From 554c9b08f6648926e6e6efae215421ab924b750f Mon Sep 17 00:00:00 2001 From: Martin Fleischmann Date: Fri, 30 Aug 2024 16:33:10 +0200 Subject: [PATCH] ENH: add .path property to Dataset providing local path to cache (#25) * ENH: add .path property to Dataset providing local path to cache * docs * fix api docs --- doc/source/api.rst | 3 +- doc/source/introduction.ipynb | 2287 ++++++++++++++------------------- geodatasets/api.py | 14 +- geodatasets/lib.py | 30 + geodatasets/tests/test_lib.py | 16 + 5 files changed, 1039 insertions(+), 1311 deletions(-) diff --git a/doc/source/api.rst b/doc/source/api.rst index ba72d8a..0145053 100644 --- a/doc/source/api.rst +++ b/doc/source/api.rst @@ -27,7 +27,8 @@ Database-level API The database of dataset metadata is handled via custom dict-based classes. -.. class:: Dataset +.. autoclass:: Dataset + :members: path A dict with attribute-access and that can be called to update keys. diff --git a/doc/source/introduction.ipynb b/doc/source/introduction.ipynb index d2397d8..406d056 100644 --- a/doc/source/introduction.ipynb +++ b/doc/source/introduction.ipynb @@ -159,14 +159,14 @@ "
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geodatasets.Bunch
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    • \n", - " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", "
  • \n", - " \n", - " \n", + " \n", + " \n", "
    \n", " \n", "
    \n", " \n", "
    \n", "
    \n", - "
    geodatasets.Dataset
    \n", - "
    geoda.spirals
    \n", + "
    geodatasets.Bunch
    \n", + "
    1 items
    \n", "
    \n", "
    \n", - "
    \n", - "
    url
    https://geodacenter.github.io/data-and-lab//data/spirals.csv
    license
    NA
    attribution
    Center for Spatial Data Science, University of Chicago
    description
    Synthetic spiral points
    nrows
    301
    ncols
    2
    details
    https://geodacenter.github.io/data-and-lab//spirals/
    hash
    3203b0a6db37c1207b0f1727c980814f541ce0a222597475f9c91540b1d372f1
    filename
    spirals.csv
    \n", - "
    \n", - "
    \n", - "
    \n", - "
    \n", - " \n", - "
    \n", - "
    • \n", - " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
  • \n", + " \n", + " \n", + "
    \n", + " \n", + "
    \n", + " \n", + "
    \n", + "
    \n", + "
    geodatasets.Bunch
    \n", + "
    2 items
    \n", + "
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      \n", + " \n", "
    • \n", - " \n", - " \n", + " \n", + " \n", "
      \n", " \n", "
      \n", @@ -1638,11 +1523,11 @@ "
      \n", "
      \n", "
      geodatasets.Dataset
      \n", - "
      geoda.tampa1
      \n", + "
      abs.australia
      \n", "
      \n", "
      \n", "
      \n", - "
      url
      https://geodacenter.github.io/data-and-lab//data/TampaMSA.zip
      license
      NA
      attribution
      Center for Spatial Data Science, University of Chicago
      description
      2000 Census Tract Data for Tampa, FL MSA and counties
      nrows
      547
      ncols
      30
      details
      https://geodacenter.github.io/data-and-lab//tampa1/
      hash
      9a7ea0746138f62aa589e8377edafea48a7b1be0cdca2b38798ba21665bfb463
      filename
      TampaMSA.zip
      \n", + "
      url
      https://www.abs.gov.au/statistics/standards/australian-statistical-geography-standard-asgs-edition-3/jul2021-jun2026/access-and-downloads/digital-boundary-files/AUS_2021_AUST_SHP_GDA2020.zip
      license
      CC BY 4.0
      attribution
      Australian Bureau of Statistics (ABS)
      description
      Australia land polygon including Norfolk Island, the Territory of Christmas Island, and the Territory of Cocos (Keeling) Islands.
      geometry_type
      Polygon
      nrows
      2
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      details
      https://www.abs.gov.au/statistics/standards/australian-statistical-geography-standard-asgs-edition-3/jul2021-jun2026/access-and-downloads/digital-boundary-files
      hash
      086752a6b0b3978247be201f02e02cd4e3c4f36d4f4ca74802e6831083b67129
      filename
      AUS_2021_AUST_SHP_GDA2020.zip
      \n", "
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      \n", @@ -1652,8 +1537,8 @@ "
      • \n", " \n", "
    • \n", - " \n", - " \n", + " \n", + " \n", "
      \n", " \n", "
      \n", @@ -1661,11 +1546,11 @@ "
      \n", "
      \n", "
      geodatasets.Dataset
      \n", - "
      geoda.us_sdoh
      \n", + "
      abs.australia_states_territories
      \n", "
      \n", "
      \n", "
      \n", - "
      url
      https://geodacenter.github.io/data-and-lab//data/us-sdoh-2014.zip
      license
      NA
      attribution
      Center for Spatial Data Science, University of Chicago
      description
      2014 US Social Determinants of Health Data
      nrows
      71901
      ncols
      25
      details
      https://geodacenter.github.io/data-and-lab//us-sdoh/
      hash
      076701725c4b67248f79c8b8a40e74f9ad9e194d3237e1858b3d20176a6562a5
      filename
      us-sdoh-2014.zip
      \n", + "
      url
      https://www.abs.gov.au/statistics/standards/australian-statistical-geography-standard-asgs-edition-3/jul2021-jun2026/access-and-downloads/digital-boundary-files/STE_2021_AUST_SHP_GDA2020.zip
      license
      CC BY 4.0
      attribution
      Australian Bureau of Statistics (ABS)
      description
      Australian state and territory boundaries.
      geometry_type
      Polygon
      nrows
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      details
      https://www.abs.gov.au/statistics/standards/australian-statistical-geography-standard-asgs-edition-3/jul2021-jun2026/access-and-downloads/digital-boundary-files
      hash
      d9b7f735de6085b37414faf011f796dda3c7f768c55e9dce01f96e790f399a21
      filename
      STE_2021_AUST_SHP_GDA2020.zip
      \n", "
      \n", "
      \n", "
      \n", @@ -1683,8 +1568,8 @@ "
      • \n", " \n", "
    • \n", - " \n", - " \n", + " \n", + " \n", "
      \n", " \n", "
      \n", @@ -1698,8 +1583,8 @@ "
        \n", " \n", "
      • \n", - " \n", - " \n", + " \n", + " \n", "
        \n", " \n", "
        \n", @@ -1707,11 +1592,11 @@ "
        \n", "
        \n", "
        geodatasets.Dataset
        \n", - "
        ny.bb
        \n", + "
        naturalearth.land
        \n", "
        \n", "
        \n", "
        \n", - "
        url
        https://data.cityofnewyork.us/api/geospatial/tqmj-j8zm?method=export&format=Original
        license
        NA
        attribution
        Department of City Planning (DCP)
        description
        The borough boundaries of New York City clipped to the shoreline at mean high tide.
        details
        https://data.cityofnewyork.us/City-Government/Borough-Boundaries/tqmj-j8zm
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        hash
        26257f5a3c06765557b302f36774d4d21acb257aa8f9d4a4694d436432160051
        filename
        nybb_22c.zip
        \n", + "
        url
        https://naciscdn.org/naturalearth/110m/physical/ne_110m_land.zip
        license
        CC0
        attribution
        Natural Earth
        description
        Land polygons including major islands in a 1:110m resolution.
