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The dataset generation failed because of a cast error
Error code: DatasetGenerationCastError
Exception: DatasetGenerationCastError
Message: An error occurred while generating the dataset
All the data files must have the same columns, but at some point there are 285 new columns ({'SCIENGRLP', 'MARHW', 'FSSP', 'FMILPP', 'POWSP', 'FHINS2P', 'FSCHLP', 'PWGTP76', 'PWGTP24', 'PWGTP56', 'FSSIP', 'FDREMP', 'FHINS3C', 'FHINS3P', 'CIT', 'FPERNP', 'OC', 'PUBCOV', 'FJWDP', 'PWGTP65', 'FMIGP', 'PWGTP52', 'ANC', 'PWGTP40', 'FCITWP', 'ST', 'FHICOVP', 'GCR', 'PWGTP44', 'FANCP', 'FHINS4P', 'MIGSP', 'NOP', 'FSEMP', 'FDISP', 'FFODP', 'PERNP', 'PWGTP20', 'RETP', 'PWGTP66', 'FWKLP', 'PWGTP8', 'ANC1P', 'JWRIP', 'FJWTRP', 'FMARHDP', 'PWGTP36', 'FOD2P', 'NAICSP', 'PWGTP31', 'PWGTP5', 'RACSOR', 'FSCHGP', 'MLPFG', 'PWGTP69', 'PWGTP33', 'PWGTP16', 'NWLK', 'FINTP', 'FPRIVCOVP', 'PWGTP14', 'MAR', 'WRK', 'GCM', 'PWGTP50', 'PWGTP25', 'PWGTP35', 'PWGTP70', 'SSP', 'FPOBP', 'DRIVESP', 'FHINS5P', 'GCL', 'PWGTP41', 'ESR', 'PWGTP18', 'FMARHYP', 'FSCHP', 'FHINS5C', 'PINCP', 'FDEYEP', 'SCH', 'HINS5', 'MLPCD', 'PWGTP27', 'PWGTP60', 'ESP', 'PWGTP34', 'RACBLK', 'PWGTP42', 'RELP', 'PWGTP37', 'FMARHTP', 'PWGTP15', 'WAGP', 'POBP', 'FPOWSP', 'PWGTP68', 'MSP', 'FRACP', 'PWGTP55', 'VPS', 'PWGTP45', 'MIL', 'PWGTP29', 'RAC2P', 'PWGTP59', 'LANX', 'MLPH', 'PWGTP9', 'PWGTP46', 'FMARHWP', 'PWGTP62', 'WKHP', 'PWGTP22', 'ANC2P', 'SERIALNO', 'FCOWP', 'PWGTP23', 'HINS1', 'RAC3P', 'PWGTP6', 'MLPK', 'FGCRP', 'FLANP', 'PWGTP4', 'FDRATXP', 'SPORDER', 'NWLA', 'ADJINC', 'PWGTP10', 'FFERP', 'FJWRIP', 'PWGTP53', 'FWKHP', 'PWGTP19', 'FDEARP', 'AGEP', 'PAP', 'SCIENGP', 'PWGTP77', 'FHINS4C', 'FENGP', 'ENG', 'DEYE', 'JWMNP', 'FOIP', 'NATIVITY', 'MARHM', 'PWGTP11', 'PWGTP12', 'FGCMP', 'FDDRSP', 'RACPI', 'DECADE', 'HINS4', 'FOCCP', 'RAC1P', 'PWGTP30', 'HISP', 'SCHL', 'FDRATP', 'SEX', 'PWGTP26', 'FRELP', 'PWGTP', 'RACAIAN', 'WAOB', 'PWGTP7', 'PAOC', 'PWGTP72', 'MIG', 'FHINS1P', 'FAGEP', 'PWGTP21', 'JWDP', 'FESRP', 'NWRE', 'SOCP', 'PWGTP47', 'FPUBCOVP', 'MLPI', 'PWGTP61', 'FGCLP', 'PWGTP43', 'RACWHT', 'FER', 'FHISP', 'SCHG', 'SFN', 'RC', 'DRATX', 'PWGTP54', 'WKL', 'FOD1P', 'LANP', 'PWGTP63', 'DDRS', 'PWGTP73', 'PWGTP13', 'SFR', 'PWGTP67', 'SEMP', 'RACNUM', 'PWGTP78', 'FHINS7P', 'PWGTP71', 'FPINCP', 'JWAP', 'INTP', 'MLPB', 'HINS6', 'JWTR', 'PWGTP1', 'PWGTP51', 'PWGTP2', 'PWGTP58', 'PWGTP79', 'INDP', 'MLPE', 'FSEXP', 'PWGTP3', 'COW', 'FWKWP', 'FDPHYP', 'FPAP', 'PWGTP48', 'DIVISION', 'OCCP', 'FDOUTP', 'OIP', 'PWGTP75', 'MLPA', 'FMILSP', 'PWGTP28', 'DIS', 'PWGTP17', 'PWGTP39', 'PUMA', 'PWGTP57', 'QTRBIR', 'PWGTP38', 'DRAT', 'MARHD', 'DOUT', 'PWGTP64', 'RACNH', 'FCITP', 'FLANXP', 'FWAGP', 'MIGPUMA', 'HINS7', 'FJWMNP', 'CITWP', 'FMIGSP', 'FMARP', 'FMARHMP', 'REGION', 'PRIVCOV', 'PWGTP80', 'HINS3', 'FHINS6P', 'MLPJ', 'RACASN', 'MARHYP', 'FINDP', 'NWAB', 'DREM', 'NWAV', 'FYOEP', 'PWGTP49', 'HINS2', 'DPHY', 'POVPIP', 'PWGTP74', 'HICOV', 'MARHT', 'WKW', 'YOEP', 'DEAR', 'SSIP', 'POWPUMA', 'PWGTP32', 'FRETP', 'FWRKP'}) and 6 missing columns ({'__index_level_1__', '1', '__index_level_0__', 'C', 'Record Type', 'NAME'}).
