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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 8 new columns ({'Process temperature', 'Failure', 'Type', 'Tool wear', 'Air temperature', 'Torque', 'UDI', 'Rotational speed'}) and 12 missing columns ({'Geography', 'Surname', 'Exited', 'NumOfProducts', 'Balance', 'IsActiveMember', 'CustomerId', 'CreditScore', 'EstimatedSalary', 'Age', 'HasCrCard', 'Tenure'}).

This happened while the csv dataset builder was generating data using

hf://datasets/Harsha1001/Machine-Failure-Prediction/machine-failure-prediction.csv (at revision 869dc8318bc66f935d757c5934f4d5d7039a4bfe)

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 "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1831, in _prepare_split_single
                  writer.write_table(table)
                File "/usr/local/lib/python3.12/site-packages/datasets/arrow_writer.py", line 714, in write_table
                  pa_table = table_cast(pa_table, self._schema)
                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2272, in table_cast
                  return cast_table_to_schema(table, schema)
                         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2218, in cast_table_to_schema
                  raise CastError(
              datasets.table.CastError: Couldn't cast
              UDI: int64
              Type: string
              Air temperature: double
              Process temperature: double
              Rotational speed: int64
              Torque: double
              Tool wear: int64
              Failure: int64
              -- schema metadata --
              pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 1212
              to
              {'CustomerId': Value('int64'), 'Surname': Value('string'), 'CreditScore': Value('int64'), 'Geography': Value('string'), 'Age': Value('float64'), 'Tenure': Value('int64'), 'Balance': Value('float64'), 'NumOfProducts': Value('int64'), 'HasCrCard': Value('float64'), 'IsActiveMember': Value('float64'), 'EstimatedSalary': Value('float64'), 'Exited': Value('int64')}
              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 1455, 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 1054, in convert_to_parquet
                  builder.download_and_prepare(
                File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 894, in download_and_prepare
                  self._download_and_prepare(
                File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 970, in _download_and_prepare
                  self._prepare_split(split_generator, **prepare_split_kwargs)
                File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1702, in _prepare_split
                  for job_id, done, content in self._prepare_split_single(
                                               ^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1833, 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 8 new columns ({'Process temperature', 'Failure', 'Type', 'Tool wear', 'Air temperature', 'Torque', 'UDI', 'Rotational speed'}) and 12 missing columns ({'Geography', 'Surname', 'Exited', 'NumOfProducts', 'Balance', 'IsActiveMember', 'CustomerId', 'CreditScore', 'EstimatedSalary', 'Age', 'HasCrCard', 'Tenure'}).
              
              This happened while the csv dataset builder was generating data using
              
              hf://datasets/Harsha1001/Machine-Failure-Prediction/machine-failure-prediction.csv (at revision 869dc8318bc66f935d757c5934f4d5d7039a4bfe)
              
              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)