        geometry_type
        Polygon
        details
        https://www.naturalearthdata.com/downloads/110m-physical-vectors/110m-land/
        nrows
        127
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        4
        hash
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        filename
        ne_110m_land.zip
        \n", "
        \n", "
        \n", "
        \n", @@ -1740,8 +1625,9 @@ " 'attribution': 'Center for Spatial Data Science, University of Chicago',\n", " 'name': 'geoda.airbnb',\n", " 'description': 'Airbnb rentals, socioeconomics, and crime in Chicago',\n", + " 'geometry_type': 'Polygon',\n", " 'nrows': 77,\n", - " 'ncols': 20,\n", + " 'ncols': 21,\n", " 'details': 'https://geodacenter.github.io/data-and-lab//airbnb/',\n", " 'hash': 'a2ab1e3f938226d287dd76cde18c00e2d3a260640dd826da7131827d9e76c824',\n", " 'filename': 'airbnb.zip'},\n", @@ -1750,46 +1636,19 @@ " 'attribution': 'Center for Spatial Data Science, University of Chicago',\n", " 'name': 'geoda.atlanta',\n", " 'description': 'Atlanta, GA region homicide counts and rates',\n", + " 'geometry_type': 'Polygon',\n", " 'nrows': 90,\n", - " 'ncols': 23,\n", + " 'ncols': 24,\n", " 'details': 'https://geodacenter.github.io/data-and-lab//atlanta_old/',\n", " 'hash': 'a33a76e12168fe84361e60c88a9df4856730487305846c559715c89b1a2b5e09',\n", - " 'filename': 'atlanta_hom.zip'},\n", - " 'baltimore': {'url': 'https://geodacenter.github.io/data-and-lab//data/baltimore.zip',\n", - " 'license': 'NA',\n", - " 'attribution': 'Center for Spatial Data Science, University of Chicago',\n", - " 'name': 'geoda.baltimore',\n", - " 'description': 'Baltimore house sales prices and hedonics',\n", - " 'nrows': 211,\n", - " 'ncols': 17,\n", - " 'details': 'https://geodacenter.github.io/data-and-lab//baltim/',\n", - " 'hash': '23f04f479026f33565fb84802f19c4142a5287c0a20072cb2ac1d3c145677b2c',\n", - " 'filename': 'baltimore.zip'},\n", - " 'bostonhsg': {'url': 'https://geodacenter.github.io/data-and-lab//data/boston.zip',\n", - " 'license': 'NA',\n", - " 'attribution': 'Center for Spatial Data Science, University of Chicago',\n", - " 'name': 'geoda.bostonhsg',\n", - " 'description': 'Boston housing and neighborhood data',\n", - " 'nrows': 506,\n", - " 'ncols': 23,\n", - " 'details': 'https://geodacenter.github.io/data-and-lab//boston-housing/',\n", - " 'hash': 'ee6c3138e3b3f1989a7a28edb8a98eb4a5fa2835ee2d45d9bf4d5cd4ebbe76c7',\n", - " 'filename': 'boston.zip'},\n", - " 'buenosaires': {'url': 'https://geodacenter.github.io/data-and-lab//data/buenosaires.zip',\n", - " 'license': 'NA',\n", - " 'attribution': 'Center for Spatial Data Science, University of Chicago',\n", - " 'name': 'geoda.buenosaires',\n", - " 'description': 'Electoral Data for 1999 Argentinean Elections',\n", - " 'nrows': 209,\n", - " 'ncols': 21,\n", - " 'details': 'https://geodacenter.github.io/data-and-lab//buenos-aires_old/',\n", - " 'hash': 'd011ba3d082eef8a0d694b14b4cef41546766621ae6aff1ce536d0a4f62e589e',\n", - " 'filename': 'buenosaires.zip'},\n", + " 'filename': 'atlanta_hom.zip',\n", + " 'members': ['atlanta_hom/atl_hom.geojson']},\n", " 'cars': {'url': 'https://geodacenter.github.io/data-and-lab//data/Abandoned_Vehicles_Map.csv',\n", " 'license': 'NA',\n", " 'attribution': 'Center for Spatial Data Science, University of Chicago',\n", " 'name': 'geoda.cars',\n", " 'description': '2011 abandoned vehicles in Chicago (311 complaints).',\n", + " 'geometry_type': 'Point',\n", " 'nrows': 137867,\n", " 'ncols': 21,\n", " 'details': 'https://geodacenter.github.io/data-and-lab//1-source-and-description/',\n", @@ -1800,28 +1659,33 @@ " 'attribution': 'Center for Spatial Data Science, University of Chicago',\n", " 'name': 'geoda.charleston1',\n", " 'description': '2000 Census Tract Data for Charleston, SC MSA and counties',\n", + " 'geometry_type': 'Polygon',\n", " 'nrows': 117,\n", - " 'ncols': 30,\n", + " 'ncols': 31,\n", " 'details': 'https://geodacenter.github.io/data-and-lab//charleston-1_old/',\n", " 'hash': '4a4fa9c8dd4231ae0b2f12f24895b8336bcab0c28c48653a967cffe011f63a7c',\n", - " 'filename': 'CharlestonMSA.zip'},\n", + " 'filename': 'CharlestonMSA.zip',\n", + " 'members': ['CharlestonMSA/sc_final_census2.gpkg']},\n", " 'charleston2': {'url': 'https://geodacenter.github.io/data-and-lab//data/CharlestonMSA2.zip',\n", " 'license': 'NA',\n", " 'attribution': 'Center for Spatial Data Science, University of Chicago',\n", " 'name': 'geoda.charleston2',\n", " 'description': '1998 and 2001 Zip Code Business Patterns (Census Bureau) for Charleston, SC MSA',\n", - " 'nrows': 44,\n", - " 'ncols': 97,\n", + " 'geometry_type': 'Polygon',\n", + " 'nrows': 42,\n", + " 'ncols': 60,\n", " 'details': 'https://geodacenter.github.io/data-and-lab//charleston2/',\n", " 'hash': '056d5d6e236b5bd95f5aee26c77bbe7d61bd07db5aaf72866c2f545205c1d8d7',\n", - " 'filename': 'CharlestonMSA2.zip'},\n", + " 'filename': 'CharlestonMSA2.zip',\n", + " 'members': ['CharlestonMSA2/CharlestonMSA2.gpkg']},\n", " 'chicago_health': {'url': 'https://geodacenter.github.io/data-and-lab//data/comarea.zip',\n", " 'license': 'NA',\n", " 'attribution': 'Center for Spatial Data Science, University of Chicago',\n", " 'name': 'geoda.chicago_health',\n", " 'description': 'Chicago Health + Socio-Economics',\n", + " 'geometry_type': 'Polygon',\n", " 'nrows': 77,\n", - " 'ncols': 86,\n", + " 'ncols': 87,\n", " 'details': 'https://geodacenter.github.io/data-and-lab//comarea_vars/',\n", " 'hash': '4e872adb552786eae2fcd745524696e5e4cd33cc9a6c032471c0e75328871401',\n", " 'filename': 'comarea.zip'},\n", @@ -1830,108 +1694,113 @@ " 'attribution': 'Center for Spatial Data Science, University of Chicago',\n", " 'name': 'geoda.chicago_commpop',\n", " 'description': 'Chicago Community Area Population Percent Change for 2000 and 2010',\n", + " 'geometry_type': 'Polygon',\n", " 'nrows': 77,\n", - " 'ncols': 8,\n", + " 'ncols': 9,\n", " 'details': 'https://geodacenter.github.io/data-and-lab//commpop/',\n", " 'hash': '1dbebb50c8ea47e2279ea819ef64ba793bdee2b88e4716bd6c6ec0e0d8e0e05b',\n", - " 'filename': 'chicago_commpop.zip'},\n", + " 'filename': 'chicago_commpop.zip',\n", + " 'members': ['chicago_commpop/chicago_commpop.geojson']},\n", " 'chile_labor': {'url': 'https://geodacenter.github.io/data-and-lab//data/flma.zip',\n", " 'license': 'NA',\n", " 'attribution': 'Center for Spatial Data Science, University of Chicago',\n", " 'name': 'geoda.chile_labor',\n", " 'description': 'Labor Markets in Chile (1982-2002)',\n", - " 'nrows': 141,\n", - " 'ncols': 62,\n", + " 'geometry_type': 'Polygon',\n", + " 'nrows': 64,\n", + " 'ncols': 140,\n", " 'details': 'https://geodacenter.github.io/data-and-lab//FLMA/',\n", " 'hash': '4777072268d0127b3d0be774f51d0f66c15885e9d3c92bc72c641a72f220796c',\n", - " 'filename': 'flma.zip'},\n", + " 'filename': 'flma.zip',\n", + " 'members': ['flma/FLMA.geojson']},\n", " 'cincinnati': {'url': 'https://geodacenter.github.io/data-and-lab//data/walnuthills_updated.zip',\n", " 'license': 'NA',\n", " 'attribution': 'Center for Spatial Data Science, University of Chicago',\n", " 'name': 'geoda.cincinnati',\n", " 'description': '2008 Cincinnati Crime + Socio-Demographics',\n", + " 'geometry_type': 'Polygon',\n", " 'nrows': 457,\n", - " 'ncols': 89,\n", + " 'ncols': 73,\n", " 'details': 'https://geodacenter.github.io/data-and-lab//walnut_hills/',\n", " 