Tutorial: Get local 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 manage) GIS resources such as content, users, and groups. Additionally, import the Geometry and Point classes from the arcgis.geometry module, the FeatureSet class from arcgis.features module and the Country method from the arcgis.geoenrichment module.

   Use dark colors for code blocks

   1
   2
   3
   4
   5
   6
   7
   8
   9
   10
   11
   12
   13
   14
   15
   16
   17
   18
   19
   20
   21
   22
   23
   24
   25
   26
   27
   28
   29
   30
   31
   32
   33
   34
   35
   36
   37
   38
   39
   40
   41
   42
   43
   44
   45
   46
   47
   48
   49
   50
   51
   52
   53
   54
   55
   56
   57
   58
   
   from arcgis.gis import GIS
   from arcgis.features import FeatureSet
   from arcgis.geoenrichment import Country
   from arcgis.geometry import Geometry, Point
   
   
   

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

   Use dark colors for code blocks

   1
   2
   3
   4
   5
   6
   7
   8
   9
   10
   11
   12
   13
   14
   15
   16
   17
   18
   19
   20
   21
   22
   23
   24
   25
   26
   27
   28
   29
   30
   31
   32
   33
   34
   35
   36
   37
   38
   39
   40
   41
   42
   43
   44
   45
   46
   47
   48
   49
   50
   51
   52
   53
   54
   55
   56
   57
   58
   
   from arcgis.gis import GIS
   from arcgis.features import FeatureSet
   from arcgis.geoenrichment import Country
   from arcgis.geometry import Geometry, Point
   
   
   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 Nashville, Tennessee.

   Use dark colors for code blocks

   1
   2
   3
   4
   5
   6
   7
   8
   9
   10
   11
   12
   13
   14
   15
   16
   17
   18
   19
   20
   21
   22
   23
   24
   25
   26
   27
   28
   29
   30
   31
   32
   33
   34
   35
   36
   37
   38
   39
   40
   41
   42
   43
   44
   45
   46
   47
   48
   49
   50
   51
   52
   53
   54
   55
   56
   57
   58
   
   portal = GIS("home")
   print(f"Connected to {portal.properties.name} as {portal.properties.user.username}")
   
   study_area_pt = Point({"x": -86.7679, "y": 36.1745, "spatialReference": {"wkid": 4326}})
   
   

Get demographic data

1. Use the Country class from the arcgis.geoenrichment module. This provides access to local variables for a specific country. Pass in the study area point and the following variable names :

   • PsychographicsShopping.MP28067A_B
   • transportation.X7027_I
   • entertainment.X9005_I
   • lifemodegroupsNEW.TLIFENAME

   To learn more about the data collections and variables, go to Data Collections and GeoEnrichment coverage.

   Use dark colors for code blocks

   1
   2
   3
   4
   5
   6
   7
   8
   9
   10
   11
   12
   13
   14
   15
   16
   17
   18
   19
   20
   21
   22
   23
   24
   25
   26
   27
   28
   29
   30
   31
   32
   33
   34
   35
   36
   37
   38
   39
   40
   41
   42
   43
   44
   45
   46
   47
   48
   49
   50
   51
   52
   53
   54
   55
   56
   57
   58
   
   study_area_pt = Point({"x": -86.7679, "y": 36.1745, "spatialReference": {"wkid": 4326}})
   
   usa_data = Country("usa", portal)
   
   enrich_results = usa_data.enrich(
       study_areas=[study_area_pt],
       enrich_variables=[
           "PsychographicsShopping.MP28067A_B",
           "transportation.X7027_I",
           "entertainment.X9005_I",
           "lifemodegroupsNEW.TLIFENAME",
       ],
   )
   
   

2. To view the values returned from the enrichment, use the dataframe object returned from the enrich method to display the results as a table. Pass in an array of field names to limit the results to a subset of columns.

