Tutorial: Get global data

Import modules and log in

1. Import the GIS class from the arcgis.gis module. The GIS class provides helper objects to manage (search, create, and access) GIS resources such as content, users, and groups. Additionally, import the Geometry and Point classes from the arcgis.geometry module and the enrich method from the arcgis.geoenrichment module.

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   from arcgis.gis import GIS
   from arcgis.geometry import Geometry, Point
   from arcgis.features import FeatureSet
   from arcgis.geoenrichment import enrich
   
   
   

2. Log in to your portal. In hosted notebooks, You can use the "home" parameter to use the credentials of the currently logged in account.

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   from arcgis.gis import GIS
   from arcgis.geometry import Geometry, Point
   from arcgis.features import FeatureSet
   from arcgis.geoenrichment import enrich
   
   
   portal = GIS("home")
   print(f"Connected to {portal.properties.name} as {portal.properties.user.username}")
   
   

Create study area point

1. Use the Point class to construct a point geometry by passing in the coordinates and spatial reference representing a location in London, England.

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   portal = GIS("home")
   print(f"Connected to {portal.properties.name} as {portal.properties.user.username}")
   
   study_area_pt = Point(
       {"x": 0.1278, "y": 51.5074, "spatialReference": {"wkid": 4326}}
   )  # London, England
   
   

Get demographic data

1. Use the enrich function, passing in the study area point and the data collection text string of KeyGlobalFacts to get the demographic data. To learn more about data collections, go to Data enrichment.

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   study_area_pt = Point(
       {"x": 0.1278, "y": 51.5074, "spatialReference": {"wkid": 4326}}
   )  # London, England
   
   enrichment_results = enrich(
       study_areas=[study_area_pt], data_collections=["KeyGlobalFacts"]
   )
   enrichment_results
   
   enriched_features = FeatureSet.from_dataframe(enrichment_results)
   enriched_features
   
   

Display the results

1. Create a map and set its basemap to arcgis-navigation.

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   enrichment_results = enrich(
       study_areas=[study_area_pt], data_collections=["KeyGlobalFacts"]
   )
   enrichment_results
   
   enriched_features = FeatureSet.from_dataframe(enrichment_results)
   enriched_features
   
   map = portal.map("London, England")
   map.basemap.basemap = "arcgis-navigation"
   map
   
   

2. Use the enrichment results to construct a PopupInfo object.

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   # set popup info
   from arcgis.map.popups import PopupInfo
   popup_fields = [
       "Population: {totpop}",
       "Males: {totmales}",
       "Females: {totfemales}",
       "Average household size: {avghhsz}",
   ]
   pi = PopupInfo(title="Data for a 1 mile search radius", description="<br>".join(popup_fields))
   
   

3. Use the add method and pass in the enriched geomety and popup info to add the results to the maps content. Set the extent of the map to the result geometry's extent by calling the zoom_to_layer method.

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   # set popup info
   from arcgis.map.popups import PopupInfo
   popup_fields = [
       "Population: {totpop}",
       "Males: {totmales}",
       "Females: {totfemales}",
       "Average household size: {avghhsz}",
   ]
   pi = PopupInfo(title="Data for a 1 mile search radius", description="<br>".join(popup_fields))
   
   map.content.add(enriched_features, popup_info=pi)
   map.zoom_to_layer(enriched_features)

You should now see a map centered around London, England with a polygon graphic representing a 1 mile radius around the study area point. Click on the graphic to display a popup to view global demographic values.