'hash': 'd6871dd688bd14cf4710a218d721d34f6574456f2a14d5c5cfe5a92054ee9763',\n", - " 'filename': 'walnuthills_updated.zip'},\n", + " 'filename': 'walnuthills_updated.zip',\n", + " 'members': ['walnuthills_updated']},\n", " 'cleveland': {'url': 'https://geodacenter.github.io/data-and-lab//data/cleveland.zip',\n", " 'license': 'NA',\n", " 'attribution': 'Center for Spatial Data Science, University of Chicago',\n", " 'name': 'geoda.cleveland',\n", " 'description': '2015 sales prices of homes in Cleveland, OH.',\n", + " 'geometry_type': 'Point',\n", " 'nrows': 205,\n", - " 'ncols': 9,\n", + " 'ncols': 10,\n", " 'details': 'https://geodacenter.github.io/data-and-lab//clev_sls_154_core/',\n", " 'hash': '49aeba03eb06bf9b0d9cddd6507eb4a226b7c7a7561145562885c5cddfaeaadf',\n", " 'filename': 'cleveland.zip'},\n", - " 'columbus': {'url': 'https://geodacenter.github.io/data-and-lab//data/columbus.zip',\n", - " 'license': 'NA',\n", - " 'attribution': 'Center for Spatial Data Science, University of Chicago',\n", - " 'name': 'geoda.columbus',\n", - " 'description': 'Columbus neighborhood crime',\n", - " 'nrows': 49,\n", - " 'ncols': 20,\n", - " 'details': 'https://geodacenter.github.io/data-and-lab//columbus/',\n", - " 'hash': 'cf3bde1a32b31c48a63bc513587a1f8d310ecae5de9cae460dc9e66fe5a65e4d',\n", - " 'filename': 'columbus.zip'},\n", - " 'elections': {'url': 'https://geodacenter.github.io/data-and-lab//data/election.zip',\n", - " 'license': 'NA',\n", - " 'attribution': 'Center for Spatial Data Science, University of Chicago',\n", - " 'name': 'geoda.elections',\n", - " 'description': '2012 and 2016 Presidential Elections',\n", - " 'nrows': 3108,\n", - " 'ncols': 74,\n", - " 'details': 'https://geodacenter.github.io/data-and-lab//county_election_2012_2016-variables/',\n", - " 'hash': '5c5b17f5b1747065340eae16f67819276851cacd52fda80a22be119f65ad5ebe',\n", - " 'filename': 'election.zip'},\n", " 'grid100': {'url': 'https://geodacenter.github.io/data-and-lab//data/grid100.zip',\n", " 'license': 'NA',\n", " 'attribution': 'Center for Spatial Data Science, University of Chicago',\n", " 'name': 'geoda.grid100',\n", " 'description': 'Grid with simulated variables',\n", + " 'geometry_type': 'Polygon',\n", " 'nrows': 100,\n", - " 'ncols': 34,\n", + " 'ncols': 37,\n", " 'details': 'https://geodacenter.github.io/data-and-lab//grid100/',\n", " 'hash': '5702ba39606044f71d53ae6a83758b81332bd3aa216b7b7b6e1c60dd0e72f476',\n", - " 'filename': 'grid100.zip'},\n", + " 'filename': 'grid100.zip',\n", + " 'members': ['grid100/grid100s.gpkg']},\n", " 'groceries': {'url': 'https://geodacenter.github.io/data-and-lab//data/grocery.zip',\n", " 'license': 'NA',\n", " 'attribution': 'Center for Spatial Data Science, University of Chicago',\n", " 'name': 'geoda.groceries',\n", " 'description': '2015 Chicago supermarkets',\n", + " 'geometry_type': 'Point',\n", " 'nrows': 148,\n", - " 'ncols': 7,\n", + " 'ncols': 8,\n", " 'details': 'https://geodacenter.github.io/data-and-lab//chicago_sup_vars/',\n", " 'hash': 'ead10e53b21efcaa29b798428b93ba2a1c0ba1b28f046265c1737712fa83f88a',\n", - " 'filename': 'grocery.zip'},\n", + " 'filename': 'grocery.zip',\n", + " 'members': ['grocery/chicago_sup.shp',\n", + " 'grocery/chicago_sup.dbf',\n", + " 'grocery/chicago_sup.shx',\n", + " 'grocery/chicago_sup.prj']},\n", " 'guerry': {'url': 'https://geodacenter.github.io/data-and-lab//data/guerry.zip',\n", " 'license': 'NA',\n", " 'attribution': 'Center for Spatial Data Science, University of Chicago',\n", " 'name': 'geoda.guerry',\n", - " 'description': 'Moral statistics of France (Guerry, 1833)',\n", + " 'description': 'Mortal statistics of France (Guerry, 1833)',\n", + " 'geometry_type': 'Polygon',\n", " 'nrows': 85,\n", - " 'ncols': 23,\n", + " 'ncols': 24,\n", " 'details': 'https://geodacenter.github.io/data-and-lab//Guerry/',\n", " 'hash': '80d2b355ad3340fcffa0a28e5cec0698af01067f8059b1a60388d200a653b3e8',\n", - " 'filename': 'guerry.zip'},\n", - " 'health+': {'url': 'https://geodacenter.github.io/data-and-lab//data/income_diversity.zip',\n", + " 'filename': 'guerry.zip',\n", + " 'members': ['guerry/guerry.shp',\n", + " 'guerry/guerry.dbf',\n", + " 'guerry/guerry.shx',\n", + " 'guerry/guerry.prj']},\n", + " 'health': {'url': 'https://geodacenter.github.io/data-and-lab//data/income_diversity.zip',\n", " 'license': 'NA',\n", " 'attribution': 'Center for Spatial Data Science, University of Chicago',\n", - " 'name': 'geoda.health+',\n", + " 'name': 'geoda.health',\n", " 'description': '2000 Health, Income + Diversity',\n", + " 'geometry_type': 'Polygon',\n", " 'nrows': 3984,\n", - " 'ncols': 64,\n", + " 'ncols': 65,\n", " 'details': 'https://geodacenter.github.io/data-and-lab//co_income_diversity_variables/',\n", " 'hash': 'eafee1063040258bc080e7b501bdf1438d6e45ba208954d8c2e1a7562142d0a7',\n", - " 'filename': 'income_diversity.zip'},\n", + " 'filename': 'income_diversity.zip',\n", + " 'members': ['income_diversity/income_diversity.shp',\n", + " 'income_diversity/income_diversity.dbf',\n", + " 'income_diversity/income_diversity.shx',\n", + " 'income_diversity/income_diversity.prj']},\n", " 'health_indicators': {'url': 'https://geodacenter.github.io/data-and-lab//data/healthIndicators.zip',\n", " 'license': 'NA',\n", " 'attribution': 'Center for Spatial Data Science, University of Chicago',\n", " 'name': 'geoda.health_indicators',\n", " 'description': 'Chicago Health Indicators (2005-11)',\n", + " 'geometry_type': 'Polygon',\n", " 'nrows': 77,\n", - " 'ncols': 31,\n", + " 'ncols': 32,\n", " 'details': 'https://geodacenter.github.io/data-and-lab//healthindicators-variables/',\n", " 'hash': 'b43683245f8fc3b4ab69ffa75d2064920a1a91dc76b9dcc08e288765ba0c94f3',\n", " 'filename': 'healthIndicators.zip'},\n", @@ -1940,148 +1809,173 @@ " 'attribution': 'Center for Spatial Data Science, University of Chicago',\n", " 'name': 'geoda.hickory1',\n", " 'description': '2000 Census Tract Data for Hickory, NC MSA and counties',\n", + " 'geometry_type': 'Polygon',\n", " 'nrows': 68,\n", - " 'ncols': 30,\n", + " 'ncols': 31,\n", " 'details': 'https://geodacenter.github.io/data-and-lab//hickory1/',\n", " 'hash': '4c0804608d303e6e44d51966bb8927b1f5f9e060a9b91055a66478b9039d2b44',\n", - " 'filename': 'HickoryMSA.zip'},\n", + " 'filename': 'HickoryMSA.zip',\n", + " 'members': ['HickoryMSA/nc_final_census2.geojson']},\n", " 'hickory2': {'url': 'https://geodacenter.github.io/data-and-lab//data/HickoryMSA2.zip',\n", " 'license': 'NA',\n", " 'attribution': 'Center for Spatial Data Science, University of Chicago',\n", " 'name': 'geoda.hickory2',\n", " 'description': '1998 and 2001 Zip Code Business Patterns (Census Bureau) for Hickory, NC MSA',\n", + " 'geometry_type': 'Polygon',\n", " 'nrows': 29,\n", - " 'ncols': 55,\n", + " 'ncols': 56,\n", " 'details': 'https://geodacenter.github.io/data-and-lab//hickory2/',\n", " 'hash': '5e9498e1ff036297c3eea3cc42ac31501680a43b50c71b486799ef9021679d07',\n", - " 'filename': 'HickoryMSA2.zip'},\n", + " 'filename': 'HickoryMSA2.zip',\n", + " 'members': ['HickoryMSA2/HickoryMSA2.geojson']},\n", " 'home_sales': {'url': 'https://geodacenter.github.io/data-and-lab//data/kingcounty.zip',\n", " 'license': 'NA',\n", " 'attribution': 'Center for Spatial Data Science, University of Chicago',\n", " 'name': 'geoda.home_sales',\n", " 'description': '2014-15 Home Sales in King County, WA',\n", + " 