pudl.validate module

PUDL data validation functions and test case specifications.

What defines a data validation?

• What data are we checking? * What table or output does it come from? * What selection criteria do we apply to that table or output?

• What are we checking it against? * Itself (helps validate that the tests themselves are working) * A processed version of itself (aggregation or derived values) * A hard-coded external standard (e.g. heat rates, fuel heat content)

pudl.validate.bf_eia923_agg = [{'title': 'Coal ash content', 'query': "fuel_type_code_pudl=='coal'", 'low_q': 0.2, 'mid_q': 0.7, 'hi_q': 0.95, 'data_col': 'ash_content_pct', 'weight_col': 'fuel_consumed_units'}, {'title': 'Coal sulfur content', 'query': "fuel_type_code_pudl=='coal'", 'low_q': False, 'mid_q': False, 'hi_q': False, 'data_col': 'sulfur_content_pct', 'weight_col': 'fuel_consumed_units'}, {'title': 'Coal heat content', 'query': "fuel_type_code_pudl=='coal'", 'low_q': 0.05, 'mid_q': 0.5, 'hi_q': 0.95, 'data_col': 'fuel_mmbtu_per_unit', 'weight_col': 'fuel_consumed_units'}, {'title': 'Petroleum heat content', 'query': "fuel_type_code_pudl=='oil'", 'low_q': 0.1, 'mid_q': 0.5, 'hi_q': 0.95, 'data_col': 'fuel_mmbtu_per_unit', 'weight_col': 'fuel_consumed_units'}, {'title': 'Gas heat content', 'query': "fuel_type_code_pudl=='gas'", 'low_q': 0.1, 'mid_q': 0.5, 'hi_q': 0.95, 'data_col': 'fuel_mmbtu_per_unit', 'weight_col': 'fuel_consumed_units'}]

EIA923 Boiler Fuel data validation against aggregated data.

pudl.validate.bf_eia923_coal_ash_content = [{'title': 'Bituminous coal ash content (middle)', 'query': "fuel_type_code=='BIT'", 'low_q': 0.5, 'low_bound': 6.0, 'hi_q': 0.5, 'hi_bound': 15.0, 'data_col': 'ash_content_pct', 'weight_col': 'fuel_consumed_units'}, {'title': 'Sub-bituminous coal ash content (middle)', 'query': "fuel_type_code=='SUB'", 'low_q': 0.5, 'low_bound': 4.5, 'hi_q': 0.5, 'hi_bound': 7.0, 'data_col': 'ash_content_pct', 'weight_col': 'fuel_consumed_units'}, {'title': 'Lignite ash content (middle)', 'query': "fuel_type_code=='LIG'", 'low_q': 0.5, 'low_bound': 7.0, 'hi_q': 0.5, 'hi_bound': 30.0, 'data_col': 'ash_content_pct', 'weight_col': 'fuel_consumed_units'}, {'title': 'All coal ash content (middle)', 'query': "fuel_type_code_pudl=='coal'", 'low_q': 0.5, 'low_bound': 4.0, 'hi_q': 0.5, 'hi_bound': 20.0, 'data_col': 'ash_content_pct', 'weight_col': 'fuel_consumed_units'}]

Valid coal ash content (%). Based on historical reporting in EIA 923.

pudl.validate.bf_eia923_coal_heat_content = [{'title': 'Bituminous coal heat content (middle)', 'query': "fuel_type_code=='BIT'", 'low_q': 0.5, 'low_bound': 20.5, 'hi_q': 0.5, 'hi_bound': 26.5, 'data_col': 'fuel_mmbtu_per_unit', 'weight_col': 'fuel_consumed_units'}, {'title': 'Bituminous coal heat content (tails)', 'query': "fuel_type_code=='BIT'", 'low_q': 0.05, 'low_bound': 17.0, 'hi_q': 0.95, 'hi_bound': 30.0, 'data_col': 'fuel_mmbtu_per_unit', 'weight_col': 'fuel_consumed_units'}, {'title': 'Sub-bituminous coal heat content (middle)', 'query': "fuel_type_code=='SUB'", 'low_q': 0.5, 'low_bound': 16.5, 'hi_q': 0.5, 'hi_bound': 18.0, 'data_col': 'fuel_mmbtu_per_unit', 'weight_col': 'fuel_consumed_units'}, {'title': 'Sub-bituminous coal heat content (tails)', 'query': "fuel_type_code=='SUB'", 'low_q': 0.05, 'low_bound': 15.0, 'hi_q': 0.95, 'hi_bound': 20.5, 'data_col': 'fuel_mmbtu_per_unit', 'weight_col': 'fuel_consumed_units'}, {'title': 'Lignite heat content (middle)', 'query': "fuel_type_code=='LIG'", 'low_q': 0.5, 'low_bound': 12.0, 'hi_q': 0.5, 'hi_bound': 14.0, 'data_col': 'fuel_mmbtu_per_unit', 'weight_col': 'fuel_consumed_units'}, {'title': 'Lignite heat content (tails)', 'query': "fuel_type_code=='LIG'", 'low_q': 0.05, 'low_bound': 10.0, 'hi_q': 0.95, 'hi_bound': 15.0, 'data_col': 'fuel_mmbtu_per_unit', 'weight_col': 'fuel_consumed_units'}, {'title': 'All coal heat content (middle)', 'query': "fuel_type_code_pudl=='coal'", 'low_q': 0.5, 'low_bound': 10.0, 'hi_q': 0.5, 'hi_bound': 30.0, 'data_col': 'fuel_mmbtu_per_unit', 'weight_col': 'fuel_consumed_units'}]

