": "0.4.1",
        "yanked": false,
        "yanked_reason": null
    },
    "last_serial": 11063931,
    "releases": {
        "0.1.0": [
            {
                "comment_text": "",
                "digests": {
                    "md5": "1ccd75561ee0e5de838fff1038d97c7d",
                    "sha256": "c26e50c31cff48e33a7d36bd0dd0c8a6e65aa3dd70f3dfe8d40afca11d56fde9"
                },
                "downloads": -1,
                "filename": "datenguidepy-0.1.0.tar.gz",
                "has_sig": false,
                "md5_digest": "1ccd75561ee0e5de838fff1038d97c7d",
                "packagetype": "sdist",
                "python_version": "source",
                "requires_python": null,
                "size": 142381,
                "upload_time": "2019-10-07T19:25:58",
                "upload_time_iso_8601": "2019-10-07T19:25:58.243294Z",
                "url": "https://files.pythonhosted.org/packages/d2/bf/d04ac7be7d56bfa03df44fb3d9b2a36da6d4dc675aaad644232da9699c6c/datenguidepy-0.1.0.tar.gz",
                "yanked": false,
                "yanked_reason": null
            }
        ],
        "0.1.1": [
            {
                "comment_text": "",
                "digests": {
                    "md5": "9b7aed301b43ebfaceaceba52dac99d1",
                    "sha256": "98459461b54294c621e87204f58b93b4be122c63d3897c2d2f36f1ac8bcd979d"
                },
                "downloads": -1,
                "filename": "datenguidepy-0.1.1-py2.py3-none-any.whl",
                "has_sig": false,
                "md5_digest": "9b7aed301b43ebfaceaceba52dac99d1",
                "packagetype": "bdist_wheel",
                "python_version": "py2.py3",
                "requires_python": null,
                "size": 130028,
                "upload_time": "2019-10-09T17:39:48",
                "upload_time_iso_8601": "2019-10-09T17:39:48.430429Z",
                "url": "https://files.pythonhosted.org/packages/cb/e8/74496026e8a6babc3b56e41f301b0e9db17dfdd0f6134de9f1326e1e05ae/datenguidepy-0.1.1-py2.py3-none-any.whl",
                "yanked": false,
                "yanked_reason": null
            },
            {
                "comment_text": "",
                "digests": {
                    "md5": "21bfd030b5194c3d4e6709fe88a0070f",
                    "sha256": "9698586e986484c19b5db6c17fc4c9df2fb619004229924027e1d918721e587d"
                },
                "downloads": -1,
                "filename": "datenguidepy-0.1.1.tar.gz",
                "has_sig": false,
                "md5_digest": "21bfd030b5194c3d4e6709fe88a0070f",
                "packagetype": "sdist",
                "python_version": "source",
                "requires_python": null,
                "size": 142835,
                "upload_time": "2019-10-09T17:39:50",
                "upload_time_iso_8601": "2019-10-09T17:39:50.877894Z",
                "url": "https://files.pythonhosted.org/packages/17/53/88e50db79d9612b622f2f0b4d939b6ce4764f8811d84ef4a902d6e5b574b/datenguidepy-0.1.1.tar.gz",
                "yanked": false,
                "yanked_reason": null
            }
        ],
        "0.1.2": [
            {
                "comment_text": "",
                "digests": {
                    "md5": "aa7c6fa9ffcfaabc92aa070e709f2049",
                    "sha256": "e7c4a527d558760d1ec42d042802843089a435735131574763c7bed7b844a02f"
                },
                "downloads": -1,
                "filename": "datenguidepy-0.1.2.tar.gz",
                "has_sig": false,
                "md5_digest": "aa7c6fa9ffcfaabc92aa070e709f2049",
                "packagetype": "sdist",
                "python_version": "source",
                "requires_python": null,
                "size": 151787,
                "upload_time": "2019-10-26T06:37:29",
                "upload_time_iso_8601": "2019-10-26T06:37:29.451912Z",
                "url": "https://files.pythonhosted.org/packages/b4/46/1ab1ae814ea108c73af90f5285773ddf39f3a8a2b58201dabb520f0301b5/datenguidepy-0.1.2.tar.gz",