'geometry_type': 'Point',\n", " 'nrows': 21613,\n", - " 'ncols': 21,\n", + " 'ncols': 22,\n", " 'details': 'https://geodacenter.github.io/data-and-lab//KingCounty-HouseSales2015/',\n", " 'hash': 'b979f0eb2cef6ebd2c761d552821353f795635eb8db53a95f2815fc46e1f644c',\n", - " 'filename': 'kingcounty.zip'},\n", + " 'filename': 'kingcounty.zip',\n", + " 'members': ['kingcounty/kc_house.shp',\n", + " 'kingcounty/kc_house.dbf',\n", + " 'kingcounty/kc_house.shx',\n", + " 'kingcounty/kc_house.prj']},\n", " 'houston': {'url': 'https://geodacenter.github.io/data-and-lab//data/houston_hom.zip',\n", " 'license': 'NA',\n", " 'attribution': 'Center for Spatial Data Science, University of Chicago',\n", " 'name': 'geoda.houston',\n", " 'description': 'Houston, TX region homicide counts and rates',\n", + " 'geometry_type': 'Polygon',\n", " 'nrows': 52,\n", - 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" 'filename': 'lasrosas.zip'},\n", + " 'filename': 'lasrosas.zip',\n", + " 'members': ['lasrosas/rosas1999.gpkg']},\n", " 'liquor_stores': {'url': 'https://geodacenter.github.io/data-and-lab//data/liquor.zip',\n", " 'license': 'NA',\n", " 'attribution': 'Center for Spatial Data Science, University of Chicago',\n", " 'name': 'geoda.liquor_stores',\n", " 'description': '2015 Chicago Liquor Stores',\n", + " 'geometry_type': 'Point',\n", " 'nrows': 571,\n", - " 'ncols': 2,\n", + " 'ncols': 3,\n", " 'details': 'https://geodacenter.github.io/data-and-lab//liq_chicago/',\n", " 'hash': '6a483a6a7066a000bc97bfe71596cf28834d3088fbc958455b903a0938b3b530',\n", - " 'filename': 'liquor.zip'},\n", + " 'filename': 'liquor.zip',\n", + " 'members': ['liq_Chicago.shp',\n", + " 'liq_Chicago.dbf',\n", + " 'liq_Chicago.shx',\n", + " 'liq_Chicago.prj']},\n", " 'malaria': {'url': 'https://geodacenter.github.io/data-and-lab//data/malariacolomb.zip',\n", " 'license': 'NA',\n", " 'attribution': 'Center for Spatial Data Science, University of Chicago',\n", " 'name': 'geoda.malaria',\n", " 'description': 'Malaria incidence and population (1973, 95, 93 censuses and projections until 2005)',\n", + " 'geometry_type': 'Polygon',\n", " 'nrows': 1068,\n", - 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" 'ncols': 55,\n", + " 'ncols': 60,\n", " 'details': 'https://geodacenter.github.io/data-and-lab//milwaukee2/',\n", " 'hash': '7f74212d63addb9ab84fac9447ee898498c8fafc284edcffe1f1ac79c2175d60',\n", - " 'filename': 'MilwaukeeMSA2.zip'},\n", + " 'filename': 'MilwaukeeMSA2.zip',\n", + " 'members': ['MilwaukeeMSA2/MilwaukeeMSA2.gpkg']},\n", " 'ncovr': {'url': 'https://geodacenter.github.io/data-and-lab//data/ncovr.zip',\n", " 'license': 'NA',\n", " 'attribution': 'Center for Spatial Data Science, University of Chicago',\n", " 'name': 'geoda.ncovr',\n", " 'description': 'US county homicides 1960-1990',\n", + " 'geometry_type': 'Polygon',\n", " 'nrows': 3085,\n", - " 'ncols': 69,\n", + " 'ncols': 70,\n", " 'details': 'https://geodacenter.github.io/data-and-lab//ncovr/',\n", " 'hash': 'e8cb04e6da634c6cd21808bd8cfe4dad6e295b22e8d40cc628e666887719cfe9',\n", - " 'filename': 'ncovr.zip'},\n", + " 'filename': 'ncovr.zip',\n", + " 'members': ['ncovr/NAT.gpkg']},\n", " 'natregimes': {'url': 'https://geodacenter.github.io/data-and-lab//data/natregimes.zip',\n", " 'license': 'NA',\n", " 'attribution': 'Center for Spatial Data Science, University of Chicago',\n", " 'name': 'geoda.natregimes',\n", " 'description': 'NCOVR with regimes (book/PySAL)',\n", + " 'geometry_type': 'Polygon',\n", " 'nrows': 3085,\n", - " 'ncols': 73,\n", + " 'ncols': 74,\n", " 'details': 'https://geodacenter.github.io/data-and-lab//natregimes/',\n", " 'hash': '431d0d95ffa000692da9319e6bd28701b1156f7b8e716d4bfcd1e09b6e357918',\n", " 'filename': 'natregimes.zip'},\n", @@ -2090,18 +1984,21 @@ " 'attribution': 'Center for Spatial Data Science, University of Chicago',\n", " 'name': 'geoda.ndvi',\n", " 'description': 'Normalized Difference Vegetation Index grid',\n", + " 'geometry_type': 'Polygon',\n", " 'nrows': 49,\n", - " 'ncols': 5,\n", + " 'ncols': 8,\n", " 'details': 'https://geodacenter.github.io/data-and-lab//ndvi/',\n", " 'hash': 'a89459e50a4495c24ead1d284930467ed10eb94829de16a693a9fa89dea2fe22',\n", - " 'filename': 'ndvi.zip'},\n", + " 'filename': 'ndvi.zip',\n", + " 'members': ['ndvi/ndvigrid.gpkg']},\n", " 'nepal': {'url': 'https://geodacenter.github.io/data-and-lab//data/nepal.zip',\n", " 'license': 'NA',\n", " 'attribution': 'Center for Spatial Data Science, University of Chicago',\n", " 'name': 'geoda.nepal',\n", " 'description': 'Health, poverty and education indicators for Nepal districts',\n", + " 'geometry_type': 'Polygon',\n", " 'nrows': 75,\n", - " 'ncols': 61,\n", + " 'ncols': 62,\n", " 'details': 'https://geodacenter.github.io/data-and-lab//nepal/',\n", " 'hash': 'd7916568fe49ff258d0f03ac115e68f64cdac572a9fd2b29de2d70554ac2b20d',\n", " 'filename': 'nepal.zip'},\n", @@ -2110,8 +2007,9 @@ " 'attribution': 'Center for Spatial Data Science, University of Chicago',\n", " 'name': 'geoda.nyc',\n", " 'description': 'Demographic and housing data for New York City subboroughs, 2002-09',\n", + " 'geometry_type': 'Polygon',\n", " 'nrows': 55,\n", - " 'ncols': 34,\n", + " 'ncols': 35,\n", " 'details': 'https://geodacenter.github.io/data-and-lab//nyc/',\n", " 'hash': 'a67dff2f9e6da9e11737e6be5a16e1bc33954e2c954332d68bcbf6ff7203702b',\n", " 'filename': 'nyc.zip'},\n", @@ -2120,8 +2018,9 @@ " 'attribution': 'Center for Spatial Data Science, University of Chicago',\n", " 'name': 'geoda.nyc_earnings',\n", " 'description': 'Block-level Earnings in NYC (2002-14)',\n", + " 'geometry_type': 'Polygon',\n", " 'nrows': 108487,\n", - " 'ncols': 70,\n", + " 'ncols': 71,\n", " 'details': 'https://geodacenter.github.io/data-and-lab//LEHD_Data/',\n", " 'hash': '771fe11e59a16d4c15c6471d9a81df5e9c9bda5ef0a207e77d8ff21b2c16891b',\n", " 'filename': 'lehd.zip'},\n", @@ -2130,8 +2029,9 @@ " 'attribution': 'Center for Spatial Data Science, University of Chicago',\n", " 'name': 'geoda.nyc_education',\n", " 'description': 'NYC Education (2000)',\n", + " 'geometry_type': 'Polygon',\n", " 'nrows': 2216,\n", - 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" 'filename': 'SavannahMSA.zip'},\n", + " 'filename': 'SavannahMSA.zip',\n", + " 'members': ['SavannahMSA/ga_final_census2.gpkg']},\n", " 'savannah2': {'url': 'https://geodacenter.github.io/data-and-lab//data/SavannahMSA2.zip',\n", " 'license': 'NA',\n", " 'attribution': 'Center for Spatial Data Science, University of Chicago',\n", " 'name': 'geoda.savannah2',\n", " 'description': '1998 and 2001 Zip Code Business Patterns (Census Bureau) for Savannah, GA MSA',\n", + " 'geometry_type': 'Polygon',\n", " 'nrows': 24,\n", - " 'ncols': 55,\n", + " 'ncols': 60,\n", " 'details': 'https://geodacenter.github.io/data-and-lab//savannah2/',\n", " 'hash': '5b22b84a8665434cb91e800a039337f028b888082b8ef7a26d77eb6cc9aea8c1',\n", - " 'filename': 'SavannahMSA2.zip'},\n", - " 'scotlip': {'url': 'https://geodacenter.github.io/data-and-lab//data/scotlip.zip',\n", - " 'license': 'NA',\n", - " 'attribution': 'Center for Spatial Data Science, University of Chicago',\n", - " 'name': 'geoda.scotlip',\n", - " 'description': 'Male lip cancer in Scotland, 1975-80',\n", - 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" 'ncols': 17,\n", + " 'ncols': 19,\n", " 'details': 