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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 1 new columns ({'Engine Condition'}) and 1 missing columns ({'temp_differential'}).

This happened while the csv dataset builder was generating data using

hf://datasets/noormd100/predictive-maintenance-data/engine_data.csv (at revision d14f3ae5fff68a022c75b93f99d9379fd99550f4), ['hf://datasets/noormd100/predictive-maintenance-data@d14f3ae5fff68a022c75b93f99d9379fd99550f4/Xtest.csv', 'hf://datasets/noormd100/predictive-maintenance-data@d14f3ae5fff68a022c75b93f99d9379fd99550f4/Xtrain.csv', 'hf://datasets/noormd100/predictive-maintenance-data@d14f3ae5fff68a022c75b93f99d9379fd99550f4/engine_data.csv', 'hf://datasets/noormd100/predictive-maintenance-data@d14f3ae5fff68a022c75b93f99d9379fd99550f4/ytest.csv', 'hf://datasets/noormd100/predictive-maintenance-data@d14f3ae5fff68a022c75b93f99d9379fd99550f4/ytrain.csv']

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/python3.14/site-packages/datasets/builder.py", line 1837, in _prepare_split_single
                  writer.write_table(table)
                  ~~~~~~~~~~~~~~~~~~^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/arrow_writer.py", line 765, in write_table
                  self._write_table(pa_table, writer_batch_size=writer_batch_size)
                  ~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/arrow_writer.py", line 773, in _write_table
                  pa_table = table_cast(pa_table, self._schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2369, in table_cast
                  return cast_table_to_schema(table, schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2297, in cast_table_to_schema
                  raise CastError(
                  ...<3 lines>...
                  )
              datasets.table.CastError: Couldn't cast
              Engine rpm: int64
              Lub oil pressure: double
              Fuel pressure: double
              Coolant pressure: double
              lub oil temp: double
              Coolant temp: double
              Engine Condition: int64
              -- schema metadata --
              pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 1170
              to
              {'Engine rpm': Value('int64'), 'Lub oil pressure': Value('float64'), 'Fuel pressure': Value('float64'), 'Coolant pressure': Value('float64'), 'lub oil temp': Value('float64'), 'Coolant temp': Value('float64'), 'temp_differential': Value('float64')}
              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 1369, in compute_config_parquet_and_info_response
                  parquet_operations, partial, estimated_dataset_info = stream_convert_to_parquet(
                                                                        ~~~~~~~~~~~~~~~~~~~~~~~~~^
                      builder, max_dataset_size_bytes=max_dataset_size_bytes
                      ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                  )
                  ^
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 948, in stream_convert_to_parquet
                  builder._prepare_split(split_generator=splits_generators[split], file_format="parquet")
                  ~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1683, in _prepare_split
                  for job_id, done, content in self._prepare_split_single(
                                               ~~~~~~~~~~~~~~~~~~~~~~~~~~^
                      gen_kwargs=gen_kwargs, job_id=job_id, **_prepare_split_args
                      ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                  ):
                  ^
                File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1839, in _prepare_split_single
                  raise DatasetGenerationCastError.from_cast_error(
                  ...<4 lines>...
                  )
              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 1 new columns ({'Engine Condition'}) and 1 missing columns ({'temp_differential'}).
              
              This happened while the csv dataset builder was generating data using
              
              hf://datasets/noormd100/predictive-maintenance-data/engine_data.csv (at revision d14f3ae5fff68a022c75b93f99d9379fd99550f4), ['hf://datasets/noormd100/predictive-maintenance-data@d14f3ae5fff68a022c75b93f99d9379fd99550f4/Xtest.csv', 'hf://datasets/noormd100/predictive-maintenance-data@d14f3ae5fff68a022c75b93f99d9379fd99550f4/Xtrain.csv', 'hf://datasets/noormd100/predictive-maintenance-data@d14f3ae5fff68a022c75b93f99d9379fd99550f4/engine_data.csv', 'hf://datasets/noormd100/predictive-maintenance-data@d14f3ae5fff68a022c75b93f99d9379fd99550f4/ytest.csv', 'hf://datasets/noormd100/predictive-maintenance-data@d14f3ae5fff68a022c75b93f99d9379fd99550f4/ytrain.csv']
              
