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"info": {
"author": "Forest Gregg",
"author_email": "fgregg@datamade.us",
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"Development Status :: 4 - Beta",
"Intended Audience :: Developers",
"Intended Audience :: Science/Research",
"License :: OSI Approved :: MIT License",
"Natural Language :: English",
"Operating System :: MacOS :: MacOS X",
"Operating System :: Microsoft :: Windows",
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"Programming Language :: Python :: 3.5",
"Topic :: Scientific/Engineering",
"Topic :: Scientific/Engineering :: Information Analysis",
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"description": "============\nCensus Areas\n============\n\nThis Python library extends the Sunlight Foundation's `Census API Wrapper `_ to allow querying Census tracts, block groups, and blocks by Census place, as well as by arbitrary geographies.\n\nSetup\n======\n\nGet the library and its dependencies using `pip `_:\n\n::\n\n pip install census_area\n\nUsage\n======\n\n::\n\n from census_area import Census\n\n c = Census(\"MY_API_KEY\")\n old_homes = c.acs5.state_place_tract(('NAME', 'B25034_010E'), 17, 14000)\n\nThe call above will return the name of the census tract and the number of homes that were built before 1939 for every tract in the City of Chicago. ``17`` is the FIPS code for Illinois and ``14000`` is the FIPS code for Chicago.\n\nBy default, this method will return a list of dictionaries, where each dictionary represents the data for one tract. \n\nWith the ``return_geometry`` argument, you can have the method return a geojson-like dictionary. Each tract is a feature, and the census variables about the tract appear in the feature's property attributes.\n::\n\n old_homes_geojson = c.acs5.state_place_tract(('NAME', 'B25034_010E'), 17, 14000), return_geometry=True)\n\nThere are similar methods for block groups\n::\n\n old_home_block_groups = c.acs5.state_place_blockgroup(('NAME', 'B25034_010E'), 17, 14000))\n\nAnd blocks. Note that block level geographies are only available for the short-form data from the Decennial Census\n::\n\n owner_occupied = c.sf1.state_place_block(('NAME', 'H016F0002'), 17, 14000)\n\nThe tract and blockgroup methods are also available for the Decennial Census.\n::\n\n owner_occupied_blockgroup = c.sf1.state_place_tract(('NAME', 'H016F0002'), 17, 14000)\n owner_occupied_tract = c.sf1.state_place_blockgroup(('NAME', 'H016F0002'), 17, 14000)\n\n old_homes = c.sf3.state_place_tract('NAME', 'H034010'), 17, 14000)\n old_homes = c.sf3.state_place_blockgroup('NAME', 'H034010'), 17, 14000)\n\nIn addition to these convenient methods, there are three lower level ways to get census tracts, blocks, and groups for arbitrary geometries.\n\n::\n\n import json\n\n with open('my_shape.geojson') as infile:\n my_shape_geojson = json.load(infile)\n features = []\n old_homes = c.acs5.geo_tract(('NAME', 'B25034_010E'), my_shape_geojson['geometry'])\n for tract_geojson, tract_data, tract_proportion in old_homes:\n tract_geojson['properties'].update(tract_data)\n features.append(tract)\n\n my_shape_with_new_data_geojson = {'type': \"FeatureCollection\", 'features': features}\n\n\nThe method takes in the census variables you want and a geojson geometry, and returns a **generator** of the tract shapes, as geojson features, and the variables for that tract. Additionally, the generator returns a \"tract proportion\"; this is the proportion of the area of the tract that falls within your target shape.\n\nSimilar methods are provided for block groups and blocks, for the ACS 5-year and Decennial Census.\n::\n\n c.acs5.geo_blockgroup(('NAME', 'B25034_010E'), my_shape_geojson['geometry'])\n\n c.sf1.geo_block(('NAME', 'H016F0002'), my_shape_geojson['geometry'])\n c.sf1.geo_blockgroup(('NAME', 'H016F0002'), my_shape_geojson['geometry'])\n c.sf1.geo_tract(('NAME', 'H016F0002'), my_shape_geojson['geometry'])\n\n c.sf3.state_place_tract('NAME', 'H034010'), my_shape_geojson['geometry'])\n c.sf3.state_place_blockgroup('NAME', 'H034010'), my_shape_geojson['geometry'])\n\nTeam\n====\n\n* Jean Cochrane, DataMade\n* Forest Gregg, DataMade\n\nErrors and bugs\n===============\n\nIf something is not behaving intuitively, it is a bug and should be reported.\nReport it here by creating an issue: https://github.com/datamade/census_area/issues\n\nHelp us fix the problem as quickly as possible by following `Mozilla's guidelines for reporting bugs. `_\n\nPatches and pull requests\n=========================\n\nYour patches are welcome. Here's our suggested workflow:\n\n* Fork the project.\n* Make your feature addition or bug fix.\n* Send us a pull request with a description of your work. Bonus points for topic branches!\n\nCopyright and attribution\n=========================\n\nCopyright (c) 2016 DataMade. Released under the `MIT License `_.\n\n\n\n",
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