Exemple #1
0
def get_matches_for_inventories(inventory_list=stewi_inventories):
    program_list = get_programs_for_inventory_list(inventory_list)
    facilitymatches = pd.read_csv(output_dir +
                                  'FacilityMatchList_forStEWI.csv',
                                  dtype={
                                      "REGISTRY_ID": "str",
                                      "PGM_SYS_ID": "str"
                                  })
    facilitymatches = filter_bridges_by_program_list(facilitymatches,
                                                     program_list)
    #Set program names back to inventory names
    FRS_to_inventory_pgm_acronymn = invert_inventory_to_FRS()
    facilitymatches['PGM_SYS_ACRNM'].replace(FRS_to_inventory_pgm_acronymn,
                                             inplace=True)
    return facilitymatches
Exemple #2
0
def write_NAICS_matches():
    file = glob.FRS_config['FRS_NAICS_file']
    file_path = glob.FRSpath + '/' + file

    # Check to see if file exists
    if not (os.path.exists(file_path)):
        glob.download_extract_FRS_combined_national(file)

    col_dict = {
        'REGISTRY_ID': 'str',
        'PGM_SYS_ACRNM': 'str',
        'NAICS_CODE': 'str',
        'PRIMARY_INDICATOR': 'str'
    }
    FRS_NAICS = glob.read_FRS_file(file, col_dict)

    # Filter this list for stewi
    # Programs of interest
    stewi_programs = glob.get_programs_for_inventory_list(
        glob.stewi_inventories)

    # Limit to EPA programs of interest for StEWI
    stewi_NAICS = glob.filter_by_program_list(FRS_NAICS, stewi_programs)

    # Drop duplicates
    stewi_NAICS = stewi_NAICS.drop_duplicates()

    # Replace program acronymn with inventory acronymn
    program_to_inventory = glob.invert_inventory_to_FRS()
    stewi_NAICS['PGM_SYS_ACRNM'] = stewi_NAICS['PGM_SYS_ACRNM'].replace(
        to_replace=program_to_inventory)

    # Rename columns to be consistent with standards
    stewi_NAICS = stewi_NAICS.rename(columns={
        'REGISTRY_ID': 'FRS_ID',
        'PGM_SYS_ACRNM': 'Source',
        'NAICS_CODE': 'NAICS'
    })

    glob.store_fm_file(stewi_NAICS, 'FRS_NAICSforStEWI', sources=[file])
                        header=0,
                        usecols=columns_to_keep,
                        dtype=dtype_dict)

#Load from pickle
#FRS_NAICS = pd.read_pickle('work/FRS_NAICS.pk')

#Filter this list for stewi
#Programs of interest
stewi_programs = get_programs_for_inventory_list(stewi_inventories)

#Limit to EPA programs of interest for StEWI
stewi_NAICS = filter_by_program_list(FRS_NAICS, stewi_programs)

#Drop duplicates
stewi_NAICS = stewi_NAICS.drop_duplicates()

#Replace program acronymn with inventory acronymn
program_to_inventory = invert_inventory_to_FRS()
stewi_NAICS['PGM_SYS_ACRNM'] = stewi_NAICS['PGM_SYS_ACRNM'].replace(
    to_replace=program_to_inventory)

#Rename columns to be consistent with standards
stewi_NAICS = stewi_NAICS.rename(columns={
    'REGISTRY_ID': 'FRS_ID',
    'PGM_SYS_ACRNM': 'Source',
    'NAICS_CODE': 'NAICS'
})

stewi_NAICS.to_csv(output_dir + 'FRS_NAICSforStEWI.csv', index=False)
def write_facility_matches():
    file = glob.FRS_config['FRS_bridge_file']
    file_path = glob.FRSpath + '/' + file

    # Check to see if file exists
    if not (os.path.exists(file_path)):
        glob.download_extract_FRS_combined_national(file)

    # Import FRS bridge which provides ID matches
    col_dict = {
        'REGISTRY_ID': "str",
        'PGM_SYS_ACRNM': "str",
        'PGM_SYS_ID': "str"
    }
    FRS_Bridges = glob.read_FRS_file(file, col_dict)

    # Programs of interest
    stewi_programs = glob.get_programs_for_inventory_list(
        glob.stewi_inventories)

    # Limit to EPA programs of interest for StEWI
    stewi_bridges = glob.filter_by_program_list(FRS_Bridges, stewi_programs)

    # Separate out eGRID and EIA-860 matches to identify EIA matches to
    # add to eGRID set
    eia_bridges = glob.filter_by_program_list(FRS_Bridges, ['EIA-860'])
    egrid_bridges = glob.filter_by_program_list(FRS_Bridges, ['EGRID'])

    # get a list of all FRS in each
    eia_unique_frs = set(list(pd.unique(eia_bridges['REGISTRY_ID'])))
    egrid_unique_frs = set(list(pd.unique(egrid_bridges['REGISTRY_ID'])))

    eia_not_in_egrid = eia_unique_frs - egrid_unique_frs
    eia_to_add = eia_bridges[eia_bridges['REGISTRY_ID'].isin(
        eia_not_in_egrid)].reset_index(drop=True)

    # Rename to EGRID and add the subset back at the top so that EIA-860 is
    # preferred to eGRID data for improved matching
    eia_to_add['PGM_SYS_ACRNM'] = 'EGRID'
    stewi_bridges = pd.concat([eia_to_add, stewi_bridges], ignore_index=True)
    stewi_bridges = stewi_bridges.drop_duplicates()
    stewi_bridges.reset_index(drop=True)

    # Replace program acronymn with inventory acronymn
    program_to_inventory = glob.invert_inventory_to_FRS()
    stewi_bridges['PGM_SYS_ACRNM'] = stewi_bridges['PGM_SYS_ACRNM'].replace(
        to_replace=program_to_inventory)

    stewi_bridges = stewi_bridges.rename(
        columns={
            'REGISTRY_ID': 'FRS_ID',
            'PGM_SYS_ACRNM': 'Source',
            'PGM_SYS_ID': 'FacilityID'
        })

    # Add in manual matches
    stewi_bridges = glob.add_manual_matches(stewi_bridges)

    # Add in smart matching here

    # Write matches to bridge
    glob.store_fm_file(stewi_bridges,
                       'FacilityMatchList_forStEWI',
                       sources=[file])