Valid coal (bituminous, sub-bituminous, and lignite) heat content values.

Based on IEA coal grade definitions: https://www.iea.org/statistics/resources/balancedefinitions/

pudl.validate.bf_eia923_coal_sulfur_content = [{'title': 'Coal sulfur content (tails)', 'query': "fuel_type_code_pudl=='coal'", 'hi_q': 0.95, 'hi_bound': 4.0, 'low_q': 0.05, 'low_bound': 0.15, 'data_col': 'sulfur_content_pct', 'weight_col': 'fuel_consumed_units'}]

Valid coal sulfur content values.

Based on historically reported values in EIA 923 Fuel Receipts and Costs.

pudl.validate.bf_eia923_gas_heat_content = [{'title': 'Natural Gas heat content (middle)', 'query': "fuel_type_code_pudl=='gas'", 'hi_q': 0.5, 'hi_bound': 1.036, 'low_q': 0.5, 'low_bound': 1.018, 'data_col': 'fuel_mmbtu_per_unit', 'weight_col': 'fuel_consumed_units'}, {'title': 'Natural Gas heat content (tails)', 'query': "fuel_type_code_pudl=='gas'", 'hi_q': 0.99, 'hi_bound': 1.15, 'low_q': 0.01, 'low_bound': 0.95, 'data_col': 'fuel_mmbtu_per_unit', 'weight_col': 'fuel_consumed_units'}]

Valid natural gas heat content values.

Based on historically reported values in EIA 923 Fuel Receipts and Costs. May fail because of a population of bad data around 0.1 mmbtu/unit. This appears to be an off-by-10x error, possibly due to reporting error in units used.

pudl.validate.bf_eia923_oil_heat_content = [{'title': 'Diesel Fuel Oil heat content (tails)', 'query': "fuel_type_code=='DFO'", 'low_q': 0.05, 'low_bound': 5.5, 'hi_q': 0.95, 'hi_bound': 6.0, 'data_col': 'fuel_mmbtu_per_unit', 'weight_col': 'fuel_consumed_units'}, {'title': 'Diesel Fuel Oil heat content (middle)', 'query': "fuel_type_code=='DFO'", 'low_q': 0.5, 'low_bound': 5.75, 'hi_q': 0.5, 'hi_bound': 5.85, 'data_col': 'fuel_mmbtu_per_unit', 'weight_col': 'fuel_consumed_units'}, {'title': 'All petroleum heat content (tails)', 'query': "fuel_type_code_pudl=='oil'", 'low_q': 0.05, 'low_bound': 5.0, 'hi_q': 0.95, 'hi_bound': 6.5, 'data_col': 'fuel_mmbtu_per_unit', 'weight_col': 'fuel_consumed_units'}]

Valid petroleum based fuel heat content values.

Based on historically reported values in EIA 923 Fuel Receipts and Costs.

pudl.validate.bf_eia923_self = [{'title': 'Bituminous coal ash content', 'query': "fuel_type_code=='BIT'", 'low_q': 0.05, 'mid_q': 0.25, 'hi_q': 0.95, 'data_col': 'ash_content_pct', 'weight_col': 'fuel_consumed_units'}, {'title': 'Subbituminous coal ash content', 'query': "fuel_type_code=='SUB'", 'low_q': 0.05, 'mid_q': 0.5, 'hi_q': 0.95, 'data_col': 'ash_content_pct', 'weight_col': 'fuel_consumed_units'}, {'title': 'Lignite coal ash content', 'query': "fuel_type_code=='LIG'", 'low_q': 0.05, 'mid_q': 0.5, 'hi_q': 0.95, 'data_col': 'ash_content_pct', 'weight_col': 'fuel_consumed_units'}, {'title': 'Bituminous coal heat content', 'query': "fuel_type_code=='BIT'", 'low_q': 0.07, 'mid_q': 0.5, 'hi_q': 0.98, 'data_col': 'fuel_mmbtu_per_unit', 'weight_col': 'fuel_consumed_units'}, {'title': 'Subbituminous coal heat content', 'query': "fuel_type_code=='SUB'", 'low_q': 0.05, 'mid_q': 0.5, 'hi_q': 0.9, 'data_col': 'fuel_mmbtu_per_unit', 'weight_col': 'fuel_consumed_units'}, {'title': 'Lignite heat content', 'query': "fuel_type_code=='LIG'", 'low_q': 0.1, 'mid_q': 0.5, 'hi_q': 0.95, 'data_col': 'fuel_mmbtu_per_unit', 'weight_col': 'fuel_consumed_units'}, {'title': 'Diesel Fuel Oil heat content', 'query': "fuel_type_code=='DFO'", 'low_q': 0.05, 'mid_q': 0.5, 'hi_q': 0.95, 'data_col': 'fuel_mmbtu_per_unit', 'weight_col': 'fuel_consumed_units'}]