This happened while the csv dataset builder was generating data using
hf://datasets/davidboetius/ACSIncome-2018-1-Year/psam_p01.csv (at revision 2c42fc79349462e98c7c8290a5f5e679a0ccd201)
Please either edit the data files to have matching columns, or separate them into different configurations (see docs at https://hf.co/docs/hub/datasets-manual-configuration#multiple-configurations)
Traceback: Traceback (most recent call last):
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1871, in _prepare_split_single
writer.write_table(table)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/arrow_writer.py", line 643, in write_table
pa_table = table_cast(pa_table, self._schema)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2293, in table_cast
return cast_table_to_schema(table, schema)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2241, in cast_table_to_schema
raise CastError(
datasets.table.CastError: Couldn't cast
RT: string
SERIALNO: string
DIVISION: int64
SPORDER: int64
PUMA: int64
REGION: int64
ST: int64
ADJINC: int64
PWGTP: int64
AGEP: int64
CIT: int64
CITWP: double
COW: double
DDRS: double
DEAR: int64
DEYE: int64
DOUT: double
DPHY: double
DRAT: double
DRATX: double
DREM: double
ENG: double
FER: double
GCL: double
GCM: double
GCR: double
HINS1: int64
HINS2: int64
HINS3: int64
HINS4: int64
HINS5: int64
HINS6: int64
HINS7: int64
INTP: double
JWMNP: double
JWRIP: double
JWTR: double
LANX: double
MAR: int64
MARHD: double
MARHM: double
MARHT: double
MARHW: double
MARHYP: double
MIG: double
MIL: double
MLPA: double
MLPB: double
MLPCD: double
MLPE: double
MLPFG: double
MLPH: double
MLPI: double
MLPJ: double
MLPK: double
NWAB: double
NWAV: double
NWLA: double
NWLK: double
NWRE: double
OIP: double
PAP: double
RELP: int64
RETP: double
SCH: double
SCHG: double
SCHL: double
SEMP: double
SEX: int64
SSIP: double
SSP: double
WAGP: double
WKHP: double
WKL: double
WKW: double
WRK: double
YOEP: double
ANC: int64
ANC1P: int64
ANC2P: int64
DECADE: double
DIS: int64
DRIVESP: double
ESP: double
ESR: double
FOD1P: double
FOD2P: double
HICOV: int64
HISP: int64
INDP: double
JWAP: double
JWDP: double
LANP: double
MIGPUMA: double
MIGSP: double
MSP: double
NAICSP: string
NATIVITY: int64
NOP: double
OC: double
OCCP: double
PAOC: double
PERNP: double
PINCP: double
POBP: int64
POVPIP: double
POWPUMA: double
POWSP: double
PRIVCOV: int64
PUBCOV: int64
QTRBIR: int64
RAC1P: int64
RAC2P: int64
RAC3P: int64
RACAIAN: i
...
