Wolfram Language™

Enhance Curated Datasets with Built-In Data

The extensive collection of built-in socioeconomic data in the Wolfram Knowledgebase can be used to enhance external data sources.

Start with a dataset of Head Start locations, imported from the US Department of Housing and Urban Development.

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hs = ResourceData["Head Start Locations"][ All, {"CenterName", "CenterAddress", "CenterStateEntity", "CenterCityEntity", "CenterZipCodeEntity", "Coordinates"}];

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Take[hs, 5]

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Use a selection operator to extract a subset of locations.

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hsChicago = hs[Select[#CenterCityEntity === Entity["City", {"Chicago", "Illinois", "UnitedStates"}] &]];

Represent them on a map of Chicago.

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GeoListPlot[hsChicago[All, #Coordinates &]]

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Group Head Start locations and plot their distribution by ZIP code.

In[5]:=

chicagoCounts = Length /@ GroupBy[hsChicago, #CenterZipCodeEntity &];

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GeoRegionValuePlot[chicagoCounts]

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Retrieve built-in data about the school-age population in Chicago ZIP codes and plot those values against counts of Head Start locations derived from the external HUD data.

In[7]:=

zipcodes = Normal@Keys[chicagoCounts]

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In[8]:=

chicagoMedian = EntityValue[zipcodes, EntityProperty["ZIPCode", "Population", {"Age" -> "SchoolAge"}], "EntityAssociation"];

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locsVSkids = Merge[{Normal@chicagoCounts, chicagoMedian}, Identity]; ListPlot[locsVSkids, FrameLabel -> {"Head Start locations", "School age population"}, ImageSize -> 550, PlotTheme -> "Detailed"]

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