Datasets:

---

nataliecastro

/

climate-bills

like 0

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 21699 new columns ({'sensitivities', 'grave', 'huge', 'academies', 'incubator', 'furnace', 'postponed', 'membersno', 'interestswith', 'modificationsection', 'defeat', 'terrorismthe', 'conceal', 'assessmentnotwithstanding', 'nontarget', 'keating', 'prohibitionbeginning', 'assessmentsthe', 'logbooksthe', 'wastea', 'overtime', 'quarters', 'spacethe', 'coir', 'banked', 'election', 'carey', 'offering', 'postabatement', 'prospectus', 'adjustmentsthe', 'creditors', 'mandated', 'options', 'caregivers', 'acquisitions', 'society', 'nugent', 'husband', 'reconcile', 'murphy', 'repeatable', 'boilersnot', 'lagoon', 'alternatea', 'planan', 'reasons', 'dispensing', 'debriefing', 'registerif', 'solidified', 'inclusionseach', 'disclosuresubject', 'respondent', 'sealant', 'exceeding', 'fimbriata', 'reliability', 'natives', 'arbitration', 'classificationa', 'apprentices', 'viconforming', 'maintenanceeach', 'studiessection', 'operationsin', 'harmful', 'signal', 'percentageif', 'baker', 'capped', 'methodsit', 'americasubsection', 'tradition', 'projectseach', 'phased', 'impactssection', 'mercurythe', 'damper', 'demanded', 'swallow', 'references', 'northup', 'simultaneous', 'occupies', 'harbors', 'prime', 'beekeeping', 'individuals', 'fields', 'half', 'productthe', 'termsall', 'vistudies', 'dioxidethe', 'unacceptably', 'reproductive', 'building', 'disrepair', 'movie', 'childrenas', 'waterground', 'childrenan', 'luminaire', 'save', 'auspices', 'stanton', 'noticeswith', 'similarly', 'implementationin', 'objectives', 'de
...
ng', 'reexported', 'wiling', 'auchincloss', 'workings', 'hubsthe', 'listadditional', 'broadest', 'surveythe', 'tucson', 'minimumthe', 'tsunamis', 'statementseach', 'reposein', 'chloride', 'claimthe', 'credibly', 'navigate', 'stress', 'objection', 'washwater', 'olefins', 'controversy', 'governorsa', 'roe', 'reregistration', 'iteratively', 'magistrate', 'improvementinformation', 'generalall', 'borders', 'subcontracts', 'assigning', 'gone', 'posed', 'seekers', 'worksa', 'unbiased', 'subsidiesto', 'filter', 'resourcesan', 'trade', 'summit', 'watershedthe', 'agencywith', 'trichloroethylene', 'impairing', 'voteeach', 'chavez', 'letterthe', 'formation', 'underestimates', 'generalprior', 'repose', 'programthere', 'backed', 'areawhen', 'aquacultural', 'orderan', 'theoretical', 'helped', 'inclusionfor', 'ruleat', 'preexport', 'exceptionsubsection', 'obsolete', 'wishes', 'spills', 'wells', 'predisaster', 'highwater', 'boosting', 'validate', 'subrogated', 'sandy', 'zoos', 'vchild', 'generalwith', 'desire', 'markets', 'generic', 'sablan', 'conditionin', 'deforestation', 'exact', 'nonrecyclable', 'enormous', 'carnahan', 'activitiesoutreach', 'photosynthetic', 'reassert', 'nondetectable', 'repurpose', 'responsiblethe', 'incidence', 'commemorates', 'contemporary', 'jana', 'principally', 'generalized', 'extractive', 'downturn', 'warned', 'enjoinment', 'incoming', 'originated', 'vauthorization', 'ombudsmansection', 'fat', 'custodians', 'conspicuously', 'curbing', 'registries', 'populationsin'}) and 19 missing columns ({'Bill Text', 'Date Proposed', 'Congress', 'Amends Amendment', 'Latest Action Date', 'Date Offered', 'Sponsor', 'Amends Bill', 'API URL', 'Date of Introduction', 'Legislation Number', 'Bill Number', 'Congress Number', 'Date Submitted', 'Title', 'Latest Action', 'Number of Cosponsors', 'Bill Title (XML)', 'URL_y'}).

