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README.md

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@@ -6,6 +6,8 @@ The `geodatasets` contains an API on top of a JSON with metadata of externally h
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datasets containing geospatial information useful for illustrative and educational
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purposes.
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See the documentation at [geodatasets.readthedocs.io/](https://geodatasets.readthedocs.io/).
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## Install
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From PyPI:
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'hash': 'a2ab1e3f938226d287dd76cde18c00e2d3a260640dd826da7131827d9e76c824',
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'filename': 'airbnb.zip'}
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```
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The whole structure `Bunch` class is based on a dictionary and can be flattened. If you want
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to see all available datasets, you can use:
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```py
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In [7]: geodatasets.data.flatten().keys()
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Out[7]: dict_keys(['geoda.airbnb', 'geoda.atlanta', 'geoda.cars', 'geoda.charleston1', 'geoda.charleston2', 'geoda.chicago_health', 'geoda.chicago_commpop', 'geoda.chile_labor', 'geoda.cincinnati', 'geoda.cleveland', 'geoda.columbus', 'geoda.grid100', 'geoda.groceries', 'geoda.guerry', 'geoda.health', 'geoda.health_indicators', 'geoda.hickory1', 'geoda.hickory2', 'geoda.home_sales', 'geoda.houston', 'geoda.juvenile', 'geoda.lansing1', 'geoda.lansing2', 'geoda.lasrosas', 'geoda.liquor_stores', 'geoda.malaria', 'geoda.milwaukee1', 'geoda.milwaukee2', 'geoda.ncovr', 'geoda.natregimes', 'geoda.ndvi', 'geoda.nepal', 'geoda.nyc', 'geoda.nyc_earnings', 'geoda.nyc_education', 'geoda.nyc_neighborhoods', 'geoda.orlando1', 'geoda.orlando2', 'geoda.oz9799', 'geoda.phoenix_acs', 'geoda.police', 'geoda.sacramento1', 'geoda.sacramento2', 'geoda.savannah1', 'geoda.savannah2', 'geoda.seattle1', 'geoda.seattle2', 'geoda.sids', 'geoda.sids2', 'geoda.south', 'geoda.spirals', 'geoda.stlouis', 'geoda.tampa1', 'geoda.us_sdoh', 'ny.bb', 'eea.large_rivers', 'naturalearth.land'])
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```

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