EIA923 Boiler Fuel data validation against itself.

pudl.validate.bounds_histogram(df, data_col, weight_col, query, low_q, hi_q, low_bound, hi_bound, title='')

Plot a weighted histogram showing acceptable bounds/actual values.

pudl.validate.frc_eia923_agg = [{'title': 'Coal ash content', 'query': "fuel_type_code_pudl=='coal'", 'low_q': 0.2, 'mid_q': 0.7, 'hi_q': 0.95, 'data_col': 'ash_content_pct', 'weight_col': 'fuel_qty_units'}, {'title': 'Coal chlorine content', 'query': "fuel_type_code_pudl=='coal'", 'low_q': False, 'mid_q': False, 'hi_q': False, 'data_col': 'chlorine_content_ppm', 'weight_col': 'fuel_qty_units'}, {'title': 'Coal fuel costs', 'query': "fuel_type_code_pudl=='coal'", 'low_q': 0.05, 'mid_q': 0.5, 'hi_q': 0.95, 'data_col': 'fuel_cost_per_mmbtu', 'weight_col': 'fuel_qty_units'}, {'title': 'Coal sulfur content', 'query': "fuel_type_code_pudl=='coal'", 'low_q': False, 'mid_q': False, 'hi_q': False, 'data_col': 'sulfur_content_pct', 'weight_col': 'fuel_qty_units'}, {'title': 'Gas heat content', 'query': "fuel_type_code_pudl=='gas'", 'low_q': 0.1, 'mid_q': 0.5, 'hi_q': 0.95, 'data_col': 'heat_content_mmbtu_per_unit', 'weight_col': 'fuel_qty_units'}, {'title': 'Gas fuel costs', 'query': "fuel_type_code_pudl=='gas'", 'low_q': False, 'mid_q': 0.5, 'hi_q': False, 'data_col': 'fuel_cost_per_mmbtu', 'weight_col': 'fuel_qty_units'}, {'title': 'Petroleum fuel cost', 'query': "fuel_type_code_pudl=='oil'", 'low_q': False, 'mid_q': 0.5, 'hi_q': False, 'data_col': 'fuel_cost_per_mmbtu', 'weight_col': 'fuel_qty_units'}, {'title': 'Petroleum heat content', 'query': "fuel_type_code_pudl=='oil'", 'low_q': 0.1, 'mid_q': 0.5, 'hi_q': 0.95, 'data_col': 'heat_content_mmbtu_per_unit', 'weight_col': 'fuel_qty_units'}]

EIA923 fuel receipts & costs data validation against aggregated data.

pudl.validate.frc_eia923_coal_ash_content = [{'title': 'Bituminous coal ash content (middle)', 'query': "energy_source_code=='BIT'", 'low_q': 0.5, 'low_bound': 6.0, 'hi_q': 0.5, 'hi_bound': 15.0, 'data_col': 'ash_content_pct', 'weight_col': 'fuel_qty_units'}, {'title': 'Sub-bituminous coal ash content (middle)', 'query': "energy_source_code=='SUB'", 'low_q': 0.5, 'low_bound': 4.5, 'hi_q': 0.5, 'hi_bound': 7.0, 'data_col': 'ash_content_pct', 'weight_col': 'fuel_qty_units'}, {'title': 'Lignite ash content (middle)', 'query': "energy_source_code=='LIG'", 'low_q': 0.5, 'low_bound': 7.0, 'hi_q': 0.5, 'hi_bound': 30.0, 'data_col': 'ash_content_pct', 'weight_col': 'fuel_qty_units'}, {'title': 'All coal ash content (middle)', 'query': "fuel_type_code_pudl=='coal'", 'low_q': 0.5, 'low_bound': 4.0, 'hi_q': 0.5, 'hi_bound': 20.0, 'data_col': 'ash_content_pct', 'weight_col': 'fuel_qty_units'}]

