Transform eia861 short form

src/pudl/metadata/fields.py

@@ -892,6 +892,10 @@
         "description": "Annual demand per km2 of a given service territory.",
         "unit": "MWh/km2",
     },
+    "demand_side_management": {
+        "type": "boolean",
+        "description": "Were there strategies or measures used to control electricity demand by customers?",
+    },
     "depreciation_type": {
         "type": "string",
         "description": (
@@ -1715,6 +1719,10 @@
         "type": "string",
         "description": "Category of geographic aggregation in EIA bulk electricity data.",
     },
+    "green_pricing": {
+        "type": "boolean",
+        "description": "Was there green pricing program associated with this utility during the reporting year?",
+    },
     "green_pricing_revenue": {
         "type": "number",
         "description": (

src/pudl/metadata/resources/eia861.py

@@ -694,6 +694,37 @@
         "sources": ["eia861"],
         "etl_group": "eia861",
     },
+    "core_eia861__yearly_short_form": {
+        "description": "Abbreviated version of the EIA-861 data.",
+        "schema": {
+            "fields": [
+                "report_date",
+                "utility_id_eia",
+                "utility_name_eia",
+                "entity_type",
+                "state",
+                "balancing_authority_code_eia",
+                "sales_revenue",
+                "sales_mwh",
+                "customers",
+                "water_heater",
+                "net_metering",
+                "demand_side_management",
+                "time_responsive_programs",
+                "green_pricing",
+                "data_maturity",
+            ],
+            "primary_key": [
+                "utility_id_eia",
+                "state",
+                "report_date",
+                "balancing_authority_code_eia",
+            ],
+        },
+        "field_namespace": "eia",
+        "sources": ["eia861"],
+        "etl_group": "eia861",
+    },
     "core_eia861__yearly_service_territory": {
         "description": "County FIPS codes for counties composing utility service territories.",
         "schema": {

src/pudl/output/pudltabl.py

@@ -181,6 +181,7 @@ def _register_output_methods(self: Self):
             # eia861 (clean)
             "core_eia861__yearly_service_territory": "service_territory_eia861",
             "core_eia861__yearly_sales": "sales_eia861",
+            "core_eia861__yearly_short_form": "short_form_eia861",
             "core_eia861__yearly_advanced_metering_infrastructure": "advanced_metering_infrastructure_eia861",
             "core_eia861__yearly_demand_response": "demand_response_eia861",
             "core_eia861__yearly_demand_response_water_heater": "demand_response_water_heater_eia861",

src/pudl/package_data/eia861/column_maps/short_form_eia861.csv

@@ -4,13 +4,13 @@ utility_id_eia,1,1,1,1,1,1,1,-1,1,1,1
 utility_name_eia,2,2,2,2,2,2,2,-1,2,2,2
 entity_type,-1,-1,-1,3,3,3,3,-1,3,3,3
 state,3,3,3,4,4,4,4,-1,4,4,4
-ba_code,-1,4,4,5,5,5,5,-1,5,5,5
-total_revenue,4,5,5,6,6,6,6,-1,6,6,6
-total_sales,5,6,6,7,7,7,7,-1,7,7,7
-total_customers,6,7,7,8,8,8,8,-1,8,8,8
+balancing_authority_code_eia,-1,4,4,5,5,5,5,-1,5,5,5
+sales_revenue,4,5,5,6,6,6,6,-1,6,6,6
+sales_mwh,5,6,6,7,7,7,7,-1,7,7,7
+customers,6,7,7,8,8,8,8,-1,8,8,8
 water_heater,-1,8,8,9,9,9,9,-1,9,9,9
 net_metering,8,9,9,10,10,10,10,-1,10,10,10
 demand_side_management,9,10,10,11,11,11,11,-1,11,11,11
-time_based_programs,10,11,11,12,12,12,12,-1,12,12,12
+time_responsive_programs,10,11,11,12,12,12,12,-1,12,12,12
 green_pricing,7,-1,-1,-1,-1,-1,-1,-1,-1,-1,-1
 early_release,-1,-1,-1,-1,-1,-1,-1,-1,-1,-1,-1

src/pudl/transform/eia861.py

@@ -1216,6 +1216,48 @@ def core_eia861__yearly_sales(raw_eia861__sales: pd.DataFrame) -> pd.DataFrame:
     return _post_process(transformed_sales)
 
 
+@asset(io_manager_key="pudl_io_manager")
+def core_eia861__yearly_short_form(
+    raw_eia861__short_form: pd.DataFrame,
+) -> pd.DataFrame:
+    """Transform the EIA 861 Short Form table.
+    Transformations include:
+    * Drop primary key duplicates.
+    * Convert N/Y values to boolean
+    * Change NA BA codes to 'UNK'
+    """
+    idx_cols = [
+        "utility_id_eia",
+        "state",
+        "report_date",
+        "balancing_authority_code_eia",
+    ]
+
+    bool_cols = [
+        "water_heater",
+        "net_metering",
+        "demand_side_management",
+        "time_responsive_programs",
+        "green_pricing",
+    ]
+
+    raw_sf = _pre_process(raw_eia861__short_form)
+    # * fill NA BA values with 'UNK'
+    raw_sf["balancing_authority_code_eia"] = raw_sf[
+        "balancing_authority_code_eia"
+    ].fillna("UNK")
+
+    # * Drop Duplicates based on primary keys
+    deduped_sf = _drop_dupes(df=raw_sf, df_name="Short Form", subset=idx_cols)
+
+    # * Make Y/N's into booleans
+    logger.info("Performing value transformations on EIA 861 Short Form table.")
+    for col in bool_cols:
+        deduped_sf[col] = _make_yn_bool(deduped_sf[col])
+
+    return _post_process(deduped_sf)
+
+
 @asset(io_manager_key="pudl_io_manager")
 def core_eia861__yearly_advanced_metering_infrastructure(
     raw_eia861__advanced_metering_infrastructure: pd.DataFrame,
@@ -2440,6 +2482,7 @@ def core_utility_data_eia861(raw_eia861__utility_data: pd.DataFrame):
         "core_eia861__yearly_operational_data_revenue": AssetIn(),
         "core_eia861__yearly_reliability": AssetIn(),
         "core_eia861__yearly_sales": AssetIn(),
+        "core_eia861__yearly_short_form": AssetIn(),
         "core_eia861__yearly_utility_data_misc": AssetIn(),
         "core_eia861__yearly_utility_data_nerc": AssetIn(),
         "core_eia861__yearly_utility_data_rto": AssetIn(),