'https://geodacenter.github.io/data-and-lab//sids2/',\n", " 'hash': 'b5875ffbdb261e6fa75dc4580d67111ef1434203f2d6a5d63ffac16db3a14bd0',\n", - " 'filename': 'sids2.zip'},\n", - " 'snow': {'url': 'https://geodacenter.github.io/data-and-lab//data/snow.zip',\n", - " 'license': 'NA',\n", - " 'attribution': 'Center for Spatial Data Science, University of Chicago',\n", - " 'name': 'geoda.snow',\n", - " 'description': 'John Snow & the 19th Century Cholera Epidemic',\n", - " 'nrows': 'missing',\n", - " 'ncols': 'missing',\n", - " 'details': 'https://geodacenter.github.io/data-and-lab//snow/',\n", - " 'hash': 'd974dbe3c16a31459e213556f4e4c5e3494db620615aa624104582cde0e2d83c',\n", - " 'filename': 'snow.zip'},\n", + " 'filename': 'sids2.zip',\n", + " 'members': ['sids2/sids2.gpkg']},\n", " 'south': {'url': 'https://geodacenter.github.io/data-and-lab//data/south.zip',\n", " 'license': 'NA',\n", " 'attribution': 'Center for Spatial Data Science, University of Chicago',\n", " 'name': 'geoda.south',\n", " 'description': 'US Southern county homicides 1960-1990',\n", + " 'geometry_type': 'Polygon',\n", " 'nrows': 1412,\n", - " 'ncols': 69,\n", + " 'ncols': 70,\n", " 'details': 'https://geodacenter.github.io/data-and-lab//south/',\n", " 'hash': '8f151d99c643b187aad37cfb5c3212353e1bc82804a4399a63de369490e56a7a',\n", - " 'filename': 'south.zip'},\n", + " 'filename': 'south.zip',\n", + " 'members': ['south/south.gpkg']},\n", " 'spirals': {'url': 'https://geodacenter.github.io/data-and-lab//data/spirals.csv',\n", " 'license': 'NA',\n", " 'attribution': 'Center for Spatial Data Science, University of Chicago',\n", " 'name': 'geoda.spirals',\n", " 'description': 'Synthetic spiral points',\n", - " 'nrows': 301,\n", + " 'geometry_type': 'Point',\n", + " 'nrows': 300,\n", " 'ncols': 2,\n", " 'details': 'https://geodacenter.github.io/data-and-lab//spirals/',\n", " 'hash': '3203b0a6db37c1207b0f1727c980814f541ce0a222597475f9c91540b1d372f1',\n", @@ -2360,8 +2230,9 @@ " 'attribution': 'Center for Spatial Data Science, University of Chicago',\n", " 'name': 'geoda.stlouis',\n", " 'description': 'St Louis region county homicide counts and rates',\n", + " 'geometry_type': 'Polygon',\n", " 'nrows': 78,\n", - 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" 'ncols': 25,\n", + " 'ncols': 26,\n", " 'details': 'https://geodacenter.github.io/data-and-lab//us-sdoh/',\n", " 'hash': '076701725c4b67248f79c8b8a40e74f9ad9e194d3237e1858b3d20176a6562a5',\n", - " 'filename': 'us-sdoh-2014.zip'}},\n", - " 'ny': {'bb': {'url': 'https://data.cityofnewyork.us/api/geospatial/tqmj-j8zm?method=export&format=Original',\n", + " 'filename': 'us-sdoh-2014.zip',\n", + " 'members': ['us-sdoh-2014/us-sdoh-2014.shp',\n", + " 'us-sdoh-2014/us-sdoh-2014.dbf',\n", + " 'us-sdoh-2014/us-sdoh-2014.shx',\n", + " 'us-sdoh-2014/us-sdoh-2014.prj']}},\n", + " 'ny': {'bb': {'url': 'https://www.nyc.gov/assets/planning/download/zip/data-maps/open-data/nybb_16a.zip',\n", " 'license': 'NA',\n", " 'attribution': 'Department of City Planning (DCP)',\n", " 'name': 'ny.bb',\n", - " 'description': 'The borough boundaries of New York City clipped to the shoreline at mean high tide.',\n", + " 'description': 'The borough boundaries of New York City clipped to the shoreline at mean high tide for 2016.',\n", + " 'geometry_type': 'Polygon',\n", " 'details': 'https://data.cityofnewyork.us/City-Government/Borough-Boundaries/tqmj-j8zm',\n", " 'nrows': 5,\n", " 'ncols': 5,\n", - 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          geoda.airbnb
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          geodatasets.Dataset
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          geoda.atlanta
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          geodatasets.Dataset
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          geodatasets.Dataset
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          geoda.bostonhsg
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          geodatasets.Dataset
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          url
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          geodatasets.Dataset
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          \n", - "
          \n", - "
          \n", - "
          url
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          NA
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          \n", - " \n", - "
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          \n", - "
          geodatasets.Dataset
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          \n", - "
          \n", - "
          \n", - "
          url
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          NA
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          Center for Spatial Data Science, University of Chicago
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          \n", - "
          \n", - "
          \n", - "
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          \n", + "
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            geodatasets.Dataset
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            geoda.chicago_health
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            geoda.airbnb
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            \n", "
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            \n", - "
            url
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            Center for Spatial Data Science, University of Chicago
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            Airbnb rentals, socioeconomics, and crime in Chicago
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          • \n", - " \n", - " \n", + " \n", + " \n", "
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            \n", @@ -2766,11 +2509,11 @@ "
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            geodatasets.Dataset
            \n", - "
            geoda.chicago_commpop
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            geoda.atlanta
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            \n", "
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            \n", - "
            url
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            NA
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            Center for Spatial Data Science, University of Chicago
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            Chicago Community Area Population Percent Change for 2000 and 2010
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            url
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            NA
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            Center for Spatial Data Science, University of Chicago
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            Atlanta, GA region homicide counts and rates
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            • \n", " \n", "
          • \n", - " \n", - " \n", + " \n", + " \n", "
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            \n", @@ -2789,11 +2532,11 @@ "
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            \n", "
            geodatasets.Dataset
            \n", - "
            geoda.chile_labor
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            geoda.cars