Valid coal ash content (%). Based on historical reporting in EIA 923.

pudl.validate.frc_eia923_coal_heat_content = [{'title': 'Bituminous coal heat content (middle)', 'query': "energy_source_code=='BIT'", 'low_q': 0.5, 'low_bound': 20.5, 'hi_q': 0.5, 'hi_bound': 26.5, 'data_col': 'heat_content_mmbtu_per_unit', 'weight_col': 'fuel_qty_units'}, {'title': 'Bituminous coal heat content (tails)', 'query': "energy_source_code=='BIT'", 'low_q': 0.05, 'low_bound': 17.0, 'hi_q': 0.95, 'hi_bound': 30.0, 'data_col': 'heat_content_mmbtu_per_unit', 'weight_col': 'fuel_qty_units'}, {'title': 'Sub-bituminous coal heat content (middle)', 'query': "energy_source_code=='SUB'", 'low_q': 0.5, 'low_bound': 16.5, 'hi_q': 0.5, 'hi_bound': 18.0, 'data_col': 'heat_content_mmbtu_per_unit', 'weight_col': 'fuel_qty_units'}, {'title': 'Sub-bituminous coal heat content (tails)', 'query': "energy_source_code=='SUB'", 'low_q': 0.05, 'low_bound': 15.0, 'hi_q': 0.95, 'hi_bound': 20.5, 'data_col': 'heat_content_mmbtu_per_unit', 'weight_col': 'fuel_qty_units'}, {'title': 'Lignite heat content (middle)', 'query': "energy_source_code=='LIG'", 'low_q': 0.5, 'low_bound': 12.0, 'hi_q': 0.5, 'hi_bound': 14.0, 'data_col': 'heat_content_mmbtu_per_unit', 'weight_col': 'fuel_qty_units'}, {'title': 'Lignite heat content (tails)', 'query': "energy_source_code=='LIG'", 'low_q': 0.05, 'low_bound': 10.0, 'hi_q': 0.95, 'hi_bound': 15.0, 'data_col': 'heat_content_mmbtu_per_unit', 'weight_col': 'fuel_qty_units'}, {'title': 'All coal heat content (middle)', 'query': "fuel_type_code_pudl=='coal'", 'low_q': 0.5, 'low_bound': 10.0, 'hi_q': 0.5, 'hi_bound': 30.0, 'data_col': 'heat_content_mmbtu_per_unit', 'weight_col': 'fuel_qty_units'}]

Valid coal (bituminous, sub-bituminous, and lignite) heat content values.

Based on IEA coal grade definitions: https://www.iea.org/statistics/resources/balancedefinitions/

pudl.validate.frc_eia923_coal_mercury_content = [{'title': 'Coal mercury content (upper tail)', 'query': "fuel_type_code_pudl=='coal'", 'low_q': False, 'low_bound': False, 'hi_q': 0.95, 'hi_bound': 1.0, 'data_col': 'mercury_content_ppm', 'weight_col': 'fuel_qty_units'}, {'title': 'Coal mercury content (middle)', 'query': "fuel_type_code_pudl=='coal'", 'low_q': 0.5, 'low_bound': 0.04, 'hi_q': 0.5, 'hi_bound': 0.19, 'data_col': 'mercury_content_ppm', 'weight_col': 'fuel_qty_units'}]

Valid coal mercury content limits.

Based on USGS FS095-01: https://pubs.usgs.gov/fs/fs095-01/fs095-01.html Upper tail may fail because of a population of extremely high mercury content coal (9.0ppm) which is likely a reporting error.

pudl.validate.frc_eia923_coal_moisture_content = [{'title': 'Bituminous coal moisture content (middle)', 'query': "energy_source_code=='BIT'", 'low_q': 0.5, 'low_bound': 5.0, 'hi_q': 0.5, 'hi_bound': 16.5, 'data_col': 'moisture_content_pct', 'weight_col': 'fuel_qty_units'}, {'title': 'Sub-bituminous coal moisture content (middle)', 'query': "energy_source_code=='SUB'", 'low_q': 0.5, 'low_bound': 15.0, 'hi_q': 0.5, 'hi_bound': 32.5, 'data_col': 'moisture_content_pct', 'weight_col': 'fuel_qty_units'}, {'title': 'Lignite moisture content (middle)', 'query': "energy_source_code=='LIG'", 'low_q': 0.5, 'low_bound': 25.0, 'hi_q': 0.5, 'hi_bound': 45.0, 'data_col': 'moisture_content_pct', 'weight_col': 'fuel_qty_units'}, {'title': 'All coal moisture content (middle)', 'query': "fuel_type_code_pudl=='coal'", 'low_q': 0.5, 'low_bound': 5.0, 'hi_q': 0.5, 'hi_bound': 40.0, 'data_col': 'moisture_content_pct', 'weight_col': 'fuel_qty_units'}]

