# Wolfram Mathematica

## 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.

In[1]:=
```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.

In[3]:=
```hsChicago = hs[Select[#CenterCityEntity === Entity["City", {"Chicago", "Illinois", "UnitedStates"}] &]];```

Represent them on a map of Chicago.

In[4]:=
`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"];```
show complete Wolfram Language input
In[9]:=
```locsVSkids = Merge[{Normal@chicagoCounts, chicagoMedian}, Identity]; ListPlot[locsVSkids, FrameLabel -> {"Head Start locations", "School age population"}, ImageSize -> 550, PlotTheme -> "Detailed"]```
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