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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 130 new columns ({'Train_83', 'Train_35', 'Train_67', 'Train_120', 'Train_130', 'Train_86', 'Train_31', 'Train_11', 'Train_92', 'Train_108', 'Train_89', 'Train_33', 'Train_40', 'Train_113', 'Train_117', 'Train_112', 'Train_127', 'Train_69', 'Train_30', 'Train_74', 'Train_105', 'Train_19', 'Train_70', 'Train_14', 'Train_68', 'Train_57', 'Train_82', 'Train_51', 'Train_58', 'Train_23', 'Train_42', 'Train_26', 'Train_73', 'Train_98', 'Train_54', 'Train_114', 'Train_80', 'Train_84', 'Train_46', 'Train_121', 'Train_95', 'Train_109', 'Train_13', 'Train_97', 'Train_18', 'Train_87', 'Train_34', 'Train_27', 'Train_28', 'Train_128', 'Train_62', 'Train_07', 'Train_93', 'Train_96', 'Train_44', 'Train_102', 'Train_90', 'Train_85', 'Train_17', 'Train_65', 'Train_122', 'Train_24', 'Train_48', 'Train_32', 'Train_39', 'Train_02', 'Train_50', 'Train_81', 'Train_79', 'Train_63', 'Train_37', 'Train_103', 'Train_36', 'Train_75', 'Train_100', 'Train_116', 'Train_38', 'Train_15', 'Train_09', 'Train_64', 'Train_22', 'Train_10', 'Train_119', 'Train_49', 'Train_25', 'Train_05', 'Train_124', 'Train_107', 'Train_55', 'Train_29', 'Train_47', 'Train_91', 'Train_08', 'Train_104', 'Train_94', 'Train_115', 'Train_123', 'Train_45', 'Train_56', 'Train_99', 'Train_66', 'Train_118', 'Train_16', 'Train_77', 'Train_20', 'Train_06', 'Train_52', 'Train_53', 'Train_60', 'Train_106', 'Train_01', 'Train_43', 'Train_59', 'Train_111', 'Train_04', 'Train_71', 'Train_129', 'Train_03', 'Train_78', 'Train_88', 'Train_110', 'Train_72', 'Train_126', 'Train_12', 'Train_101', 'Train_41', 'Train_125', 'Train_61', 'Train_21', 'Train_76'}) and 100 missing columns ({'Test_58', 'Test_32', 'Test_07', 'Test_87', 'Test_46', 'Test_20', 'Test_70', 'Test_22', 'Test_50', 'Test_73', 'Test_90', 'Test_37', 'Test_38', 'Test_02', 'Test_14', 'Test_66', 'Test_85', 'Test_35', 'Test_76', 'Test_31', 'Test_91', 'Test_17', 'Test_13', 'Test_49', 'Test_43', 'Test_52', 'Test_45', 'Test_69', 'Test_75', 'Test_98', 'Test_44', 'Test_65', 'Test_19', 'Test_53', 'Test_51', 'Test_78', 'Test_01', 'Test_15', 'Test_26', 'Test_79', 'Test_64', 'Test_41', 'Test_63', 'Test_28', 'Test_99', 'Test_33', 'Test_40', 'Test_96', 'Test_39', 'Test_89', 'Test_84', 'Test_48', 'Test_61', 'Test_06', 'Test_34', 'Test_77', 'Test_05', 'Test_95', 'Test_71', 'Test_62', 'Test_12', 'Test_27', 'Test_25', 'Test_80', 'Test_67', 'Test_09', 'Test_47', 'Test_08', 'Test_59', 'Test_42', 'Test_68', 'Test_93', 'Test_55', 'Test_54', 'Test_03', 'Test_82', 'Test_29', 'Test_92', 'Test_04', 'Test_16', 'Test_100', 'Test_57', 'Test_60', 'Test_86', 'Test_24', 'Test_72', 'Test_94', 'Test_88', 'Test_11', 'Test_21', 'Test_97', 'Test_36', 'Test_30', 'Test_74', 'Test_10', 'Test_23', 'Test_81', 'Test_83', 'Test_18', 'Test_56'}).

