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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 3 new columns ({'lub oil temp', 'Engine Condition', 'Coolant pressure'}) and 3 missing columns ({'temp_diff', 'rpm_pressure_ratio', 'pressure_diff'}).

This happened while the csv dataset builder was generating data using

hf://datasets/Rajanan/ds-predictive-engine-maintenance-v1/engine_data.csv (at revision 5efeb8f9fdfcff2e445f03a053b4b8e668428a29), [/tmp/hf-datasets-cache/medium/datasets/30017426496806-config-parquet-and-info-Rajanan-ds-predictive-eng-c69e5058/hub/datasets--Rajanan--ds-predictive-engine-maintenance-v1/snapshots/5efeb8f9fdfcff2e445f03a053b4b8e668428a29/Xtest.csv (origin=hf://datasets/Rajanan/ds-predictive-engine-maintenance-v1@5efeb8f9fdfcff2e445f03a053b4b8e668428a29/Xtest.csv), /tmp/hf-datasets-cache/medium/datasets/30017426496806-config-parquet-and-info-Rajanan-ds-predictive-eng-c69e5058/hub/datasets--Rajanan--ds-predictive-engine-maintenance-v1/snapshots/5efeb8f9fdfcff2e445f03a053b4b8e668428a29/Xtrain.csv (origin=hf://datasets/Rajanan/ds-predictive-engine-maintenance-v1@5efeb8f9fdfcff2e445f03a053b4b8e668428a29/Xtrain.csv), /tmp/hf-datasets-cache/medium/datasets/30017426496806-config-parquet-and-info-Rajanan-ds-predictive-eng-c69e5058/hub/datasets--Rajanan--ds-predictive-engine-maintenance-v1/snapshots/5efeb8f9fdfcff2e445f03a053b4b8e668428a29/engine_data.csv (origin=hf://datasets/Rajanan/ds-predictive-engine-maintenance-v1@5efeb8f9fdfcff2e445f03a053b4b8e668428a29/engine_data.csv), /tmp/hf-datasets-cache/medium/datasets/30017426496806-config-parquet-and-info-Rajanan-ds-predictive-eng-c69e5058/hub/datasets--Rajanan--ds-predictive-engine-maintenance-v1/snapshots/5efeb8f9fdfcff2e445f03a053b4b8e668428a29/ytest.csv (origin=hf://datasets/Rajanan/ds-predictive-engine-maintenance-v1@5efeb8f9fdfcff2e445f03a053b4b8e668428a29/ytest.csv), /tmp/hf-datasets-cache/medium/datasets/30017426496806-config-parquet-and-info-Rajanan-ds-predictive-eng-c69e5058/hub/datasets--Rajanan--ds-predictive-engine-maintenance-v1/snapshots/5efeb8f9fdfcff2e445f03a053b4b8e668428a29/ytrain.csv (origin=hf://datasets/Rajanan/ds-predictive-engine-maintenance-v1@5efeb8f9fdfcff2e445f03a053b4b8e668428a29/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/python3.12/site-packages/datasets/builder.py", line 1890, in _prepare_split_single
                  writer.write_table(table)
                File "/usr/local/lib/python3.12/site-packages/datasets/arrow_writer.py", line 760, 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
              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, "' + 1152
              to
              {'Engine rpm': Value('int64'), 'Lub oil pressure': Value('float64'), 'Fuel pressure': Value('float64'), 'Coolant temp': Value('float64'), 'pressure_diff': Value('float64'), 'temp_diff': Value('float64'), 'rpm_pressure_ratio': 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 1347, 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 980, in convert_to_parquet
                  builder.download_and_prepare(
                File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 884, in download_and_prepare
                  self._download_and_prepare(
                File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 947, in _download_and_prepare
                  self._prepare_split(split_generator, **prepare_split_kwargs)
                File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1739, 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 1892, 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 3 new columns ({'lub oil temp', 'Engine Condition', 'Coolant pressure'}) and 3 missing columns ({'temp_diff', 'rpm_pressure_ratio', 'pressure_diff'}).
              