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CustomerId
int64
Surname
string
CreditScore
int64
Geography
string
Age
float64
Tenure
int64
Balance
float64
NumOfProducts
int64
HasCrCard
float64
IsActiveMember
float64
EstimatedSalary
float64
Exited
int64
15,634,602
Hargrave
619
France
42
2
0
1
1
1
101,348.88
1
15,647,311
Hill
608
Spain
41
1
83,807.86
1
0
1
112,542.58
0
15,619,304
Onio
502
France
42
8
159,660.8
3
1
0
113,931.57
1
15,701,354
Boni
699
France
39
1
0
2
0
0
93,826.63
0
15,737,888
Mitchell
850
Spain
43
2
125,510.82
1
null
1
79,084.1
0
15,574,012
Chu
645
Spain
44
8
113,755.78
2
1
0
149,756.71
1
15,592,531
Bartlett
822
null
50
7
0
2
1
1
10,062.8
0
15,656,148
Obinna
376
Germany
29
4
115,046.74
4
1
0
119,346.88
1
15,792,365
He
501
France
44
4
142,051.07
2
0
null
74,940.5
0
15,592,389
H?
684
France
null
2
134,603.88
1
1
1
71,725.73
0
15,767,821
Bearce
528
France
31
6
102,016.72
2
0
0
80,181.12
0
15,737,173
Andrews
497
Spain
24
3
0
2
1
0
76,390.01
0
15,632,264
Kay
476
France
34
10
0
2
1
0
26,260.98
0
15,691,483
Chin
549
France
25
5
0
2
0
0
190,857.79
0
15,600,882
Scott
635
Spain
35
7
0
2
1
1
65,951.65
0
15,643,966
Goforth
616
Germany
45
3
143,129.41
2
0
1
64,327.26
0
15,737,452
Romeo
653
Germany
58
1
132,602.88
1
1
0
5,097.67
1
15,788,218
Henderson
549
Spain
24
9
0
2
1
1
14,406.41
0
15,661,507
Muldrow
587
Spain
45.25
6
0
1
0
0
158,684.81
0
15,568,982
Hao
726
France
24
6
0
2
1
1
54,724.03
0
15,577,657
McDonald
732
France
41
8
0
2
1
1
170,886.17
0
15,597,945
Dellucci
636
Spain
32.34
8
0
2
1
0
138,555.46
0
15,699,309
Gerasimov
510
Spain
38
4
0
1
1
0
118,913.53
1
15,725,737
Mosman
669
France
46
3
0
2
0
1
8,487.75
0
15,625,047
Yen
846
France
38
5
0
1
1
1
187,616.16
0
15,738,191
Maclean
577
France
25
3
0
2
0
1
124,508.29
0
15,736,816
Young
756
Germany
36.44
2
136,815.64
1
1
1
170,041.95
0
15,700,772
Nebechi
571
France
44
9
0
2
0
0
38,433.35
0
15,728,693
McWilliams
574
Germany
43
3
141,349.43
1
1
1
100,187.43
0
15,656,300
Lucciano
411
France
29
0
59,697.17
2
1
1
53,483.21
0
15,589,475
Azikiwe
591
Spain
39
3
0
3
1
0
140,469.38
1
15,706,552
Odinakachukwu
533
France
36
7
85,311.7
1
0
1
156,731.91
0
15,750,181
Sanderson
553
Germany
41
9
110,112.54
2
0
0
81,898.81
0
15,659,428
Maggard
520
Spain
42
6
0
2
1
1
34,410.55
0
15,732,963
Clements
722
Spain
29
9
0
2
1
1
142,033.07
0
15,794,171
Lombardo
475
France
45
0
134,264.04
1
1
0
27,822.99
1
15,788,448
Watson
490
Spain
31
3
145,260.23
1
0
1
114,066.77
0
15,729,599
Lorenzo
804
Spain
33
7
76,548.6
1
0
1
98,453.45
0
15,717,426
Armstrong
850
France
36
7
0
1
1
1
40,812.9
0
15,585,768
Cameron
582
Germany
41
6
70,349.48
2
0
1
178,074.04
0
15,619,360
Hsiao
472
Spain
40
4
0
1
1
0
70,154.22
0
15,738,148
Clarke
465
France
51
8
122,522.32
1
0
0
181,297.65
1
15,687,946
Osborne
556
France
61
2
117,419.35
1
1
1
94,153.83
0
15,755,196
Lavine
834
France
49
2
131,394.56
1
0
0
194,365.76
1
15,684,171
Bianchi
660
Spain
61
5
155,931.11
1
1
1
158,338.39
0
15,754,849
Tyler
776
Germany
32
4
109,421.13
2
1
1
126,517.46
0
15,602,280
Martin
829
Germany
27
9
112,045.67
1
1
1
119,708.21
1
15,771,573
Okagbue
637
Germany
39
9
137,843.8
1
1
1
117,622.8
1
15,766,205
Yin
550
