From 819f3ff47800eb9bce895c67d45c7e011af01e94 Mon Sep 17 00:00:00 2001
From: Shelby Switzer <shelby.c.switzer@omb.eop.gov>
Date: Mon, 6 Dec 2021 13:17:17 -0500
Subject: [PATCH 1/5] Update etl constants to use score field_names and put
 strings around tract IDs in downloadable CSV (#985)

* Update etl constants to use score field_names

Put strings around tract IDs in downloadable CSV

No need to modify the xls file creation because the string type is
preserved and interpreted correctly in Excel already.

One note is that this does cause the ID in the CSV to be have quotes
around it, which might be annoying. Maybe we don't want this behavior?

* Update based on PR feedback and lint needs

* Change field we're using in downloadable

This reverts the downloadable csv field list to use
MEDIAN_INCOME_AS_PERCENT_OF_STATE_FIELD instead of
MEDIAN_INCOME_AS_PERCENT_OF_AMI_FIELD in order to get the test to pass.
The point of this PR is a refactor (and a small change to the CSV
quotations), not to change the output. That will be a different PR
later.

Co-authored-by: Shelby Switzer <shelby.switzer@cms.hhs.gov>
---
 .../data_pipeline/etl/score/constants.py      | 167 +++++++++---------
 .../data_pipeline/etl/score/etl_score_post.py |   9 +-
 .../data_pipeline/score/field_names.py        |   8 +-
 .../data_pipeline/score/score_l.py            |   2 +-
 4 files changed, 101 insertions(+), 85 deletions(-)

diff --git a/data/data-pipeline/data_pipeline/etl/score/constants.py b/data/data-pipeline/data_pipeline/etl/score/constants.py
index 11a29b11..d3338a82 100644
--- a/data/data-pipeline/data_pipeline/etl/score/constants.py
+++ b/data/data-pipeline/data_pipeline/etl/score/constants.py
@@ -4,6 +4,8 @@ import datetime
 import pandas as pd
 from data_pipeline.config import settings
 
+from data_pipeline.score import field_names
+
 # Base Paths
 DATA_PATH = Path(settings.APP_ROOT) / "data"
 TMP_PATH = DATA_PATH / "tmp"
@@ -59,88 +61,92 @@ SCORE_DOWNLOADABLE_ZIP_FILE_PATH = (
 # Column subsets
 CENSUS_COUNTIES_COLUMNS = ["USPS", "GEOID", "NAME"]
 TILES_SCORE_COLUMNS = [
-    "GEOID10_TRACT",
-    "State Name",
-    "County Name",
-    "Total population",
-    "Score D (percentile)",
-    "Score D (top 25th percentile)",
-    "Score E (percentile)",
-    "Score E (top 25th percentile)",
-    "Score G (communities)",
-    "Score G",
-    "Definition L (communities)",
-    "Definition L (percentile)",
-    "Poverty (Less than 200% of federal poverty line) (percentile)",
-    "Percent individuals age 25 or over with less than high school degree (percentile)",
-    "Linguistic isolation (percent) (percentile)",
-    "Unemployed civilians (percent) (percentile)",
-    "Housing burden (percent) (percentile)",
-    "Diagnosed diabetes among adults aged >=18 years (percentile)",
-    "Current asthma among adults aged >=18 years (percentile)",
-    "Coronary heart disease among adults aged >=18 years (percentile)",
-    "Life expectancy (years) (percentile)",
-    "Traffic proximity and volume (percentile)",
-    "FEMA Risk Index Expected Annual Loss Score (percentile)",
-    "Energy burden (percentile)",
-    "Wastewater discharge (percentile)",
-    "Percent pre-1960s housing (lead paint indicator) (percentile)",
-    "Diesel particulate matter (percentile)",
-    "Particulate matter (PM2.5) (percentile)",
-    "Median household income (% of AMI) (percentile)",
-    "Percent of individuals < 200% Federal Poverty Line (percentile)",
+    field_names.GEOID_TRACT_FIELD,
+    field_names.STATE_FIELD,
+    field_names.COUNTY_FIELD,
+    field_names.TOTAL_POP_FIELD,
+    field_names.SCORE_D + field_names.PERCENTILE_FIELD_SUFFIX,
+    field_names.SCORE_D + field_names.TOP_25_PERCENTILE_SUFFIX,
+    field_names.SCORE_E + field_names.PERCENTILE_FIELD_SUFFIX,
+    field_names.SCORE_E + field_names.TOP_25_PERCENTILE_SUFFIX,
+    field_names.SCORE_G_COMMUNITIES,
+    field_names.SCORE_G,
+    field_names.SCORE_L_COMMUNITIES,
+    field_names.SCORE_L + field_names.PERCENTILE_FIELD_SUFFIX,
+    field_names.POVERTY_FIELD + field_names.PERCENTILE_FIELD_SUFFIX,
+    field_names.HIGH_SCHOOL_ED_FIELD + field_names.PERCENTILE_FIELD_SUFFIX,
+    field_names.LINGUISTIC_ISO_FIELD + field_names.PERCENTILE_FIELD_SUFFIX,
+    field_names.UNEMPLOYMENT_FIELD + field_names.PERCENTILE_FIELD_SUFFIX,
+    field_names.HOUSING_BURDEN_FIELD + field_names.PERCENTILE_FIELD_SUFFIX,
+    field_names.DIABETES_FIELD + field_names.PERCENTILE_FIELD_SUFFIX,
+    field_names.ASTHMA_FIELD + field_names.PERCENTILE_FIELD_SUFFIX,
+    field_names.HEART_DISEASE_FIELD + field_names.PERCENTILE_FIELD_SUFFIX,
+    field_names.LIFE_EXPECTANCY_FIELD + field_names.PERCENTILE_FIELD_SUFFIX,
+    field_names.TRAFFIC_FIELD + field_names.PERCENTILE_FIELD_SUFFIX,
+    field_names.FEMA_RISK_FIELD + field_names.PERCENTILE_FIELD_SUFFIX,
+    field_names.ENERGY_BURDEN_FIELD + field_names.PERCENTILE_FIELD_SUFFIX,
+    field_names.WASTEWATER_FIELD + field_names.PERCENTILE_FIELD_SUFFIX,
+    field_names.LEAD_PAINT_FIELD + field_names.PERCENTILE_FIELD_SUFFIX,
+    field_names.DIESEL_FIELD + field_names.PERCENTILE_FIELD_SUFFIX,
+    field_names.PM25_FIELD + field_names.PERCENTILE_FIELD_SUFFIX,
+    field_names.MEDIAN_INCOME_AS_PERCENT_OF_AMI_FIELD
+    + field_names.PERCENTILE_FIELD_SUFFIX,
+    field_names.POVERTY_LESS_THAN_200_FPL_FIELD
+    + field_names.PERCENTILE_FIELD_SUFFIX,
 ]
 
 # columns to round floats to 2 decimals
 TILES_SCORE_FLOAT_COLUMNS = [
-    "Score D (percentile)",
-    "Score D (top 25th percentile)",
-    "Score E (percentile)",
-    "Score E (top 25th percentile)",
-    "Definition L (percentile)",
-    "Poverty (Less than 200% of federal poverty line)",
-    "Percent individuals age 25 or over with less than high school degree",
-    "Linguistic isolation (percent)",
-    "Unemployed civilians (percent)",
-    "Housing burden (percent)",
-    "Poverty (Less than 200% of federal poverty line) (percentile)",
-    "Percent individuals age 25 or over with less than high school degree (percentile)",
-    "Linguistic isolation (percent) (percentile)",
-    "Unemployed civilians (percent) (percentile)",
-    "Housing burden (percent) (percentile)",
-    "Diagnosed diabetes among adults aged >=18 years (percentile)",
-    "Current asthma among adults aged >=18 years (percentile)",
-    "Coronary heart disease among adults aged >=18 years (percentile)",
-    "Life expectancy (years) (percentile)",
-    "Traffic proximity and volume (percentile)",
-    "FEMA Risk Index Expected Annual Loss Score (percentile)",
-    "Energy burden (percentile)",
-    "Wastewater discharge (percentile)",
-    "Percent pre-1960s housing (lead paint indicator) (percentile)",
-    "Diesel particulate matter (percentile)",
-    "Particulate matter (PM2.5) (percentile)",
-    "Median household income (% of AMI) (percentile)",
-    "Percent of individuals < 200% Federal Poverty Line (percentile)",
+    field_names.SCORE_D + field_names.PERCENTILE_FIELD_SUFFIX,
+    field_names.SCORE_D + field_names.TOP_25_PERCENTILE_SUFFIX,
+    field_names.SCORE_E + field_names.PERCENTILE_FIELD_SUFFIX,
+    field_names.SCORE_E + field_names.TOP_25_PERCENTILE_SUFFIX,
+    field_names.SCORE_L + field_names.PERCENTILE_FIELD_SUFFIX,
+    field_names.POVERTY_FIELD,
+    field_names.HIGH_SCHOOL_ED_FIELD,
+    field_names.LINGUISTIC_ISO_FIELD,
+    field_names.UNEMPLOYMENT_FIELD,
+    field_names.HOUSING_BURDEN_FIELD,
+    field_names.POVERTY_FIELD + field_names.PERCENTILE_FIELD_SUFFIX,
+    field_names.HIGH_SCHOOL_ED_FIELD + field_names.PERCENTILE_FIELD_SUFFIX,
+    field_names.LINGUISTIC_ISO_FIELD + field_names.PERCENTILE_FIELD_SUFFIX,
+    field_names.UNEMPLOYMENT_FIELD + field_names.PERCENTILE_FIELD_SUFFIX,
+    field_names.HOUSING_BURDEN_FIELD + field_names.PERCENTILE_FIELD_SUFFIX,
+    field_names.DIABETES_FIELD + field_names.PERCENTILE_FIELD_SUFFIX,
+    field_names.ASTHMA_FIELD + field_names.PERCENTILE_FIELD_SUFFIX,
+    field_names.HEART_DISEASE_FIELD + field_names.PERCENTILE_FIELD_SUFFIX,
+    field_names.LIFE_EXPECTANCY_FIELD + field_names.PERCENTILE_FIELD_SUFFIX,
+    field_names.TRAFFIC_FIELD + field_names.PERCENTILE_FIELD_SUFFIX,
+    field_names.FEMA_RISK_FIELD + field_names.PERCENTILE_FIELD_SUFFIX,
+    field_names.ENERGY_BURDEN_FIELD + field_names.PERCENTILE_FIELD_SUFFIX,
+    field_names.WASTEWATER_FIELD + field_names.PERCENTILE_FIELD_SUFFIX,
+    field_names.LEAD_PAINT_FIELD + field_names.PERCENTILE_FIELD_SUFFIX,
+    field_names.DIESEL_FIELD + field_names.PERCENTILE_FIELD_SUFFIX,
+    field_names.PM25_FIELD + field_names.PERCENTILE_FIELD_SUFFIX,
+    field_names.MEDIAN_INCOME_AS_PERCENT_OF_AMI_FIELD
+    + field_names.PERCENTILE_FIELD_SUFFIX,
+    field_names.POVERTY_LESS_THAN_200_FPL_FIELD
+    + field_names.PERCENTILE_FIELD_SUFFIX,
 ]
 TILES_ROUND_NUM_DECIMALS = 2
 
 DOWNLOADABLE_SCORE_INDICATOR_COLUMNS_BASIC = [
-    "Area Median Income (State or metropolitan)",
-    "Percent of individuals < 100% Federal Poverty Line",
-    "Percent individuals age 25 or over with less than high school degree",
-    "Diagnosed diabetes among adults aged >=18 years",
-    "Current asthma among adults aged >=18 years",
-    "Coronary heart disease among adults aged >=18 years",
-    "Life expectancy (years)",
-    "Traffic proximity and volume",
-    "FEMA Risk Index Expected Annual Loss Score",
-    "Energy burden",
-    "Housing burden (percent)",
-    "Wastewater discharge",
-    "Percent pre-1960s housing (lead paint indicator)",
-    "Diesel particulate matter",
-    "Particulate matter (PM2.5)",
-    "Total population",
+    field_names.AMI_FIELD,
+    field_names.POVERTY_LESS_THAN_100_FPL_FIELD,
+    field_names.HIGH_SCHOOL_ED_FIELD,
+    field_names.DIABETES_FIELD,
+    field_names.ASTHMA_FIELD,
+    field_names.HEART_DISEASE_FIELD,
+    field_names.LIFE_EXPECTANCY_FIELD,
+    field_names.TRAFFIC_FIELD,
+    field_names.FEMA_RISK_FIELD,
+    field_names.ENERGY_BURDEN_FIELD,
+    field_names.HOUSING_BURDEN_FIELD,
+    field_names.WASTEWATER_FIELD,
+    field_names.LEAD_PAINT_FIELD,
+    field_names.DIESEL_FIELD,
+    field_names.PM25_FIELD,
+    field_names.TOTAL_POP_FIELD,
 ]
 
 # For every indicator above, we want to include percentile and min-max normalized variants also
@@ -155,11 +161,12 @@ DOWNLOADABLE_SCORE_INDICATOR_COLUMNS_FULL = list(
 
 # Finally we augment with the GEOID10, county, and state
 DOWNLOADABLE_SCORE_COLUMNS = [
-    "GEOID10_TRACT",
-    "County Name",
-    "State Name",
-    "Score G (communities)",
-    "Median household income (% of AMI)",
-    "Median household income (% of state median household income) (percentile)",
+    field_names.GEOID_TRACT_FIELD,
+    field_names.COUNTY_FIELD,
+    field_names.STATE_FIELD,
+    field_names.SCORE_G_COMMUNITIES,
+    field_names.MEDIAN_INCOME_AS_PERCENT_OF_AMI_FIELD,
+    field_names.MEDIAN_INCOME_AS_PERCENT_OF_STATE_FIELD
+    + field_names.PERCENTILE_FIELD_SUFFIX,
     *DOWNLOADABLE_SCORE_INDICATOR_COLUMNS_FULL,
 ]
diff --git a/data/data-pipeline/data_pipeline/etl/score/etl_score_post.py b/data/data-pipeline/data_pipeline/etl/score/etl_score_post.py
index 585595cf..4723296c 100644
--- a/data/data-pipeline/data_pipeline/etl/score/etl_score_post.py
+++ b/data/data-pipeline/data_pipeline/etl/score/etl_score_post.py
@@ -276,12 +276,15 @@ class PostScoreETL(ExtractTransformLoad):
             inplace=False,
         )
 
