pudl.output.eia923 module

Functions for pulling EIA 923 data out of the PUDl DB.

pudl.output.eia923.boiler_fuel_eia923(pudl_engine, freq=None, start_date=None, end_date=None)[source]

Pull records from the boiler_fuel_eia923 table in a given data range.

Optionally, aggregate the records over some timescale – monthly, yearly, quarterly, etc. as well as by fuel type within a plant.

If the records are not being aggregated, all of the database fields are available. If they’re being aggregated, then we preserve the following fields. Per-unit values are re-calculated based on the aggregated totals. Totals are summed across whatever time range is being used, within a given plant and fuel type.

  • fuel_consumed_units (sum)

  • fuel_mmbtu_per_unit (weighted average)

  • total_heat_content_mmbtu (sum)

  • sulfur_content_pct (weighted average)

  • ash_content_pct (weighted average)

In addition, plant and utility names and IDs are pulled in from the EIA 860 tables.

Parameters

  • pudl_engine (sqlalchemy.engine.Engine) – SQLAlchemy connection engine for the PUDL DB.

  • freq (str) – a pandas timeseries offset alias. The original data is reported monthly, so the best time frequencies to use here are probably month start (freq=’MS’) and year start (freq=’YS’).

  • start_date (date-like) – date-like object, including a string of the form ‘YYYY-MM-DD’ which will be used to specify the date range of records to be pulled. Dates are inclusive.

  • end_date (date-like) – date-like object, including a string of the form ‘YYYY-MM-DD’ which will be used to specify the date range of records to be pulled. Dates are inclusive.

Returns

A DataFrame containing all records from the EIA 923 Boiler Fuel table.

Return type

pandas.DataFrame

pudl.output.eia923.fuel_receipts_costs_eia923(pudl_engine, freq=None, start_date=None, end_date=None, rolling=False)[source]

Pull records from fuel_receipts_costs_eia923 table in given date range.

Optionally, aggregate the records at a monthly or longer timescale, as well as by fuel type within a plant, by setting freq to something other than the default None value.

If the records are not being aggregated, then all of the fields found in the PUDL database are available. If they are being aggregated, then the following fields are preserved, and appropriately summed or re-calculated based on the specified aggregation. In both cases, new total values are calculated, for total fuel heat content and total fuel cost.

  • plant_id_eia

  • report_date

  • fuel_type_code_pudl (formerly energy_source_simple)

  • fuel_qty_units (sum)

  • fuel_cost_per_mmbtu (weighted average)

  • total_fuel_cost (sum)

  • total_heat_content_mmbtu (sum)

  • heat_content_mmbtu_per_unit (weighted average)

  • sulfur_content_pct (weighted average)

  • ash_content_pct (weighted average)

  • moisture_content_pct (weighted average)

  • mercury_content_ppm (weighted average)

  • chlorine_content_ppm (weighted average)

In addition, plant and utility names and IDs are pulled in from the EIA 860 tables.

Parameters

  • pudl_engine (sqlalchemy.engine.Engine) – SQLAlchemy connection engine for the PUDL DB.

  • freq (str) – a pandas timeseries offset alias. The original data is reported monthly, so the best time frequencies to use here are probably month start (freq=’MS’) and year start (freq=’YS’).

  • start_date (date-like) – date-like object, including a string of the form ‘YYYY-MM-DD’ which will be used to specify the date range of records to be pulled. Dates are inclusive.

  • end_date (date-like) – date-like object, including a string of the form ‘YYYY-MM-DD’ which will be used to specify the date range of records to be pulled. Dates are inclusive.

Returns

A DataFrame containing all records from the EIA 923 Fuel Receipts and Costs table.

Return type

pandas.DataFrame

pudl.output.eia923.generation_eia923(pudl_engine, freq=None, start_date=None, end_date=None)[source]

Pull records from the boiler_fuel_eia923 table in a given data range.

Parameters

  • pudl_engine (sqlalchemy.engine.Engine) – SQLAlchemy connection engine for the PUDL DB.

  • freq (str) – a pandas timeseries offset alias. The original data is reported monthly, so the best time frequencies to use here are probably month start (freq=’MS’) and year start (freq=’YS’).

  • start_date (date-like) – date-like object, including a string of the form ‘YYYY-MM-DD’ which will be used to specify the date range of records to be pulled. Dates are inclusive.

  • end_date (date-like) – date-like object, including a string of the form ‘YYYY-MM-DD’ which will be used to specify the date range of records to be pulled. Dates are inclusive.

Returns

A DataFrame containing all records from the EIA 923 Generation table.

Return type

pandas.DataFrame

pudl.output.eia923.generation_fuel_eia923(pudl_engine, freq=None, start_date=None, end_date=None)[source]

Pull records from the generation_fuel_eia923 table in given date range.

Optionally, aggregate the records over some timescale – monthly, yearly, quarterly, etc. as well as by fuel type within a plant.

If the records are not being aggregated, all of the database fields are available. If they’re being aggregated, then we preserve the following fields. Per-unit values are re-calculated based on the aggregated totals. Totals are summed across whatever time range is being used, within a given plant and fuel type.

  • plant_id_eia

  • report_date

  • fuel_type_code_pudl

  • fuel_consumed_units

  • fuel_consumed_for_electricity_units

  • fuel_mmbtu_per_unit

  • fuel_consumed_mmbtu

  • fuel_consumed_for_electricity_mmbtu

  • net_generation_mwh

In addition, plant and utility names and IDs are pulled in from the EIA 860 tables.

Parameters

  • pudl_engine (sqlalchemy.engine.Engine) – SQLAlchemy connection engine for the PUDL DB.

  • freq (str) – a pandas timeseries offset alias. The original data is reported monthly, so the best time frequencies to use here are probably month start (freq=’MS’) and year start (freq=’YS’).

  • start_date (date-like) – date-like object, including a string of the form ‘YYYY-MM-DD’ which will be used to specify the date range of records to be pulled. Dates are inclusive.

  • end_date (date-like) – date-like object, including a string of the form ‘YYYY-MM-DD’ which will be used to specify the date range of records to be pulled. Dates are inclusive.

Returns

A DataFrame containing all records from the EIA 923 Generation Fuel table.

Return type

pandas.DataFrame