Datasets:

DongjaeHeo

/

housing

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 34 new columns ({'사용허가여부', 'k-관리비부과면적', 'k-85㎡~135㎡이하', '청소비관리형태', '단지신청일', 'k-시행사', 'k-주거전용면적', 'k-세대타입(분양형태)', 'k-전용면적별세대현황(60㎡~85㎡이하)', 'k-전체세대수', 'k-단지분류(아파트,주상복합등등)', '아파트명', '전용면적(㎡)', '고용보험관리번호', 'k-135㎡초과', 'k-난방방식', 'k-수정일자', '관리비 업로드', '부번', '기타/의무/임대/임의=1/2/3/4', '세대전기계약방법', 'k-연면적', '단지승인일', 'k-등록일자', 'k-복도유형', '본번', 'k-전용면적별세대현황(60㎡이하)', 'k-관리방식', 'k-건설사(시공사)', '시군구', 'k-사용검사일-사용승인일', 'k-전체동수', '도로명', '경비비관리형태'}) and 66 missing columns ({'강남여부', '경비비관리형태_NULL', 'k_연면적', 'k_복도유형_타워형', 'k_세대타입_분양형태_NULL', '경비비관리형태_위탁', 'k_복도유형_NULL', '기타/의무/임대/임의=1/2/3/4_임대', 'k_관리방식_위탁관리', 'k_난방방식_중앙난방', '경비비관리형태_직영', '세대전기계약방법_단일계약', 'k_난방방식_NULL', '청소비관리형태_기타', 'k_관리방식_NULL', 'k_관리방식_자치관리', '사용허가여부_Y', 'k_전체세대수', '청소비관리형태_NULL', 'k_단지분류_아파트_주상복합등등_주상복합', '기타/의무/임대/임의=1/2/3/4_임의', 'k_난방방식_지역난방', '기타/의무/임대/임의=1/2/3/4_NULL', 'k_단지분류_아파트_주상복합등등_도시형_생활주택_주상복합', 'address_mean_target', 'k_세대타입_분양형태_임대', '사용허가여부_NULL', '관리비_업로드_NULL', 'k_복도유형_혼합식', 'k_수정일자', 'mean_target_gu_dong', 'k_단지분류_아파트_주상복합등등_아파트', 'k_복도유형_복도식', '기타/의무/임대/임의=1/2/3/4_의무', 'k_전용면적별세대현황_60_이하', 'k_85_~135_이하', '관리비_업로드_Y', 'k_복도유형_계단식', 'k_세대타입_분양형태_분양', '청소비관리형태_직영', '전용면적', 'k_관리방식_직영', 'mean_target', 'k_단지분류_아파트_주상복합등등_연립주택', 'k_전체동수', 'k_전용면적별세대현황_60_~85_이하', 'k_난방방식_개별난방', '기타/의무/임대/임의=1/2/3/4_기타', '청소비관리형태_위탁', 'k_135_초과', 'k_관리비부과면적', '거래유형_중개거래', 'k_주거전용면적', '거래유형_직거래', '경비비관리형태_위탁+직영', 'k_복도유형_기타', '청소비관리형태_위탁+직영', '세대전기계약방법_NULL', 'k_단지분류_아파트_주상복합등등_NULL', '경비비관리형태_기타', '관리비_업로드_N', 'k_세대타입_분양형태_기타', 'k_난방방식_기타', 'apt_mean_target', '세대전기계약방법_종합계약', 'k_단지분류_아파트_주상복합등등_도시형_생활주택_아파트'}).

This happened while the csv dataset builder was generating data using

hf://datasets/DongjaeHeo/housing/geocoded_addresses.csv (at revision 75e92f1178c41acfa2fad5359e986fe25a25be6f)