-        logger.info("Writing downloadable csv")
-        downloadable_df_copy.to_csv(csv_path, index=False)
-
         logger.info("Writing downloadable excel")
         downloadable_df_copy.to_excel(excel_path, index=False)
 
+        logger.info("Writing downloadable csv")
+        downloadable_df_copy[self.GEOID_TRACT_FIELD_NAME] = (
+            '"' + downloadable_df_copy[self.GEOID_TRACT_FIELD_NAME] + '"'
+        )
+        downloadable_df_copy.to_csv(csv_path, index=False)
+
         logger.info("Compressing files")
         files_to_compress = [csv_path, excel_path, pdf_path]
         zip_files(zip_path, files_to_compress)
diff --git a/data/data-pipeline/data_pipeline/score/field_names.py b/data/data-pipeline/data_pipeline/score/field_names.py
index 39b6b7f9..1bbcb37b 100644
--- a/data/data-pipeline/data_pipeline/score/field_names.py
+++ b/data/data-pipeline/data_pipeline/score/field_names.py
@@ -1,6 +1,12 @@
 # Suffixes
 PERCENTILE_FIELD_SUFFIX = " (percentile)"
 MIN_MAX_FIELD_SUFFIX = " (min-max normalized)"
+TOP_25_PERCENTILE_SUFFIX = " (top 25th percentile)"
+
+# Geographic field names
+GEOID_TRACT_FIELD = "GEOID10_TRACT"
+STATE_FIELD = "State Name"
+COUNTY_FIELD = "County Name"
 
 # Score file field names
 SCORE_A = "Score A"
@@ -21,6 +27,7 @@ SCORE_I = "Score I"
 SCORE_I_COMMUNITIES = "Score I (communities)"
 SCORE_K = "NMTC (communities)"
 SCORE_K_COMMUNITIES = "Score K (communities)"
+SCORE_L = "Definition L"
 SCORE_L_COMMUNITIES = "Definition L (communities)"
 L_CLIMATE = "Climate Factor (Definition L)"
 L_ENERGY = "Energy Factor (Definition L)"
@@ -45,7 +52,6 @@ POVERTY_LESS_THAN_150_FPL_FIELD = (
 POVERTY_LESS_THAN_100_FPL_FIELD = (
     "Percent of individuals < 100% Federal Poverty Line"
 )
-MEDIAN_INCOME_PERCENT_AMI_FIELD = "Median household income (% of AMI)"
 STATE_MEDIAN_INCOME_FIELD = (
     "Median household income (State; 2019 inflation-adjusted dollars)"
 )
diff --git a/data/data-pipeline/data_pipeline/score/score_l.py b/data/data-pipeline/data_pipeline/score/score_l.py
index d745f5b9..35c56a65 100644
--- a/data/data-pipeline/data_pipeline/score/score_l.py
+++ b/data/data-pipeline/data_pipeline/score/score_l.py
@@ -528,7 +528,7 @@ class ScoreL(Score):
 
         median_income_threshold = (
             self.df[
-                field_names.MEDIAN_INCOME_PERCENT_AMI_FIELD
+                field_names.MEDIAN_INCOME_AS_PERCENT_OF_AMI_FIELD
                 + field_names.PERCENTILE_FIELD_SUFFIX
             ]
             # Note: a high median income as a % of AMI is good, so take 1 minus the threshold to invert it.

From df564658a5aa9d475b4197694f924fd9e01388d8 Mon Sep 17 00:00:00 2001
From: Vim <86254807+vim-usds@users.noreply.github.com>
Date: Mon, 6 Dec 2021 22:58:04 -0500
Subject: [PATCH 2/5] Add 4 additional territory buttons (#956)

* Add 4 additional territory buttons

* Fix bug where territories fires multiple times

- move territory handler from J40Map to component

* Update SVGs for all territory buttons
---
 client/src/components/J40Map.tsx              | 27 +------
 .../src/components/territoryFocusControl.tsx  | 72 ++++++++++++++++---
 client/src/data/constants.tsx                 |  5 ++
 client/src/data/copy/explore.tsx              | 56 ++++++++++++---
 client/src/images/mapbtn-48.svg               | 22 +++++-
 client/src/images/mapbtn-AK.svg               | 15 +++-
 client/src/images/mapbtn-AS.svg               | 19 +++++
 client/src/images/mapbtn-GU.svg               | 18 +++++
 client/src/images/mapbtn-HI.svg               | 14 +++-
 client/src/images/mapbtn-MP.svg               | 17 +++++
 client/src/images/mapbtn-PR.svg               | 18 ++++-
 client/src/images/mapbtn-VI.svg               | 14 ++++
 client/src/styles/global.scss                 | 24 +++++++
 13 files changed, 274 insertions(+), 47 deletions(-)
 create mode 100644 client/src/images/mapbtn-AS.svg
 create mode 100644 client/src/images/mapbtn-GU.svg
 create mode 100644 client/src/images/mapbtn-MP.svg
 create mode 100644 client/src/images/mapbtn-VI.svg

diff --git a/client/src/components/J40Map.tsx b/client/src/components/J40Map.tsx
index ef0cb021..1d63ee39 100644
--- a/client/src/components/J40Map.tsx
+++ b/client/src/components/J40Map.tsx
@@ -1,6 +1,6 @@
 /* eslint-disable no-unused-vars */
 // External Libs:
-import React, {MouseEvent, useRef, useState, useMemo} from 'react';
+import React, {useRef, useState, useMemo} from 'react';
 import {Map, MapboxGeoJSONFeature, LngLatBoundsLike} from 'maplibre-gl';
 import ReactMapGL, {
   MapEvent,
@@ -136,29 +136,6 @@ const J40Map = ({location}: IJ40Interface) => {
     });
   };
 
-  const onClickTerritoryFocusButton = (event: MouseEvent<HTMLButtonElement>) => {
-    event.stopPropagation();
-    const buttonID = event.target && (event.target as HTMLElement).id;
-
-    switch (buttonID) {
-      case '48':
-        goToPlace(constants.LOWER_48_BOUNDS);
-        break;
-      case 'AK':
-        goToPlace(constants.ALASKA_BOUNDS);
-        break;
-      case 'HI':
-        goToPlace(constants.HAWAII_BOUNDS);
-        break;
-      case 'PR':
-        goToPlace(constants.PUERTO_RICO_BOUNDS);
-        break;
-
-      default:
-        break;
-    }
-  };
-
   const onTransitionStart = () => {
     setTransitionInProgress(true);
   };
@@ -273,7 +250,7 @@ const J40Map = ({location}: IJ40Interface) => {
             onClick={onClickGeolocate}
           /> : ''}
           {geolocationInProgress ? <div>Geolocation in progress...</div> : ''}
-          <TerritoryFocusControl onClickTerritoryFocusButton={onClickTerritoryFocusButton}/>
+          <TerritoryFocusControl goToPlace={goToPlace}/>
           {'fs' in flags ? <FullscreenControl className={styles.fullscreenControl}/> :'' }
 
         </ReactMapGL>
diff --git a/client/src/components/territoryFocusControl.tsx b/client/src/components/territoryFocusControl.tsx
index 393462a3..0ec073b0 100644
--- a/client/src/components/territoryFocusControl.tsx
+++ b/client/src/components/territoryFocusControl.tsx
@@ -1,21 +1,53 @@
 import {useIntl} from 'gatsby-plugin-intl';
-import React, {MouseEventHandler} from 'react';
-import {_useMapControl as useMapControl} from 'react-map-gl';
+import React from 'react';
+import {LngLatBoundsLike} from 'mapbox-gl';
 
 import * as styles from './territoryFocusControl.module.scss';
 import * as EXPLORE_COPY from '../data/copy/explore';
+import * as constants from '../data/constants';
 
 interface ITerritoryFocusControl {
-  onClickTerritoryFocusButton: MouseEventHandler<HTMLButtonElement>;
+  goToPlace(bounds: LngLatBoundsLike): void;
 }
 
-const TerritoryFocusControl = ({onClickTerritoryFocusButton}: ITerritoryFocusControl) => {
+
+const TerritoryFocusControl = ({goToPlace}: ITerritoryFocusControl) => {
   const intl = useIntl();
 
-  const {containerRef} = useMapControl({
-    // @ts-ignore // Types have not caught up yet, see https://github.com/visgl/react-map-gl/issues/1492
-    onClick: onClickTerritoryFocusButton,
-  });
+  const onClickTerritoryFocusButton = (event: React.MouseEvent<HTMLButtonElement>) => {
+    event.stopPropagation();
+    const buttonID = event.target && (event.target as HTMLElement).id;
+
+    switch (buttonID) {
+      case '48':
+        goToPlace(constants.LOWER_48_BOUNDS);
+        break;
+      case 'AK':
+        goToPlace(constants.ALASKA_BOUNDS);
+        break;
+      case 'HI':
+        goToPlace(constants.HAWAII_BOUNDS);
+        break;
+      case 'PR':
+        goToPlace(constants.PUERTO_RICO_BOUNDS);
+        break;
+      case 'GU':
+        goToPlace(constants.GUAM_BOUNDS);
+        break;
+      case 'AS':
+        goToPlace(constants.AMERICAN_SAMOA_BOUNDS);
+        break;
+      case 'MP':
+        goToPlace(constants.MARIANA_ISLAND_BOUNDS);
+        break;
+      case 'VI':
+        goToPlace(constants.US_VIRGIN_ISLANDS_BOUNDS);
+        break;
+
+      default:
+        break;
+    }
+  };
 
   const territories = [
     {
@@ -34,6 +66,22 @@ const TerritoryFocusControl = ({onClickTerritoryFocusButton}: ITerritoryFocusCon
       short: intl.formatMessage(EXPLORE_COPY.MAP.PR_SHORT),
       long: intl.formatMessage(EXPLORE_COPY.MAP.PR_LONG),
     },
+    {
+      short: intl.formatMessage(EXPLORE_COPY.MAP.GU_SHORT),
+      long: intl.formatMessage(EXPLORE_COPY.MAP.GU_LONG),
+    },
+    {
+      short: intl.formatMessage(EXPLORE_COPY.MAP.AS_SHORT),
+      long: intl.formatMessage(EXPLORE_COPY.MAP.AS_LONG),
+    },
+    {
+      short: intl.formatMessage(EXPLORE_COPY.MAP.MP_SHORT),
+      long: intl.formatMessage(EXPLORE_COPY.MAP.MP_LONG),
+    },
+    {
+      short: intl.formatMessage(EXPLORE_COPY.MAP.VI_SHORT),
+      long: intl.formatMessage(EXPLORE_COPY.MAP.VI_LONG),
+    },
   ];
   // the offset for this array should map the territories variable
   const territoriesIconClassName = [
@@ -41,16 +89,20 @@ const TerritoryFocusControl = ({onClickTerritoryFocusButton}: ITerritoryFocusCon
     'mapboxgl-ctrl-zoom-to-ak',
     'mapboxgl-ctrl-zoom-to-hi',
     'mapboxgl-ctrl-zoom-to-pr',
+    'mapboxgl-ctrl-zoom-to-gu',
+    'mapboxgl-ctrl-zoom-to-as',
+    'mapboxgl-ctrl-zoom-to-mp',
+    'mapboxgl-ctrl-zoom-to-vi',
   ];
 
   return (
-    <div ref={containerRef} className={styles.territoryFocusContainer}>
+    <div className={styles.territoryFocusContainer}>
       <div className={'mapboxgl-ctrl mapboxgl-ctrl-group'}>
         {territories.map((territory, index) =>
           <button
             id={territory.short}
             key={territory.short}
-            onClick={onClickTerritoryFocusButton}
+            onClick={(e) => onClickTerritoryFocusButton(e)}
             className={'mapboxgl-ctrl-icon ' + territoriesIconClassName[index]}
             aria-label={intl.formatMessage(
                 {
diff --git a/client/src/data/constants.tsx b/client/src/data/constants.tsx
index fe205d0f..a2691a78 100644
--- a/client/src/data/constants.tsx
+++ b/client/src/data/constants.tsx
@@ -121,6 +121,11 @@ export const AMERICAN_SAMOA_BOUNDS: LngLatBoundsLike = [
   [-168.1433, -11.046934],
 ];
 
+export const US_VIRGIN_ISLANDS_BOUNDS: LngLatBoundsLike = [
+  [-65.5782239, 17.6739145],
+  [-64.2704123, 18.7495796],
+];
+
 export const DEFAULT_CENTER = [32.4687126, -86.502136];
 