              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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Engine rpm
int64
Lub oil pressure
float64
Fuel pressure
float64
Coolant pressure
float64
lub oil temp
float64
Coolant temp
float64
temp_differential
float64
634
2.61126
10.453517
2.771041
75.86364
79.245834
3.382194
856
4.04384
5.829366
2.460446
73.860133
71.047078
-2.813054
814
4.073486
5.25712
1.866571
81.84007
76.715591
-5.124479
379
2.724639
4.712955
1.981593
77.09226
76.106727
-0.985533
868
2.672809
5.273917
1.905387
78.475478
72.088361
-6.387116
486
2.751187
4.981189
1.947335
77.915084
82.366213
4.451129
584
2.017893
7.132055
2.591518
75.530132
76.892572
1.36244
642
3.9584
6.737429
1.969273
77.925034
66.415888
-11.509146
1,041
4.521053
6.210473
3.187334
79.197006
71.817446
-7.37956
1,427
2.843245
4.407384
2.191826
75.031977
78.144296
3.112319
1,123
3.211094
5.409431
1.711328
78.549739
91.426048
12.876309
965
5.528486
15.001236
1.98097
77.003742
81.298834
4.295093
486
3.98722
10.195593
2.41434
77.262093
80.299991
3.037899
579
1.883619
7.229599
2.422351
75.585566
66.912858
-8.672709
690
4.396677
4.546554
4.79766
77.070856
86.781604
9.710748
707
2.823438
10.330139
2.366586
78.438727
68.779584
-9.659142
499
4.237938
5.19752
1.561667
76.660087
83.861419
7.201332
700
2.946622
5.100845
2.015737
77.140404
74.759147
-2.381257
789
3.967424
8.73506
1.681298
77.01658
79.795167
2.778587
1,018
4.238126
8.273003
1.617142
77.053007
78.434893
1.381886
414
2.959878
9.779071
2.704704
75.193618
70.866775
-4.326843
954
2.016859
3.514317
2.123193
78.44476
74.049494
-4.395265
1,200
2.584647
7.104494
1.439068
78.971899
76.239123
-2.732777
723
2.847779
18.21288
3.116209
77.298042
88.598069
11.300027
937
3.541316
10.704341
2.888997
76.600056
72.102083
-4.497973
474
3.812962
13.472693
1.666002
77.838465
74.424184
-3.41428
1,484
4.695227
7.098034
1.33657
74.223201
68.957024
-5.266176
1,119
3.223373
7.793733
1.689749
77.653993
82.166274
4.512281
692
2.198147
6.763849
2.909702
73.582929
71.041773
-2.541156
1,011
5.085095
5.451618
1.3622
83.722624
74.444864
-9.27776
697
4.58614
5.980066
1.411176
76.482926
79.626088
3.143162
563
4.61394
6.511851
1.640371
73.730509
74.400183
0.669674
882
3.981534
4.610832
4.091422
78.324789
80.388539
2.063749
919
2.524388
5.262508
1.560854
75.0724
77.914513
2.842113
508
2.649771
13.77961
2.124557
76.951287
73.155234
-3.796053
576
3.634043
3.993163
2.701828
75.820912
84.370682
8.54977
625
3.347637
8.21048
2.389763
77.431721
74.826085
-2.605636
1,320
2.460606
6.232507
1.655347
76.172532
80.888912
4.71638
1,065
2.980682
7.989947
2.358523
75.667198
74.257403
-1.409795
383
2.450984
4.52132
1.675139
75.25322
86.457624
11.204403
936
3.520735
6.521204
1.128547
89.241175
81.057789
-8.183386
620
2.364693
6.088848
6.287516
77.442036
86.720841
9.278805
825
2.922278
13.23025
3.007005
76.947925
82.774509
5.826584
1,022
2.661488
5.247992
2.75108
77.459595
81.898691
4.439096
926
4.023769
8.90698
1.753711
78.035056
81.447592
3.412536
758
3.635973
8.612594
4.991061
74.050831
71.843185
-2.207646
972
3.124232
6.554847
1.894652
80.572759
76.736655
-3.836105
857
2.627537
8.841238
1.130811
80.198149
68.386121
-11.812029