This happened while the csv dataset builder was generating data using

hf://datasets/nataliecastro/climate-bills/Bills - Count Vectorizer.csv (at revision a2b872c45926383c9079e70ee1e203a6bf554a41)

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 1870, in _prepare_split_single
                  writer.write_table(table)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/arrow_writer.py", line 622, 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 2292, in table_cast
                  return cast_table_to_schema(table, schema)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2240, in cast_table_to_schema
                  raise CastError(
              datasets.table.CastError: Couldn't cast
              Unnamed: 0: int64
              Bill Type: string
              Sponser Affiliation: string
              Sponser State: string
              Committees: string
              ___: int64
              ____: int64
              ______: int64
              ________: int64
              aa: int64
              aaa: int64
              aarhus: int64
              ab: int64
              abandon: int64
              abandoned: int64
              abandoning: int64
              abandonment: int64
              abandonthe: int64
              abate: int64
              abatement: int64
              abating: int64
              abbreviated: int64
              abercrombie: int64
              abeyance: int64
              abide: int64
              abilities: int64
              ability: int64
              abiotic: int64
              able: int64
              ables: int64
              abnormal: int64
              aboard: int64
              abode: int64
              aboveground: int64
              abraham: int64
              abridged: int64
              abroad: int64
              abrogate: int64
              abrogated: int64
              abrogates: int64
              abrogating: int64
              abrupt: int64
              absence: int64
              absent: int64
              absolute: int64
              absolutely: int64
              absorb: int64
              absorbed: int64
              absorbing: int64
              absorbs: int64
              absorption: int64
              absorptive: int64
              abstracts: int64
              abuilding: int64
              abundance: int64
              abundant: int64
              abuse: int64
              abused: int64
              abuses: int64
              abut: int64
              abutting: int64
              academia: int64
              academic: int64
              academics: int64
              academies: int64
              academiesthe: int64
              academy: int64
              academythe: int64
              accelerate: int64
              accelerated: int64
              accelerates: int64
              accelerating: int64
              acceleration: int64
              accept: int64
              acceptable: int64
              acceptance: int64
              acceptancethe: int64
              accepted: int64
              accepting: int64
              acceptor: int64
              accepts: int64
              access: int64
              accessall: int64
              accessed: int64
              accessibility: int64
              accessibilityeach: int64
              accessibilitythe: int64
              accessible: int64
              accessif: int64
              accessin: int64
              accessing: int64
              access
              ...
              dler: int64
              wynn: int64
              wyoming: int64
              xeriscaping: int64
              xi: int64
              xii: int64
              xiii: int64
              xiv: int64
              xix: int64
              xli: int64
              xother: int64
              xv: int64
              xvi: int64
              xvii: int64
              xviii: int64
              xx: int64
              xxi: int64
              xxiienergy: int64
              xxvi: int64
              xxxiv: int64
              xylene: int64
              xylenol: int64
              yakama: int64
              yakym: int64
              yard: int64
              yards: int64
              yarmuth: int64
              yearapplicable: int64
              yearemission: int64
              yearfor: int64
              yearin: int64
              yearling: int64
              yearly: int64
              yearnumber: int64
              yearone: int64
              yearpercent: int64
              yearpercentage: int64
              yearprior: int64
              yearreduction: int64
              yearrequired: int64
              yearsat: int64
              yearsfor: int64
              yearsin: int64
              yearssection: int64
              yearsubparagraphs: int64
              yearswith: int64
              yearthe: int64
              yearthree: int64
              yellow: int64
              yellowstone: int64
              yemen: int64
              yf: int64
              yield: int64
              yields: int64
              yl: int64
              yoder: int64
              yogurt: int64
              yoho: int64
              york: int64
              yosemite: int64
              young: int64
              younger: int64
              youth: int64
              youtha: int64
              youths: int64
              youththe: int64
              ysidro: int64
              yucca: int64
              yutu: int64
              yy: int64
              za: int64
              zaragoza: int64
              ze: int64
              zealand: int64
              zebra: int64
              zeldin: int64
              zero: int64
              zeroing: int64
              zevs: int64
              zika: int64
              zinc: int64
              zinke: int64
              zip: int64
              zoe: int64
              zone: int64