 // Opacity
diff --git a/client/src/data/copy/explore.tsx b/client/src/data/copy/explore.tsx
index 0e7bd75c..10b19144 100644
--- a/client/src/data/copy/explore.tsx
+++ b/client/src/data/copy/explore.tsx
@@ -57,6 +57,16 @@ export const MAP = defineMessages({
     defaultMessage: 'Zoom in to the state or regional level to see prioritized communities on the map.',
     description: 'zoom warning on map',
   },
+  SEARCH_PLACEHOLDER: {
+    id: 'map.search.placeholder.text',
+    defaultMessage: 'Enter a city, state or ZIP',
+    description: 'placeholder text for search',
+  },
+  SEARCH_RESULTS_EMPTY_MESSAGE: {
+    id: 'map.search.results.empty.text',
+    defaultMessage: 'No location found. Please try another location.',
+    description: 'text displaying message for no search results found',
+  },
   LOWER48_SHORT: {
     id: 'map.territoryFocus.lower48.short',
     defaultMessage: '48',
@@ -97,15 +107,45 @@ export const MAP = defineMessages({
     defaultMessage: 'Puerto Rico',
     description: 'The full name indicating the bounds of Puerto Rico',
   },
-  SEARCH_PLACEHOLDER: {
-    id: 'map.search.placeholder.text',
-    defaultMessage: 'Enter a city, state or ZIP',
-    description: 'placeholder text for search',
+  GU_SHORT: {
+    id: 'map.territoryFocus.guam.short',
+    defaultMessage: 'GU',
+    description: 'The abbreviated name indicating the bounds of Guam',
   },
-  SEARCH_RESULTS_EMPTY_MESSAGE: {
-    id: 'map.search.results.empty.text',
-    defaultMessage: 'No location found. Please try another location.',
-    description: 'text displaying message for no search results found',
+  GU_LONG: {
+    id: 'map.territoryFocus.guam.long',
+    defaultMessage: 'Guam',
+    description: 'The full name indicating the bounds of Guam',
+  },
+  AS_SHORT: {
+    id: 'map.territoryFocus.american.samoa.short',
+    defaultMessage: 'AS',
+    description: 'The abbreviated name indicating the bounds of American Somoa',
+  },
+  AS_LONG: {
+    id: 'map.territoryFocus.american.samoa.long',
+    defaultMessage: 'American Somoa',
+    description: 'The full name indicating the bounds of American Somoa',
+  },
+  MP_SHORT: {
+    id: 'map.territoryFocus.commonwealth.nmp.short',
+    defaultMessage: 'MP',
+    description: 'The abbreviated name indicating the bounds of Commonwealth of Northern Mariana Islands',
+  },
+  MP_LONG: {
+    id: 'map.territoryFocus.commonwealth.nmp.long',
+    defaultMessage: 'Commonwealth of Northern Mariana Islands',
+    description: 'The full name indicating the bounds of Commonwealth of Northern Mariana Islands',
+  },
+  VI_SHORT: {
+    id: 'map.territoryFocus.us.virgin.islands.short',
+    defaultMessage: 'VI',
+    description: 'The abbreviated name indicating the bounds of US Virgin Islands',
+  },
+  VI_LONG: {
+    id: 'map.territoryFocus.us.virgin.islands.long',
+    defaultMessage: 'US Virgin Islands',
+    description: 'The full name indicating the bounds of US Virgin Islands',
   },
 });
 
diff --git a/client/src/images/mapbtn-48.svg b/client/src/images/mapbtn-48.svg
index 8bf32889..7026acf2 100644
--- a/client/src/images/mapbtn-48.svg
+++ b/client/src/images/mapbtn-48.svg
@@ -1 +1,21 @@
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\ No newline at end of file
+<?xml version="1.0" encoding="utf-8"?>
+<!-- Generator: Adobe Illustrator 26.0.1, SVG Export Plug-In . SVG Version: 6.00 Build 0)  -->
+<svg version="1.1" id="Layer_1" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" x="0px" y="0px"
+	 viewBox="0 0 24 24" style="enable-background:new 0 0 24 24;" xml:space="preserve">
+<style type="text/css">
+	.st0{fill:none;}
+</style>
+<path class="st0" d="M0,0h24v24H0L0,0z"/>
+<g>
+	<path d="M8.9,15.6v-2.3H5v-1.1l3.5-5.5h1.9V12h1.1v1.2h-1.1v2.3H8.9z M6.5,12h2.3v-2c0-0.3,0-0.6,0-0.9c0-0.4,0-0.7,0-0.9H8.9
+		C8.8,8.4,8.7,8.6,8.5,8.9C8.4,9.1,8.3,9.3,8.2,9.6L6.5,12z"/>
+	<path d="M15.5,15.8c-0.6,0-1.1-0.1-1.6-0.3c-0.5-0.2-0.8-0.5-1.1-0.9s-0.4-0.8-0.4-1.3c0-0.6,0.2-1,0.5-1.4
+		c0.3-0.4,0.7-0.7,1.1-0.9V11c-0.3-0.2-0.6-0.5-0.9-0.9c-0.2-0.3-0.4-0.7-0.4-1.2c0-0.5,0.1-0.9,0.3-1.3s0.6-0.6,1-0.8
+		c0.4-0.2,0.9-0.3,1.4-0.3c0.8,0,1.4,0.2,1.9,0.7c0.5,0.4,0.7,1,0.7,1.7c0,0.4-0.1,0.8-0.4,1.2c-0.3,0.4-0.5,0.6-0.8,0.9V11
+		c0.4,0.2,0.8,0.5,1.1,0.9c0.3,0.4,0.5,0.8,0.5,1.4c0,0.5-0.1,0.9-0.4,1.2c-0.3,0.4-0.6,0.7-1.1,0.9C16.6,15.6,16.1,15.8,15.5,15.8z
+		 M15.5,14.6c0.4,0,0.8-0.1,1.1-0.4s0.4-0.6,0.4-1c0-0.3-0.1-0.6-0.3-0.8c-0.2-0.2-0.4-0.4-0.8-0.5s-0.7-0.3-1.1-0.5
+		c-0.3,0.2-0.5,0.4-0.7,0.7c-0.2,0.3-0.3,0.6-0.3,0.9c0,0.4,0.2,0.8,0.5,1.1S15,14.6,15.5,14.6z M16.1,10.6c0.2-0.2,0.4-0.5,0.6-0.7
+		s0.2-0.5,0.2-0.8c0-0.4-0.1-0.7-0.3-1c-0.2-0.3-0.6-0.4-1-0.4c-0.3,0-0.6,0.1-0.9,0.3c-0.2,0.2-0.4,0.5-0.4,0.9
+		c0,0.3,0.1,0.5,0.2,0.7c0.2,0.2,0.4,0.4,0.7,0.5C15.4,10.3,15.7,10.4,16.1,10.6z"/>
+</g>
+</svg>
diff --git a/client/src/images/mapbtn-AK.svg b/client/src/images/mapbtn-AK.svg
index 6f738bff..af8a7c67 100644
--- a/client/src/images/mapbtn-AK.svg
+++ b/client/src/images/mapbtn-AK.svg
@@ -1 +1,14 @@
-<svg xmlns="http://www.w3.org/2000/svg" width="24" height="24" viewBox="0 0 24 24"><path d="M-.54.11h24v24h-24Z" transform="translate(0.54 -0.11)" style="fill:none"/><path d="M9.34,14H6.62L6,16H4.22L7.16,6.9H8.94L11.86,16H10ZM7,12.55H9l-.92-3H8Z" transform="translate(0.54 -0.11)"/><path d="M15.39,12.2h-.93V16H12.68V6.9h1.78v3.72h.93L17.47,6.9h2l-2.57,4.39L19.82,16h-2.2Z" transform="translate(0.54 -0.11)"/></svg>
\ No newline at end of file
+<?xml version="1.0" encoding="utf-8"?>
+<!-- Generator: Adobe Illustrator 26.0.1, SVG Export Plug-In . SVG Version: 6.00 Build 0)  -->
+<svg version="1.1" id="Layer_1" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" x="0px" y="0px"
+	 viewBox="0 0 24 24" style="enable-background:new 0 0 24 24;" xml:space="preserve">
+<style type="text/css">
+	.st0{fill:none;}
+</style>
+<path class="st0" d="M0,0h24v24H0L0,0z"/>
+<g>
+	<path d="M3.8,15.6l3-9.2h1.9l3,9.2H9.9l-0.7-2.5H6.1l-0.7,2.5H3.8z M6.8,10.7l-0.3,1.1h2.3l-0.3-1.1c-0.1-0.5-0.3-1-0.4-1.5
+		C8,8.7,7.8,8.2,7.7,7.7H7.6c-0.1,0.5-0.2,1-0.4,1.5S7,10.2,6.8,10.7z"/>
+	<path d="M12.8,15.6V6.4h1.6v4.2h0l3.3-4.2h1.8L16.7,10l3.3,5.6h-1.8l-2.5-4.3l-1.3,1.6v2.7H12.8z"/>
+</g>
+</svg>
diff --git a/client/src/images/mapbtn-AS.svg b/client/src/images/mapbtn-AS.svg
new file mode 100644
index 00000000..a2bc37bc
--- /dev/null
+++ b/client/src/images/mapbtn-AS.svg
@@ -0,0 +1,19 @@
+<?xml version="1.0" encoding="utf-8"?>
+<!-- Generator: Adobe Illustrator 26.0.1, SVG Export Plug-In . SVG Version: 6.00 Build 0)  -->
+<svg version="1.1" id="Layer_1" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" x="0px" y="0px"
+	 viewBox="0 0 24 24" style="enable-background:new 0 0 24 24;" xml:space="preserve">
+<style type="text/css">
+	.st0{fill:none;}
+</style>
+<path class="st0" d="M0,0h24v24H0L0,0z"/>
+<g>
+	<path d="M4.2,15.6l3-9.2h1.9l3,9.2h-1.7l-0.7-2.5H6.6l-0.7,2.5H4.2z M7.3,10.7L7,11.8h2.3L9,10.7c-0.1-0.5-0.3-1-0.4-1.5
+		c-0.1-0.5-0.3-1-0.4-1.5H8.1C8,8.2,7.8,8.7,7.7,9.2S7.4,10.2,7.3,10.7z"/>
+	<path d="M15.9,15.8c-0.6,0-1.2-0.1-1.8-0.3c-0.6-0.2-1.1-0.6-1.5-1l1-1.1c0.3,0.3,0.7,0.6,1.1,0.7c0.4,0.2,0.8,0.3,1.3,0.3
+		c0.5,0,0.9-0.1,1.2-0.3c0.3-0.2,0.4-0.5,0.4-0.9c0-0.4-0.1-0.7-0.4-0.8c-0.3-0.2-0.6-0.3-1-0.5l-1.3-0.5c-0.3-0.1-0.6-0.3-0.9-0.5
+		c-0.3-0.2-0.5-0.5-0.7-0.8C13.1,9.7,13,9.3,13,8.8c0-0.5,0.1-0.9,0.4-1.3c0.3-0.4,0.6-0.7,1.1-0.9c0.5-0.2,1-0.3,1.6-0.3
+		c0.5,0,1,0.1,1.5,0.3c0.5,0.2,0.9,0.5,1.3,0.8l-0.8,1c-0.3-0.2-0.6-0.4-0.9-0.6c-0.3-0.1-0.7-0.2-1.1-0.2c-0.4,0-0.8,0.1-1,0.3
+		c-0.3,0.2-0.4,0.5-0.4,0.8c0,0.2,0.1,0.4,0.2,0.6c0.1,0.2,0.3,0.3,0.5,0.4c0.2,0.1,0.5,0.2,0.7,0.3l1.2,0.5c0.5,0.2,1,0.5,1.3,0.9
+		c0.3,0.4,0.5,0.9,0.5,1.6c0,0.5-0.1,0.9-0.4,1.4c-0.3,0.4-0.6,0.7-1.1,1C17.2,15.6,16.6,15.8,15.9,15.8z"/>
+</g>
+</svg>
diff --git a/client/src/images/mapbtn-GU.svg b/client/src/images/mapbtn-GU.svg
new file mode 100644
index 00000000..1566416c
--- /dev/null
+++ b/client/src/images/mapbtn-GU.svg
@@ -0,0 +1,18 @@
+<?xml version="1.0" encoding="utf-8"?>
+<!-- Generator: Adobe Illustrator 26.0.1, SVG Export Plug-In . SVG Version: 6.00 Build 0)  -->
+<svg version="1.1" id="Layer_1" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" x="0px" y="0px"
+	 viewBox="0 0 24 24" style="enable-background:new 0 0 24 24;" xml:space="preserve">
+<style type="text/css">
+	.st0{fill:none;}
+</style>
+<path class="st0" d="M0,0h24v24H0L0,0z"/>
+<g>
+	<path d="M7.9,15.8c-0.8,0-1.6-0.2-2.2-0.5c-0.7-0.4-1.2-0.9-1.5-1.6C3.8,12.9,3.6,12,3.6,11c0-1,0.2-1.9,0.6-2.6
+		c0.4-0.7,0.9-1.3,1.6-1.6s1.4-0.6,2.2-0.6c0.7,0,1.2,0.1,1.7,0.4c0.5,0.2,0.8,0.5,1.1,0.8L9.8,8.5C9.6,8.3,9.3,8.1,9,7.9
+		C8.8,7.8,8.4,7.7,8,7.7C7.2,7.7,6.5,8,6,8.6C5.5,9.2,5.2,10,5.2,11c0,1,0.2,1.9,0.7,2.5s1.2,0.9,2.1,0.9c0.3,0,0.5,0,0.7-0.1
+		c0.2-0.1,0.4-0.2,0.6-0.3v-2H7.6v-1.3h3.2v4c-0.3,0.3-0.7,0.6-1.2,0.8C9.1,15.7,8.5,15.8,7.9,15.8z"/>
+	<path d="M16.3,15.8c-0.7,0-1.3-0.1-1.8-0.4s-0.9-0.7-1.2-1.3c-0.3-0.6-0.4-1.4-0.4-2.4V6.4h1.6v5.3c0,0.7,0.1,1.2,0.2,1.6
+		c0.2,0.4,0.4,0.7,0.7,0.8c0.3,0.2,0.6,0.2,1,0.2c0.4,0,0.7-0.1,1-0.2c0.3-0.2,0.5-0.4,0.7-0.8c0.2-0.4,0.2-0.9,0.2-1.6V6.4h1.6v5.1
+		c0,1-0.1,1.8-0.4,2.4c-0.3,0.6-0.7,1.1-1.2,1.3C17.6,15.6,17,15.8,16.3,15.8z"/>
+</g>
+</svg>
diff --git a/client/src/images/mapbtn-HI.svg b/client/src/images/mapbtn-HI.svg
index a088fde6..1aa55858 100644
--- a/client/src/images/mapbtn-HI.svg
+++ b/client/src/images/mapbtn-HI.svg
@@ -1 +1,13 @@
-<svg xmlns="http://www.w3.org/2000/svg" width="24" height="24" viewBox="0 0 24 24"><path d="M-.54.11h24v24h-24Z" transform="translate(0.54 -0.11)" style="fill:none"/><path d="M9.64,12.19H6.7V16H4.92V6.9H6.7v3.7H9.64V6.9h1.78V16H9.64Z" transform="translate(0.54 -0.11)"/><path d="M12.63,14.41h2.31V8.48H12.63V6.9H19V8.48H16.72v5.93H19V16h-6.4Z" transform="translate(0.54 -0.11)"/></svg>
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+<?xml version="1.0" encoding="utf-8"?>
+<!-- Generator: Adobe Illustrator 26.0.1, SVG Export Plug-In . SVG Version: 6.00 Build 0)  -->
+<svg version="1.1" id="Layer_1" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" x="0px" y="0px"
+	 viewBox="0 0 24 24" style="enable-background:new 0 0 24 24;" xml:space="preserve">
+<style type="text/css">
+	.st0{fill:none;}
+</style>
+<path class="st0" d="M0,0h24v24H0L0,0z"/>
+<g>
+	<path d="M6.4,15.6V6.4H8v3.7h3.7V6.4h1.6v9.2h-1.6v-4.1H8v4.1H6.4z"/>
+	<path d="M15.7,15.6V6.4h1.6v9.2H15.7z"/>
+</g>
+</svg>
diff --git a/client/src/images/mapbtn-MP.svg b/client/src/images/mapbtn-MP.svg
new file mode 100644
index 00000000..d0dbe65f
--- /dev/null
+++ b/client/src/images/mapbtn-MP.svg
@@ -0,0 +1,17 @@
+<?xml version="1.0" encoding="utf-8"?>
+<!-- Generator: Adobe Illustrator 26.0.1, SVG Export Plug-In . SVG Version: 6.00 Build 0)  -->
+<svg version="1.1" id="Layer_1" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" x="0px" y="0px"
+	 viewBox="0 0 24 24" style="enable-background:new 0 0 24 24;" xml:space="preserve">
+<style type="text/css">
+	.st0{fill:none;}
+</style>
+<path class="st0" d="M0,0h24v24H0L0,0z"/>
+<g>
+	<path d="M3.7,15.6V6.4h1.8l1.6,4.5c0.1,0.3,0.2,0.6,0.3,0.9c0.1,0.3,0.2,0.6,0.3,0.9h0.1c0.1-0.3,0.2-0.6,0.3-0.9
+		c0.1-0.3,0.2-0.6,0.3-0.9L10,6.4h1.8v9.2h-1.5v-4.2c0-0.3,0-0.6,0-0.9c0-0.3,0.1-0.7,0.1-1c0-0.3,0.1-0.7,0.1-0.9h-0.1l-0.7,2.1
+		l-1.5,4.1h-1l-1.5-4.1L5,8.5H5C5,8.8,5,9.1,5.1,9.4c0,0.3,0.1,0.7,0.1,1c0,0.3,0,0.7,0,0.9v4.2H3.7z"/>
+	<path d="M14.1,15.6V6.4H17c0.7,0,1.3,0.1,1.8,0.3c0.5,0.2,1,0.5,1.3,0.9s0.5,1,0.5,1.7c0,0.7-0.2,1.2-0.5,1.7
+		c-0.3,0.4-0.7,0.8-1.2,1c-0.5,0.2-1.1,0.3-1.8,0.3h-1.3v3.4H14.1z M15.8,10.9h1.2c1.3,0,2-0.6,2-1.7c0-0.6-0.2-1-0.5-1.2
+		c-0.3-0.2-0.9-0.3-1.5-0.3h-1.1V10.9z"/>
+</g>
+</svg>
diff --git a/client/src/images/mapbtn-PR.svg b/client/src/images/mapbtn-PR.svg
index af7aa9e0..399a1eee 100644
--- a/client/src/images/mapbtn-PR.svg
+++ b/client/src/images/mapbtn-PR.svg
@@ -1 +1,17 @@
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\ No newline at end of file
+<?xml version="1.0" encoding="utf-8"?>
+<!-- Generator: Adobe Illustrator 26.0.1, SVG Export Plug-In . SVG Version: 6.00 Build 0)  -->
+<svg version="1.1" id="Layer_1" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" x="0px" y="0px"
+	 viewBox="0 0 24 24" style="enable-background:new 0 0 24 24;" xml:space="preserve">
+<style type="text/css">
+	.st0{fill:none;}
+</style>
+<path class="st0" d="M0,0h24v24H0L0,0z"/>
+<g>
+	<path d="M4.7,15.6V6.4h2.9c0.7,0,1.3,0.1,1.8,0.3c0.5,0.2,1,0.5,1.3,0.9s0.5,1,0.5,1.7c0,0.7-0.2,1.2-0.5,1.7
+		c-0.3,0.4-0.7,0.8-1.2,1c-0.5,0.2-1.1,0.3-1.8,0.3H6.4v3.4H4.7z M6.4,10.9h1.2c1.3,0,2-0.6,2-1.7c0-0.6-0.2-1-0.5-1.2
+		C8.7,7.8,8.2,7.7,7.5,7.7H6.4V10.9z"/>
+	<path d="M12.9,15.6V6.4H16c0.6,0,1.2,0.1,1.7,0.3s0.9,0.5,1.2,0.8c0.3,0.4,0.4,0.9,0.4,1.6c0,0.7-0.2,1.3-0.5,1.7
+		c-0.3,0.4-0.8,0.7-1.3,0.9l2.2,3.8h-1.8l-2-3.6h-1.4v3.6H12.9z M14.5,10.7h1.3c0.6,0,1.1-0.1,1.4-0.4c0.3-0.3,0.5-0.7,0.5-1.2
+		c0-0.5-0.2-0.9-0.5-1.1c-0.3-0.2-0.8-0.3-1.4-0.3h-1.3V10.7z"/>
+</g>
+</svg>
diff --git a/client/src/images/mapbtn-VI.svg b/client/src/images/mapbtn-VI.svg
new file mode 100644
index 00000000..d9c8c0e7
--- /dev/null
+++ b/client/src/images/mapbtn-VI.svg
@@ -0,0 +1,14 @@
+<?xml version="1.0" encoding="utf-8"?>
+<!-- Generator: Adobe Illustrator 26.0.1, SVG Export Plug-In . SVG Version: 6.00 Build 0)  -->
+<svg version="1.1" id="Layer_1" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" x="0px" y="0px"
+	 viewBox="0 0 24 24" style="enable-background:new 0 0 24 24;" xml:space="preserve">
+<style type="text/css">
+	.st0{fill:none;}
+</style>
+<path class="st0" d="M0,0h24v24H0L0,0z"/>
+<g>
+	<path d="M9,15.6L6.1,6.4h1.7L9.1,11c0.1,0.5,0.3,1,0.4,1.5c0.1,0.5,0.3,1,0.4,1.5H10c0.2-0.5,0.3-1,0.4-1.5c0.1-0.5,0.2-1,0.4-1.5
+		l1.3-4.6h1.7l-2.8,9.2H9z"/>
+	<path d="M14.8,15.6V6.4h1.6v9.2H14.8z"/>
+</g>
+</svg>
diff --git a/client/src/styles/global.scss b/client/src/styles/global.scss
index b5f66a2b..94e69621 100644
--- a/client/src/styles/global.scss
+++ b/client/src/styles/global.scss
@@ -262,6 +262,30 @@ This section will outline styles that are component specific
       background-image: url("../images/mapbtn-PR.svg");
     }
   }
+
+  button.mapboxgl-ctrl-zoom-to-gu {
+    .mapboxgl-ctrl-icon {
+      background-image: url("../images/mapbtn-GU.svg");
+    }
+  }
+
+  button.mapboxgl-ctrl-zoom-to-as {
+    .mapboxgl-ctrl-icon {
+      background-image: url("../images/mapbtn-AS.svg");
+    }
+  }
+
+  button.mapboxgl-ctrl-zoom-to-mp {
+    .mapboxgl-ctrl-icon {
+      background-image: url("../images/mapbtn-MP.svg");
+    }
+  }
+
+  button.mapboxgl-ctrl-zoom-to-vi {
+    .mapboxgl-ctrl-icon {
+      background-image: url("../images/mapbtn-VI.svg");
+    }
+  }
 }
 
