pudl.metadata.dfs

Static database tables.

Attributes

IMPUTATION_REASON_CODES

FERC_ACCOUNTS

FERC electric plant account IDs with associated row numbers and descriptions.

BALANCING_AUTHORITY_SUBREGIONS_EIA

EIA_SECTOR_AGGREGATE_ASSN

Association table describing the many-to-many relationships between plant sectors and

EIA_FUEL_AGGREGATE_ASSN

Association table describing the many-to-many relationships between fuel types and

POLITICAL_SUBDIVISIONS

Static attributes of sub-national political jurisdictions.

Classes

ImputationReasonCodes

Defines all reasons a value might be flagged for imputation.

Module Contents

class pudl.metadata.dfs.ImputationReasonCodes(*args, **kwds)[source]

Bases: enum.Enum

Defines all reasons a value might be flagged for imputation.

MISSING_VALUE = 'Indicates that reported value was already NULL.'[source]
ANOMALOUS_REGION = 'Indicates that value is surrounded by flagged values.'[source]
NEGATIVE_OR_ZERO = 'Indicates value is negative or zero.'[source]
IDENTICAL_RUN = 'Indicates value is part of an identical run of values, excluding first value in run.'[source]
GLOBAL_OUTLIER = 'Indicates value is greater or less than n times the global median.'[source]
GLOBAL_OUTLIER_NEIGHBOR = 'Indicates value neighbors global outliers.'[source]
LOCAL_OUTLIER_HIGH = 'Indicates value is a local outlier on the high end.'[source]
LOCAL_OUTLIER_LOW = 'Indicates value is a local outlier on the low end.'[source]
DOUBLE_DELTA = 'Indicates value is very different from neighbors on either side.'[source]
SINGLE_DELTA = 'Indicates value is significantly different from nearest unflagged value.'[source]
pudl.metadata.dfs.IMPUTATION_REASON_CODES[source]
pudl.metadata.dfs.FERC_ACCOUNTS: pandas.DataFrame[source]

FERC electric plant account IDs with associated row numbers and descriptions. From FERC Form 1 pages 204-207, Electric Plant in Service. Descriptions from: https://www.law.cornell.edu/cfr/text/18/part-101

pudl.metadata.dfs.BALANCING_AUTHORITY_SUBREGIONS_EIA: pandas.DataFrame[source]
pudl.metadata.dfs.EIA_SECTOR_AGGREGATE_ASSN = None[source]

Association table describing the many-to-many relationships between plant sectors and various aggregates in core_eia__yearly_fuel_receipts_costs_aggs.

pudl.metadata.dfs.EIA_FUEL_AGGREGATE_ASSN = None[source]

Association table describing the many-to-many relationships between fuel types and various aggregates in core_eia__yearly_fuel_receipts_costs_aggs.

Missing from these aggregates are all the “other” categories of gases: OG, BFG, SGP, SC, PG. But those gases combine for about 0.2% of total MMBTU of reported fuel receipts.

pudl.metadata.dfs.POLITICAL_SUBDIVISIONS: pandas.DataFrame = None[source]

Static attributes of sub-national political jurisdictions.

Note AK and PR have incomplete EPA CEMS data, and so are excluded from is_epacems_state: See https://github.com/catalyst-cooperative/pudl/issues/1264