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            \n", - "
            url
            https://geodacenter.github.io/data-and-lab//data/flma.zip
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            NA
            attribution
            Center for Spatial Data Science, University of Chicago
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            Labor Markets in Chile (1982-2002)
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            62
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            filename
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            url
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            NA
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            Center for Spatial Data Science, University of Chicago
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          • \n", - " \n", - " \n", + " \n", + " \n", "
            \n", " \n", "
            \n", @@ -2812,11 +2555,11 @@ "
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            geodatasets.Dataset
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            geoda.cincinnati
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            geoda.charleston1
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            \n", "
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            url
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            license
            NA
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            Center for Spatial Data Science, University of Chicago
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            2008 Cincinnati Crime + Socio-Demographics
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            89
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            filename
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            url
            https://geodacenter.github.io/data-and-lab//data/CharlestonMSA.zip
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            NA
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            Center for Spatial Data Science, University of Chicago
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            2000 Census Tract Data for Charleston, SC MSA and counties
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            \n", @@ -2826,8 +2569,8 @@ "
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            geodatasets.Dataset
            \n", - "
            geoda.cleveland
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            geoda.charleston2
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            \n", "
            \n", "
            \n", - "
            url
            https://geodacenter.github.io/data-and-lab//data/cleveland.zip
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            NA
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            Center for Spatial Data Science, University of Chicago
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            Center for Spatial Data Science, University of Chicago
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            1998 and 2001 Zip Code Business Patterns (Census Bureau) for Charleston, SC MSA
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            \n", "
            geodatasets.Dataset
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            geoda.columbus
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            geoda.chicago_health
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            \n", - "
            url
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            NA
            attribution
            Center for Spatial Data Science, University of Chicago
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            Columbus neighborhood crime
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            Center for Spatial Data Science, University of Chicago
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            geodatasets.Dataset
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            geoda.elections
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            geoda.chicago_commpop
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            \n", "
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            url
            https://geodacenter.github.io/data-and-lab//data/election.zip
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            NA
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            geodatasets.Dataset
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            geoda.grid100
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            geoda.chile_labor
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            NA
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            Center for Spatial Data Science, University of Chicago
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            geodatasets.Dataset
            \n", - "
            geoda.groceries
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            geoda.cincinnati
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            \n", - "
            url
            https://geodacenter.github.io/data-and-lab//data/grocery.zip
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            NA
            attribution
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            geodatasets.Dataset
            \n", - "
            geoda.guerry
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            geoda.cleveland
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            \n", - "
            url
            https://geodacenter.github.io/data-and-lab//data/guerry.zip
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            NA
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            Center for Spatial Data Science, University of Chicago
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            Moral statistics of France (Guerry, 1833)
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            guerry.zip
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            geodatasets.Dataset
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            geoda.health+
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            geoda.grid100
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            \n", "
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            url
            https://geodacenter.github.io/data-and-lab//data/income_diversity.zip
            license
            NA
            attribution
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            income_diversity.zip
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            url
            https://geodacenter.github.io/data-and-lab//data/grid100.zip
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            Center for Spatial Data Science, University of Chicago
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            Grid with simulated variables
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            geodatasets.Dataset
            \n", - "
            geoda.health_indicators