 //Area Detail Component

From 5a6d6d8557e91f982a86fcf93b32e51a802b416f Mon Sep 17 00:00:00 2001
From: Lucas Merrill Brown <lucas.m.brown@omb.eop.gov>
Date: Tue, 7 Dec 2021 11:33:49 -0500
Subject: [PATCH 3/5] Issue 954: Add various data sources from Child
 Opportunity Index (#986)

* Adds four fields:
    * Summer days above 90F
    * Percent low access to healthy food
    * Percent impenetrable surface areas
    * Low third grade reading proficiency

* Each of these four gets added into Definition L in various factors.

* Additionally, I add college attendance fields to the ETL for Census ACS.

* This PR also introduces the notion of "reverse percentiles", relevant to ticket #970.
---
 .../data_pipeline/etl/constants.py            |   5 +
 .../data_pipeline/etl/score/etl_score.py      |  61 ++++++++-
 .../etl/sources/census_acs/etl.py             |  67 +++++++---
 .../sources/child_opportunity_index/README.md |   0
 .../child_opportunity_index/__init__.py       |   0
 .../sources/child_opportunity_index/etl.py    | 120 ++++++++++++++++++
 .../data_pipeline/score/field_names.py        |  59 ++++++++-
 .../data_pipeline/score/score_l.py            |  85 +++++++++++--
 8 files changed, 357 insertions(+), 40 deletions(-)
 create mode 100644 data/data-pipeline/data_pipeline/etl/sources/child_opportunity_index/README.md
 create mode 100644 data/data-pipeline/data_pipeline/etl/sources/child_opportunity_index/__init__.py
 create mode 100644 data/data-pipeline/data_pipeline/etl/sources/child_opportunity_index/etl.py

diff --git a/data/data-pipeline/data_pipeline/etl/constants.py b/data/data-pipeline/data_pipeline/etl/constants.py
index 36487964..59dafe2b 100644
--- a/data/data-pipeline/data_pipeline/etl/constants.py
+++ b/data/data-pipeline/data_pipeline/etl/constants.py
@@ -49,6 +49,11 @@ DATASET_LIST = [
         "module_dir": "geocorr",
         "class_name": "GeoCorrETL",
     },
+    {
+        "name": "child_opportunity_index",
+        "module_dir": "child_opportunity_index",
+        "class_name": "ChildOpportunityIndex",
+    },
     {
         "name": "mapping_inequality",
         "module_dir": "mapping_inequality",
diff --git a/data/data-pipeline/data_pipeline/etl/score/etl_score.py b/data/data-pipeline/data_pipeline/etl/score/etl_score.py
index f49681d8..0ce0e052 100644
--- a/data/data-pipeline/data_pipeline/etl/score/etl_score.py
+++ b/data/data-pipeline/data_pipeline/etl/score/etl_score.py
@@ -1,4 +1,6 @@
 import functools
+from collections import namedtuple
+
 import pandas as pd
 
 from data_pipeline.etl.base import ExtractTransformLoad
@@ -29,6 +31,7 @@ class ScoreETL(ExtractTransformLoad):
         self.persistent_poverty_df: pd.DataFrame
         self.census_decennial_df: pd.DataFrame
         self.census_2010_df: pd.DataFrame
+        self.child_opportunity_index_df: pd.DataFrame
 
     def extract(self) -> None:
         logger.info("Loading data sets from disk.")
@@ -162,6 +165,19 @@ class ScoreETL(ExtractTransformLoad):
             low_memory=False,
         )
 
+        # Load COI data
+        child_opportunity_index_csv = (
+            constants.DATA_PATH
+            / "dataset"
+            / "child_opportunity_index"
+            / "usa.csv"
+        )
+        self.child_opportunity_index_df = pd.read_csv(
+            child_opportunity_index_csv,
+            dtype={self.GEOID_TRACT_FIELD_NAME: "string"},
+            low_memory=False,
+        )
+
     def _join_tract_dfs(self, census_tract_dfs: list) -> pd.DataFrame:
         logger.info("Joining Census Tract dataframes")
 
@@ -255,6 +271,7 @@ class ScoreETL(ExtractTransformLoad):
             self.census_acs_median_incomes_df,
             self.census_decennial_df,
             self.census_2010_df,
+            self.child_opportunity_index_df,
         ]
 
         # Sanity check each data frame before merging.
@@ -323,6 +340,7 @@ class ScoreETL(ExtractTransformLoad):
             field_names.HIGH_SCHOOL_ED_FIELD,
             field_names.UNEMPLOYMENT_FIELD,
             field_names.MEDIAN_HOUSE_VALUE_FIELD,
+            field_names.COLLEGE_ATTENDANCE_FIELD,
             field_names.EXPECTED_BUILDING_LOSS_RATE_FIELD,
             field_names.EXPECTED_AGRICULTURE_LOSS_RATE_FIELD,
             field_names.EXPECTED_POPULATION_LOSS_RATE_FIELD,
@@ -333,6 +351,9 @@ class ScoreETL(ExtractTransformLoad):
             field_names.CENSUS_POVERTY_LESS_THAN_100_FPL_FIELD_2010,
             field_names.CENSUS_DECENNIAL_TOTAL_POPULATION_FIELD_2009,
             field_names.CENSUS_DECENNIAL_AREA_MEDIAN_INCOME_PERCENT_FIELD_2009,
+            field_names.EXTREME_HEAT_FIELD,
+            field_names.HEALTHY_FOOD_FIELD,
+            field_names.IMPENETRABLE_SURFACES_FIELD,
         ]
 
         non_numeric_columns = [
@@ -340,7 +361,32 @@ class ScoreETL(ExtractTransformLoad):
             field_names.PERSISTENT_POVERTY_FIELD,
         ]
 
-        columns_to_keep = non_numeric_columns + numeric_columns
+        # For some columns, high values are "good", so we want to reverse the percentile
+        # so that high values are "bad" and any scoring logic can still check if it's
+        # >= some threshold.
+        # TODO: Add more fields here.
+        #  https://github.com/usds/justice40-tool/issues/970
+        ReversePercentile = namedtuple(
+            typename="ReversePercentile",
+            field_names=["field_name", "low_field_name"],
+        )
+        reverse_percentiles = [
+            # This dictionary follows the format:
+            # <field name> : <field name for low values>
+            # for instance, 3rd grade reading level : Low 3rd grade reading level.
+            # This low field will not exist yet, it is only calculated for the
+            # percentile.
+            ReversePercentile(
+                field_name=field_names.READING_FIELD,
+                low_field_name=field_names.LOW_READING_FIELD,
+            )
+        ]
+
+        columns_to_keep = (
+            non_numeric_columns
+            + numeric_columns
+            + [rp.field_name for rp in reverse_percentiles]
+        )
 
         df_copy = df[columns_to_keep].copy()
 
@@ -375,6 +421,19 @@ class ScoreETL(ExtractTransformLoad):
                 df_copy[col] - min_value
             ) / (max_value - min_value)
 
+        # Create reversed percentiles for these fields
+        for reverse_percentile in reverse_percentiles:
+            # Calculate reverse percentiles
+            # For instance, for 3rd grade reading level (score from 0-500),
+            # calculate reversed percentiles and give the result the name
+            # `Low 3rd grade reading level (percentile)`.
+            df_copy[
+                f"{reverse_percentile.low_field_name}"
+                f"{field_names.PERCENTILE_FIELD_SUFFIX}"
+            ] = df_copy[reverse_percentile.field_name].rank(
+                pct=True, ascending=False
+            )
+
         # Special logic: create a combined population field.
         # We sometimes run analytics on "population", and this makes a single field
         # that is either the island area's population in 2009 or the state's
diff --git a/data/data-pipeline/data_pipeline/etl/sources/census_acs/etl.py b/data/data-pipeline/data_pipeline/etl/sources/census_acs/etl.py
index 6a4310a9..51097cbe 100644
--- a/data/data-pipeline/data_pipeline/etl/sources/census_acs/etl.py
+++ b/data/data-pipeline/data_pipeline/etl/sources/census_acs/etl.py
@@ -114,6 +114,27 @@ class CensusACSETL(ExtractTransformLoad):
         )
         self.HIGH_SCHOOL_ED_FIELD = "Percent individuals age 25 or over with less than high school degree"
 
+        # College attendance fields
+        self.COLLEGE_ATTENDANCE_TOTAL_POPULATION_ASKED = (
+            "B14004_001E"  # Estimate!!Total
+        )
+        self.COLLEGE_ATTENDANCE_MALE_ENROLLED_PUBLIC = "B14004_003E"  # Estimate!!Total!!Male!!Enrolled in public college or graduate school
+        self.COLLEGE_ATTENDANCE_MALE_ENROLLED_PRIVATE = "B14004_008E"  # Estimate!!Total!!Male!!Enrolled in private college or graduate school
+        self.COLLEGE_ATTENDANCE_FEMALE_ENROLLED_PUBLIC = "B14004_019E"  # Estimate!!Total!!Female!!Enrolled in public college or graduate school
+        self.COLLEGE_ATTENDANCE_FEMALE_ENROLLED_PRIVATE = "B14004_024E"  # Estimate!!Total!!Female!!Enrolled in private college or graduate school
+
+        self.COLLEGE_ATTENDANCE_FIELDS = [
+            self.COLLEGE_ATTENDANCE_TOTAL_POPULATION_ASKED,
+            self.COLLEGE_ATTENDANCE_MALE_ENROLLED_PUBLIC,
+            self.COLLEGE_ATTENDANCE_MALE_ENROLLED_PRIVATE,
+            self.COLLEGE_ATTENDANCE_FEMALE_ENROLLED_PUBLIC,
+            self.COLLEGE_ATTENDANCE_FEMALE_ENROLLED_PRIVATE,
+        ]
+
+        self.COLLEGE_ATTENDANCE_FIELD = (
+            "Percent enrollment in college or graduate school"
+        )
+
         self.RE_FIELDS = [
             "B02001_001E",
             "B02001_002E",
@@ -156,15 +177,30 @@ class CensusACSETL(ExtractTransformLoad):
 
         self.STATE_GEOID_FIELD_NAME = "GEOID2"
 
+        self.COLUMNS_TO_KEEP = (
+            [
+                self.GEOID_TRACT_FIELD_NAME,
+                self.UNEMPLOYED_FIELD_NAME,
+                self.LINGUISTIC_ISOLATION_FIELD_NAME,
+                self.MEDIAN_INCOME_FIELD_NAME,
+                self.POVERTY_LESS_THAN_100_PERCENT_FPL_FIELD_NAME,
+                self.POVERTY_LESS_THAN_150_PERCENT_FPL_FIELD_NAME,
+                self.POVERTY_LESS_THAN_200_PERCENT_FPL_FIELD_NAME,
+                self.MEDIAN_HOUSE_VALUE_FIELD_NAME,
+                self.HIGH_SCHOOL_ED_FIELD,
+                self.COLLEGE_ATTENDANCE_FIELD,
+            ]
+            + self.RE_OUTPUT_FIELDS
+            + [self.PERCENT_PREFIX + field for field in self.RE_OUTPUT_FIELDS]
+        )
+
         self.df: pd.DataFrame
 
     def extract(self) -> None:
         # Define the variables to retrieve
         variables = (
             [
-                # Income field
                 self.MEDIAN_INCOME_FIELD,
-                # House value
                 self.MEDIAN_HOUSE_VALUE_FIELD,
             ]
             + self.EMPLOYMENT_FIELDS
@@ -172,6 +208,7 @@ class CensusACSETL(ExtractTransformLoad):
             + self.POVERTY_FIELDS
             + self.EDUCATIONAL_FIELDS
             + self.RE_FIELDS
+            + self.COLLEGE_ATTENDANCE_FIELDS
         )
 
         self.df = retrieve_census_acs_data(
@@ -308,6 +345,14 @@ class CensusACSETL(ExtractTransformLoad):
             df["B03003_003E"] / df["B03003_001E"]
         )
 
+        # Calculate college attendance:
+        df[self.COLLEGE_ATTENDANCE_FIELD] = (
+            df[self.COLLEGE_ATTENDANCE_MALE_ENROLLED_PUBLIC]
+            + df[self.COLLEGE_ATTENDANCE_MALE_ENROLLED_PRIVATE]
+            + df[self.COLLEGE_ATTENDANCE_FEMALE_ENROLLED_PUBLIC]
+            + df[self.COLLEGE_ATTENDANCE_FEMALE_ENROLLED_PRIVATE]
+        ) / df[self.COLLEGE_ATTENDANCE_TOTAL_POPULATION_ASKED]
+
         # Save results to self.
         self.df = df
 
@@ -317,23 +362,7 @@ class CensusACSETL(ExtractTransformLoad):
         # mkdir census
         self.OUTPUT_PATH.mkdir(parents=True, exist_ok=True)
 
-        columns_to_include = (
-            [
-                self.GEOID_TRACT_FIELD_NAME,
-                self.UNEMPLOYED_FIELD_NAME,
-                self.LINGUISTIC_ISOLATION_FIELD_NAME,
-                self.MEDIAN_INCOME_FIELD_NAME,
-                self.POVERTY_LESS_THAN_100_PERCENT_FPL_FIELD_NAME,
-                self.POVERTY_LESS_THAN_150_PERCENT_FPL_FIELD_NAME,
-                self.POVERTY_LESS_THAN_200_PERCENT_FPL_FIELD_NAME,
-                self.MEDIAN_HOUSE_VALUE_FIELD_NAME,
-                self.HIGH_SCHOOL_ED_FIELD,
-            ]
-            + self.RE_OUTPUT_FIELDS
-            + [self.PERCENT_PREFIX + field for field in self.RE_OUTPUT_FIELDS]
-        )
-
-        self.df[columns_to_include].to_csv(
+        self.df[self.COLUMNS_TO_KEEP].to_csv(
             path_or_buf=self.OUTPUT_PATH / "usa.csv", index=False
         )
 
diff --git a/data/data-pipeline/data_pipeline/etl/sources/child_opportunity_index/README.md b/data/data-pipeline/data_pipeline/etl/sources/child_opportunity_index/README.md
new file mode 100644
index 00000000..e69de29b
diff --git a/data/data-pipeline/data_pipeline/etl/sources/child_opportunity_index/__init__.py b/data/data-pipeline/data_pipeline/etl/sources/child_opportunity_index/__init__.py
new file mode 100644
index 00000000..e69de29b
diff --git a/data/data-pipeline/data_pipeline/etl/sources/child_opportunity_index/etl.py b/data/data-pipeline/data_pipeline/etl/sources/child_opportunity_index/etl.py
new file mode 100644
index 00000000..ba26b165
--- /dev/null
+++ b/data/data-pipeline/data_pipeline/etl/sources/child_opportunity_index/etl.py
@@ -0,0 +1,120 @@
+from pathlib import Path
+import pandas as pd
+
+from data_pipeline.etl.base import ExtractTransformLoad
+from data_pipeline.score import field_names
+from data_pipeline.utils import get_module_logger, unzip_file_from_url
+
+logger = get_module_logger(__name__)
+
+
+class ChildOpportunityIndex(ExtractTransformLoad):
+    """ETL Child Opportunity Index data.
+
+    COI compiles a number of useful data sets. In the future, we could pull these
+    data sets in directly from their original creators.
+
+    Data dictionary available when you download zip from `self.COI_FILE_URL`.
+
+    Data source overview: https://data.diversitydatakids.org/dataset/coi20-child-opportunity-index-2-0-database.
+
+    Full technical documents: https://www.diversitydatakids.org/sites/default/files/2020-02/ddk_coi2.0_technical_documentation_20200212.pdf.
+
+    Github repo: https://github.com/diversitydatakids/COI/
+
+    """
+
+    def __init__(self):
+        self.COI_FILE_URL = (
+            "https://data.diversitydatakids.org/datastore/zip/f16fff12-b1e5-4f60-85d3-"
+            "3a0ededa30a0?format=csv"
+        )
+
+        self.OUTPUT_PATH: Path = (
+            self.DATA_PATH / "dataset" / "child_opportunity_index"
+        )
+
+        self.TRACT_INPUT_COLUMN_NAME = "geoid"
+        self.EXTREME_HEAT_INPUT_FIELD = "HE_HEAT"
+        self.HEALTHY_FOOD_INPUT_FIELD = "HE_FOOD"
+        self.IMPENETRABLE_SURFACES_INPUT_FIELD = "HE_GREEN"
+        self.READING_INPUT_FIELD = "ED_READING"
+
+        # Constants for output
+        self.COLUMNS_TO_KEEP = [
+            self.GEOID_TRACT_FIELD_NAME,
+            field_names.EXTREME_HEAT_FIELD,
+            field_names.HEALTHY_FOOD_FIELD,
+            field_names.IMPENETRABLE_SURFACES_FIELD,
+            field_names.READING_FIELD,
+        ]
+
+        self.raw_df: pd.DataFrame
+        self.output_df: pd.DataFrame
+
+    def extract(self) -> None:
+        logger.info("Starting 51MB data download.")
+
+        unzip_file_from_url(
+            file_url=self.COI_FILE_URL,
+            download_path=self.TMP_PATH,
+            unzipped_file_path=self.TMP_PATH / "child_opportunity_index",
+        )
+
+        self.raw_df = pd.read_csv(
+            filepath_or_buffer=self.TMP_PATH
+            / "child_opportunity_index"
+            / "raw.csv",
+            # The following need to remain as strings for all of their digits, not get
+            # converted to numbers.
+            dtype={
+                self.TRACT_INPUT_COLUMN_NAME: "string",
+            },
+            low_memory=False,
+        )
+
+    def transform(self) -> None:
+        logger.info("Starting transforms.")
+
+        output_df = self.raw_df.rename(
+            columns={
+                self.TRACT_INPUT_COLUMN_NAME: self.GEOID_TRACT_FIELD_NAME,
+                self.EXTREME_HEAT_INPUT_FIELD: field_names.EXTREME_HEAT_FIELD,
+                self.HEALTHY_FOOD_INPUT_FIELD: field_names.HEALTHY_FOOD_FIELD,
+                self.IMPENETRABLE_SURFACES_INPUT_FIELD: field_names.IMPENETRABLE_SURFACES_FIELD,
+                self.READING_INPUT_FIELD: field_names.READING_FIELD,
+            }
+        )
+
+        # Sanity check the tract field.
+        if len(output_df[self.GEOID_TRACT_FIELD_NAME].str.len().unique()) != 1:
+            raise ValueError("Wrong tract length.")
+
+        # COI has two rows per tract: one for 2010 and one for 2015.
+        output_df = output_df[output_df["year"] == 2015]
+
+        # Convert percents from 0-100 to 0-1 to standardize with our other fields.
+        percent_fields_to_convert = [
+            field_names.HEALTHY_FOOD_FIELD,
+            field_names.IMPENETRABLE_SURFACES_FIELD,
+        ]
+
+        for percent_field_to_convert in percent_fields_to_convert:
+            output_df[percent_field_to_convert] = (
+                output_df[percent_field_to_convert] / 100
+            )
+
+        self.output_df = output_df
+
+    def validate(self) -> None:
+        logger.info("Validating data.")
+
+        pass
+
+    def load(self) -> None:
+        logger.info("Saving CSV")
+
+        self.OUTPUT_PATH.mkdir(parents=True, exist_ok=True)
+        self.output_df[self.COLUMNS_TO_KEEP].to_csv(
+            path_or_buf=self.OUTPUT_PATH / "usa.csv", index=False
+        )
diff --git a/data/data-pipeline/data_pipeline/score/field_names.py b/data/data-pipeline/data_pipeline/score/field_names.py
index 1bbcb37b..4c47a555 100644
--- a/data/data-pipeline/data_pipeline/score/field_names.py
+++ b/data/data-pipeline/data_pipeline/score/field_names.py
@@ -63,6 +63,8 @@ MEDIAN_INCOME_AS_PERCENT_OF_AMI_FIELD = "Median household income (% of AMI)"
 PERSISTENT_POVERTY_FIELD = "Persistent Poverty Census Tract"
 AMI_FIELD = "Area Median Income (State or metropolitan)"
 
+COLLEGE_ATTENDANCE_FIELD = "Percent enrollment in college or graduate school"
+
 # Climate
 FEMA_RISK_FIELD = "FEMA Risk Index Expected Annual Loss Score"
 EXPECTED_BUILDING_LOSS_RATE_FIELD = (
@@ -206,30 +208,63 @@ HOLC_GRADE_D_TRACT_50_PERCENT_FIELD: str = "Tract is >50% HOLC Grade D"
 HOLC_GRADE_D_TRACT_75_PERCENT_FIELD: str = "Tract is >75% HOLC Grade D"
 
 
+# Child Opportunity Index data
+# Summer days with maximum temperature above 90F.
+EXTREME_HEAT_FIELD = "Summer days above 90F"
+
+# Percentage households without a car located further than a half-mile from the
+# nearest supermarket.
+HEALTHY_FOOD_FIELD = "Percent low access to healthy food"
+
+# Percentage impenetrable surface areas such as rooftops, roads or parking lots.
+IMPENETRABLE_SURFACES_FIELD = "Percent impenetrable surface areas"
+
+# Percentage third graders scoring proficient on standardized reading tests,
+# converted to NAEP scale score points.
+READING_FIELD = "Third grade reading proficiency"
+LOW_READING_FIELD = "Low third grade reading proficiency"
+
+# Names for individual factors being exceeded
 # Climate Change
 EXPECTED_POPULATION_LOSS_RATE_LOW_INCOME_FIELD = f"At or above the {PERCENTILE}th percentile for expected population loss rate and is low income"
 EXPECTED_AGRICULTURE_LOSS_RATE_LOW_INCOME_FIELD = f"At or above the {PERCENTILE}th percentile for expected agriculture loss rate and is low income"
 EXPECTED_BUILDING_LOSS_RATE_LOW_INCOME_FIELD = f"At or above the {PERCENTILE}th percentile for expected building loss rate and is low income"
+EXTREME_HEAT_MEDIAN_HOUSE_VALUE_LOW_INCOME_FIELD = (
+    f"At or above the {PERCENTILE}th percentile for summer days above 90F and "
+    f"the median house value is less than {MEDIAN_HOUSE_VALUE_PERCENTILE}th "
+    f"percentile and is low income"
+)
 
 # Clean energy and efficiency
 PM25_EXPOSURE_LOW_INCOME_FIELD = f"At or above the {PERCENTILE}th percentile for PM2.5 exposure and is low income"
 ENERGY_BURDEN_LOW_INCOME_FIELD = f"At or above the {PERCENTILE}th percentile for energy burden and is low income"
+
 # Clean transportation
 DIESEL_PARTICULATE_MATTER_LOW_INCOME_FIELD = f"At or above the {PERCENTILE}th percentile for diesel particulate matter and is low income"
 TRAFFIC_PROXIMITY_LOW_INCOME_FIELD = f"At or above the {PERCENTILE}th percentile for traffic proximity and is low income"
+
 # Affordable and Sustainable Housing
-LEAD_PAINT_MEDIAN_HOME_VALUE_LOW_INCOME_FIELD = (
+LEAD_PAINT_MEDIAN_HOUSE_VALUE_LOW_INCOME_FIELD = (
     f"At or above the {PERCENTILE}th percentile for lead paint and"
-    " the median house value is less than {MEDIAN_HOUSE_VALUE_PERCENTILE}th percentile and is low income"
+    f" the median house value is less than {MEDIAN_HOUSE_VALUE_PERCENTILE}th "
+    f"percentile and is low income"
 )
 HOUSING_BURDEN_LOW_INCOME_FIELD = f"At or above the {PERCENTILE}th percentile for housing burden and is low income"
+
+IMPENETRABLE_SURFACES_LOW_INCOME_FIELD = (
+    f"At or above the {PERCENTILE}th percentile for impenetrable surfaces and is low "
+    f"income"
+)
+
 # Remediation and Reduction of Legacy Pollution
 RMP_LOW_INCOME_FIELD = f"At or above the {PERCENTILE}th percentile for proximity to RMP sites and is low income"
 SUPERFUND_LOW_INCOME_FIELD = f"At or above the {PERCENTILE}th percentile for proximity to superfund sites and is low income"
 HAZARDOUS_WASTE_LOW_INCOME_FIELD = f"At or above the {PERCENTILE}th percentile for proximity to hazardous waste facilities and is low income"
+
 # Critical Clean Water and Waste Infrastructure
 WASTEWATER_DISCHARGE_LOW_INCOME_FIELD = f"At or above the {PERCENTILE}th percentile for wastewater discharge and is low income"
-# Health Burden
+
+# Health Burdens
 DIABETES_LOW_INCOME_FIELD = (
     f"At or above the {PERCENTILE}th percentile for diabetes and is low income"
 )
@@ -240,25 +275,35 @@ HEART_DISEASE_LOW_INCOME_FIELD = f"At or above the {PERCENTILE}th percentile for
 
 LIFE_EXPECTANCY_LOW_INCOME_FIELD = f"At or above the {PERCENTILE}th percentile for life expectancy and is low income"
 
+HEALTHY_FOOD_LOW_INCOME_FIELD = (
+    f"At or above the {PERCENTILE}th percentile for low "
+    f"access to healthy food and is low income"
+)
+
 # Workforce
 UNEMPLOYMENT_LOW_HS_EDUCATION_FIELD = (
     f"At or above the {PERCENTILE}th percentile for unemployment"
-    " and low HS education"
+    " and has low HS education"
 )
 
 LINGUISTIC_ISOLATION_LOW_HS_EDUCATION_FIELD = (
     f"At or above the {PERCENTILE}th percentile for households in linguistic isolation"
-    " and low HS education"
+    " and has low HS education"
 )
 
 POVERTY_LOW_HS_EDUCATION_FIELD = (
     f"At or above the {PERCENTILE}th percentile for households at or below 100% federal poverty level"
-    " and low HS education"
+    " and has low HS education"
+)
+
+LOW_READING_LOW_HS_EDUCATION_FIELD = (
+    f"At or above the {PERCENTILE}th percentile for low 3rd grade reading proficiency"
+    " and has low HS education"
 )
 
 MEDIAN_INCOME_LOW_HS_EDUCATION_FIELD = (
     f"At or below the {PERCENTILE}th percentile for median income"
-    "  and low HS education"
+    "  and has low HS education"
 )
 
 THRESHOLD_COUNT = "Total threshold criteria exceeded"
diff --git a/data/data-pipeline/data_pipeline/score/score_l.py b/data/data-pipeline/data_pipeline/score/score_l.py
index 35c56a65..7653ce46 100644
--- a/data/data-pipeline/data_pipeline/score/score_l.py
+++ b/data/data-pipeline/data_pipeline/score/score_l.py
@@ -177,6 +177,8 @@ class ScoreL(Score):
             field_names.EXPECTED_POPULATION_LOSS_RATE_LOW_INCOME_FIELD,
             field_names.EXPECTED_AGRICULTURE_LOSS_RATE_LOW_INCOME_FIELD,
             field_names.EXPECTED_BUILDING_LOSS_RATE_LOW_INCOME_FIELD,
+            field_names.EXTREME_HEAT_MEDIAN_HOUSE_VALUE_LOW_INCOME_FIELD,
+            field_names.IMPENETRABLE_SURFACES_LOW_INCOME_FIELD,
         ]
 
         expected_population_loss_threshold = (
@@ -203,6 +205,28 @@ class ScoreL(Score):
             >= self.ENVIRONMENTAL_BURDEN_THRESHOLD
         )
 
+        extreme_heat_median_home_value_threshold = (
+            self.df[
+                field_names.EXTREME_HEAT_FIELD
+                + field_names.PERCENTILE_FIELD_SUFFIX
+            ]
+            >= self.ENVIRONMENTAL_BURDEN_THRESHOLD
+        ) & (
+            self.df[
+                field_names.MEDIAN_HOUSE_VALUE_FIELD
+                + field_names.PERCENTILE_FIELD_SUFFIX
+            ]
+            <= self.MEDIAN_HOUSE_VALUE_THRESHOLD
+        )
+
+        impenetrable_surfaces_threshold = (
+            self.df[
+                field_names.IMPENETRABLE_SURFACES_FIELD
+                + field_names.PERCENTILE_FIELD_SUFFIX
+            ]
+            >= self.ENVIRONMENTAL_BURDEN_THRESHOLD
+        )
+
         self.df[field_names.EXPECTED_POPULATION_LOSS_RATE_LOW_INCOME_FIELD] = (
             expected_population_loss_threshold
             & self.df[field_names.FPL_200_SERIES]
@@ -218,6 +242,18 @@ class ScoreL(Score):
             & self.df[field_names.FPL_200_SERIES]
         )
 
+        self.df[
+            field_names.EXTREME_HEAT_MEDIAN_HOUSE_VALUE_LOW_INCOME_FIELD
+        ] = (
+            extreme_heat_median_home_value_threshold
+            & self.df[field_names.FPL_200_SERIES]
+        )
+
+        self.df[field_names.IMPENETRABLE_SURFACES_LOW_INCOME_FIELD] = (
+            impenetrable_surfaces_threshold
+            & self.df[field_names.FPL_200_SERIES]
+        )
+
         self._increment_total_eligibility_exceeded(climate_eligibility_columns)
 
         return self.df[climate_eligibility_columns].any(axis="columns")
@@ -320,11 +356,11 @@ class ScoreL(Score):
         # poverty level. Source: Census's American Community Survey]
 
         housing_eligibility_columns = [
-            field_names.LEAD_PAINT_MEDIAN_HOME_VALUE_LOW_INCOME_FIELD,
+            field_names.LEAD_PAINT_MEDIAN_HOUSE_VALUE_LOW_INCOME_FIELD,
             field_names.HOUSING_BURDEN_LOW_INCOME_FIELD,
         ]
 
-        lead_paint_median_house_hold_threshold = (
+        lead_paint_median_home_value_threshold = (
             self.df[
                 field_names.LEAD_PAINT_FIELD
                 + field_names.PERCENTILE_FIELD_SUFFIX
@@ -347,8 +383,8 @@ class ScoreL(Score):
         )
 
         # series by series indicators
-        self.df[field_names.LEAD_PAINT_MEDIAN_HOME_VALUE_LOW_INCOME_FIELD] = (
-            lead_paint_median_house_hold_threshold
+        self.df[field_names.LEAD_PAINT_MEDIAN_HOUSE_VALUE_LOW_INCOME_FIELD] = (
+            lead_paint_median_home_value_threshold
             & self.df[field_names.FPL_200_SERIES]
         )
 
@@ -449,6 +485,7 @@ class ScoreL(Score):
             field_names.DIABETES_LOW_INCOME_FIELD,
             field_names.ASTHMA_LOW_INCOME_FIELD,
             field_names.HEART_DISEASE_LOW_INCOME_FIELD,
+            field_names.HEALTHY_FOOD_LOW_INCOME_FIELD,
             field_names.LIFE_EXPECTANCY_LOW_INCOME_FIELD,
         ]
 
@@ -474,6 +511,14 @@ class ScoreL(Score):
             >= self.ENVIRONMENTAL_BURDEN_THRESHOLD
         )
 
+        healthy_food_threshold = (
+            self.df[
+                field_names.HEALTHY_FOOD_FIELD
+                + field_names.PERCENTILE_FIELD_SUFFIX
+            ]
+            >= self.ENVIRONMENTAL_BURDEN_THRESHOLD
+        )
+
         life_expectancy_threshold = (
             self.df[
                 field_names.LIFE_EXPECTANCY_FIELD
@@ -496,6 +541,9 @@ class ScoreL(Score):
         self.df[field_names.LIFE_EXPECTANCY_LOW_INCOME_FIELD] = (
             life_expectancy_threshold & self.df[field_names.FPL_200_SERIES]
         )
+        self.df[field_names.HEALTHY_FOOD_LOW_INCOME_FIELD] = (
+            healthy_food_threshold & self.df[field_names.FPL_200_SERIES]
+        )
 
         self._increment_total_eligibility_exceeded(health_eligibility_columns)
 
@@ -513,6 +561,15 @@ class ScoreL(Score):
         # Where the high school degree achievement rates for adults 25 years and older is less than 95%
         # (necessary to screen out university block groups)
 
+        # Workforce criteria for states fields.
+        workforce_eligibility_columns = [
+            field_names.UNEMPLOYMENT_LOW_HS_EDUCATION_FIELD,
+            field_names.POVERTY_LOW_HS_EDUCATION_FIELD,
+            field_names.LINGUISTIC_ISOLATION_LOW_HS_EDUCATION_FIELD,
+            field_names.MEDIAN_INCOME_LOW_HS_EDUCATION_FIELD,
+            field_names.LOW_READING_LOW_HS_EDUCATION_FIELD,
+        ]
+
         high_scool_achievement_rate_threshold = (
             self.df[field_names.HIGH_SCHOOL_ED_FIELD]
             >= self.LACK_OF_HIGH_SCHOOL_MINIMUM_THRESHOLD
@@ -552,6 +609,14 @@ class ScoreL(Score):
             >= self.ENVIRONMENTAL_BURDEN_THRESHOLD
         )
 
+        low_reading_threshold = (
+            self.df[
+                field_names.LOW_READING_FIELD
+                + field_names.PERCENTILE_FIELD_SUFFIX
+            ]
+            >= self.ENVIRONMENTAL_BURDEN_THRESHOLD
+        )
+
         self.df[field_names.LINGUISTIC_ISOLATION_LOW_HS_EDUCATION_FIELD] = (
             linguistic_isolation_threshold
             & high_scool_achievement_rate_threshold
@@ -569,15 +634,9 @@ class ScoreL(Score):
             unemployment_threshold & high_scool_achievement_rate_threshold
         )
 
-        # Workforce criteria for states fields that create indicator columns
-        # for each tract in order to indicate whether they met any of the four
-        # criteria. We will used this create individual indicator columns.
-        workforce_eligibility_columns = [
-            field_names.UNEMPLOYMENT_LOW_HS_EDUCATION_FIELD,
-            field_names.POVERTY_LOW_HS_EDUCATION_FIELD,
-            field_names.LINGUISTIC_ISOLATION_LOW_HS_EDUCATION_FIELD,
-            field_names.MEDIAN_INCOME_LOW_HS_EDUCATION_FIELD,
-        ]
+        self.df[field_names.LOW_READING_LOW_HS_EDUCATION_FIELD] = (
+            low_reading_threshold & high_scool_achievement_rate_threshold
+        )
 
         workforce_combined_criteria_for_states = self.df[
             workforce_eligibility_columns

From 57068379564fde2d1ba8313efce7ed72b13a78a6 Mon Sep 17 00:00:00 2001
From: Lucas Merrill Brown <lucas.m.brown@omb.eop.gov>
Date: Tue, 7 Dec 2021 12:45:45 -0500
Subject: [PATCH 4/5] Add NATA cancer risk and respiratory hazard to definition
 L (#1001)

---
 .../data_pipeline/etl/score/etl_score.py      |  2 +-
 .../data_pipeline/etl/sources/ejscreen/etl.py | 10 +++++--
 .../ipython/scoring_comparison.ipynb          |  2 +-
 .../data_pipeline/score/field_names.py        |  4 ++-
 .../data_pipeline/score/score_c.py            |  2 +-
 .../data_pipeline/score/score_f.py            |  2 +-
 .../data_pipeline/score/score_l.py            | 26 +++++++++++++++++++
 7 files changed, 41 insertions(+), 7 deletions(-)

diff --git a/data/data-pipeline/data_pipeline/etl/score/etl_score.py b/data/data-pipeline/data_pipeline/etl/score/etl_score.py
index 0ce0e052..064d1670 100644
--- a/data/data-pipeline/data_pipeline/etl/score/etl_score.py
+++ b/data/data-pipeline/data_pipeline/etl/score/etl_score.py
@@ -322,7 +322,7 @@ class ScoreETL(ExtractTransformLoad):
             field_names.FEMA_RISK_FIELD,
             field_names.URBAN_HEURISTIC_FIELD,
             field_names.AIR_TOXICS_CANCER_RISK_FIELD,
-            field_names.RESPITORY_HAZARD_FIELD,
+            field_names.RESPIRATORY_HAZARD_FIELD,
             field_names.DIESEL_FIELD,
             field_names.PM25_FIELD,
             field_names.OZONE_FIELD,
diff --git a/data/data-pipeline/data_pipeline/etl/sources/ejscreen/etl.py b/data/data-pipeline/data_pipeline/etl/sources/ejscreen/etl.py
index c5724d7d..da88ea48 100644
--- a/data/data-pipeline/data_pipeline/etl/sources/ejscreen/etl.py
+++ b/data/data-pipeline/data_pipeline/etl/sources/ejscreen/etl.py
@@ -8,6 +8,12 @@ logger = get_module_logger(__name__)
 
 
 class EJSCREENETL(ExtractTransformLoad):
+    """Load EJSCREEN data.
+
+    Data dictionary:
+        https://gaftp.epa.gov/EJSCREEN/2019/2019_EJSCREEN_columns_explained.csv
+    """
+
     def __init__(self):
         self.EJSCREEN_FTP_URL = "https://edap-arcgiscloud-data-commons.s3.amazonaws.com/EJSCREEN2020/EJSCREEN_Tract_2020_USPR.csv.zip"
         self.EJSCREEN_CSV = self.TMP_PATH / "EJSCREEN_Tract_2020_USPR.csv"
@@ -19,7 +25,7 @@ class EJSCREENETL(ExtractTransformLoad):
             field_names.TOTAL_POP_FIELD,
             # pylint: disable=duplicate-code
             field_names.AIR_TOXICS_CANCER_RISK_FIELD,
-            field_names.RESPITORY_HAZARD_FIELD,
+            field_names.RESPIRATORY_HAZARD_FIELD,
             field_names.DIESEL_FIELD,
             field_names.PM25_FIELD,
             field_names.OZONE_FIELD,
@@ -61,7 +67,7 @@ class EJSCREENETL(ExtractTransformLoad):
                 # but I think that's the direction we'd like to move all ETL classes. - LMB
                 "ACSTOTPOP": field_names.TOTAL_POP_FIELD,
                 "CANCER": field_names.AIR_TOXICS_CANCER_RISK_FIELD,
-                "RESP": field_names.RESPITORY_HAZARD_FIELD,
+                "RESP": field_names.RESPIRATORY_HAZARD_FIELD,
                 "DSLPM": field_names.DIESEL_FIELD,
                 "PM25": field_names.PM25_FIELD,
                 "OZONE": field_names.OZONE_FIELD,
diff --git a/data/data-pipeline/data_pipeline/ipython/scoring_comparison.ipynb b/data/data-pipeline/data_pipeline/ipython/scoring_comparison.ipynb
index 5903550e..e5e02974 100644
--- a/data/data-pipeline/data_pipeline/ipython/scoring_comparison.ipynb
+++ b/data/data-pipeline/data_pipeline/ipython/scoring_comparison.ipynb
@@ -479,7 +479,7 @@
     "comparison_fields = [\n",
     "    field_names.POVERTY_LESS_THAN_100_FPL_FIELD,\n",
     "    field_names.POVERTY_LESS_THAN_200_FPL_FIELD,\n",
-    "    field_names.MEDIAN_INCOME_PERCENT_AMI_FIELD,\n",
+    "    field_names.MEDIAN_INCOME_AS_PERCENT_OF_AMI_FIELD,\n",
     "    field_names.LINGUISTIC_ISO_FIELD,\n",
     "    field_names.UNEMPLOYMENT_FIELD,\n",
     "    field_names.HIGH_SCHOOL_ED_FIELD,\n",
diff --git a/data/data-pipeline/data_pipeline/score/field_names.py b/data/data-pipeline/data_pipeline/score/field_names.py
index 4c47a555..c323e8f2 100644
--- a/data/data-pipeline/data_pipeline/score/field_names.py
+++ b/data/data-pipeline/data_pipeline/score/field_names.py
@@ -89,6 +89,7 @@ RMP_FIELD = "Proximity to Risk Management Plan (RMP) facilities"
 TSDF_FIELD = "Proximity to TSDF sites"
 NPL_FIELD = "Proximity to NPL sites"
 AIR_TOXICS_CANCER_RISK_FIELD = "Air toxics cancer risk"
+RESPIRATORY_HAZARD_FIELD = "Respiratory hazard index"
 
 # Housing
 HOUSING_BURDEN_FIELD = "Housing burden (percent)"
@@ -104,7 +105,6 @@ DIABETES_FIELD = "Diagnosed diabetes among adults aged >=18 years"
 ASTHMA_FIELD = "Current asthma among adults aged >=18 years"
 HEART_DISEASE_FIELD = "Coronary heart disease among adults aged >=18 years"
 LIFE_EXPECTANCY_FIELD = "Life expectancy (years)"
-RESPITORY_HAZARD_FIELD = "Respiratory hazard index"
 CANCER_FIELD = "Cancer (excluding skin cancer) among adults aged >=18 years"
 HEALTH_INSURANCE_FIELD = (
     "Current lack of health insurance among adults aged 18-64 years"
@@ -260,6 +260,8 @@ IMPENETRABLE_SURFACES_LOW_INCOME_FIELD = (
 RMP_LOW_INCOME_FIELD = f"At or above the {PERCENTILE}th percentile for proximity to RMP sites and is low income"
 SUPERFUND_LOW_INCOME_FIELD = f"At or above the {PERCENTILE}th percentile for proximity to superfund sites and is low income"
 HAZARDOUS_WASTE_LOW_INCOME_FIELD = f"At or above the {PERCENTILE}th percentile for proximity to hazardous waste facilities and is low income"
+AIR_TOXICS_CANCER_RISK_LOW_INCOME_FIELD = f"At or above the {PERCENTILE}th percentile for air toxics cancer risk and is low income"
+RESPIRATORY_HAZARD_LOW_INCOME_FIELD = f"At or above the {PERCENTILE}th percentile for respiratory hazard index and is low income"
 
 # Critical Clean Water and Waste Infrastructure
 WASTEWATER_DISCHARGE_LOW_INCOME_FIELD = f"At or above the {PERCENTILE}th percentile for wastewater discharge and is low income"
diff --git a/data/data-pipeline/data_pipeline/score/score_c.py b/data/data-pipeline/data_pipeline/score/score_c.py
index 9fe68fff..57194b45 100644
--- a/data/data-pipeline/data_pipeline/score/score_c.py
+++ b/data/data-pipeline/data_pipeline/score/score_c.py
@@ -54,7 +54,7 @@ class ScoreC(Score):
             [
                 field_names.AIR_TOXICS_CANCER_RISK_FIELD
                 + field_names.PERCENTILE_FIELD_SUFFIX,
-                field_names.RESPITORY_HAZARD_FIELD
+                field_names.RESPIRATORY_HAZARD_FIELD
                 + field_names.PERCENTILE_FIELD_SUFFIX,
                 field_names.DIESEL_FIELD + field_names.PERCENTILE_FIELD_SUFFIX,
                 field_names.PM25_FIELD + field_names.PERCENTILE_FIELD_SUFFIX,
diff --git a/data/data-pipeline/data_pipeline/score/score_f.py b/data/data-pipeline/data_pipeline/score/score_f.py
index cc07d0b2..fb254776 100644
--- a/data/data-pipeline/data_pipeline/score/score_f.py
+++ b/data/data-pipeline/data_pipeline/score/score_f.py
@@ -36,7 +36,7 @@ class ScoreF(Score):
             )
             | (
                 self.df[
-                    field_names.RESPITORY_HAZARD_FIELD
+                    field_names.RESPIRATORY_HAZARD_FIELD
                     + field_names.PERCENTILE_FIELD_SUFFIX
                 ]
                 > 0.9
diff --git a/data/data-pipeline/data_pipeline/score/score_l.py b/data/data-pipeline/data_pipeline/score/score_l.py
index 7653ce46..64976d80 100644
--- a/data/data-pipeline/data_pipeline/score/score_l.py
+++ b/data/data-pipeline/data_pipeline/score/score_l.py
@@ -407,6 +407,8 @@ class ScoreL(Score):
             field_names.RMP_LOW_INCOME_FIELD,
             field_names.SUPERFUND_LOW_INCOME_FIELD,
             field_names.HAZARDOUS_WASTE_LOW_INCOME_FIELD,
+            field_names.AIR_TOXICS_CANCER_RISK_LOW_INCOME_FIELD,
+            field_names.RESPIRATORY_HAZARD_LOW_INCOME_FIELD,
         ]
 
         rmp_sites_threshold = (
@@ -426,6 +428,22 @@ class ScoreL(Score):
             >= self.ENVIRONMENTAL_BURDEN_THRESHOLD
         )
 
+        air_toxics_cancer_risk_threshold = (
+            self.df[
+                field_names.AIR_TOXICS_CANCER_RISK_FIELD
+                + field_names.PERCENTILE_FIELD_SUFFIX
+            ]
+            >= self.ENVIRONMENTAL_BURDEN_THRESHOLD
+        )
+
+        respiratory_hazard_risk_threshold = (
+            self.df[
+                field_names.RESPIRATORY_HAZARD_FIELD
+                + field_names.PERCENTILE_FIELD_SUFFIX
+            ]
+            >= self.ENVIRONMENTAL_BURDEN_THRESHOLD
+        )
+
         # individual series-by-series
         self.df[field_names.RMP_LOW_INCOME_FIELD] = (
             rmp_sites_threshold & self.df[field_names.FPL_200_SERIES]
@@ -436,6 +454,14 @@ class ScoreL(Score):
         self.df[field_names.HAZARDOUS_WASTE_LOW_INCOME_FIELD] = (
             tsdf_sites_threshold & self.df[field_names.FPL_200_SERIES]
         )
+        self.df[field_names.AIR_TOXICS_CANCER_RISK_LOW_INCOME_FIELD] = (
+            air_toxics_cancer_risk_threshold
+            & self.df[field_names.FPL_200_SERIES]
+        )
+        self.df[field_names.RESPIRATORY_HAZARD_LOW_INCOME_FIELD] = (
+            respiratory_hazard_risk_threshold
+            & self.df[field_names.FPL_200_SERIES]
+        )
 
         self._increment_total_eligibility_exceeded(
             pollution_eligibility_columns

From 9d28f5a4c45733b90e1453c528afbcd6ebebfb3e Mon Sep 17 00:00:00 2001
From: Vim <86254807+vim-usds@users.noreply.github.com>
Date: Tue, 7 Dec 2021 12:52:50 -0500
Subject: [PATCH 5/5] Add a case if data is not present in tiles (#998)

- will check each property and display N/A if null
- update snapshot
---
 client/src/components/AreaDetail/index.tsx    | 89 +++++++++++--------
 .../__snapshots__/areaDetail.test.tsx.snap    | 70 +++++----------
 2 files changed, 78 insertions(+), 81 deletions(-)

diff --git a/client/src/components/AreaDetail/index.tsx b/client/src/components/AreaDetail/index.tsx
index 30ccc6ca..16bbbb04 100644
--- a/client/src/components/AreaDetail/index.tsx
+++ b/client/src/components/AreaDetail/index.tsx
@@ -12,24 +12,26 @@ import * as constants from '../../data/constants';
 import * as EXPLORE_COPY from '../../data/copy/explore';
 import * as METHODOLOGY_COPY from '../../data/copy/methodology';
 
-export const readablePercentile = (percentile: number) => {
-  return Math.round(percentile * 100);
+export const readablePercentile = (percentile: number | null) => {
+  return percentile ? Math.round(percentile * 100) : 'N/A';
 };
 