This happened while the csv dataset builder was generating data using

hf://datasets/vasudevgupta/prml_data_contest/Dataset_1_Training.csv (at revision cb5afacd5f28ef2066612316a7c35f0954181ce1)

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
              ID_REF: string
              Train_01: double
              Train_02: double
              Train_03: double
              Train_04: double
              Train_05: double
              Train_06: double
              Train_07: double
              Train_08: double
              Train_09: double
              Train_10: double
              Train_11: double
              Train_12: double
              Train_13: double
              Train_14: double
              Train_15: double
              Train_16: double
              Train_17: double
              Train_18: double
              Train_19: double
              Train_20: double
              Train_21: double
              Train_22: double
              Train_23: double
              Train_24: double
              Train_25: double
              Train_26: double
              Train_27: double
              Train_28: double
              Train_29: double
              Train_30: double
              Train_31: double
              Train_32: double
              Train_33: double
              Train_34: double
              Train_35: double
              Train_36: double
              Train_37: double
              Train_38: double
              Train_39: double
              Train_40: double
              Train_41: double
              Train_42: double
              Train_43: double
              Train_44: double
              Train_45: double
              Train_46: double
              Train_47: double
              Train_48: double
              Train_49: double
              Train_50: double
              Train_51: double
              Train_52: double
              Train_53: double
              Train_54: double
              Train_55: double
              Train_56: double
              Train_57: double
              Train_58: double
              Train_59: double
              Train_60: double
              Train_61: double
              Train_62: double
              Train_63: double
              Train_64: double
              Train_65: double
              Train_66: double
              Train_67: double
              Train_68: double
              Train_69: double
              Train_70: double
              Train_71: double
              Train_72: double
              Train_73: double
              Train_74: double
              Train_75: double
              Train_76: double
              Train_77: double
              Train_78: double
              Train_79: double
              Train_80: double
              Train_81: double
              Train_82: double
              Train_83: double
              Train_84: double
              Train_85: double
              Train_86: double
              Train_87: double
              Train_88: double
              Train_89: double
              Train_90: double
              Train_91: double
              Train_92: double
              Train_93: double
              Train_94: double
              Train_95: double
              Train_96: double
              Train_97: double
              Train_98: double
              Train_99: double
              Train_100: double
              Train_101: double
              Train_102: double
              Train_103: double
              Train_104: double
              Train_105: double
              Train_106: double
              Train_107: double
              Train_108: double
              Train_109: double
              Train_110: double
              Train_111: double
              Train_112: double
              Train_113: double
              Train_114: double
              Train_115: double
              Train_116: double
              Train_117: double
              Train_118: double
              Train_119: double
              Train_120: double
              Train_121: double
              Train_122: double
              Train_123: double
              Train_124: double
              Train_125: double
              Train_126: double
              Train_127: double
              Train_128: double
              Train_129: double
              Train_130: double
              -- schema metadata --
              pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 15647
              to
              {'ID_REF': Value(dtype='string', id=None), 'Test_01': Value(dtype='float64', id=None), 'Test_02': Value(dtype='float64', id=None), 'Test_03': Value(dtype='float64', id=None), 'Test_04': Value(dtype='float64', id=None), 'Test_05': Value(dtype='float64', id=None), 'Test_06': Value(dtype='float64', id=None), 'Test_07': Value(dtype='float64', id=None), 'Test_08': Value(dtype='float64', id=None), 'Test_09': Value(dtype='float64', id=None), 'Test_10': Value(dtype='float64', id=None), 'Test_11': Value(dtype='float64', id=None), 'Test_12': Value(dtype='float64', id=None), 'Test_13': Value(dtype='float64', id=None), 'Test_14': Value(dtype='float64', id=None), 'Test_15': Value(dtype='float64', id=None), 'Test_16': Value(dtype='float64', id=None), 'Test_17': Value(dtype='float64', id=None), 'Test_18': Value(dtype='float64', id=None), 'Test_19': Value(dtype='float64', id=None), 'Test_20': Value(dtype='float64', id=None), 'Test_21': Value(dtype='float64', id=None), 'Test_22': Value(dtype='float64', id=None), 'Test_23': Value(dtype='float64', id=None), 'Test_24': Value(dtype='float64', id=None), 'Test_25': Value(dtype='float64', id=None), 'Test_26': Value(dtype='float64', id=None), 'Test_27': Value(dtype='float64', id=None), 'Test_28': Value(dtype='float64', id=None), 'Test_29': Value(dtype='float64', id=None), 'Test_30': Value(dtype='float64', id=None), 'Test_31': Value(dtype='float64', id=None), 'Test_32': Value(dtype='float64', id=None), 'Test_33': Value(dtype='float64', id=None), 'Test
              ...