              zonea: int64
              zoned: int64
              zones: int64
              zonesnotwithstanding: int64
              zonethe: int64
              zoning: int64
              zoo: int64
              zoological: int64
              zoonotic: int64
              zooplankton: int64
              zoos: int64
              zquez: int64
              ºc: int64
              -- schema metadata --
              pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 2515820
              to
              {'Unnamed: 0': Value(dtype='int64', id=None), 'API URL': Value(dtype='string', id=None), 'Congress Number': Value(dtype='int64', id=None), 'Bill Type': Value(dtype='string', id=None), 'Bill Number': Value(dtype='int64', id=None), 'Legislation Number': Value(dtype='string', id=None), 'URL_y': Value(dtype='string', id=None), 'Congress': Value(dtype='string', id=None), 'Title': Value(dtype='string', id=None), 'Sponsor': Value(dtype='string', id=None), 'Date of Introduction': Value(dtype='string', id=None), 'Committees': Value(dtype='string', id=None), 'Latest Action': Value(dtype='string', id=None), 'Latest Action Date': Value(dtype='string', id=None), 'Number of Cosponsors': Value(dtype='int64', id=None), 'Amends Bill': Value(dtype='float64', id=None), 'Date Offered': Value(dtype='float64', id=None), 'Date Submitted': Value(dtype='float64', id=None), 'Date Proposed': Value(dtype='float64', id=None), 'Amends Amendment': Value(dtype='float64', id=None), 'Sponser Affiliation': Value(dtype='string', id=None), 'Sponser State': Value(dtype='string', id=None), 'Bill Title (XML)': Value(dtype='string', id=None), 'Bill Text': 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 1420, 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 1052, in convert_to_parquet
                  builder.download_and_prepare(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 924, in download_and_prepare
                  self._download_and_prepare(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1000, 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 1741, 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 1872, 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 21699 new columns ({'sensitivities', 'grave', 'huge', 'academies', 'incubator', 'furnace', 'postponed', 'membersno', 'interestswith', 'modificationsection', 'defeat', 'terrorismthe', 'conceal', 'assessmentnotwithstanding', 'nontarget', 'keating', 'prohibitionbeginning', 'assessmentsthe', 'logbooksthe', 'wastea', 'overtime', 'quarters', 'spacethe', 'coir', 'banked', 'election', 'carey', 'offering', 'postabatement', 'prospectus', 'adjustmentsthe', 'creditors', 'mandated', 'options', 'caregivers', 'acquisitions', 'society', 'nugent', 'husband', 'reconcile', 'murphy', 'repeatable', 'boilersnot', 'lagoon', 'alternatea', 'planan', 'reasons', 'dispensing', 'debriefing', 'registerif', 'solidified', 'inclusionseach', 'disclosuresubject', 'respondent', 'sealant', 'exceeding', 'fimbriata', 'reliability', 'natives', 'arbitration', 'classificationa', 'apprentices', 'viconforming', 'maintenanceeach', 'studiessection', 'operationsin', 'harmful', 'signal', 'percentageif', 'baker', 'capped', 'methodsit', 'americasubsection', 'tradition', 'projectseach', 'phased', 'impactssection', 'mercurythe', 'damper', 'demanded', 'swallow', 'references', 'northup', 'simultaneous', 'occupies', 'harbors', 'prime', 'beekeeping', 'individuals', 'fields', 'half', 'productthe', 'termsall', 'vistudies', 'dioxidethe', 'unacceptably', 'reproductive', 'building', 'disrepair', 'movie', 'childrenas', 'waterground', 'childrenan', 'luminaire', 'save', 'auspices', 'stanton', 'noticeswith', 'similarly', 'implementationin', 'objectives', 'de
              ...
              ng', 'reexported', 'wiling', 'auchincloss', 'workings', 'hubsthe', 'listadditional', 'broadest', 'surveythe', 'tucson', 'minimumthe', 'tsunamis', 'statementseach', 'reposein', 'chloride', 'claimthe', 'credibly', 'navigate', 'stress', 'objection', 'washwater', 'olefins', 'controversy', 'governorsa', 'roe', 'reregistration', 'iteratively', 'magistrate', 'improvementinformation', 'generalall', 'borders', 'subcontracts', 'assigning', 'gone', 'posed', 'seekers', 'worksa', 'unbiased', 'subsidiesto', 'filter', 'resourcesan', 'trade', 'summit', 'watershedthe', 'agencywith', 'trichloroethylene', 'impairing', 'voteeach', 'chavez', 'letterthe', 'formation', 'underestimates', 'generalprior', 'repose', 'programthere', 'backed', 'areawhen', 'aquacultural', 'orderan', 'theoretical', 'helped', 'inclusionfor', 'ruleat', 'preexport', 'exceptionsubsection', 'obsolete', 'wishes', 'spills', 'wells', 'predisaster', 'highwater', 'boosting', 'validate', 'subrogated', 'sandy', 'zoos', 'vchild', 'generalwith', 'desire', 'markets', 'generic', 'sablan', 'conditionin', 'deforestation', 'exact', 'nonrecyclable', 'enormous', 'carnahan', 'activitiesoutreach', 'photosynthetic', 'reassert', 'nondetectable', 'repurpose', 'responsiblethe', 'incidence', 'commemorates', 'contemporary', 'jana', 'principally', 'generalized', 'extractive', 'downturn', 'warned', 'enjoinment', 'incoming', 'originated', 'vauthorization', 'ombudsmansection', 'fat', 'custodians', 'conspicuously', 'curbing', 'registries', 'populationsin'}) and 19 missing columns ({'Bill Text', 'Date Proposed', 'Congress', 'Amends Amendment', 'Latest Action Date', 'Date Offered', 'Sponsor', 'Amends Bill', 'API URL', 'Date of Introduction', 'Legislation Number', 'Bill Number', 'Congress Number', 'Date Submitted', 'Title', 'Latest Action', 'Number of Cosponsors', 'Bill Title (XML)', 'URL_y'}).
              
              This happened while the csv dataset builder was generating data using
              
              hf://datasets/nataliecastro/climate-bills/Bills - Count Vectorizer.csv (at revision a2b872c45926383c9079e70ee1e203a6bf554a41)
              
              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)