                "yanked": false,
                "yanked_reason": null
            }
        ],
        "0.2.0": [
            {
                "comment_text": "",
                "digests": {
                    "md5": "7ddb91767cf5395295f87f2c08ca8e2f",
                    "sha256": "897d992c1b98eb7222bd5225383a8a98ef2f0424307223a50d2637ca4b7957d5"
                },
                "downloads": -1,
                "filename": "datenguidepy-0.2.0.tar.gz",
                "has_sig": false,
                "md5_digest": "7ddb91767cf5395295f87f2c08ca8e2f",
                "packagetype": "sdist",
                "python_version": "source",
                "requires_python": null,
                "size": 155246,
                "upload_time": "2019-11-30T06:06:29",
                "upload_time_iso_8601": "2019-11-30T06:06:29.372877Z",
                "url": "https://files.pythonhosted.org/packages/20/a4/3f536fc3d4dc511295679e7e126df56c9dff0a2033c8cb4cce0195453745/datenguidepy-0.2.0.tar.gz",
                "yanked": false,
                "yanked_reason": null
            }
        ],
        "0.2.1": [
            {
                "comment_text": "",
                "digests": {
                    "md5": "609f29f5153786311253049fb782a04e",
                    "sha256": "84bf477f036cff681bc57030cebd91b169b822d7cc5a2564dd70de678c3bc575"
                },
                "downloads": -1,
                "filename": "datenguidepy-0.2.1.tar.gz",
                "has_sig": false,
                "md5_digest": "609f29f5153786311253049fb782a04e",
                "packagetype": "sdist",
                "python_version": "source",
                "requires_python": null,
                "size": 173216,
                "upload_time": "2020-05-17T15:55:26",
                "upload_time_iso_8601": "2020-05-17T15:55:26.494429Z",
                "url": "https://files.pythonhosted.org/packages/06/9e/e0878bddee3035feb63bbfee11739eafc7bda81f50c22fb8fe761dd1bb80/datenguidepy-0.2.1.tar.gz",
                "yanked": false,
                "yanked_reason": null
            }
        ],
        "0.2.2": [
            {
                "comment_text": "",
                "digests": {
                    "md5": "6e7cf98f38ccb3bd6e9fa7c2e662bef2",
                    "sha256": "c476f5f5f860c22fa89d5e981003c17ac59da842523884a893e750fea98447aa"
                },
                "downloads": -1,
                "filename": "datenguidepy-0.2.2.tar.gz",
                "has_sig": false,
                "md5_digest": "6e7cf98f38ccb3bd6e9fa7c2e662bef2",
                "packagetype": "sdist",
                "python_version": "source",
                "requires_python": null,
                "size": 672730,
                "upload_time": "2020-05-23T23:24:49",
                "upload_time_iso_8601": "2020-05-23T23:24:49.209105Z",
                "url": "https://files.pythonhosted.org/packages/7e/b4/24506b4a521c357c6e924bfb7d83cca7cd993312cf96e1e9d05e1d188b6e/datenguidepy-0.2.2.tar.gz",
                "yanked": false,
                "yanked_reason": null
            }
        ],
        "0.3.0": [
            {
                "comment_text": "",
                "digests": {
                    "md5": "7e54b78b8b5bb270e4e73ccd8b4e8265",
                    "sha256": "a73909e75faba9c074ffcfe0e3b66b213ea8720d354f17b98d16bbb72b4040af"
                },
                "downloads": -1,
                "filename": "datenguidepy-0.3.0.tar.gz",
                "has_sig": false,
                "md5_digest": "7e54b78b8b5bb270e4e73ccd8b4e8265",
                "packagetype": "sdist",
                "python_version": "source",
                "requires_python": null,
                "size": 1992705,
                "upload_time": "2020-06-24T20:41:25",
                "upload_time_iso_8601": "2020-06-24T20:41:25.257264Z",
                "url": "https://files.pythonhosted.org/packages/6d/00/cadc484ab7e71f69bf79f43183d948dcbac8ddec045c3c24fa40df91e94d/datenguidepy-0.3.0.tar.gz",
                "yanked": false,