Valid coal moisture content, based on historical EIA 923 reporting.

pudl.validate.frc_eia923_coal_sulfur_content = [{'title': 'Coal sulfur content (tails)', 'query': "fuel_type_code_pudl=='coal'", 'hi_q': 0.95, 'hi_bound': 4.0, 'low_q': 0.05, 'low_bound': 0.15, 'data_col': 'sulfur_content_pct', 'weight_col': 'fuel_qty_units'}]

Valid coal sulfur content values.

Based on historically reported values in EIA 923 Fuel Receipts and Costs.

pudl.validate.frc_eia923_gas_heat_content = [{'title': 'Natural Gas heat content (middle)', 'query': "fuel_type_code_pudl=='gas'", 'hi_q': 0.5, 'hi_bound': 1.036, 'low_q': 0.5, 'low_bound': 1.018, 'data_col': 'heat_content_mmbtu_per_unit', 'weight_col': 'fuel_qty_units'}, {'title': 'Natural Gas heat content (tails)', 'query': "fuel_type_code_pudl=='gas'", 'hi_q': 0.99, 'hi_bound': 1.15, 'low_q': 0.01, 'low_bound': 0.95, 'data_col': 'heat_content_mmbtu_per_unit', 'weight_col': 'fuel_qty_units'}]

Valid natural gas heat content values.

Based on historically reported values in EIA 923 Fuel Receipts and Costs. May fail because of a population of bad data around 0.1 mmbtu/unit. This appears to be an off-by-10x error, possibly due to reporting error in units used.

pudl.validate.frc_eia923_oil_heat_content = [{'title': 'Diesel Fuel Oil heat content (tails)', 'query': "energy_source_code=='DFO'", 'low_q': 0.05, 'low_bound': 5.5, 'hi_q': 0.95, 'hi_bound': 6.0, 'data_col': 'heat_content_mmbtu_per_unit', 'weight_col': 'fuel_qty_units'}, {'title': 'Diesel Fuel Oil heat content (middle)', 'query': "energy_source_code=='DFO'", 'low_q': 0.5, 'low_bound': 5.75, 'hi_q': 0.5, 'hi_bound': 5.85, 'data_col': 'heat_content_mmbtu_per_unit', 'weight_col': 'fuel_qty_units'}, {'title': 'All petroleum heat content (tails)', 'query': "fuel_type_code_pudl=='oil'", 'low_q': 0.05, 'low_bound': 5.0, 'hi_q': 0.95, 'hi_bound': 6.5, 'data_col': 'heat_content_mmbtu_per_unit', 'weight_col': 'fuel_qty_units'}]

Valid petroleum based fuel heat content values.

Based on historically reported values in EIA 923 Fuel Receipts and Costs.

pudl.validate.frc_eia923_self = [{'title': 'Bituminous coal ash content', 'query': "energy_source_code=='BIT'", 'low_q': 0.05, 'mid_q': 0.25, 'hi_q': 0.95, 'data_col': 'ash_content_pct', 'weight_col': 'fuel_qty_units'}, {'title': 'Subbituminous coal ash content', 'query': "energy_source_code=='SUB'", 'low_q': 0.05, 'mid_q': 0.5, 'hi_q': 0.95, 'data_col': 'ash_content_pct', 'weight_col': 'fuel_qty_units'}, {'title': 'Lignite coal ash content', 'query': "energy_source_code=='LIG'", 'low_q': 0.05, 'mid_q': 0.5, 'hi_q': 0.95, 'data_col': 'ash_content_pct', 'weight_col': 'fuel_qty_units'}, {'title': 'Bituminous coal heat content', 'query': "energy_source_code=='BIT'", 'low_q': 0.07, 'mid_q': 0.5, 'hi_q': 0.98, 'data_col': 'heat_content_mmbtu_per_unit', 'weight_col': 'fuel_qty_units'}, {'title': 'Subbituminous coal heat content', 'query': "energy_source_code=='SUB'", 'low_q': 0.05, 'mid_q': 0.5, 'hi_q': 0.9, 'data_col': 'heat_content_mmbtu_per_unit', 'weight_col': 'fuel_qty_units'}, {'title': 'Lignite heat content', 'query': "energy_source_code=='LIG'", 'low_q': 0.1, 'mid_q': 0.5, 'hi_q': 0.95, 'data_col': 'heat_content_mmbtu_per_unit', 'weight_col': 'fuel_qty_units'}, {'title': 'Diesel Fuel Oil heat content', 'query': "energy_source_code=='DFO'", 'low_q': 0.05, 'mid_q': 0.5, 'hi_q': 0.95, 'data_col': 'heat_content_mmbtu_per_unit', 'weight_col': 'fuel_qty_units'}, {'title': 'Bituminous coal moisture content', 'query': "energy_source_code=='BIT'", 'low_q': 0.05, 'mid_q': 0.5, 'hi_q': 0.95, 'data_col': 'moisture_content_pct', 'weight_col': 'fuel_qty_units'}, {'title': 'Subbituminous coal moisture content', 'query': "energy_source_code=='SUB'", 'low_q': 0.05, 'mid_q': 0.5, 'hi_q': 0.95, 'data_col': 'moisture_content_pct', 'weight_col': 'fuel_qty_units'}, {'title': 'Lignite moisture content', 'query': "energy_source_code=='LIG'", 'low_q': 0.05, 'mid_q': 0.5, 'hi_q': 1.0, 'data_col': 'moisture_content_pct', 'weight_col': 'fuel_qty_units'}]