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            geoda.groceries
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" 'license': 'NA',\n", - " 'attribution': 'Center for Spatial Data Science, University of Chicago',\n", - " 'name': 'geoda.sanfran_crime',\n", - " 'description': 'July-Dec 2012 crime incidents in San Francisco (points + area) - for CAST',\n", - " 'nrows': 3384,\n", - " 'ncols': 13,\n", - " 'details': 'https://geodacenter.github.io/data-and-lab//SFcrimes_vars/',\n", - " 'hash': 'a3cb7ac51875914389bee73aca6815244fca1d2461f97ef7b03f2ee9f66df74b',\n", - " 'filename': 'SFCrime_July_Dec2012.zip'},\n", + " 'filename': 'SacramentoMSA2.zip',\n", + " 'members': ['SacramentoMSA2/SacramentoMSA2.gpkg']},\n", " 'savannah1': {'url': 'https://geodacenter.github.io/data-and-lab//data/SavannahMSA.zip',\n", " 'license': 'NA',\n", " 'attribution': 'Center for Spatial Data Science, University of Chicago',\n", " 'name': 'geoda.savannah1',\n", " 'description': '2000 Census Tract Data for Savannah, GA MSA and counties',\n", + " 'geometry_type': 'Polygon',\n", " 'nrows': 77,\n", - " 'ncols': 30,\n", + " 'ncols': 31,\n", " 'details': 'https://geodacenter.github.io/data-and-lab//savannah1/',\n", " 'hash': 'df48c228776d2122c38935b2ebbf4cbb90c0bacc68df01161e653aab960e4208',\n", - " 'filename': 'SavannahMSA.zip'},\n", + " 'filename': 'SavannahMSA.zip',\n", + " 'members': ['SavannahMSA/ga_final_census2.gpkg']},\n", " 'savannah2': {'url': 'https://geodacenter.github.io/data-and-lab//data/SavannahMSA2.zip',\n", " 'license': 'NA',\n", " 'attribution': 'Center for Spatial Data Science, University of Chicago',\n", " 'name': 'geoda.savannah2',\n", " 'description': '1998 and 2001 Zip Code Business Patterns (Census Bureau) for Savannah, GA MSA',\n", + " 'geometry_type': 'Polygon',\n", " 'nrows': 24,\n", - " 'ncols': 55,\n", + " 'ncols': 60,\n", " 'details': 'https://geodacenter.github.io/data-and-lab//savannah2/',\n", " 'hash': '5b22b84a8665434cb91e800a039337f028b888082b8ef7a26d77eb6cc9aea8c1',\n", - " 'filename': 'SavannahMSA2.zip'},\n", - " 'scotlip': {'url': 'https://geodacenter.github.io/data-and-lab//data/scotlip.zip',\n", - " 'license': 'NA',\n", - " 'attribution': 'Center for Spatial Data Science, University of Chicago',\n", - " 'name': 'geoda.scotlip',\n", - " 'description': 'Male lip cancer in Scotland, 1975-80',\n", - " 'nrows': 56,\n", - " 'ncols': 11,\n", - " 'details': 'https://geodacenter.github.io/data-and-lab//scotlip/',\n", - " 'hash': 'b83e23d6ec294d6ca53f36f85f1dfb335ce1cb5bf4b85892b48072415cac0e83',\n", - " 'filename': 'scotlip.zip'},\n", + " 'filename': 'SavannahMSA2.zip',\n", + " 'members': ['SavannahMSA2/SavannahMSA2.gpkg']},\n", " 'seattle1': {'url': 'https://geodacenter.github.io/data-and-lab//data/SeattleMSA.zip',\n", " 'license': 'NA',\n", " 'attribution': 'Center for Spatial Data Science, University of Chicago',\n", " 'name': 'geoda.seattle1',\n", " 'description': '2000 Census Tract Data for Seattle, WA MSA and counties',\n", + " 'geometry_type': 'Polygon',\n", " 'nrows': 664,\n", - " 'ncols': 30,\n", + " 'ncols': 31,\n", " 'details': 'https://geodacenter.github.io/data-and-lab//seattle1/',\n", " 'hash': '46fb75a30f0e7963e6108bdb19af4d7db4c72c3d5a020025cafa528c96e09daa',\n", - " 'filename': 'SeattleMSA.zip'},\n", + " 'filename': 'SeattleMSA.zip',\n", + " 'members': ['SeattleMSA/wa_final_census2.gpkg']},\n", " 'seattle2': {'url': 'https://geodacenter.github.io/data-and-lab//data/SeattleMSA2.zip',\n", " 'license': 'NA',\n", " 'attribution': 'Center for Spatial Data Science, University of Chicago',\n", " 'name': 'geoda.seattle2',\n", " 'description': '1998 and 2001 Zip Code Business Patterns (Census Bureau) for Seattle, WA MSA',\n", + " 'geometry_type': 'Polygon',\n", " 'nrows': 145,\n", - " 'ncols': 59,\n", + " 'ncols': 60,\n", " 'details': 'https://geodacenter.github.io/data-and-lab//seattle2/',\n", " 'hash': '3dac2fa5b8c8dfa9dd5273a85de7281e06e18ab4f197925607f815f4e44e4d0c',\n", - " 'filename': 'SeattleMSA2.zip'},\n", + " 'filename': 'SeattleMSA2.zip',\n", + " 'members': ['SeattleMSA2/SeattleMSA2.gpkg']},\n", " 'sids': {'url': 'https://geodacenter.github.io/data-and-lab//data/sids.zip',\n", " 'license': 'NA',\n", " 'attribution': 'Center for Spatial Data Science, University of Chicago',\n", " 'name': 'geoda.sids',\n", " 'description': 'North Carolina county SIDS death counts',\n", + " 'geometry_type': 'Polygon',\n", " 'nrows': 100,\n", - " 'ncols': 13,\n", + " 'ncols': 15,\n", " 'details': 'https://geodacenter.github.io/data-and-lab//sids/',\n", " 'hash': 'e2f7b210b9a57839423fd170e47c02cf7a2602a480a1036bb0324e1112a4eaab',\n", - " 'filename': 'sids.zip'},\n", + " 'filename': 'sids.zip',\n", + " 'members': ['sids/sids.gpkg']},\n", " 'sids2': {'url': 'https://geodacenter.github.io/data-and-lab//data/sids2.zip',\n", " 'license': 'NA',\n", " 'attribution': 'Center for Spatial Data Science, University of Chicago',\n", " 'name': 'geoda.sids2',\n", " 'description': 'North Carolina county SIDS death counts and rates',\n", + " 'geometry_type': 'Polygon',\n", " 'nrows': 100,\n", - " 'ncols': 17,\n", + " 'ncols': 19,\n", " 'details': 'https://geodacenter.github.io/data-and-lab//sids2/',\n", " 'hash': 'b5875ffbdb261e6fa75dc4580d67111ef1434203f2d6a5d63ffac16db3a14bd0',\n", - " 'filename': 'sids2.zip'},\n", - " 'snow': {'url': 'https://geodacenter.github.io/data-and-lab//data/snow.zip',\n", - " 'license': 'NA',\n", - " 'attribution': 'Center for Spatial Data Science, University of Chicago',\n", - " 'name': 'geoda.snow',\n", - " 'description': 'John Snow & the 19th Century Cholera Epidemic',\n", - " 'nrows': 'missing',\n", - " 'ncols': 'missing',\n", - " 'details': 'https://geodacenter.github.io/data-and-lab//snow/',\n", - " 'hash': 'd974dbe3c16a31459e213556f4e4c5e3494db620615aa624104582cde0e2d83c',\n", - " 'filename': 'snow.zip'},\n", + " 'filename': 'sids2.zip',\n", + " 'members': ['sids2/sids2.gpkg']},\n", " 'south': {'url': 'https://geodacenter.github.io/data-and-lab//data/south.zip',\n", " 'license': 'NA',\n", " 'attribution': 'Center for Spatial Data Science, University of Chicago',\n", " 'name': 'geoda.south',\n", " 'description': 'US Southern county homicides 1960-1990',\n", + " 'geometry_type': 'Polygon',\n", " 'nrows': 1412,\n", - " 'ncols': 69,\n", + " 'ncols': 70,\n", " 'details': 'https://geodacenter.github.io/data-and-lab//south/',\n", " 'hash': '8f151d99c643b187aad37cfb5c3212353e1bc82804a4399a63de369490e56a7a',\n", - " 'filename': 'south.zip'},\n", + " 'filename': 'south.zip',\n", + " 'members': ['south/south.gpkg']},\n", " 'spirals': {'url': 'https://geodacenter.github.io/data-and-lab//data/spirals.csv',\n", " 'license': 'NA',\n", " 'attribution': 'Center for Spatial Data Science, University of Chicago',\n", " 'name': 'geoda.spirals',\n", " 'description': 'Synthetic spiral points',\n", - " 'nrows': 301,\n", + " 'geometry_type': 'Point',\n", + " 'nrows': 300,\n", " 'ncols': 2,\n", " 'details': 'https://geodacenter.github.io/data-and-lab//spirals/',\n", " 'hash': '3203b0a6db37c1207b0f1727c980814f541ce0a222597475f9c91540b1d372f1',\n", @@ -4676,8 +4312,9 @@ " 'attribution': 'Center for Spatial Data Science, University of Chicago',\n", " 'name': 'geoda.stlouis',\n", " 'description': 'St Louis region county homicide counts and rates',\n", + " 'geometry_type': 'Polygon',\n", " 'nrows': 78,\n", - " 'ncols': 23,\n", + " 'ncols': 