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 2011, in _prepare_split_single
                  writer.write_table(table)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/arrow_writer.py", line 585, 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 2302, in table_cast
                  return cast_table_to_schema(table, schema)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2256, in cast_table_to_schema
                  raise CastError(
              datasets.table.CastError: Couldn't cast
              시군구: string
              본번: double
              부번: double
              아파트명: string
              전용면적(㎡): double
              계약년월: int64
              계약일: int64
              층: int64
              건축년도: int64
              도로명: string
              거래유형: string
              k-단지분류(아파트,주상복합등등): string
              k-세대타입(분양형태): string
              k-관리방식: string
              k-복도유형: string
              k-난방방식: string
              k-전체동수: double
              k-전체세대수: double
              k-건설사(시공사): string
              k-시행사: string
              k-사용검사일-사용승인일: string
              k-연면적: double
              k-주거전용면적: double
              k-관리비부과면적: double
              k-전용면적별세대현황(60㎡이하): double
              k-전용면적별세대현황(60㎡~85㎡이하): double
              k-85㎡~135㎡이하: double
              k-135㎡초과: double
              k-등록일자: string
              k-수정일자: string
              고용보험관리번호: string
              경비비관리형태: string
              세대전기계약방법: string
              청소비관리형태: string
              건축면적: double
              주차대수: double
              기타/의무/임대/임의=1/2/3/4: string
              단지승인일: string
              사용허가여부: string
              관리비 업로드: string
              단지신청일: string
              target: double
              is_test: int64
              latitude: double
              longitude: double
              -- schema metadata --
              pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 7625
              to
              {'전용면적': Value(dtype='float64', id=None), '계약년월': Value(dtype='int64', id=None), '계약일': Value(dtype='int64', id=None), '층': Value(dtype='int64', id=None), '건축년도': Value(dtype='int64', id=None), 'k_전체동수': Value(dtype='float64', id=None), 'k_전체세대수': Value(dtype='float64', id=None), 'k_연면적': Value(dtype='float64', id=None), 'k_주거전용면적': Value(dtype='float64', id=None), 'k_관리비부과면적': Value(dtype='float64', id=None), 'k_전용면적별세대현황_60_이하': Value(dtype='float64', id=None), 'k_전용면적별세대현황_60_~85_이하': Value(dtype='float64', id=None), 'k_85_~135_이하': Value(dtype='float64', id=None), 'k_135_초과': Value(dtype='float64', id=None), 'k_수정일자': Value(dtype='string', id=None), '건축면적': Value(dtype='float64', id=None), '주차대수': Value(dtype='float64', id=None), 'target': Value(dtype='float64', id=None), 'is_test': Value(dtype='int64', id=None), 'latitude': Value(dtype='float64', id=None), 'longitude': Value(dtype='float64', id=None), '강남여부': Value(dtype='int64', id=None), 'mean_target': Value(dtype='float64', id=None), 'apt_mean_target': Value(dtype='float64', id=None), 'address_mean_target': Value(dtype='float64', id=None), 'mean_target_gu_dong': Value(dtype='float64', id=None), '거래유형': Value(dtype='int64', id=None), '거래유형_중개거래': Value(dtype='int64', id=None), '거래유형_직거래': Value(dtype='int64', id=None), 'k_단지분류_아파트_주상복합등등_NULL': Value(dtype='int64', id=None), 'k_단지분류_아파트_주상복합등등_도시형_생활주택_아파트': Value(dtype='int64', id=None), 'k_단지분류_아파트_주상복합등등_도시형_생활주택_주상복합': Value(dtype='int64', id=None), 'k_단지분류_아파트_주상복
              ...
