Update 2022 data

[tomay]

Steps

• [x] Upload CSV named Carto_2022_Data_extra 20240604 to Drive (saved here)
• [x] Remove columns carto_id and geom
• [x] Export as CSV (copy saved here)
• [x] Upload that CSV to CARTO, named data_2022_update
• [x] Create a copy of the existing production table, called seattle_buildings_2022_update_copy
• [x] Delete existing 2022 data from that copy with this SQL:

  DELETE from seattle_buildings_2022_update_copy where year = 2022

• [x] Update the copy of the production table with this SQL:

  INSERT INTO seattle_buildings_2022_update_copy (the_geom, property_type, id, xepaid, year, property_name, reported_address, city, state, zip, latitude, longitude, neighborhood, councildistrict, yearbuilt, numfloors, numbuildings, reported_gross_floor_area, energy_star_score, site_eui_wn, site_eui, total_kbtu, source_eui_wn, source_eui, electricity, steam, gas, epapropertytype, total_ghg_emissions, total_ghg_emissions_intensity, building_type_eui, building_type_eui_wn, electricity_pct, gas_pct, steam_pct, electricity_ghg, gas_ghg, steam_ghg, electricity_ghg_percent, gas_ghg_percent, steam_ghg_percent, cos_median_eui, percent_from_median, higher_or_lower, numunits, yearbuilt_string, ess_cert, cost_annual, cost_sq_ft, percent_save, amount_save, comments, pct_sum, parentid, cbps_euit, cbps_date, cbps_flag, uniqueid)
  SELECT the_geom, property_type, id, xepaid, year, property_name, reported_address, city, state, zip, latitude, longitude, neighborhood, councildistrict, yearbuilt, numfloors, numbuildings, reported_gross_floor_area, energy_star_score, site_eui_wn, site_eui, total_kbtu, source_eui_wn, source_eui, electricity, steam, gas, epapropertytype, total_ghg_emissions, total_ghg_emissions_intensity, building_type_eui, building_type_eui_wn, electricity_pct, gas_pct, steam_pct, electricity_ghg, gas_ghg, steam_ghg, electricity_ghg_percent, gas_ghg_percent, steam_ghg_percent, cos_median_eui, percent_from_median, higher_or_lower, numunits, yearbuilt_string, ess_cert, cost_annual, cost_sq_ft, percent_save, amount_save, comments, pct_sum, parentid, cbps_euit, cbps_date, cbps_flag, uniqueid
  FROM data_2022_update

• [x] Run the app locally, and udate the table name to seattle_buildings_2022_update_copy
• [x] Build, commit and confirm this is running on GH pages

┆Issue is synchronized with this Asana task

[tomay]

Result of the above shows a count of 3695 buildings for 2022, matching the spreadsheet

[tomay]

Noting a couple of data issues in the data as provided

property_type

• newline chars in name

• values of 0

higher_or_lower

• Values of 0

[tomay]

This is running on GH pages for review

As noted above, the issues with building_type produce the following selections in the dropdown

And selecting Self-storage Facility results in a blank map

A few additional issues I notice:

site_eui is sometimes presented as an integer, sometimes not:

There are values for energy_star_score that are 0, that probably should be blank in the original CSV (null), unless they are truly 0:

Same for site_eui: