Alternative energy-related definition of DACs

data/data-pipeline/data_pipeline/etl/constants.py

@@ -89,6 +89,11 @@ DATASET_LIST = [
         "module_dir": "hud_recap",
         "class_name": "HudRecapETL",
     },
+    {
+        "name": "energy_definition_alternative_draft",
+        "module_dir": "energy_definition_alternative_draft",
+        "class_name": "EnergyDefinitionAlternativeDraft",
+    },
     {
         "name": "tree_equity_score",
         "module_dir": "tree_equity_score",

data/data-pipeline/data_pipeline/etl/sources/energy_definition_alternative_draft/etl.py

@@ -0,0 +1,113 @@
+from pathlib import Path
+import pandas as pd
+
+from data_pipeline.config import settings
+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 EnergyDefinitionAlternativeDraft(ExtractTransformLoad):
+    def __init__(self):
+        self.DEFINITION_ALTERNATIVE_FILE_URL = (
+            settings.AWS_JUSTICE40_DATASOURCES_URL
+            + "/alternative DAC definition.csv.zip"
+        )
+
+        self.OUTPUT_PATH: Path = (
+            self.DATA_PATH / "dataset" / "energy_definition_alternative_draft"
+        )
+
+        self.TRACT_INPUT_COLUMN_NAME = "GEOID"
+        self.ALTERNATIVE_DEFINITION_INPUT_COLUMN_NAME = "J40_DAC"
+
+        # Constants for output
+        self.COLUMNS_TO_KEEP = [
+            self.GEOID_TRACT_FIELD_NAME,
+            field_names.ENERGY_RELATED_COMMUNITIES_DEFINITION_ALTERNATIVE,
+            field_names.COAL_EMPLOYMENT,
+            field_names.OUTAGE_EVENTS,
+            field_names.HOMELESSNESS,
+            field_names.DISABLED_POPULATION,
+            field_names.OUTAGE_DURATION,
+            field_names.JOB_ACCESS,
+            field_names.FOSSIL_ENERGY_EMPLOYMENT,
+            field_names.FOOD_DESERT,
+            field_names.INCOMPLETE_PLUMBING,
+            field_names.NON_GRID_CONNECTED_HEATING_FUEL,
+            field_names.PARKS,
+            field_names.GREATER_THAN_30_MIN_COMMUTE,
+            field_names.INTERNET_ACCESS,
+            field_names.MOBILE_HOME,
+            field_names.SINGLE_PARENT,
+            field_names.TRANSPORTATION_COSTS,
+        ]
+
+        self.df: pd.DataFrame
+
+    def extract(self) -> None:
+        logger.info("Starting data download.")
+
+        unzip_file_from_url(
+            file_url=self.DEFINITION_ALTERNATIVE_FILE_URL,
+            download_path=self.TMP_PATH,
+            unzipped_file_path=self.TMP_PATH
+            / "energy_definition_alternative_draft",
+        )
+
+        self.df = pd.read_csv(
+            filepath_or_buffer=self.TMP_PATH
+            / "energy_definition_alternative_draft"
+            / "J40 alternative DAC definition.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.")
+
+        self.df = self.df.rename(
+            columns={
+                self.TRACT_INPUT_COLUMN_NAME: self.GEOID_TRACT_FIELD_NAME,
+                self.ALTERNATIVE_DEFINITION_INPUT_COLUMN_NAME: field_names.ENERGY_RELATED_COMMUNITIES_DEFINITION_ALTERNATIVE,
+                "Coal_Emp_Ratio": field_names.COAL_EMPLOYMENT,
+                "COUNT_Outage_Events": field_names.OUTAGE_EVENTS,
+                "den_hmls_pop": field_names.HOMELESSNESS,
+                "disability_pct": field_names.DISABLED_POPULATION,
+                "Duration_in_Minutes": field_names.OUTAGE_DURATION,
+                "emp_ovrll_ndx": field_names.JOB_ACCESS,
+                "FE_Emp_Ratio": field_names.FOSSIL_ENERGY_EMPLOYMENT,
+                "Food_LAhalfand10": field_names.FOOD_DESERT,
+                "incomplete_plumbing_pct": field_names.INCOMPLETE_PLUMBING,
+                "nongrid_heat_pct": field_names.NON_GRID_CONNECTED_HEATING_FUEL,
+                "num_parks": field_names.PARKS,
+                "Per_MoT_Dur_gte30": field_names.GREATER_THAN_30_MIN_COMMUTE,
+                "Per_NoInt": field_names.INTERNET_ACCESS,
+                "population_mobile_home_pct": field_names.MOBILE_HOME,
+                "single_parent_pct": field_names.SINGLE_PARENT,
+                "t_ami": field_names.TRANSPORTATION_COSTS,
+            }
+        )
+
+        # Convert to boolean:
+        self.df[field_names.ENERGY_RELATED_COMMUNITIES_DEFINITION_ALTERNATIVE] = \
+            self.df[field_names.ENERGY_RELATED_COMMUNITIES_DEFINITION_ALTERNATIVE
+            ].astype('bool')
+
+    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.df[self.COLUMNS_TO_KEEP].to_csv(
+            path_or_buf=self.OUTPUT_PATH / "usa.csv", index=False
+        )

data/data-pipeline/data_pipeline/ipython/scoring_comparison.ipynb

@@ -276,6 +276,25 @@
     "mapping_inequality_df"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "605af1ff",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Load alternative energy-related definition \n",
+    "energy_definition_alternative_draft_path = (\n",
+    "    DATA_DIR / \"dataset\" / \"energy_definition_alternative_draft\" / \"usa.csv\"\n",
+    ")\n",
+    "energy_definition_alternative_draft_df = pd.read_csv(\n",
+    "    energy_definition_alternative_draft_path,\n",
+    "    dtype={ExtractTransformLoad.GEOID_TRACT_FIELD_NAME: \"string\"},\n",
+    ")\n",
+    "\n",
+    "energy_definition_alternative_draft_df"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -291,6 +310,7 @@
     "    calenviroscreen_df,\n",
     "    persistent_poverty_df,\n",
     "    mapping_inequality_df,\n",
+    "    energy_definition_alternative_draft_df,\n",
     "]\n",
     "\n",
     "merged_df = functools.reduce(\n",
@@ -431,6 +451,11 @@
     "            priority_communities_field=PERSISTENT_POVERTY_TRACT_LEVEL_FIELD,\n",
     "            other_census_tract_fields_to_keep=[],\n",
     "        ),\n",
+    "        Index(\n",
+    "            method_name=field_names.ENERGY_RELATED_COMMUNITIES_DEFINITION_ALTERNATIVE,\n",
+    "            priority_communities_field=field_names.ENERGY_RELATED_COMMUNITIES_DEFINITION_ALTERNATIVE,\n",
+    "            other_census_tract_fields_to_keep=[],\n",
+    "        ),\n",
     "    ]\n",
     "    # Insert indices for each of the HOLC factors.\n",
     "    # Note: since these involve no renaming, we write them using list comprehension.\n",

data/data-pipeline/data_pipeline/score/field_names.py

@@ -230,6 +230,27 @@ IMPENETRABLE_SURFACES_FIELD = "Percent impenetrable surface areas"
 READING_FIELD = "Third grade reading proficiency"
 LOW_READING_FIELD = "Low third grade reading proficiency"
 
+# Alternative energy-related definition of DACs
+ENERGY_RELATED_COMMUNITIES_DEFINITION_ALTERNATIVE = (
+    "Energy-related alternative definition of communities"
+)
+COAL_EMPLOYMENT = "Coal employment"
+OUTAGE_EVENTS = "Outage Events"
+HOMELESSNESS = "Homelessness"
+DISABLED_POPULATION = "Disabled population"
+OUTAGE_DURATION = "Outage Duration"
+JOB_ACCESS = "JobAccess"
+FOSSIL_ENERGY_EMPLOYMENT = "Fossil energy employment"
+FOOD_DESERT = "Food Desert"
+INCOMPLETE_PLUMBING = "Incomplete Plumbing"
+NON_GRID_CONNECTED_HEATING_FUEL = "Non-grid-connected heating fuel"
+PARKS = "Parks"
+GREATER_THAN_30_MIN_COMMUTE = "Greater than 30 min commute"
+INTERNET_ACCESS = "Internet Access"
+MOBILE_HOME = "Mobile Home"
+SINGLE_PARENT = "Single Parent"
+TRANSPORTATION_COSTS = "Transportation Costs"
+
 #####
 # Names for individual factors being exceeded
 # Climate Change