P: int64
FRELP: int64
FRETP: int64
FSCHGP: int64
FSCHLP: int64
FSCHP: int64
FSEMP: int64
FSEXP: int64
FSSIP: int64
FSSP: int64
FWAGP: int64
FWKHP: int64
FWKLP: int64
FWKWP: int64
FWRKP: int64
FYOEP: int64
PWGTP1: int64
PWGTP2: int64
PWGTP3: int64
PWGTP4: int64
PWGTP5: int64
PWGTP6: int64
PWGTP7: int64
PWGTP8: int64
PWGTP9: int64
PWGTP10: int64
PWGTP11: int64
PWGTP12: int64
PWGTP13: int64
PWGTP14: int64
PWGTP15: int64
PWGTP16: int64
PWGTP17: int64
PWGTP18: int64
PWGTP19: int64
PWGTP20: int64
PWGTP21: int64
PWGTP22: int64
PWGTP23: int64
PWGTP24: int64
PWGTP25: int64
PWGTP26: int64
PWGTP27: int64
PWGTP28: int64
PWGTP29: int64
PWGTP30: int64
PWGTP31: int64
PWGTP32: int64
PWGTP33: int64
PWGTP34: int64
PWGTP35: int64
PWGTP36: int64
PWGTP37: int64
PWGTP38: int64
PWGTP39: int64
PWGTP40: int64
PWGTP41: int64
PWGTP42: int64
PWGTP43: int64
PWGTP44: int64
PWGTP45: int64
PWGTP46: int64
PWGTP47: int64
PWGTP48: int64
PWGTP49: int64
PWGTP50: int64
PWGTP51: int64
PWGTP52: int64
PWGTP53: int64
PWGTP54: int64
PWGTP55: int64
PWGTP56: int64
PWGTP57: int64
PWGTP58: int64
PWGTP59: int64
PWGTP60: int64
PWGTP61: int64
PWGTP62: int64
PWGTP63: int64
PWGTP64: int64
PWGTP65: int64
PWGTP66: int64
PWGTP67: int64
PWGTP68: int64
PWGTP69: int64
PWGTP70: int64
PWGTP71: int64
PWGTP72: int64
PWGTP73: int64
PWGTP74: int64
PWGTP75: int64
PWGTP76: int64
PWGTP77: int64
PWGTP78: int64
PWGTP79: int64
PWGTP80: int64
-- schema metadata --
pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 31497
to
{'NAME': Value(dtype='string', id=None), 'RT': Value(dtype='int64', id=None), 'C': Value(dtype='string', id=None), '1': Value(dtype='string', id=None), 'Record Type': Value(dtype='string', id=None), '__index_level_0__': Value(dtype='string', id=None), '__index_level_1__': Value(dtype='string', id=None)}
because column names don't match
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1433, in compute_config_parquet_and_info_response
parquet_operations = convert_to_parquet(builder)
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1050, in convert_to_parquet
builder.download_and_prepare(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 925, in download_and_prepare
self._download_and_prepare(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1001, in _download_and_prepare
self._prepare_split(split_generator, **prepare_split_kwargs)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1742, in _prepare_split