              This happened while the csv dataset builder was generating data using
              
              hf://datasets/Rajanan/ds-predictive-engine-maintenance-v1/engine_data.csv (at revision 5efeb8f9fdfcff2e445f03a053b4b8e668428a29), [/tmp/hf-datasets-cache/medium/datasets/30017426496806-config-parquet-and-info-Rajanan-ds-predictive-eng-c69e5058/hub/datasets--Rajanan--ds-predictive-engine-maintenance-v1/snapshots/5efeb8f9fdfcff2e445f03a053b4b8e668428a29/Xtest.csv (origin=hf://datasets/Rajanan/ds-predictive-engine-maintenance-v1@5efeb8f9fdfcff2e445f03a053b4b8e668428a29/Xtest.csv), /tmp/hf-datasets-cache/medium/datasets/30017426496806-config-parquet-and-info-Rajanan-ds-predictive-eng-c69e5058/hub/datasets--Rajanan--ds-predictive-engine-maintenance-v1/snapshots/5efeb8f9fdfcff2e445f03a053b4b8e668428a29/Xtrain.csv (origin=hf://datasets/Rajanan/ds-predictive-engine-maintenance-v1@5efeb8f9fdfcff2e445f03a053b4b8e668428a29/Xtrain.csv), /tmp/hf-datasets-cache/medium/datasets/30017426496806-config-parquet-and-info-Rajanan-ds-predictive-eng-c69e5058/hub/datasets--Rajanan--ds-predictive-engine-maintenance-v1/snapshots/5efeb8f9fdfcff2e445f03a053b4b8e668428a29/engine_data.csv (origin=hf://datasets/Rajanan/ds-predictive-engine-maintenance-v1@5efeb8f9fdfcff2e445f03a053b4b8e668428a29/engine_data.csv), /tmp/hf-datasets-cache/medium/datasets/30017426496806-config-parquet-and-info-Rajanan-ds-predictive-eng-c69e5058/hub/datasets--Rajanan--ds-predictive-engine-maintenance-v1/snapshots/5efeb8f9fdfcff2e445f03a053b4b8e668428a29/ytest.csv (origin=hf://datasets/Rajanan/ds-predictive-engine-maintenance-v1@5efeb8f9fdfcff2e445f03a053b4b8e668428a29/ytest.csv), /tmp/hf-datasets-cache/medium/datasets/30017426496806-config-parquet-and-info-Rajanan-ds-predictive-eng-c69e5058/hub/datasets--Rajanan--ds-predictive-engine-maintenance-v1/snapshots/5efeb8f9fdfcff2e445f03a053b4b8e668428a29/ytrain.csv (origin=hf://datasets/Rajanan/ds-predictive-engine-maintenance-v1@5efeb8f9fdfcff2e445f03a053b4b8e668428a29/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)

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.