   Use dark colors for code blocks

   1
   2
   3
   4
   5
   6
   7
   8
   9
   10
   11
   12
   13
   14
   15
   16
   17
   18
   19
   20
   21
   22
   23
   24
   25
   26
   27
   28
   29
   30
   31
   32
   33
   34
   35
   36
   37
   38
   39
   40
   41
   42
   43
   44
   45
   46
   47
   48
   49
   50
   51
   52
   53
   54
   55
   56
   57
   58
   
   usa_data = Country("usa", portal)
   
   enrich_results = usa_data.enrich(
       study_areas=[study_area_pt],
       enrich_variables=[
           "PsychographicsShopping.MP28067A_B",
           "transportation.X7027_I",
           "entertainment.X9005_I",
           "lifemodegroupsNEW.TLIFENAME",
       ],
   )
   
   
   display_cols = [
       "aggregation_method",
       "population_to_polygon_size_rating",
       "apportionment_confidence",
       "tlifename",
       "x9005_i",
       "mp28067a_b",
       "x7027_i",
   ]
   enrich_results[display_cols]
   
   

Display the results on a map

1. Use the map property from the GIS class to create a map. To set the initial extent of the map, pass in the string Nashville, TN This will set the map to an extent that is appropriate for the results. Set the basemap of the map to arcgis-navigation.

   Use dark colors for code blocks

   1
   2
   3
   4
   5
   6
   7
   8
   9
   10
   11
   12
   13
   14
   15
   16
   17
   18
   19
   20
   21
   22
   23
   24
   25
   26
   27
   28
   29
   30
   31
   32
   33
   34
   35
   36
   37
   38
   39
   40
   41
   42
   43
   44
   45
   46
   47
   48
   49
   50
   51
   52
   53
   54
   55
   56
   57
   58
   
   
   display_cols = [
       "aggregation_method",
       "population_to_polygon_size_rating",
       "apportionment_confidence",
       "tlifename",
       "x9005_i",
       "mp28067a_b",
       "x7027_i",
   ]
   enrich_results[display_cols]
   
   map = portal.map("Nashville, TN")
   map.basemap.basemap = "arcgis-navigation"
   map
   
   

2. Use the FeatureSet class to convert the returned Pandas DataFrame into a feature set. Create a popup object that will display formatted attribute values when a feature is clicked in the map.

   Use dark colors for code blocks

   1
   2
   3
   4
   5
   6
   7
   8
   9
   10
   11
   12
   13
   14
   15
   16
   17
   18
   19
   20
   21
   22
   23
   24
   25
   26
   27
   28
   29
   30
   31
   32
   33
   34
   35
   36
   37
   38
   39
   40
   41
   42
   43
   44
   45
   46
   47
   48
   49
   50
   51
   52
   53
   54
   55
   56
   57
   58
   
   map = portal.map("Nashville, TN")
   map.basemap.basemap = "arcgis-navigation"
   map
   
   enrich_features = FeatureSet.from_dataframe(enrich_results)
   enrich_features
   
   # set popup info
   from arcgis.map.popups import PopupInfo
   popup_fields = [
       "Buys natural products: {mp28067a_b}",
       "Membership fees for Social Clubs: {x9005_i}",
       "Auto/Truck rental on trips: {x7027_i}",
       "Tapestry group name: {tlifename}",
   ]
   pi = PopupInfo(
     title="Data for a 1 mile search radius",
     description="<br>".join(popup_fields)
   )
   
   
   

3. Use the add method to pass in the enriched geometry and popup info to add the results to the map content.

   Use dark colors for code blocks

   1
   2
   3
   4
   5
   6
   7
   8
   9
   10
   11
   12
   13
   14
   15
   16
   17
   18
   19
   20
   21
   22
   23
   24
   25
   26
   27
   28
   29
   30
   31
   32
   33
   34
   35
   36
   37
   38
   39
   40
   41
   42
   43
   44
   45
   46
   47
   48
   49
   50
   51
   52
   53
   54
   55
   56
   57
   58
   
   enrich_features = FeatureSet.from_dataframe(enrich_results)
   enrich_features
   
   # set popup info
   from arcgis.map.popups import PopupInfo
   popup_fields = [
       "Buys natural products: {mp28067a_b}",
       "Membership fees for Social Clubs: {x9005_i}",
       "Auto/Truck rental on trips: {x7027_i}",
       "Tapestry group name: {tlifename}",
   ]
   pi = PopupInfo(
     title="Data for a 1 mile search radius",
     description="<br>".join(popup_fields)
   )
   
   
   map.content.add(enrich_features, popup_info=pi)

You should see a map centered around Nashville, TN with a graphic representing a 1 mile radius around the study area point. Click on the graphic to display a popup containing local demographic values.