for job_id, done, content in self._prepare_split_single(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1873, in _prepare_split_single
raise DatasetGenerationCastError.from_cast_error(
datasets.exceptions.DatasetGenerationCastError: An error occurred while generating the dataset
All the data files must have the same columns, but at some point there are 285 new columns ({'SCIENGRLP', 'MARHW', 'FSSP', 'FMILPP', 'POWSP', 'FHINS2P', 'FSCHLP', 'PWGTP76', 'PWGTP24', 'PWGTP56', 'FSSIP', 'FDREMP', 'FHINS3C', 'FHINS3P', 'CIT', 'FPERNP', 'OC', 'PUBCOV', 'FJWDP', 'PWGTP65', 'FMIGP', 'PWGTP52', 'ANC', 'PWGTP40', 'FCITWP', 'ST', 'FHICOVP', 'GCR', 'PWGTP44', 'FANCP', 'FHINS4P', 'MIGSP', 'NOP', 'FSEMP', 'FDISP', 'FFODP', 'PERNP', 'PWGTP20', 'RETP', 'PWGTP66', 'FWKLP', 'PWGTP8', 'ANC1P', 'JWRIP', 'FJWTRP', 'FMARHDP', 'PWGTP36', 'FOD2P', 'NAICSP', 'PWGTP31', 'PWGTP5', 'RACSOR', 'FSCHGP', 'MLPFG', 'PWGTP69', 'PWGTP33', 'PWGTP16', 'NWLK', 'FINTP', 'FPRIVCOVP', 'PWGTP14', 'MAR', 'WRK', 'GCM', 'PWGTP50', 'PWGTP25', 'PWGTP35', 'PWGTP70', 'SSP', 'FPOBP', 'DRIVESP', 'FHINS5P', 'GCL', 'PWGTP41', 'ESR', 'PWGTP18', 'FMARHYP', 'FSCHP', 'FHINS5C', 'PINCP', 'FDEYEP', 'SCH', 'HINS5', 'MLPCD', 'PWGTP27', 'PWGTP60', 'ESP', 'PWGTP34', 'RACBLK', 'PWGTP42', 'RELP', 'PWGTP37', 'FMARHTP', 'PWGTP15', 'WAGP', 'POBP', 'FPOWSP', 'PWGTP68', 'MSP', 'FRACP', 'PWGTP55', 'VPS', 'PWGTP45', 'MIL', 'PWGTP29', 'RAC2P', 'PWGTP59', 'LANX', 'MLPH', 'PWGTP9', 'PWGTP46', 'FMARHWP', 'PWGTP62', 'WKHP', 'PWGTP22', 'ANC2P', 'SERIALNO', 'FCOWP', 'PWGTP23', 'HINS1', 'RAC3P', 'PWGTP6', 'MLPK', 'FGCRP', 'FLANP', 'PWGTP4', 'FDRATXP', 'SPORDER', 'NWLA', 'ADJINC', 'PWGTP10', 'FFERP', 'FJWRIP', 'PWGTP53', 'FWKHP', 'PWGTP19', 'FDEARP', 'AGEP', 'PAP', 'SCIENGP', 'PWGTP77', 'FHINS4C', 'FENGP', 'ENG', 'DEYE', 'JWMNP', 'FOIP', 'NATIVITY', 'MARHM', 'PWGTP11', 'PWGTP12', 'FGCMP', 'FDDRSP', 'RACPI', 'DECADE', 'HINS4', 'FOCCP', 'RAC1P', 'PWGTP30', 'HISP', 'SCHL', 'FDRATP', 'SEX', 'PWGTP26', 'FRELP', 'PWGTP', 'RACAIAN', 'WAOB', 'PWGTP7', 'PAOC', 'PWGTP72', 'MIG', 'FHINS1P', 'FAGEP', 'PWGTP21', 'JWDP', 'FESRP', 'NWRE', 'SOCP', 'PWGTP47', 'FPUBCOVP', 'MLPI', 'PWGTP61', 'FGCLP', 'PWGTP43', 'RACWHT', 'FER', 'FHISP', 'SCHG', 'SFN', 'RC', 'DRATX', 'PWGTP54', 'WKL', 'FOD1P', 'LANP', 'PWGTP63', 'DDRS', 'PWGTP73', 'PWGTP13', 'SFR', 'PWGTP67', 'SEMP', 'RACNUM', 'PWGTP78', 'FHINS7P', 'PWGTP71', 'FPINCP', 'JWAP', 'INTP', 'MLPB', 'HINS6', 'JWTR', 'PWGTP1', 