Engine rpm
int64
Lub oil pressure
float64
Fuel pressure
float64
Coolant temp
float64
pressure_diff
float64
temp_diff
float64
rpm_pressure_ratio
float64
634
2.61126
10.453517
79.245834
7.682476
3.382194
60.64944
856
4.04384
5.829366
71.047078
3.36892
-2.813054
146.842703
814
4.073486
5.25712
76.715591
3.39055
-5.124479
154.837593
379
2.724639
4.712955
76.106727
2.731362
-0.985533
80.416614
868
2.672809
5.273917
72.088361
3.368529
-6.387116
164.583529
486
2.751187
4.981189
82.366213
3.033853
4.451129
97.567052
584
2.017893
7.132055
76.892572
4.540537
1.36244
81.883818
642
3.9584
6.737429
66.415888
4.768156
-11.509146
95.288563
1,041
4.521053
6.210473
71.817446
3.02314
-7.37956
167.620045
1,427
2.843245
4.407384
78.144296
2.215559
3.112319
323.774722
1,123
3.211094
5.409431
91.426048
3.698103
12.876309
207.600346
965
5.528486
15.001236
81.298834
13.020266
4.295093
64.32803
486
3.98722
10.195593
80.299991
7.781253
3.037899
47.66765
579
1.883619
7.229599
66.912858
4.807247
-8.672709
80.087423
690
4.396677
4.546554
86.781604
-0.251105
9.710748
151.763254
707
2.823438
10.330139
68.779584
7.963553
-9.659142
68.440508
499
4.237938
5.19752
83.861419
3.635853
7.201332
96.007313
700
2.946622
5.100845
74.759147
3.085108
-2.381257
137.232137
789
3.967424
8.73506
79.795167
7.053762
2.778587
90.325642
1,018
4.238126
8.273003
78.434893
6.655862
1.381886
123.050823
414
2.959878
9.779071
70.866775
7.074367
-4.326843
42.335306
954
2.016859
3.514317
74.049494
1.391123
-4.395265
271.460941
1,200
2.584647
7.104494
76.239123
5.665426
-2.732777
168.907151
723
2.847779
18.21288
88.598069
15.096671
11.300027
39.697179
937
3.541316
10.704341
72.102083
7.815344
-4.497973
87.534574
474
3.812962
13.472693
74.424184
11.806692
-3.41428
35.182272
1,484
4.695227
7.098034
68.957024
5.761465
-5.266176
209.071934
1,119
3.223373
7.793733
82.166274
6.103984
4.512281
143.576882
692
2.198147
6.763849
71.041773
3.854147
-2.541156
102.308591
1,011
5.085095
5.451618
74.444864
4.089417
-9.27776
185.44951
697
4.58614
5.980066
79.626088
4.56889
3.143162
116.553874
563
4.61394
6.511851
74.400183
4.87148
0.669674
86.457735
882
3.981534
4.610832
80.388539
0.51941
2.063749
191.288653
919
2.524388
5.262508
77.914513
3.701653
2.842113
174.631535
508
2.649771
13.77961
73.155234
11.655053
-3.796053
36.866063
576
3.634043
3.993163
84.370682
1.291336
8.54977
144.24651
625
3.347637
8.21048
74.826085
5.820717
-2.605636
76.122211
1,320
2.460606
6.232507
80.888912
4.57716
4.71638
211.792749
1,065
2.980682
7.989947
74.257403
5.631424
-1.409795
133.292485
383
2.450984
4.52132
86.457624
2.846181
11.204403
84.709751
936
3.520735
6.521204
81.057789
5.392657
-8.183386
143.531759
620
2.364693
6.088848
86.720841
-0.198667
9.278805
101.825477
825
2.922278
13.23025
82.774509
10.223245
5.826584
62.357094
1,022
2.661488
5.247992
81.898691
2.496912
4.439096
194.741115
926
4.023769
8.90698
81.447592
7.153269
3.412536
103.963393
758
3.635973
8.612594
71.843185
3.621532
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88.010642
972
3.124232
6.554847
76.736655
4.660196
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148.287187
857
2.627537
8.841238
68.386121
7.710427
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96.932115
487
2.730183
6.292673
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3.493921
9.593566
77.391583
1,115
2.463577
6.764073
92.485425
4.106741
16.256009
164.841483
515
3.706905
6.084796
90.412117
1.346502
14.660905
84.637173
597
3.493871
4.278638
76.261661
2.125791
-8.429495
139.530361
625
3.517158
9.034119
80.701022
7.333033
5.636305
69.182167
749
3.379445
4.377736
88.563646
1.361736
11.515713
171.092983
854
3.046016
6.86104
87.655168
5.608253
14.262693
124.470907
943
2.042534
3.918224
74.210794
1.796453
-2.77541
240.67019
610
3.705538
4.348259
79.749636
0.847729
3.683026
140.28599
749
2.501936
6.059382
85.476779
3.145835
4.125627
123.609943
610
4.2298
5.423975
79.418284
2.351428
2.72578
112.463618
349
3.025148
8.33602
87.039148
5.356447
9.910447
41.866499
891
2.850596
8.154001
76.86181
5.342651
-6.939057
109.271499
464
4.664719
6.96606
79.127255
2.240655
1.670485
66.608658
955
2.395127
6.369333
80.349823
4.387004
5.72539
149.937186
771
2.309491
8.236678
77.399565
3.617145
0.440799
93.605689
871
3.191391
9.358875
80.564482
8.06477
5.208368
93.06673
1,052
3.541473
7.53083
87.813984
6.098625
0.744195
139.692418
675
1.932625
6.730167
82.552358
5.384175
5.982056
100.294675
1,034
2.199228
13.756577
86.255252
11.604622
11.223025
75.164042
613
2.306297
5.756438
78.07323
3.994854
3.141209
106.489441
658
2.613013
7.390182
87.847442
4.320679
11.504884
89.037039
884
2.286296
11.478891
80.892102
8.983976
3.906612
77.010917
874
2.707494
7.566031
71.241471
5.540174
-3.992748
115.516302
768
3.930076
8.669401
74.763685
7.191575
-1.693923
88.587422
509
4.205848
4.837473
77.975902
2.682521
0.457396
105.220196
1,101
3.768244
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86.8136
5.142704
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144.808912
712
2.488928
6.077248
87.466333
4.056947
10.944714
117.158273
1,538
1.88755
8.339654
84.450975
7.147146
7.949212
184.420109
396
3.502444
11.759858
77.278335
10.033765
-0.697287
33.673875
479
4.612233
6.27422
81.038839
2.116088
-0.496514
76.344137
651
3.033
5.965319
79.098577
3.536712
1.680077
109.130783
1,169
3.151479
10.445171
77.768837
7.682374
3.686762
111.917736
441
5.480847
2.612642
75.551796
-0.095071
-2.450842
168.794618
929
1.937725
5.647741
78.046233
4.480982
1.587389
164.490516
1,411
3.518329
4.158887
86.243027
2.114471
8.219141
339.273381
606
1.793986
8.889421
75.842171
7.5167
0.128073
68.170909
409
2.279944
6.168619
73.99291
3.4793
-3.640467
66.303322
362
2.690016
9.815306
83.934359
8.190412
5.952727
36.881169
453
3.079325
8.347691
86.845918
6.540457
9.479379
54.266498
704
4.716561
7.273391
73.268722
5.126109
-2.221576
96.791157
680
2.64324
3.488218
73.270345
2.051362
-4.135155
194.941862
1,050
4.727144
3.978103
83.19783
2.93178
6.815208
263.944827
467
2.293461
6.479747
68.356809
4.90352
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72.070699
768
3.823979
7.787524
77.86305
6.412215
-2.78414
98.619261
896
2.726268
4.944198
83.055968
1.76847
3.562245
181.222491
452
4.826599
7.299444
82.747062
4.145962
7.839665
61.922513
547
2.258771
6.162558
76.170602
3.514359
-7.714732
88.761831
1,406
4.14821
4.905387
89.864285
3.662543
6.054886
286.623615
694
1.757083
7.696475
88.181948
4.305586
9.237532
90.171132
498
4.273981
5.117908
87.953473
3.100925
13.42361
97.305361
880
2.99093
7.762248
80.533924
5.944679
4.564693
113.369207
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