Germany
38
2
103,391.38
1
0
1
90,878.13
0
15,771,873
Buccho
776
Germany
37
2
103,769.22
2
1
0
194,099.12
0
15,616,550
Chidiebele
698
Germany
44
10
116,363.37
2
1
0
198,059.16
0
15,768,193
Trevisani
585
Germany
36
5
146,050.97
2
0
0
86,424.57
0
15,683,553
O'Brien
788
France
33
5
0
2
0
0
116,978.19
0
15,702,298
Parkhill
655
Germany
41
8
125,561.97
1
0
0
164,040.94
1
15,569,590
Yoo
601
Germany
42
1
98,495.72
1
1
0
40,014.76
1
15,760,861
Phillipps
619
France
43
1
125,211.92
1
1
1
113,410.49
0
15,630,053
Tsao
656
France
45
5
127,864.4
1
1
0
87,107.57
0
15,647,091
Endrizzi
725
Germany
19
0
75,888.2
1
0
0
45,613.75
0
15,623,944
T'ien
511
Spain
66
4
0
1
1
0
1,643.11
1
15,804,771
Velazquez
614
France
51
4
40,685.92
1
1
1
46,775.28
0
15,651,280
Hunter
742
Germany
35
5
136,857
1
0
0
84,509.57
0
15,773,469
Clark
687
Germany
27
9
152,328.88
2
0
0
126,494.82
0
15,702,014
Jeffrey
555
Spain
33
1
56,084.69
2
0
0
178,798.13
0
15,751,208
Pirozzi
684
Spain
56
8
78,707.16
1
1
1
99,398.36
0
15,592,461
Jackson
603
Germany
26
4
109,166.37
1
1
1
92,840.67
0
15,789,484
Hammond
751
Germany
36
6
169,831.46
2
1
1
27,758.36
0
15,696,061
Brownless
581
Germany
34
1
101,633.04
1
1
0
110,431.51
0
15,641,582
Chibugo
735
Germany
43
10
123,180.01
2
1
1
196,673.28
0
15,638,424
Glauert
661
Germany
35
5
150,725.53
2
0
1
113,656.85
0
15,755,648
Pisano
675
France
21
8
98,373.26
1
1
0
18,203
0
15,703,793
Konovalova
738
Germany
58
2
133,745.44
4
1
0
28,373.86
1
15,620,344
McKee
813
France
29
6
0
1
1
0
33,953.87
0
15,812,518
Palermo
657
Spain
37
0
163,607.18
1
0
1
44,203.55
0
15,779,052
Ballard
604
Germany
25
5
157,780.84
2
1
1
58,426.81
0
15,770,811
Wallace
519
France
36
9
0
2
0
1
145,562.4
0
15,780,961
Cavenagh
735
France
21
1
178,718.19
2
1
0
22,388
0
15,614,049
Hu
664
France
55
8
0
2
1
1
139,161.64
0
15,662,085
Read
678
France
32
9
0
1
1
1
148,210.64
0
15,575,185
Bushell
757
Spain
33
5
77,253.22
1
0
1
194,239.63
0
15,803,136
Postle
416
Germany
41
10
122,189.66
2
1
0
98,301.61
0
15,706,021
Buley
665
France
34
1
96,645.54
2
0
0
171,413.66
0
15,663,706
Leonard
777
France
32
2
0
1
1
0
136,458.19
1
15,641,732
Mills
543
France
36
3
0
2
0
0
26,019.59
0
15,701,164
Onyeorulu
506
France
34
4
90,307.62
1
1
1
159,235.29
0
15,738,751
Beit
493
France
46
4
0
2
1
0
1,907.66
0
15,805,254
Ndukaku
652
Spain
75
10
0
2
1
1
114,675.75
0
15,762,418
Gant
750
Spain
22
3
121,681.82
1
1
0
128,643.35
1
15,625,759
Rowley
729
France
30
9
0
2
1
0
151,869.35
0
15,622,897
Sharpe
646
France
46
4
0
3
1
0
93,251.42
1
15,767,954
Osborne
635
Germany
28
3
81,623.67
2
1
1
156,791.36
0
15,757,535
Heap
647
Spain
44
5
0
3
1
1
174,205.22
1
15,731,511
Ritchie
808
France
45
7
118,626.55
2
1
0
147,132.46
0
15,809,248
Cole
524
France
36
10
0
2
1
0
109,614.57
0
15,640,635
Capon
769
France
29
8
0
2
1
1
172,290.61
0
15,676,966
Capon
730
Spain
42
4
0
2
0
1
85,982.47
0
15,699,461
Fiorentini
515
Spain
35
10
176,273.95
1
0
1
121,277.78
0
15,738,721
Graham
773
Spain
41
9
102,827.44
1
0
1
64,595.25
0
15,693,683
Yuille
814
Germany
29
8
97,086.4
2
1
1
197,276.13
0
15,604,348
Allard
710
Spain
22
8
0
2
0
0
99,645.04
0
15,633,059
Fanucci
413
France
34
9
0
2
0
0
6,534.18
0
End of preview.