'PWGTP51', 'PWGTP2', 'PWGTP58', 'PWGTP79', 'INDP', 'MLPE', 'FSEXP', 'PWGTP3', 'COW', 'FWKWP', 'FDPHYP', 'FPAP', 'PWGTP48', 'DIVISION', 'OCCP', 'FDOUTP', 'OIP', 'PWGTP75', 'MLPA', 'FMILSP', 'PWGTP28', 'DIS', 'PWGTP17', 'PWGTP39', 'PUMA', 'PWGTP57', 'QTRBIR', 'PWGTP38', 'DRAT', 'MARHD', 'DOUT', 'PWGTP64', 'RACNH', 'FCITP', 'FLANXP', 'FWAGP', 'MIGPUMA', 'HINS7', 'FJWMNP', 'CITWP', 'FMIGSP', 'FMARP', 'FMARHMP', 'REGION', 'PRIVCOV', 'PWGTP80', 'HINS3', 'FHINS6P', 'MLPJ', 'RACASN', 'MARHYP', 'FINDP', 'NWAB', 'DREM', 'NWAV', 'FYOEP', 'PWGTP49', 'HINS2', 'DPHY', 'POVPIP', 'PWGTP74', 'HICOV', 'MARHT', 'WKW', 'YOEP', 'DEAR', 'SSIP', 'POWPUMA', 'PWGTP32', 'FRETP', 'FWRKP'}) and 6 missing columns ({'__index_level_1__', '1', '__index_level_0__', 'C', 'Record Type', 'NAME'}).
This happened while the csv dataset builder was generating data using
hf://datasets/davidboetius/ACSIncome-2018-1-Year/psam_p01.csv (at revision 2c42fc79349462e98c7c8290a5f5e679a0ccd201)
Please either edit the data files to have matching columns, or separate them into different configurations (see docs at https://hf.co/docs/hub/datasets-manual-configuration#multiple-configurations)Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
NAME
string | RT
int64 | C
string | 1
string | Record Type
string | __index_level_0__
string | __index_level_1__
string |
|---|---|---|---|---|---|---|
C | 1 | H | H | Housing Record or Group Quarters Unit | VAL | RT |
C | 1 | P | P | Person Record | VAL | RT |
C | 13 | Housing unit/GQ person serial number | null | null | NAME | SERIALNO |
C | 13 | 2018GQ0000001 | 2018GQ9999999 | GQ Unique identifier | VAL | SERIALNO |
C | 13 | 2018HU0000001 | 2018HU9999999 | HU Unique identifier | VAL | SERIALNO |
C | 1 | Division code based on 2010 Census definitions | null | null | NAME | DIVISION |
C | 1 | 0 | 0 | Puerto Rico | VAL | DIVISION |
C | 1 | 1 | 1 | New England (Northeast region) | VAL | DIVISION |
C | 1 | 2 | 2 | Middle Atlantic (Northeast region) | VAL | DIVISION |
C | 1 | 3 | 3 | East North Central (Midwest region) | VAL | DIVISION |
C | 1 | 4 | 4 | West North Central (Midwest region) | VAL | DIVISION |
C | 1 | 5 | 5 | South Atlantic (South region) | VAL | DIVISION |
C | 1 | 6 | 6 | East South Central (South region) | VAL | DIVISION |
C | 1 | 7 | 7 | West South Central (South Region) | VAL | DIVISION |
C | 1 | 8 | 8 | Mountain (West region) | VAL | DIVISION |
C | 1 | 9 | 9 | Pacific (West region) | VAL | DIVISION |