24,\n", " 'details': 'https://geodacenter.github.io/data-and-lab//stlouis/',\n", " 'hash': '181a17a12e9a2b2bfc9013f399e149da935e0d5cb95c3595128f67898c4365f3',\n", " 'filename': 'stlouis.zip'},\n", @@ -4686,21 +4323,28 @@ " 'attribution': 'Center for Spatial Data Science, University of Chicago',\n", " 'name': 'geoda.tampa1',\n", " 'description': '2000 Census Tract Data for Tampa, FL MSA and counties',\n", + " 'geometry_type': 'Polygon',\n", " 'nrows': 547,\n", - " 'ncols': 30,\n", + " 'ncols': 31,\n", " 'details': 'https://geodacenter.github.io/data-and-lab//tampa1/',\n", " 'hash': '9a7ea0746138f62aa589e8377edafea48a7b1be0cdca2b38798ba21665bfb463',\n", - " 'filename': 'TampaMSA.zip'},\n", + " 'filename': 'TampaMSA.zip',\n", + " 'members': ['TampaMSA/tampa_final_census2.gpkg']},\n", " 'us_sdoh': {'url': 'https://geodacenter.github.io/data-and-lab//data/us-sdoh-2014.zip',\n", " 'license': 'NA',\n", " 'attribution': 'Center for Spatial Data Science, University of Chicago',\n", " 'name': 'geoda.us_sdoh',\n", " 'description': '2014 US Social Determinants of Health Data',\n", + " 'geometry_type': 'Polygon',\n", " 'nrows': 71901,\n", - " 'ncols': 25,\n", + " 'ncols': 26,\n", " 'details': 'https://geodacenter.github.io/data-and-lab//us-sdoh/',\n", " 'hash': '076701725c4b67248f79c8b8a40e74f9ad9e194d3237e1858b3d20176a6562a5',\n", - " 'filename': 'us-sdoh-2014.zip'}}" + " 'filename': 'us-sdoh-2014.zip',\n", + " 'members': ['us-sdoh-2014/us-sdoh-2014.shp',\n", + " 'us-sdoh-2014/us-sdoh-2014.dbf',\n", + " 'us-sdoh-2014/us-sdoh-2014.shx',\n", + " 'us-sdoh-2014/us-sdoh-2014.prj']}}" ] }, "execution_count": 3, @@ -4854,7 +4498,7 @@ " \n", "
    \n", "
    \n", - "
    url
    https://geodacenter.github.io/data-and-lab//data/atlanta_hom.zip
    license
    NA
    attribution
    Center for Spatial Data Science, University of Chicago
    description
    Atlanta, GA region homicide counts and rates
    nrows
    90
    ncols
    23
    details
    https://geodacenter.github.io/data-and-lab//atlanta_old/
    hash
    a33a76e12168fe84361e60c88a9df4856730487305846c559715c89b1a2b5e09
    filename
    atlanta_hom.zip
    \n", + "
    url
    https://geodacenter.github.io/data-and-lab//data/atlanta_hom.zip
    license
    NA
    attribution
    Center for Spatial Data Science, University of Chicago
    description
    Atlanta, GA region homicide counts and rates
    geometry_type
    Polygon
    nrows
    90
    ncols
    24
    details
    https://geodacenter.github.io/data-and-lab//atlanta_old/
    hash
    a33a76e12168fe84361e60c88a9df4856730487305846c559715c89b1a2b5e09
    filename
    atlanta_hom.zip
    members
    ['atlanta_hom/atl_hom.geojson']
    \n", "
    \n", "
    \n", " \n", @@ -4867,11 +4511,13 @@ " 'attribution': 'Center for Spatial Data Science, University of Chicago',\n", " 'name': 'geoda.atlanta',\n", " 'description': 'Atlanta, GA region homicide counts and rates',\n", + " 'geometry_type': 'Polygon',\n", " 'nrows': 90,\n", - " 'ncols': 23,\n", + " 'ncols': 24,\n", " 'details': 'https://geodacenter.github.io/data-and-lab//atlanta_old/',\n", " 'hash': 'a33a76e12168fe84361e60c88a9df4856730487305846c559715c89b1a2b5e09',\n", - " 'filename': 'atlanta_hom.zip'}" + " 'filename': 'atlanta_hom.zip',\n", + " 'members': ['atlanta_hom/atl_hom.geojson']}" ] }, "execution_count": 4, @@ -4928,17 +4574,10 @@ "execution_count": 6, "metadata": {}, "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "Downloading file 'atlanta_hom.zip' from 'https://geodacenter.github.io/data-and-lab//data/atlanta_hom.zip' to '/Users/martin/Library/Caches/geodatasets'.\n" - ] - }, { "data": { "text/plain": [ - "'/Users/martin/Library/Caches/geodatasets/atlanta_hom.zip'" + "'/Users/martin/Library/Caches/geodatasets/atlanta_hom.zip.unzip/atlanta_hom/atl_hom.geojson'" ] }, "execution_count": 6, @@ -4949,6 +4588,60 @@ "source": [ "geodatasets.get_path(\"geoda atlanta\")" ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The same can be extracted via `url` and `path` properties of the `Dataset`." + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "'https://geodacenter.github.io/data-and-lab//data/atlanta_hom.zip'" + ] + }, + "execution_count": 7, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "geodatasets.data.geoda.atlanta.url" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Retrieving the path optionally triggers file download as `get_path`." + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "'/Users/martin/Library/Caches/geodatasets/atlanta_hom.zip.unzip/atlanta_hom/atl_hom.geojson'" + ] + }, + "execution_count": 8, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "geodatasets.data.geoda.atlanta.path" + ] } ], "metadata": { @@ -4967,7 +4660,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.10.6" + "version": "3.12.5" }, "orig_nbformat": 4, "vscode": { diff --git a/geodatasets/api.py b/geodatasets/api.py index e665b45..bfa135d 100644 --- a/geodatasets/api.py +++ b/geodatasets/api.py @@ -84,19 +84,7 @@ def get_path(name): '/Users/martin/Library/Caches/geodatasets/airbnb.zip' """ dataset = data.query_name(name) - if "members" in dataset.keys(): - unzipped_files = CACHE.fetch( - dataset.filename, processor=pooch.Unzip(members=dataset.members) - ) - if len(unzipped_files) == 1: - return unzipped_files[0] - elif len(unzipped_files) > 1: # shapefile - return [f for f in unzipped_files if f.endswith(".shp")][0] - else: - raise - - else: - return CACHE.fetch(dataset.filename) + return dataset.path def fetch(name): diff --git a/geodatasets/lib.py b/geodatasets/lib.py index 6beaf1f..2eed603 100644 --- a/geodatasets/lib.py +++ b/geodatasets/lib.py @@ -10,6 +10,8 @@ import uuid from typing import Callable +import pooch + GEOMETRY_TYPES = ["POINT", "LINESTRING", "POLYGON", "MIXED"] QUERY_NAME_TRANSLATION = str.maketrans({x: "" for x in "., -_/"}) @@ -284,6 +286,34 @@ def copy(self, **kwargs) -> Dataset: new = Dataset(self) # takes a copy preserving the class return new + @property + def path(self) -> str: + """Get the absolute path to a file in the local storage. + + If it’s not in the local storage, it will be downloaded. + + For Datasets containing multiple files, the archive is automatically extracted. + + Returns + ------- + str + loacal path + """ + from .api import CACHE + + if "members" in self.keys(): + unzipped_files = CACHE.fetch( + self.filename, processor=pooch.Unzip(members=self.members) + ) + if len(unzipped_files) == 1: + return unzipped_files[0] + elif len(unzipped_files) > 1: # shapefile + return [f for f in unzipped_files if f.endswith(".shp")][0] + else: + raise + + return CACHE.fetch(self.filename) + def _repr_html_(self, inside=False): item_info = "" for key, val in self.items(): diff --git a/geodatasets/tests/test_lib.py b/geodatasets/tests/test_lib.py index 86f5785..de98a72 100644 --- a/geodatasets/tests/test_lib.py +++ b/geodatasets/tests/test_lib.py @@ -1,3 +1,7 @@ +import os +from pathlib import Path + +import pooch import pytest from geodatasets import Bunch, Dataset, data @@ -156,3 +160,15 @@ def custom(provider): return False assert len(test_bunch.filter(function=custom).flatten()) == 1 + + +@pytest.mark.request +def test_get_path(): + in_cache = pooch.os_cache("geodatasets").joinpath("nybb_16a.zip") + if Path(in_cache).exists(): + os.remove(in_cache) + + assert Path(data.ny.bb.path).exists() + + # cleanup + os.remove(in_cache)