487
2.730183
6.292673
2.798752
73.761799
83.355365
9.593566
1,115
2.463577
6.764073
2.657332
76.229416
92.485425
16.256009
515
3.706905
6.084796
4.738294
75.751212
90.412117
14.660905
597
3.493871
4.278638
2.152846
84.691156
76.261661
-8.429495
625
3.517158
9.034119
1.701086
75.064717
80.701022
5.636305
749
3.379445
4.377736
3.016
77.047933
88.563646
11.515713
854
3.046016
6.86104
1.252787
73.392475
87.655168
14.262693
943
2.042534
3.918224
2.121771
76.986203
74.210794
-2.77541
610
3.705538
4.348259
3.50053
76.06661
79.749636
3.683026
749
2.501936
6.059382
2.913548
81.351153
85.476779
4.125627
610
4.2298
5.423975
3.072547
76.692504
79.418284
2.72578
349
3.025148
8.33602
2.979573
77.128701
87.039148
9.910447
891
2.850596
8.154001
2.811349
83.800868
76.86181
-6.939057
464
4.664719
6.96606
4.725405
77.456771
79.127255
1.670485
955
2.395127
6.369333
1.982329
74.624433
80.349823
5.72539
771
2.309491
8.236678
4.619532
76.958766
77.399565
0.440799
871
3.191391
9.358875
1.294106
75.356114
80.564482
5.208368
1,052
3.541473
7.53083
1.432205
87.069788
87.813984
0.744195
675
1.932625
6.730167
1.345992
76.570302
82.552358
5.982056
1,034
2.199228
13.756577
2.151955
75.032227
86.255252
11.223025
613
2.306297
5.756438
1.761585
74.932022
78.07323
3.141209
658
2.613013
7.390182
3.069503
76.342558
87.847442
11.504884
884
2.286296
11.478891
2.494915
76.98549
80.892102
3.906612
874
2.707494
7.566031
2.025857
75.234218
71.241471
-3.992748
768
3.930076
8.669401
1.477826
76.457608
74.763685
-1.693923
509
4.205848
4.837473
2.154953
77.518505
77.975902
0.457396
1,101
3.768244
7.603122
2.460418
77.582597
86.8136
9.231003
712
2.488928
6.077248
2.020301
76.521619
87.466333
10.944714
1,538
1.88755
8.339654
1.192507
76.501763
84.450975
7.949212
396
3.502444
11.759858
1.726093
77.975622
77.278335
-0.697287
479
4.612233
6.27422
4.158132
81.535353
81.038839
-0.496514
651
3.033
5.965319
2.428607
77.4185
79.098577
1.680077
1,169
3.151479
10.445171
2.762797
74.082075
77.768837
3.686762
441
5.480847
2.612642
2.707713
78.002638
75.551796
-2.450842
929
1.937725
5.647741
1.166759
76.458844
78.046233
1.587389
1,411
3.518329
4.158887
2.044416
78.023885
86.243027
8.219141
606
1.793986
8.889421
1.372721
75.714098
75.842171
0.128073
409
2.279944
6.168619
2.689319
77.633378
73.99291
-3.640467
362
2.690016
9.815306
1.624894
77.981632
83.934359
5.952727
453
3.079325
8.347691
1.807234
77.366539
86.845918
9.479379
704
4.716561
7.273391
2.147282
75.490298
73.268722
-2.221576
680
2.64324
3.488218
1.436857
77.405501
73.270345
-4.135155
1,050
4.727144
3.978103
1.046323
76.382623
83.19783
6.815208
467
2.293461
6.479747
1.576227
78.345701
68.356809
-9.988892
768
3.823979
7.787524
1.37531
80.64719
77.86305
-2.78414
896
2.726268
4.944198
3.175728
79.493723
83.055968
3.562245
452
4.826599
7.299444
3.153482
74.907397
82.747062
7.839665
547
2.258771
6.162558
2.648198
83.885334
76.170602
-7.714732
1,406
4.14821
4.905387
1.242844
83.809399
89.864285
6.054886
694
1.757083
7.696475
3.390889
78.944416
88.181948
9.237532
498
4.273981
5.117908
2.016983
74.529863
87.953473
13.42361
880
2.99093
7.762248
1.817569
75.969231
80.533924
4.564693
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