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postgis_tables_summary.txt

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+PostGIS Tables Summary
+
+Database:
+data_centers
+
+Host:
+db.dadams.io:5433
+
+Credentials:
+Loaded from PGWEB_* environment variables in /home/dadams/.zsh_secrets.
+
+Point table:
+public.us_dc_sample_geocoded
+
+Point table description:
+One row per data center loaded into public.us_dc_sample_geocoded from either:
+- US_DC_Sample_geocoded.csv (Census + Nominatim geocoded sample), or
+- new/IM3_Existing_DataCenters.csv (adapted to the same schema).
+
+The geoid column stores the Census tract GEOID when assigned.
+
+Point table geometry:
+- Column: geom
+- Type: geometry(Point, 4326)
+- Generated from longitude and latitude
+
+Point table validation:
+- 1489 rows
+- 1489 geom values
+- 1489 geoid values
+- 1240 rows from IM3_Existing_DataCenters
+- 204 address_range geocoded points from U.S. Census Geocoder
+- 45 city-precision fallback points from Nominatim/OpenStreetMap
+- geocode_precision distribution: building=1039, campus=108, point=93, address_range=204, city=45
+
+Point table indexes:
+- Primary key on id
+- GiST index on geom
+- B-tree index on state_code, city
+- B-tree index on geoid
+
+Tract table:
+public.data_center_census_tracts_2024
+
+Tract table description:
+One row per 2024 Census tract containing at least one data-center point from public.us_dc_sample_geocoded.
+
+Tract table geometry:
+- Column: geom
+- Type: geometry(MultiPolygon, 4326)
+- Source: U.S. Census 2024 cartographic tract boundaries
+
+Tract table validation:
+- 611 tract rows
+- 1489 data centers assigned to tracts
+- 204 address_range data-center points assigned
+- 45 city-precision data-center points assigned
+- 0 missing ACS population values
+
+Tract table scope note:
+The tract table now reflects the expanded 1489-point dataset, including IM3 rows adapted into the point table schema.
+
+Tract table indexes:
+- Primary key on geoid
+- GiST index on geom
+- B-tree index on statefp, countyfp
+- B-tree index on data_center_count desc
+
+Tract table enrichment:
+ACS 2024 5-year profile fields were added for:
+- population
+- median age
+- households
+- average household size
+- education
+- broadband subscription
+- labor force
+- unemployment
+- household income
+- per-capita income
+- family poverty rate
+- overall poverty rate
+- Hispanic/Latino population and percent
+- non-Hispanic White population and percent
+- non-Hispanic Black population and percent
+- non-Hispanic Asian population and percent
+- industry worker counts
+
+Derived tract fields:
+- data_center_count
+- address_range_data_center_count
+- city_precision_data_center_count
+- data_center_ids
+- providers
+- primary_industry
+- primary_industry_workers
+- primary_industry_pct
+
+Primary industry note:
+primary_industry is derived from ACS DP03 industry worker categories. It is the industry category with the largest worker count in that tract, not an industry classification for the data center itself.
+
+Recommended direct join:
+Use geoid for normal analysis joins between the point table and the tract table.
+
+Example:
+select
+  dc.id,
+  dc.provider,
+  dc.facility_name,
+  tr.geoid,
+  tr.population,
+  tr.median_household_income,
+  tr.primary_industry
+from public.us_dc_sample_geocoded dc
+join public.data_center_census_tracts_2024 tr
+  on tr.geoid = dc.geoid;
+
+Array-based join:
+Use data_center_ids to reproduce the reverse point-to-tract assignment stored in the tract table.
+
+Example:
+select
+  dc.id,
+  dc.provider,
+  dc.facility_name,
+  tr.geoid,
+  tr.population,
+  tr.median_household_income,
+  tr.primary_industry
+from public.data_center_census_tracts_2024 tr
+join public.us_dc_sample_geocoded dc
+  on dc.id = any(tr.data_center_ids);
+
+Recommended spatial join:
+Use this when you want PostGIS to recalculate the tract relationship from geometry.
+
+Example:
+select
+  dc.id,
+  dc.provider,
+  dc.facility_name,
+  tr.geoid,
+  tr.population,
+  tr.primary_industry
+from public.us_dc_sample_geocoded dc
+join public.data_center_census_tracts_2024 tr
+  on st_covers(tr.geom, dc.geom);
+
+Useful tract-level query:
+select
+  geoid,
+  data_center_count,
+  population,
+  median_household_income,
+  primary_industry,
+  providers
+from public.data_center_census_tracts_2024
+order by data_center_count desc;
+
+Caveats:
+- 45 data centers used city-precision fallback coordinates, so their tract assignments are approximate.
+- Census address geocoding returns address-range coordinates, not guaranteed rooftop or building-centroid coordinates.
+- The tract table only includes tracts containing at least one data-center point. It is not a full national or selected-state tract universe.
+- ACS values are estimates from the 2024 ACS 5-year profile and should be interpreted as survey estimates.
+
+Reproducible scripts:
+- load_postgis_data_centers.py
+- create_data_center_census_tract_table.py
+
+IM3 append command used:
+python3 load_postgis_data_centers.py --source im3 --append --upsert
+
+Rebuild command used:
+python3 create_data_center_census_tract_table.py --replace-final
+
+Local audit files:
+- US_DC_Sample_geocoded.csv
+- census_tract_acs_2024_selected_states.csv
+- census_address_results.csv
+- nominatim_city_cache.csv
+
+Primary sources:
+- U.S. Census ACS API
+- U.S. Census 2024 cartographic tract boundaries
+- U.S. Census Geocoder
+- Nominatim/OpenStreetMap for city-level fallback coordinates