              ype='int64', id=None), 'k_복도유형_복도식': Value(dtype='int64', id=None), 'k_복도유형_타워형': Value(dtype='int64', id=None), 'k_복도유형_혼합식': Value(dtype='int64', id=None), 'k_난방방식_NULL': Value(dtype='int64', id=None), 'k_난방방식_개별난방': Value(dtype='int64', id=None), 'k_난방방식_기타': Value(dtype='int64', id=None), 'k_난방방식_중앙난방': Value(dtype='int64', id=None), 'k_난방방식_지역난방': Value(dtype='int64', id=None), '경비비관리형태_NULL': Value(dtype='int64', id=None), '경비비관리형태_기타': Value(dtype='int64', id=None), '경비비관리형태_위탁': Value(dtype='int64', id=None), '경비비관리형태_위탁+직영': Value(dtype='int64', id=None), '경비비관리형태_직영': Value(dtype='int64', id=None), '세대전기계약방법_NULL': Value(dtype='int64', id=None), '세대전기계약방법_단일계약': Value(dtype='int64', id=None), '세대전기계약방법_종합계약': Value(dtype='int64', id=None), '청소비관리형태_NULL': Value(dtype='int64', id=None), '청소비관리형태_기타': Value(dtype='int64', id=None), '청소비관리형태_위탁': Value(dtype='int64', id=None), '청소비관리형태_위탁+직영': Value(dtype='int64', id=None), '청소비관리형태_직영': Value(dtype='int64', id=None), '기타/의무/임대/임의=1/2/3/4_NULL': Value(dtype='int64', id=None), '기타/의무/임대/임의=1/2/3/4_기타': Value(dtype='int64', id=None), '기타/의무/임대/임의=1/2/3/4_의무': Value(dtype='int64', id=None), '기타/의무/임대/임의=1/2/3/4_임대': Value(dtype='int64', id=None), '기타/의무/임대/임의=1/2/3/4_임의': Value(dtype='int64', id=None), '사용허가여부_NULL': Value(dtype='int64', id=None), '사용허가여부_Y': Value(dtype='int64', id=None), '관리비_업로드_N': Value(dtype='int64', id=None), '관리비_업로드_NULL': Value(dtype='int64', id=None), '관리비_업로드_Y': Value(dtype='int64', 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 1572, in compute_config_parquet_and_info_response
                  parquet_operations, partial, estimated_dataset_info = stream_convert_to_parquet(
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1136, in stream_convert_to_parquet
                  builder._prepare_split(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1882, 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 2013, 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 34 new columns ({'사용허가여부', 'k-관리비부과면적', 'k-85㎡~135㎡이하', '청소비관리형태', '단지신청일', 'k-시행사', 'k-주거전용면적', 'k-세대타입(분양형태)', 'k-전용면적별세대현황(60㎡~85㎡이하)', 'k-전체세대수', 'k-단지분류(아파트,주상복합등등)', '아파트명', '전용면적(㎡)', '고용보험관리번호', 'k-135㎡초과', 'k-난방방식', 'k-수정일자', '관리비 업로드', '부번', '기타/의무/임대/임의=1/2/3/4', '세대전기계약방법', 'k-연면적', '단지승인일', 'k-등록일자', 'k-복도유형', '본번', 'k-전용면적별세대현황(60㎡이하)', 'k-관리방식', 'k-건설사(시공사)', '시군구', 'k-사용검사일-사용승인일', 'k-전체동수', '도로명', '경비비관리형태'}) and 66 missing columns ({'강남여부', '경비비관리형태_NULL', 'k_연면적', 'k_복도유형_타워형', 'k_세대타입_분양형태_NULL', '경비비관리형태_위탁', 'k_복도유형_NULL', '기타/의무/임대/임의=1/2/3/4_임대', 'k_관리방식_위탁관리', 'k_난방방식_중앙난방', '경비비관리형태_직영', '세대전기계약방법_단일계약', 'k_난방방식_NULL', '청소비관리형태_기타', 'k_관리방식_NULL', 'k_관리방식_자치관리', '사용허가여부_Y', 'k_전체세대수', '청소비관리형태_NULL', 'k_단지분류_아파트_주상복합등등_주상복합', '기타/의무/임대/임의=1/2/3/4_임의', 'k_난방방식_지역난방', '기타/의무/임대/임의=1/2/3/4_NULL', 'k_단지분류_아파트_주상복합등등_도시형_생활주택_주상복합', 'address_mean_target', 'k_세대타입_분양형태_임대', '사용허가여부_NULL', '관리비_업로드_NULL', 'k_복도유형_혼합식', 'k_수정일자', 'mean_target_gu_dong', 'k_단지분류_아파트_주상복합등등_아파트', 'k_복도유형_복도식', '기타/의무/임대/임의=1/2/3/4_의무', 'k_전용면적별세대현황_60_이하', 'k_85_~135_이하', '관리비_업로드_Y', 'k_복도유형_계단식', 'k_세대타입_분양형태_분양', '청소비관리형태_직영', '전용면적', 'k_관리방식_직영', 'mean_target', 'k_단지분류_아파트_주상복합등등_연립주택', 'k_전체동수', 'k_전용면적별세대현황_60_~85_이하', 'k_난방방식_개별난방', '기타/의무/임대/임의=1/2/3/4_기타', '청소비관리형태_위탁', 'k_135_초과', 'k_관리비부과면적', '거래유형_중개거래', 'k_주거전용면적', '거래유형_직거래', '경비비관리형태_위탁+직영', 'k_복도유형_기타', '청소비관리형태_위탁+직영', '세대전기계약방법_NULL', 'k_단지분류_아파트_주상복합등등_NULL', '경비비관리형태_기타', '관리비_업로드_N', 'k_세대타입_분양형태_기타', 'k_난방방식_기타', 'apt_mean_target', '세대전기계약방법_종합계약', 'k_단지분류_아파트_주상복합등등_도시형_생활주택_아파트'}).
              
              This happened while the csv dataset builder was generating data using
              
              hf://datasets/DongjaeHeo/housing/geocoded_addresses.csv (at revision 75e92f1178c41acfa2fad5359e986fe25a25be6f)
              
              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)