Source code for pudl.output.eia_bulk_elec

"""Interim and output tables derived from the EIA Bulk Electricity data."""
import pandas as pd
from dagster import asset

import pudl

[docs] logger = pudl.logging_helpers.get_logger(__name__)
@asset(io_manager_key=None, compute_kind="Python")
[docs] def _out_eia__monthly_state_fuel_prices( core_eia__yearly_fuel_receipts_costs_aggs: pd.DataFrame, ) -> pd.DataFrame: """Get state-level average fuel costs from EIA's bulk electricity data. This data is used to fill in missing fuel prices in the :ref:`core_eia923__monthly_fuel_receipts_costs` table. It was created as a drop-in replacement for data we were previously obtaining from EIA's unreliable API. """ aggregates = core_eia__yearly_fuel_receipts_costs_aggs.loc[ :, [ "report_date", "sector_agg", "temporal_agg", "fuel_agg", "geo_agg", "fuel_cost_per_mmbtu", ], ] aggregates = aggregates[ (aggregates.sector_agg == "all_electric_power") & (aggregates.temporal_agg == "monthly") & (aggregates.fuel_agg.isin(["all_coal", "petroleum_liquids", "natural_gas"])) & (aggregates.fuel_cost_per_mmbtu.notnull()) ].drop(columns=["sector_agg", "temporal_agg"]) fuel_map = { # convert to fuel_type_code_pudl categories "all_coal": "coal", "natural_gas": "gas", "petroleum_liquids": "oil", } aggregates["fuel_type_code_pudl"] = aggregates["fuel_agg"].map(fuel_map) aggregates = aggregates.drop(columns="fuel_agg") col_rename_dict = { "geo_agg": "state", "fuel_cost_per_mmbtu": "bulk_agg_fuel_cost_per_mmbtu", } aggregates = aggregates.rename(columns=col_rename_dict) return aggregates