              e), 'Test_67': Value(dtype='float64', id=None), 'Test_68': Value(dtype='float64', id=None), 'Test_69': Value(dtype='float64', id=None), 'Test_70': Value(dtype='float64', id=None), 'Test_71': Value(dtype='float64', id=None), 'Test_72': Value(dtype='float64', id=None), 'Test_73': Value(dtype='float64', id=None), 'Test_74': Value(dtype='float64', id=None), 'Test_75': Value(dtype='float64', id=None), 'Test_76': Value(dtype='float64', id=None), 'Test_77': Value(dtype='float64', id=None), 'Test_78': Value(dtype='float64', id=None), 'Test_79': Value(dtype='float64', id=None), 'Test_80': Value(dtype='float64', id=None), 'Test_81': Value(dtype='float64', id=None), 'Test_82': Value(dtype='float64', id=None), 'Test_83': Value(dtype='float64', id=None), 'Test_84': Value(dtype='float64', id=None), 'Test_85': Value(dtype='float64', id=None), 'Test_86': Value(dtype='float64', id=None), 'Test_87': Value(dtype='float64', id=None), 'Test_88': Value(dtype='float64', id=None), 'Test_89': Value(dtype='float64', id=None), 'Test_90': Value(dtype='float64', id=None), 'Test_91': Value(dtype='float64', id=None), 'Test_92': Value(dtype='float64', id=None), 'Test_93': Value(dtype='float64', id=None), 'Test_94': Value(dtype='float64', id=None), 'Test_95': Value(dtype='float64', id=None), 'Test_96': Value(dtype='float64', id=None), 'Test_97': Value(dtype='float64', id=None), 'Test_98': Value(dtype='float64', id=None), 'Test_99': Value(dtype='float64', id=None), 'Test_100': Value(dtype='float64', 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 1321, 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 935, in convert_to_parquet
                  builder.download_and_prepare(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1027, in download_and_prepare
                  self._download_and_prepare(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1122, 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 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 130 new columns ({'Train_83', 'Train_35', 'Train_67', 'Train_120', 'Train_130', 'Train_86', 'Train_31', 'Train_11', 'Train_92', 'Train_108', 'Train_89', 'Train_33', 'Train_40', 'Train_113', 'Train_117', 'Train_112', 'Train_127', 'Train_69', 'Train_30', 'Train_74', 'Train_105', 'Train_19', 'Train_70', 'Train_14', 'Train_68', 'Train_57', 'Train_82', 'Train_51', 'Train_58', 'Train_23', 'Train_42', 'Train_26', 'Train_73', 'Train_98', 'Train_54', 'Train_114', 'Train_80', 'Train_84', 'Train_46', 'Train_121', 'Train_95', 'Train_109', 'Train_13', 'Train_97', 'Train_18', 'Train_87', 'Train_34', 'Train_27', 'Train_28', 'Train_128', 'Train_62', 'Train_07', 'Train_93', 'Train_96', 'Train_44', 'Train_102', 'Train_90', 'Train_85', 'Train_17', 'Train_65', 'Train_122', 'Train_24', 'Train_48', 'Train_32', 'Train_39', 'Train_02', 'Train_50', 'Train_81', 'Train_79', 'Train_63', 'Train_37', 'Train_103', 'Train_36', 'Train_75', 'Train_100', 'Train_116', 'Train_38', 'Train_15', 'Train_09', 'Train_64', 'Train_22', 'Train_10', 'Train_119', 'Train_49', 'Train_25', 'Train_05', 'Train_124', 'Train_107', 'Train_55', 'Train_29', 'Train_47', 'Train_91', 'Train_08', 'Train_104', 'Train_94', 'Train_115', 'Train_123', 'Train_45', 'Train_56', 'Train_99', 'Train_66', 'Train_118', 'Train_16', 'Train_77', 'Train_20', 'Train_06', 'Train_52', 'Train_53', 'Train_60', 'Train_106', 'Train_01', 'Train_43', 