EIA923 fuel receipts & costs data validation against itself.

pudl.validate.gf_eia923_agg = [{'title': 'Coal heat content', 'query': "fuel_type_code_pudl=='coal'", 'low_q': 0.05, 'mid_q': 0.5, 'hi_q': 0.95, 'data_col': 'fuel_mmbtu_per_unit', 'weight_col': 'fuel_consumed_units'}, {'title': 'Petroleum heat content', 'query': "fuel_type_code_pudl=='oil'", 'low_q': 0.1, 'mid_q': 0.5, 'hi_q': 0.95, 'data_col': 'fuel_mmbtu_per_unit', 'weight_col': 'fuel_consumed_units'}, {'title': 'Gas heat content', 'query': "fuel_type_code_pudl=='gas'", 'low_q': 0.1, 'mid_q': 0.5, 'hi_q': 0.95, 'data_col': 'fuel_mmbtu_per_unit', 'weight_col': 'fuel_consumed_units'}]

EIA923 Boiler Fuel data validation against aggregated data.

pudl.validate.gf_eia923_coal_heat_content = [{'title': 'All coal heat content (middle)', 'query': "fuel_type_code_pudl=='coal'", 'low_q': 0.5, 'low_bound': 10.0, 'hi_q': 0.5, 'hi_bound': 30.0, 'data_col': 'fuel_mmbtu_per_unit', 'weight_col': 'fuel_consumed_units'}]

Valid coal heat content values (all coal types).

The Generation Fuel table does not break different coal types out separately, so we can only test the validity of the entire suite of coal records.

Based on IEA coal grade definitions: https://www.iea.org/statistics/resources/balancedefinitions/

pudl.validate.gf_eia923_gas_heat_content = [{'title': 'Natural Gas heat content (middle)', 'query': "fuel_type_code_pudl=='gas'", 'hi_q': 0.5, 'hi_bound': 1.036, 'low_q': 0.5, 'low_bound': 1.018, 'data_col': 'fuel_mmbtu_per_unit', 'weight_col': 'fuel_consumed_units'}, {'title': 'Natural Gas heat content (tails)', 'query': "fuel_type_code_pudl=='gas'", 'hi_q': 0.99, 'hi_bound': 1.15, 'low_q': 0.01, 'low_bound': 0.95, 'data_col': 'fuel_mmbtu_per_unit', 'weight_col': 'fuel_consumed_units'}]

Valid natural gas heat content values.

Based on historically reported values in EIA 923 Fuel Receipts and Costs. May fail because of a population of bad data around 0.1 mmbtu/unit. This appears to be an off-by-10x error, possibly due to reporting error in units used.

pudl.validate.gf_eia923_oil_heat_content = [{'title': 'Diesel Fuel Oil heat content (tails)', 'query': "fuel_type_code_aer=='DFO'", 'low_q': 0.05, 'low_bound': 5.5, 'hi_q': 0.95, 'hi_bound': 6.0, 'data_col': 'fuel_mmbtu_per_unit', 'weight_col': 'fuel_consumed_units'}, {'title': 'Diesel Fuel Oil heat content (middle)', 'query': "fuel_type_code_aer=='DFO'", 'low_q': 0.5, 'low_bound': 5.75, 'hi_q': 0.5, 'hi_bound': 5.85, 'data_col': 'fuel_mmbtu_per_unit', 'weight_col': 'fuel_consumed_units'}, {'title': 'All petroleum heat content (tails)', 'query': "fuel_type_code_pudl=='oil'", 'low_q': 0.05, 'low_bound': 5.0, 'hi_q': 0.95, 'hi_bound': 6.5, 'data_col': 'fuel_mmbtu_per_unit', 'weight_col': 'fuel_consumed_units'}]

Valid petroleum based fuel heat content values.