C | 5 | Public use microdata area code (PUMA) based on 2010 Census definition (areas with population of 100,000 or more, use with ST for unique code) | null | null | NAME | PUMA |
C | 5 | 00100 | 70301 | Public use microdata area codes | VAL | PUMA |
C | 1 | Region code based on 2010 Census definitions | null | null | NAME | REGION |
C | 1 | 1 | 1 | Northeast | VAL | REGION |
C | 1 | 2 | 2 | Midwest | VAL | REGION |
C | 1 | 3 | 3 | South | VAL | REGION |
C | 1 | 4 | 4 | West | VAL | REGION |
C | 1 | 9 | 9 | Puerto Rico | VAL | REGION |
C | 2 | State Code based on 2010 Census definitions | null | null | NAME | ST |
C | 2 | 01 | 01 | Alabama/AL | VAL | ST |
C | 2 | 02 | 02 | Alaska/AK | VAL | ST |
C | 2 | 04 | 04 | Arizona/AZ | VAL | ST |
C | 2 | 05 | 05 | Arkansas/AR | VAL | ST |
C | 2 | 06 | 06 | California/CA | VAL | ST |
C | 2 | 08 | 08 | Colorado/CO | VAL | ST |
C | 2 | 09 | 09 | Connecticut/CT | VAL | ST |
C | 2 | 10 | 10 | Delaware/DE | VAL | ST |
C | 2 | 11 | 11 | District of Columbia/DC | VAL | ST |
C | 2 | 12 | 12 | Florida/FL | VAL | ST |
C | 2 | 13 | 13 | Georgia/GA | VAL | ST |
C | 2 | 15 | 15 | Hawaii/HI | VAL | ST |
C | 2 | 16 | 16 | Idaho/ID | VAL | ST |
C | 2 | 17 | 17 | Illinois/IL | VAL | ST |
C | 2 | 18 | 18 | Indiana/IN | VAL | ST |
C | 2 | 19 | 19 | Iowa/IA | VAL | ST |
C | 2 | 20 | 20 | Kansas/KS | VAL | ST |
C | 2 | 21 | 21 | Kentucky/KY | VAL | ST |
C | 2 | 22 | 22 | Louisiana/LA | VAL | ST |
C | 2 | 23 | 23 | Maine/ME | VAL | ST |
C | 2 | 24 | 24 | Maryland/MD | VAL | ST |
C | 2 | 25 | 25 | Massachusetts/MA | VAL | ST |
C | 2 | 26 | 26 | Michigan/MI | VAL | ST |
C | 2 | 27 | 27 | Minnesota/MN | VAL | ST |
C | 2 | 28 | 28 | Mississippi/MS | VAL | ST |
C | 2 | 29 | 29 | Missouri/MO | VAL | ST |
C | 2 | 30 | 30 | Montana/MT | VAL | ST |
C | 2 | 31 | 31 | Nebraska/NE | VAL | ST |
C | 2 | 32 | 32 | Nevada/NV | VAL | ST |
C | 2 | 33 | 33 | New Hampshire/NH | VAL | ST |
C | 2 | 34 | 34 | New Jersey/NJ | VAL | ST |
C | 2 | 35 | 35 | New Mexico/NM | VAL | ST |
C | 2 | 36 | 36 | New York/NY | VAL | ST |
C | 2 | 37 | 37 | North Carolina/NC | VAL | ST |
C | 2 | 38 | 38 | North Dakota/ND | VAL | ST |
C | 2 | 39 | 39 | Ohio/OH | VAL | ST |
C | 2 | 40 | 40 | Oklahoma/OK | VAL | ST |
C | 2 | 41 | 41 | Oregon/OR | VAL | ST |
C | 2 | 42 | 42 | Pennsylvania/PA | VAL | ST |
C | 2 | 44 | 44 | Rhode Island/RI | VAL | ST |