'Train_59', 'Train_111', 'Train_04', 'Train_71', 'Train_129', 'Train_03', 'Train_78', 'Train_88', 'Train_110', 'Train_72', 'Train_126', 'Train_12', 'Train_101', 'Train_41', 'Train_125', 'Train_61', 'Train_21', 'Train_76'}) and 100 missing columns ({'Test_58', 'Test_32', 'Test_07', 'Test_87', 'Test_46', 'Test_20', 'Test_70', 'Test_22', 'Test_50', 'Test_73', 'Test_90', 'Test_37', 'Test_38', 'Test_02', 'Test_14', 'Test_66', 'Test_85', 'Test_35', 'Test_76', 'Test_31', 'Test_91', 'Test_17', 'Test_13', 'Test_49', 'Test_43', 'Test_52', 'Test_45', 'Test_69', 'Test_75', 'Test_98', 'Test_44', 'Test_65', 'Test_19', 'Test_53', 'Test_51', 'Test_78', 'Test_01', 'Test_15', 'Test_26', 'Test_79', 'Test_64', 'Test_41', 'Test_63', 'Test_28', 'Test_99', 'Test_33', 'Test_40', 'Test_96', 'Test_39', 'Test_89', 'Test_84', 'Test_48', 'Test_61', 'Test_06', 'Test_34', 'Test_77', 'Test_05', 'Test_95', 'Test_71', 'Test_62', 'Test_12', 'Test_27', 'Test_25', 'Test_80', 'Test_67', 'Test_09', 'Test_47', 'Test_08', 'Test_59', 'Test_42', 'Test_68', 'Test_93', 'Test_55', 'Test_54', 'Test_03', 'Test_82', 'Test_29', 'Test_92', 'Test_04', 'Test_16', 'Test_100', 'Test_57', 'Test_60', 'Test_86', 'Test_24', 'Test_72', 'Test_94', 'Test_88', 'Test_11', 'Test_21', 'Test_97', 'Test_36', 'Test_30', 'Test_74', 'Test_10', 'Test_23', 'Test_81', 'Test_83', 'Test_18', 'Test_56'}).
              
              This happened while the csv dataset builder was generating data using
              
              hf://datasets/vasudevgupta/prml_data_contest/Dataset_1_Training.csv (at revision cb5afacd5f28ef2066612316a7c35f0954181ce1)
              
              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.

ID_REF
string
Test_01
float64
Test_02
float64
Test_03
float64
Test_04
float64
Test_05
float64
Test_06
float64
Test_07
float64
Test_08
float64
Test_09
float64
Test_10
float64
Test_11
float64
Test_12
float64
Test_13
float64
Test_14
float64
Test_15
float64
Test_16
float64
Test_17
float64
Test_18
float64
Test_19
float64
Test_20
float64
Test_21
float64
Test_22
float64
Test_23
float64
Test_24
float64
Test_25
float64
Test_26
float64
Test_27
float64
Test_28
float64
Test_29
float64
Test_30
float64
Test_31
float64
Test_32
float64
Test_33
float64
Test_34
float64
Test_35
float64
Test_36
float64
Test_37
float64
Test_38
float64
Test_39
float64
Test_40
float64
Test_41
float64
Test_42
float64
Test_43
float64
Test_44
float64
Test_45
float64
Test_46
float64
Test_47
float64
Test_48
float64
Test_49
float64
Test_50
float64
Test_51
float64
Test_52
float64
Test_53
float64
Test_54
float64
Test_55
float64
Test_56
float64
Test_57
float64
Test_58
float64
Test_59
float64
Test_60
float64
Test_61
float64
Test_62
float64
Test_63
float64
Test_64
float64
Test_65
float64
Test_66
float64
Test_67
float64
Test_68
float64
Test_69
float64
Test_70
float64
Test_71
float64
Test_72
float64
Test_73
float64
Test_74
float64
Test_75
float64
Test_76
float64
Test_77
float64
Test_78
float64
Test_79
float64
Test_80
float64
Test_81
float64
Test_82
float64
Test_83
float64
Test_84
float64
Test_85
float64
Test_86
float64
Test_87
float64
Test_88
float64
Test_89
float64
Test_90
float64
Test_91
float64
Test_92
float64
Test_93
float64
Test_94
float64
Test_95
float64
Test_96
float64
Test_97
float64
Test_98
float64
Test_99
float64
Test_100
float64
gene_1
12.3446
12.0376
10.9684
12.1004
11.5133
12.2191
11.4786
10.7731