Based on historically reported values in EIA 923 Fuel Receipts and Costs.

pudl.validate.historical_distribution(df, data_col, weight_col, quantile)

Calculate a historical distribution of weighted values of a column.

In order to know what a “reasonable” value of a particular column is in the pudl data, we can use this function to see what the value in that column has been in each of the years of data we have on hand, and a given quantile. This population of values can then be used to set boundaries on acceptable data distributions in the aggregated and processed data.

Parameters

• df (pandas.DataFrame) – a dataframe containing historical data, with a column named either report_date or report_year.

• data_col (string) – Label of the column containing the data of interest.

• weight_col (string) – Label of the column containing the weights to be used in scaling the data.

Returns

The weighted quantiles of data, for each of the years found in the historical data of df.

Return type

list

pudl.validate.historical_histogram(orig_df, test_df, data_col, weight_col, query='', low_q=0.05, mid_q=0.5, hi_q=0.95, low_bound=None, hi_bound=None, title='')

Weighted histogram comparing distribution with historical subsamples.

pudl.validate.mcoe_coal_capacity_factor = [{'title': 'Coal Capacity Factor (middle)', 'query': "fuel_type_code_pudl=='coal' and capacity_factor!=0.0", 'low_q': 0.6, 'low_bound': 0.5, 'hi_q': 0.6, 'hi_bound': 0.9, 'data_col': 'capacity_factor', 'weight_col': 'capacity_mw'}, {'title': 'Coal Capacity Factor (tails)', 'query': "fuel_type_code_pudl=='coal' and capacity_factor!=0.0", 'low_q': 0.1, 'low_bound': 0.04, 'hi_q': 0.95, 'hi_bound': 0.95, 'data_col': 'capacity_factor', 'weight_col': 'capacity_mw'}]

Static constraints on coal fired generator capacity factors.

pudl.validate.mcoe_coal_heat_rate = [{'title': 'Coal Unit Heat Rates (middle)', 'query': "fuel_type_code_pudl=='coal'", 'low_q': 0.5, 'low_bound': 10.0, 'hi_q': 0.5, 'hi_bound': 11.0, 'data_col': 'heat_rate_mmbtu_mwh', 'weight_col': 'net_generation_mwh'}, {'title': 'Coal Unit Heat Rates (tails)', 'query': "fuel_type_code_pudl=='coal'", 'low_q': 0.05, 'low_bound': 9.0, 'hi_q': 0.95, 'hi_bound': 12.5, 'data_col': 'heat_rate_mmbtu_mwh', 'weight_col': 'net_generation_mwh'}]

Static constraints on coal fired generator heat rates.

pudl.validate.mcoe_fuel_cost_per_mmbtu = [{'title': 'Coal Fuel Costs (middle)', 'query': "fuel_type_code_pudl=='coal'", 'low_q': 0.5, 'low_bound': 1.5, 'hi_q': 0.5, 'hi_bound': 3.0, 'data_col': 'fuel_cost_per_mmbtu', 'weight_col': 'total_mmbtu'}, {'title': 'Coal Fuel Costs (tails)', 'query': "fuel_type_code_pudl=='coal'", 'low_q': 0.05, 'low_bound': 1.25, 'hi_q': 0.95, 'hi_bound': 4.5, 'data_col': 'fuel_cost_per_mmbtu', 'weight_col': 'total_mmbtu'}, {'title': 'Natural Gas Fuel Costs (middle, 2015+)', 'query': "fuel_type_code_pudl=='gas' and report_date>='2015-01-01'", 'low_q': 0.5, 'low_bound': 2.0, 'hi_q': 0.5, 'hi_bound': 4.0, 'data_col': 'fuel_cost_per_mmbtu', 'weight_col': 'total_mmbtu'}, {'title': 'Natural Gas Fuel Costs (tails, 2015+)', 'query': "fuel_type_code_pudl=='gas' and report_date>='2015-01-01'", 'low_q': 0.05, 'low_bound': 1.75, 'hi_q': 0.95, 'hi_bound': 6.0, 'data_col': 'fuel_cost_per_mmbtu', 'weight_col': 'total_mmbtu'}]

Static constraints on fuel costs per mmbtu of fuel consumed.

pudl.validate.mcoe_fuel_cost_per_mwh = [{'title': 'Coal Fuel Costs (middle)', 'query': "fuel_type_code_pudl=='coal'", 'low_q': 0.5, 'low_bound': 18.0, 'hi_q': 0.5, 'hi_bound': 27.0, 'data_col': 'fuel_cost_per_mwh', 'weight_col': 'net_generation_mwh'}, {'title': 'Coal Fuel Costs (tails)', 'query': "fuel_type_code_pudl=='coal'", 'low_q': 0.05, 'low_bound': 10.0, 'hi_q': 0.95, 'hi_bound': 50.0, 'data_col': 'fuel_cost_per_mwh', 'weight_col': 'net_generation_mwh'}, {'title': 'Natural Gas Fuel Costs (middle, 2015+)', 'query': "fuel_type_code_pudl=='gas' and report_date>='2015-01-01'", 'low_q': 0.5, 'low_bound': 20.0, 'hi_q': 0.5, 'hi_bound': 30.0, 'data_col': 'fuel_cost_per_mwh', 'weight_col': 'net_generation_mwh'}, {'title': 'Natural Gas Fuel Costs (tails, 2015+)', 'query': "fuel_type_code_pudl=='gas' and report_date>='2015-01-01'", 'low_q': 0.05, 'low_bound': 10.0, 'hi_q': 0.95, 'hi_bound': 50.0, 'data_col': 'fuel_cost_per_mwh', 'weight_col': 'net_generation_mwh'}]

Static constraints on fuel costs per MWh net generation.

pudl.validate.mcoe_gas_capacity_factor = [{'title': 'Natural Gas Capacity Factor (middle, 2015+)', 'query': "fuel_type_code_pudl=='gas' and report_date>='2015-01-01' and capacity_factor!=0.0", 'low_q': 0.65, 'low_bound': 0.4, 'hi_q': 0.65, 'hi_bound': 0.7, 'data_col': 'capacity_factor', 'weight_col': 'capacity_mw'}, {'title': 'Natural Gas Capacity Factor (tails, 2015+)', 'query': "fuel_type_code_pudl=='gas' and report_date>='2015-01-01' and capacity_factor!=0.0", 'low_q': 0.15, 'low_bound': 0.01, 'hi_q': 0.95, 'hi_bound': 0.95, 'data_col': 'capacity_factor', 'weight_col': 'capacity_mw'}]

Static constraints on natural gas generator capacity factors.

pudl.validate.mcoe_gas_heat_rate = [{'title': 'Natural Gas Unit Heat Rates (middle, 2015+)', 'query': "fuel_type_code_pudl=='gas' and report_date>='2015-01-01'", 'low_q': 0.5, 'low_bound': 7.0, 'hi_q': 0.5, 'hi_bound': 7.5, 'data_col': 'heat_rate_mmbtu_mwh', 'weight_col': 'net_generation_mwh'}, {'title': 'Natural Gas Unit Heat Rates (tails, 2015+)', 'query': "fuel_type_code_pudl=='gas' and report_date>='2015-01-01'", 'low_q': 0.05, 'low_bound': 6.5, 'hi_q': 0.95, 'hi_bound': 13.0, 'data_col': 'heat_rate_mmbtu_mwh', 'weight_col': 'net_generation_mwh'}]

Static constraints on gas fired generator heat rates.

pudl.validate.plot_vs_agg(orig_df, agg_df, validation_cases)

Validate a bunch of distributions against aggregated versions.

pudl.validate.plot_vs_bounds(df, validation_cases)

Run through a data validation based on absolute bounds.

pudl.validate.plot_vs_self(df, validation_cases)

Validate a bunch of distributions against themselves.

pudl.validate.vs_bounds(df, data_col, weight_col, query='', title='', low_q=False, low_bound=False, hi_q=False, hi_bound=False)

Test a distribution against an upper bound, lower bound, or both.

pudl.validate.vs_historical(orig_df, test_df, data_col, weight_col, query='', low_q=0.05, mid_q=0.5, hi_q=0.95, title='')

Validate aggregated distributions against original data.

pudl.validate.vs_self(df, data_col, weight_col, query='', title='', low_q=0.05, mid_q=0.5, hi_q=0.95)

Test a distribution against its own historical range.

This is a special case of the pudl.validate.vs_historical function, in which both the orig_df and test_df are the same. Mostly it helps ensure that the test itself is valid for the given distribution.

pudl.validate.weighted_quantile(data, weights, quantile)

Calculate the weighted quantile of a Series or DataFrame column.

This function allows us to take two columns from a pandas.DataFrame one of which contains an observed value (data) like heat content per unit of fuel, and the other of which (weights) contains a quantity like quantity of fuel delivered which should be used to scale the importance of the observed value in an overall distribution, and calculate the values that the scaled distribution will have at various quantiles.

Parameters

• data (pandas.Series) – A series containing numeric data.

• weights (pandas.series) – Weights to use in scaling the data. Must have the same length as data.

• quantile (float) – A number between 0 and 1, representing the quantile at which we want to find the value of the weighted data.

Returns

the value in the weighted data corresponding to the given quantile. If there are no values in the data, return numpy.na.

Return type

float