C | 2 | 45 | 45 | South Carolina/SC | VAL | ST |
C | 2 | 46 | 46 | South Dakota/SD | VAL | ST |
C | 2 | 47 | 47 | Tennessee/TN | VAL | ST |
C | 2 | 48 | 48 | Texas/TX | VAL | ST |
C | 2 | 49 | 49 | Utah/UT | VAL | ST |
C | 2 | 50 | 50 | Vermont/VT | VAL | ST |
C | 2 | 51 | 51 | Virginia/VA | VAL | ST |
C | 2 | 53 | 53 | Washington/WA | VAL | ST |
C | 2 | 54 | 54 | West Virginia/WV | VAL | ST |
C | 2 | 55 | 55 | Wisconsin/WI | VAL | ST |
C | 2 | 56 | 56 | Wyoming/WY | VAL | ST |
C | 2 | 72 | 72 | Puerto Rico/PR | VAL | ST |
C | 7 | Adjustment factor for housing dollar amounts (6 implied decimal places) | null | null | NAME | ADJHSG |
C | 7 | 1000000 | 1000000 | 2018 factor (1.000000) | VAL | ADJHSG |
C | 7 | Adjustment factor for income and earnings dollar amounts (6 implied decimal places) | null | null | NAME | ADJINC |
C | 7 | 1013097 | 1013097 | 2018 factor (1.013097) | VAL | ADJINC |
N | 5 | Housing Unit Weight | null | null | NAME | WGTP |
N | 5 | 0 | 0 | Group quarters place holder record | VAL | WGTP |
N | 5 | 1 | 9999 | Integer weight of housing unit | VAL | WGTP |
N | 2 | Number of persons in this household | null | null | NAME | NP |
N | 2 | 0 | 0 | Vacant unit | VAL | NP |
N | 2 | 1 | 1 | One person in household or any person in group quarters | VAL | NP |
N | 2 | 2 | 20 | Number of persons in household | VAL | NP |
C | 1 | Type of unit | null | null | NAME | TYPE |
C | 1 | 1 | 1 | Housing unit | VAL | TYPE |
C | 1 | 2 | 2 | Institutional group quarters | VAL | TYPE |
C | 1 | 3 | 3 | Noninstitutional group quarters | VAL | TYPE |
C | 1 | Access to the Internet | null | null | NAME | ACCESS |
C | 1 | b | b | N/A (GQ/vacant) | VAL | ACCESS |
C | 1 | 1 | 1 | Yes, by paying a cell phone company or Internet service provider | VAL | ACCESS |
C | 1 | 2 | 2 | Yes, without paying a cell phone company or Internet service provider | VAL | ACCESS |
C | 1 | 3 | 3 | No access to the Internet at this house, apartment, or mobile home | VAL | ACCESS |
C | 1 | Lot size | null | null | NAME | ACR |
C | 1 | b | b | N/A (GQ/not a one-family house or mobile home) | VAL | ACR |
C | 1 | 1 | 1 | House on less than one acre | VAL | ACR |
End of preview.
ACSIncome 2018 1-Year
This is the US Census Income data underlying the default folktables dataset.
The original data source went offline in 2025.
This data was uploaded for use with the MiniACSIncome dataset.
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