                "yanked_reason": null
            }
        ],
        "0.3.1": [
            {
                "comment_text": "",
                "digests": {
                    "md5": "1c66a5c3457c2a6fad4f2de24527068c",
                    "sha256": "6e77a3dabaad5247d660b6bcf64614a111110050b30db0f9c45b2564f560b1ed"
                },
                "downloads": -1,
                "filename": "datenguidepy-0.3.1.tar.gz",
                "has_sig": false,
                "md5_digest": "1c66a5c3457c2a6fad4f2de24527068c",
                "packagetype": "sdist",
                "python_version": "source",
                "requires_python": null,
                "size": 1998934,
                "upload_time": "2020-07-14T21:00:12",
                "upload_time_iso_8601": "2020-07-14T21:00:12.991041Z",
                "url": "https://files.pythonhosted.org/packages/d7/92/cd9b69a551df39ca83f02a36bc45bcc84814a029852ecb038ac9fb155500/datenguidepy-0.3.1.tar.gz",
                "yanked": false,
                "yanked_reason": null
            }
        ],
        "0.4.0": [
            {
                "comment_text": "",
                "digests": {
                    "md5": "c45e46ee5cc7c4891f5962014b644fc4",
                    "sha256": "a0978381a38b251a1ec511194245797cc7d91e4609ac8480c525707e5631c1f2"
                },
                "downloads": -1,
                "filename": "datenguidepy-0.4.0.tar.gz",
                "has_sig": false,
                "md5_digest": "c45e46ee5cc7c4891f5962014b644fc4",
                "packagetype": "sdist",
                "python_version": "source",
                "requires_python": null,
                "size": 1994814,
                "upload_time": "2021-01-23T10:48:04",
                "upload_time_iso_8601": "2021-01-23T10:48:04.226782Z",
                "url": "https://files.pythonhosted.org/packages/0b/14/e508dc322016a981153e770b8b494a32099dd6f8efb101075935e011d9bb/datenguidepy-0.4.0.tar.gz",
                "yanked": false,
                "yanked_reason": null
            }
        ],
        "0.4.1": [
            {
                "comment_text": "",
                "digests": {
                    "md5": "44f935730e3182c6546de53088b581bc",
                    "sha256": "fb435fb8b74bdff5450e326da081873902142d4463818b2d12dff726993793a3"
                },
                "downloads": -1,
                "filename": "datenguidepy-0.4.1.tar.gz",
                "has_sig": false,
                "md5_digest": "44f935730e3182c6546de53088b581bc",
                "packagetype": "sdist",
                "python_version": "source",
                "requires_python": null,
                "size": 1994875,
                "upload_time": "2021-08-01T19:38:15",
                "upload_time_iso_8601": "2021-08-01T19:38:15.422005Z",
                "url": "https://files.pythonhosted.org/packages/df/20/bc65a4f0d4eae9d7cff0b30cbb25411add7cc62601b0a3267200b63779c9/datenguidepy-0.4.1.tar.gz",
                "yanked": false,
                "yanked_reason": null
            }
        ]
    },
    "urls": [
        {
            "comment_text": "",
            "digests": {
                "md5": "44f935730e3182c6546de53088b581bc",
                "sha256": "fb435fb8b74bdff5450e326da081873902142d4463818b2d12dff726993793a3"
            },
            "downloads": -1,
            "filename": "datenguidepy-0.4.1.tar.gz",
            "has_sig": false,
            "md5_digest": "44f935730e3182c6546de53088b581bc",
            "packagetype": "sdist",
            "python_version": "source",
            "requires_python": null,
            "size": 1994875,
            "upload_time": "2021-08-01T19:38:15",
            "upload_time_iso_8601": "2021-08-01T19:38:15.422005Z",
            "url": "https://files.pythonhosted.org/packages/df/20/bc65a4f0d4eae9d7cff0b30cbb25411add7cc62601b0a3267200b63779c9/datenguidepy-0.4.1.tar.gz",
            "yanked": false,
            "yanked_reason": null
        }
    ],
    "vulnerabilities": []
}