10.9787
12.5782
11.8791
11.9716
11.961
12.3903
11.707
11.5398
11.1113
11.4986
12.2528
10.2911
11.8509
12.1978
11.4072
12.7367
11.9765
11.3246
12.0941
10.7466
11.0495
11.7385
11.5092
11.7728
12.1022
12.0736
11.2111
11.8962
12.124
10.9237
12.236
10.7914
12.2148
11.7166
12.7646
11.9024
12.0173
11.2714
11.2179
11.2065
11.4876
11.8805
11.939
11.5551
11.6529
12.0608
11.5139
11.8896
11.5006
11.9052
11.959
12.218
12.3984
12.7551
11.9883
12.0864
11.9235
11.9922
11.9809
11.9526
12.0866
12.0421
12.0653
11.6125
11.8752
12.2996
12.3869
11.8751
12.2129
11.5913
11.954
12.1595
11.9564
12.1499
11.8839
12.7356
12.1771
11.6306
12.1274
12.5949
11.0304
12.4597
12.1696
12.4202
11.9979
11.9181
11.9971
11.8023
11.4574
11.9181
11.7012
11.9795
gene_2
7.0781
7.6011
7.4696
7.9643
7.6576
8.1655
7.9101
8.6648
8.1352
7.6247
8.9005
7.647
8.9507
8.0982
7.8371
8.3329
8.3937
6.841
8.6071
5.7879
8.7986
8.8164
8.1883
8.0052
7.6044
8.2015
7.8253
4.913
9.2408
8.1488
8.145
8.6772
7.6784
7.816
7.323
8.1039
8.588
8.298
7.4006
8.6287
7.8514
8.6037
6.7644
7.9691
5.1489
7.226
8.7762
8.4165
8.1887
9.0496
8.5198
7.835
7.4979
7.8334
8.6451
8.1589
9.1396
7.7421
9.4844
7.7593
8.5418
7.7959
7.7519
8.1094
7.5099
8.9165
7.9313
8.126
8.8091
9.0085
8.1614
7.5817
8.1642
8.5171
8.4071
7.9059
7.6896
9.9503
7.914
8.425
6.838
7.8347
7.0411
7.8143
8.3576
8.7054
8.7217
7.8179
7.6113
7.7361
7.7427
7.8715
7.7001
6.8594
7.1246
7.8182
8.0488
7.389
7.7375
7.9905
gene_3
7.5017
7.3458
8.3759
6.7908
9.9053
7.6081
8.9351
7.8527
7.8096
7.1587
7.5754
9.4074
7.8502
8.3035
7.9844
8.1751
8.1448
8.4572
7.4646
8.5336
7.6671
8.9842
8.4065
7.2505
7.7339
9.2606
8.07
8.4845
8.9309
8.3088
7.5542
8.4128
9.1484
6.7201
8.6958
8.2509
8.1537
10.4419
7.7955
6.9254
6.9006
6.9041
8.079
7.5642
8.6382
9.7721
7.8778
8.0671
6.4387
8.175
11.3532
7.5747
7.279
8.1746
7.7891
8.4072
7.8892
7.9753
7.2895
8.1299
7.4417
8.5725
8.6974
8.0351
8.514
8.1214
9.3479
7.3146
7.8527
6.3289
6.6753
7.7215
7.8343
8.0176
8.0141
7.4239
7.7091
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gene_74
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gene_76
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gene_77
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gene_78
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gene_79
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gene_80
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gene_81
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gene_82
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gene_83
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10.0606
10.9085
10.8556
11.849
12.1901
10.6445
11.9188
10.7518
10.9586
10.9295
10.5877
12.1916
10.7372
10.552
11.4543
11.2683
12.3443
12.0309
11.5061
10.7715
10.9084
10.3256
10.8454
10.466
11.3228
10.5511
11.282
11.3282
10.5677
11.087
10.7546
11.4108
11.3188
11.6115
10.3522
11.3647
10.6487
11.3279
10.7731
11.0633
9.9204
10.3769
11.7331
10.7724
12.1568
11.6729
10.0214
11.0575
11.128
10.7229
11.2688
11.2986
11.3747
10.9766
11.8362
11.2905
11.9574
10.665
10.4975
10.3947
11.2913
11.2793
10.8103
10.5533
11.5169
12.0543
10.8532
11.2881
10.0678
10.554
10.9366
10.8864
11.0706
11.4233
10.388
10.4209
10.5359
10.257
10.788
10.6645
12.0826
11.1968
11.8175
10.1344
11.5401
10.4689
10.7554
9.4475
10.7833
9.7871
10.5323
11.0336
10.614
11.0578
10.9061
11.2295
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