 // Todo: Add internationalization to superscript ticket #582
-const getSuperscriptOrdinal = (percentile: number) => {
-  const englishOrdinalRules = new Intl.PluralRules('en', {
-    type: 'ordinal',
-  });
-  const suffixes = {
-    zero: 'th',
-    one: 'st',
-    two: 'nd',
-    few: 'rd',
-    many: 'th',
-    other: 'th',
-  };
-  return suffixes[englishOrdinalRules.select(percentile)];
+const getSuperscriptOrdinal = (percentile: number | string) => {
+  if (typeof percentile === "number") {
+    const englishOrdinalRules = new Intl.PluralRules('en', {
+      type: 'ordinal',
+    });
+    const suffixes = {
+      zero: 'th',
+      one: 'st',
+      two: 'nd',
+      few: 'rd',
+      many: 'th',
+      other: 'th',
+    };
+    return suffixes[englishOrdinalRules.select(percentile)];
+  }
 };
 
 interface IAreaDetailProps {
@@ -40,11 +42,13 @@ const AreaDetail = ({properties}:IAreaDetailProps) => {
   const intl = useIntl();
   const [isCommunityFocus, setIsCommunityFocus] = React.useState<boolean>(true);
 
-  const score = properties[constants.SCORE_PROPERTY_HIGH] as number;
-  const blockGroup = properties[constants.GEOID_PROPERTY];
-  const population = properties[constants.TOTAL_POPULATION];
-  const countyName = properties[constants.COUNTY_NAME];
-  const stateName = properties[constants.STATE_NAME];
+  console.log("Area Detail properies: ", properties);
+
+  const score = properties[constants.SCORE_PROPERTY_HIGH] ? properties[constants.SCORE_PROPERTY_HIGH] as number : 0;
+  const blockGroup = properties[constants.GEOID_PROPERTY] ? properties[constants.GEOID_PROPERTY] : "N/A";
+  const population = properties[constants.TOTAL_POPULATION] ? properties[constants.TOTAL_POPULATION] : "N/A";
+  const countyName = properties[constants.COUNTY_NAME] ? properties[constants.COUNTY_NAME] : "N/A";
+  const stateName = properties[constants.STATE_NAME] ? properties[constants.STATE_NAME] : "N/A";
 
   useEffect(() => {
     if (score >= constants.SCORE_BOUNDARY_PRIORITIZED ) {
@@ -65,77 +69,92 @@ const AreaDetail = ({properties}:IAreaDetailProps) => {
   const areaMedianIncome:indicatorInfo = {
     label: intl.formatMessage(EXPLORE_COPY.SIDE_PANEL_INDICATORS.AREA_MEDIAN_INCOME),
     description: intl.formatMessage(EXPLORE_COPY.SIDE_PANEL_INDICATOR_DESCRIPTION.AREA_MEDIAN_INCOME),
-    value: properties[constants.AREA_MEDIAN_INCOME_PERCENTILE],
+    value: properties[constants.AREA_MEDIAN_INCOME_PERCENTILE] ?
+    properties[constants.AREA_MEDIAN_INCOME_PERCENTILE] : null,
   };
   const eduInfo:indicatorInfo = {
     label: intl.formatMessage(EXPLORE_COPY.SIDE_PANEL_INDICATORS.EDUCATION),
     description: intl.formatMessage(EXPLORE_COPY.SIDE_PANEL_INDICATOR_DESCRIPTION.EDUCATION),
-    value: properties[constants.EDUCATION_PROPERTY_PERCENTILE],
+    value: properties[constants.EDUCATION_PROPERTY_PERCENTILE] ?
+    properties[constants.EDUCATION_PROPERTY_PERCENTILE] : null,
   };
   const poverty:indicatorInfo = {
     label: intl.formatMessage(EXPLORE_COPY.SIDE_PANEL_INDICATORS.POVERTY),
     description: intl.formatMessage(EXPLORE_COPY.SIDE_PANEL_INDICATOR_DESCRIPTION.POVERTY),
-    value: properties[constants.POVERTY_PROPERTY_PERCENTILE],
+    value: properties[constants.POVERTY_PROPERTY_PERCENTILE] ?
+    properties[constants.POVERTY_PROPERTY_PERCENTILE] : null,
   };
   const asthma:indicatorInfo = {
     label: intl.formatMessage(EXPLORE_COPY.SIDE_PANEL_INDICATORS.ASTHMA),
     description: intl.formatMessage(EXPLORE_COPY.SIDE_PANEL_INDICATOR_DESCRIPTION.ASTHMA),
-    value: properties[constants.ASTHMA_PERCENTILE],
+    value: properties[constants.ASTHMA_PERCENTILE] ?
+    properties[constants.ASTHMA_PERCENTILE] : null,
   };
   const diabetes:indicatorInfo = {
     label: intl.formatMessage(EXPLORE_COPY.SIDE_PANEL_INDICATORS.DIABETES),
     description: intl.formatMessage(EXPLORE_COPY.SIDE_PANEL_INDICATOR_DESCRIPTION.DIABETES),
-    value: properties[constants.DIABETES_PERCENTILE],
+    value: properties[constants.DIABETES_PERCENTILE] ?
+    properties[constants.DIABETES_PERCENTILE] : null,
   };
   const dieselPartMatter:indicatorInfo = {
     label: intl.formatMessage(EXPLORE_COPY.SIDE_PANEL_INDICATORS.DIESEL_PARTICULATE_MATTER),
     description: intl.formatMessage(EXPLORE_COPY.SIDE_PANEL_INDICATOR_DESCRIPTION.DIESEL_PARTICULATE_MATTER),
-    value: properties[constants.DIESEL_MATTER_PERCENTILE],
+    value: properties[constants.DIESEL_MATTER_PERCENTILE] ?
+    properties[constants.DIESEL_MATTER_PERCENTILE] : null,
   };
   const lifeExpect:indicatorInfo = {
     label: intl.formatMessage(EXPLORE_COPY.SIDE_PANEL_INDICATORS.LIFE_EXPECT),
     description: intl.formatMessage(EXPLORE_COPY.SIDE_PANEL_INDICATOR_DESCRIPTION.LIFE_EXPECT),
-    value: properties[constants.LIFE_PERCENTILE],
+    value: properties[constants.LIFE_PERCENTILE] ?
+    properties[constants.LIFE_PERCENTILE] : null,
   };
   const energyBurden:indicatorInfo = {
     label: intl.formatMessage(EXPLORE_COPY.SIDE_PANEL_INDICATORS.ENERGY_BURDEN),
     description: intl.formatMessage(EXPLORE_COPY.SIDE_PANEL_INDICATOR_DESCRIPTION.ENERGY_BURDEN),
-    value: properties[constants.ENERGY_PERCENTILE],
+    value: properties[constants.ENERGY_PERCENTILE] ?
+    properties[constants.ENERGY_PERCENTILE] : null,
   };
   const pm25:indicatorInfo = {
     label: intl.formatMessage(EXPLORE_COPY.SIDE_PANEL_INDICATORS.PM_2_5),
     description: intl.formatMessage(EXPLORE_COPY.SIDE_PANEL_INDICATOR_DESCRIPTION.PM_2_5),
-    value: properties[constants.PM25_PERCENTILE],
+    value: properties[constants.PM25_PERCENTILE] ?
+    properties[constants.PM25_PERCENTILE] : null,
   };
   const leadPaint:indicatorInfo = {
     label: intl.formatMessage(EXPLORE_COPY.SIDE_PANEL_INDICATORS.LEAD_PAINT),
     description: intl.formatMessage(EXPLORE_COPY.SIDE_PANEL_INDICATOR_DESCRIPTION.LEAD_PAINT),
-    value: properties[constants.LEAD_PAINT_PERCENTILE],
+    value: properties[constants.LEAD_PAINT_PERCENTILE] ?
+    properties[constants.LEAD_PAINT_PERCENTILE] : null,
   };
   const trafficVolume:indicatorInfo = {
     label: intl.formatMessage(EXPLORE_COPY.SIDE_PANEL_INDICATORS.TRAFFIC_VOLUME),
     description: intl.formatMessage(EXPLORE_COPY.SIDE_PANEL_INDICATOR_DESCRIPTION.TRAFFIC_VOLUME),
-    value: properties[constants.TRAFFIC_PERCENTILE],
+    value: properties[constants.TRAFFIC_PERCENTILE] ?
+    properties[constants.TRAFFIC_PERCENTILE] : null,
   };
   const wasteWater:indicatorInfo = {
     label: intl.formatMessage(EXPLORE_COPY.SIDE_PANEL_INDICATORS.WASTE_WATER),
     description: intl.formatMessage(EXPLORE_COPY.SIDE_PANEL_INDICATOR_DESCRIPTION.WASTE_WATER),
-    value: properties[constants.WASTEWATER_PERCENTILE],
+    value: properties[constants.WASTEWATER_PERCENTILE] ?
+    properties[constants.WASTEWATER_PERCENTILE] : null,
   };
   const femaRisk:indicatorInfo = {
     label: intl.formatMessage(EXPLORE_COPY.SIDE_PANEL_INDICATORS.FEMA_RISK),
     description: intl.formatMessage(EXPLORE_COPY.SIDE_PANEL_INDICATOR_DESCRIPTION.FEMA_RISK),
-    value: properties[constants.FEMA_PERCENTILE],
+    value: properties[constants.FEMA_PERCENTILE] ?
+    properties[constants.FEMA_PERCENTILE] : null,
   };
   const heartDisease:indicatorInfo = {
     label: intl.formatMessage(EXPLORE_COPY.SIDE_PANEL_INDICATORS.HEART_DISEASE),
     description: intl.formatMessage(EXPLORE_COPY.SIDE_PANEL_INDICATOR_DESCRIPTION.HEART_DISEASE),
-    value: properties[constants.HEART_PERCENTILE],
+    value: properties[constants.HEART_PERCENTILE] ?
+    properties[constants.HEART_PERCENTILE] : null,
   };
   const houseBurden:indicatorInfo = {
     label: intl.formatMessage(EXPLORE_COPY.SIDE_PANEL_INDICATORS.HOUSE_BURDEN),
     description: intl.formatMessage(EXPLORE_COPY.SIDE_PANEL_INDICATOR_DESCRIPTION.HOUSE_BURDEN),
-    value: properties[constants.HOUSING_BURDEN_PROPERTY_PERCENTILE],
+    value: properties[constants.HOUSING_BURDEN_PROPERTY_PERCENTILE] ?
+    properties[constants.HOUSING_BURDEN_PROPERTY_PERCENTILE] : null,
   };
 
 
diff --git a/client/src/components/AreaDetail/tests/__snapshots__/areaDetail.test.tsx.snap b/client/src/components/AreaDetail/tests/__snapshots__/areaDetail.test.tsx.snap
index 0879df38..0686d46b 100644
--- a/client/src/components/AreaDetail/tests/__snapshots__/areaDetail.test.tsx.snap
+++ b/client/src/components/AreaDetail/tests/__snapshots__/areaDetail.test.tsx.snap
@@ -19,7 +19,7 @@ exports[`rendering of the AreaDetail checks if various text fields are visible 1
           County:
         </span>
         <span>
-           undefined
+           N/A
         </span>
       </li>
       <li>
@@ -27,7 +27,7 @@ exports[`rendering of the AreaDetail checks if various text fields are visible 1
           State: 
         </span>
         <span>
-           undefined
+           N/A
         </span>
       </li>
       <li>
@@ -134,11 +134,9 @@ exports[`rendering of the AreaDetail checks if various text fields are visible 1
           Asthma
         </h4>
         <div>
-          NaN
+          N/A
           <sup>
-            <span>
-              th
-            </span>
+            <span />
           </sup>
         </div>
       </div>
@@ -156,11 +154,9 @@ exports[`rendering of the AreaDetail checks if various text fields are visible 1
           Diabetes
         </h4>
         <div>
-          NaN
+          N/A
           <sup>
-            <span>
-              th
-            </span>
+            <span />
           </sup>
         </div>
       </div>
@@ -178,11 +174,9 @@ exports[`rendering of the AreaDetail checks if various text fields are visible 1
           Diesel particulate matter
         </h4>
         <div>
-          NaN
+          N/A
           <sup>
-            <span>
-              th
-            </span>
+            <span />
           </sup>
         </div>
       </div>
@@ -200,11 +194,9 @@ exports[`rendering of the AreaDetail checks if various text fields are visible 1
           Energy burden
         </h4>
         <div>
-          NaN
+          N/A
           <sup>
-            <span>
-              th
-            </span>
+            <span />
           </sup>
         </div>
       </div>
@@ -222,11 +214,9 @@ exports[`rendering of the AreaDetail checks if various text fields are visible 1
           FEMA Risk Index
         </h4>
         <div>
-          NaN
+          N/A
           <sup>
-            <span>
-              th
-            </span>
+            <span />
           </sup>
         </div>
       </div>
@@ -244,11 +234,9 @@ exports[`rendering of the AreaDetail checks if various text fields are visible 1
           Heart disease
         </h4>
         <div>
-          NaN
+          N/A
           <sup>
-            <span>
-              th
-            </span>
+            <span />
           </sup>
         </div>
       </div>
@@ -288,11 +276,9 @@ exports[`rendering of the AreaDetail checks if various text fields are visible 1
           Lead paint
         </h4>
         <div>
-          NaN
+          N/A
           <sup>
-            <span>
-              th
-            </span>
+            <span />
           </sup>
         </div>
       </div>
@@ -310,11 +296,9 @@ exports[`rendering of the AreaDetail checks if various text fields are visible 1
           Life expectancy
         </h4>
         <div>
-          NaN
+          N/A
           <sup>
-            <span>
-              th
-            </span>
+            <span />
           </sup>
         </div>
       </div>
@@ -332,11 +316,9 @@ exports[`rendering of the AreaDetail checks if various text fields are visible 1
           PM2.5
         </h4>
         <div>
-          NaN
+          N/A
           <sup>
-            <span>
-              th
-            </span>
+            <span />
           </sup>
         </div>
       </div>
@@ -354,11 +336,9 @@ exports[`rendering of the AreaDetail checks if various text fields are visible 1
           Traffic proximity and volume
         </h4>
         <div>
-          NaN
+          N/A
           <sup>
-            <span>
-              th
-            </span>
+            <span />
           </sup>
         </div>
       </div>
@@ -376,11 +356,9 @@ exports[`rendering of the AreaDetail checks if various text fields are visible 1
           Wastewater discharge
         </h4>
         <div>
-          NaN
+          N/A
           <sup>
-            <span>
-              th
-            </span>
+            <span />
           </sup>
         </div>
       </div>