Dataset Preview
Full Screen
The full dataset viewer is not available (click to read why). Only showing a preview of the rows.
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 missing columns ({'failure'})

This happened while the csv dataset builder was generating data using

hf://datasets/ttxy/tabular/test.csv (at revision 7a5acc07f9db8c57080a713c40a3e24484d865c0)

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: int64
              product_code: string
              loading: double
              attribute_0: string
              attribute_1: string
              attribute_2: int64
              attribute_3: int64
              measurement_0: int64
              measurement_1: int64
              measurement_2: int64
              measurement_3: double
              measurement_4: double
              measurement_5: double
              measurement_6: double
              measurement_7: double
              measurement_8: double
              measurement_9: double
              measurement_10: double
              measurement_11: double
              measurement_12: double
              measurement_13: double
              measurement_14: double
              measurement_15: double
              measurement_16: double
              measurement_17: double
              -- schema metadata --
              pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 3375
              to
              {'id': Value(dtype='int64', id=None), 'product_code': Value(dtype='string', id=None), 'loading': Value(dtype='float64', id=None), 'attribute_0': Value(dtype='string', id=None), 'attribute_1': Value(dtype='string', id=None), 'attribute_2': Value(dtype='int64', id=None), 'attribute_3': Value(dtype='int64', id=None), 'measurement_0': Value(dtype='int64', id=None), 'measurement_1': Value(dtype='int64', id=None), 'measurement_2': Value(dtype='int64', id=None), 'measurement_3': Value(dtype='float64', id=None), 'measurement_4': Value(dtype='float64', id=None), 'measurement_5': Value(dtype='float64', id=None), 'measurement_6': Value(dtype='float64', id=None), 'measurement_7': Value(dtype='float64', id=None), 'measurement_8': Value(dtype='float64', id=None), 'measurement_9': Value(dtype='float64', id=None), 'measurement_10': Value(dtype='float64', id=None), 'measurement_11': Value(dtype='float64', id=None), 'measurement_12': Value(dtype='float64', id=None), 'measurement_13': Value(dtype='float64', id=None), 'measurement_14': Value(dtype='float64', id=None), 'measurement_15': Value(dtype='float64', id=None), 'measurement_16': Value(dtype='float64', id=None), 'measurement_17': Value(dtype='float64', id=None), 'failure': 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 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 1 missing columns ({'failure'})
              
              This happened while the csv dataset builder was generating data using
              
              hf://datasets/ttxy/tabular/test.csv (at revision 7a5acc07f9db8c57080a713c40a3e24484d865c0)
              
              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
int64
product_code
string
loading
float64
attribute_0
string
attribute_1
string
attribute_2
int64
attribute_3
int64
measurement_0
int64
measurement_1
int64
measurement_2
int64
measurement_3
float64
measurement_4
float64
measurement_5
float64
measurement_6
float64
measurement_7
float64
measurement_8
float64
measurement_9
float64
measurement_10
float64
measurement_11
float64
measurement_12
float64
measurement_13
float64
measurement_14
float64
measurement_15
float64
measurement_16
float64
measurement_17
float64
failure
int64
0
A
80.1
material_7
material_8
9
5
7
8
4
18.04
12.518
15.748
19.292
11.739
20.155
10.672
15.859
17.594
15.193
15.029
null
13.034
14.684
764.1
0
1
A
84.89
material_7
material_8
9
5
14
3
3
18.213
11.54
17.717
17.893
12.748
17.889
12.448
17.947
17.915
11.755
14.732
15.425
14.395
15.631
682.057
0
2
A
82.43
material_7
material_8
9
5
12
1
5
18.057
11.652
16.738
18.24
12.718
18.288
12.715
15.607
null
13.798
16.711
18.631
14.094
17.946
663.376
0
3
A
101.07
material_7
material_8
9
5
13
2
6
17.295
11.188
18.576
18.339
12.583
19.06
12.471
16.346
18.377
10.02
15.25
15.562
16.154
17.172
826.282
0
4
A
188.06
material_7
material_8
9
5
9
2
8
19.346
12.95
16.99
15.746
11.306
18.093
10.337
17.082
19.932
12.428
16.182
12.76
13.153
16.412
579.885
0
5
A
75.35
material_7
material_8
9
5
11
4
0
17.564
13.721
16.594
null
11.592
20.81
10.622
14.904
19.107
13.327
15.354
19.251
null
17.625
832.902
0
6
A
161.71
material_7
material_8
9
5
12
2
4
17.303
12.643
17.476
17.679
12.957
17.916
11.37
17.714
19.924
11.56
16.653
17.734
null
16.637
684.438
1
7
A
177.92
material_7
material_8
9
5
4
8
8
17.062
13.634
17.879
15.894
11.029
18.643
10.254
16.449
20.478
12.207
15.624
16.968
15.176
17.231
684
1
8
A
109.5
material_7
material_8
9
5
9
6
5
18.111
11.886
17.354
18.558
11.54
19.887
11.557
15.965
19.604
14.091
15.674
13.327
13.535
15.408
null
0
9
A
98.72
material_7
material_8
9
5
10
4
7
18.945
12.249
17.298
18.482
11.298
19.011
10.384
15.237
18.427
12.635
14.318
14.327
12.867
null
null
0
10
A
140.36
material_7
material_8
9
5
10
3
6
null
10.827
16.236
16.836
13.058
18.868
12.146
16.483
20.054
10.37
14.873
16.819
14.623
15.121
637.067
0
11
A
175.38
material_7
material_8
9
5
7
3
2
17.029
11.507
18.377
16.338
10.019
20.242
11.309
16.31
18.959
11.52
14.659
15.355
15.175
15.829
792.591
1
12
A
232.58
material_7
material_8
9
5
9
0
6
19.107
12.056
17.69
17.204
13.086
20.228
11.528
15.631
19.709
14.616
14.801
14.75
12.762
16.226
858.722
0
13
A
159.19
material_7
material_8
9
5
6
9
10
19.71
12.031
16.867
18.527
10.917
20.341
9.902
14.803
16.473
10.424
16.132
14.877
15.291
13.013
798.38
1
14
A
196.51
material_7
material_8
9
5
10
4
10
18.982
10.843
16.716
17.409
12.387
18.819
12.103
17.901
17.336
12.665
17.08
15.169
13.471
13.78
661.16
0
15
A
106.43
material_7
material_8
9
5
8
5
9
19.416
12.271
18.457
15.69
13.036
20.512
11.904
13.723
null
13.167
14.823
14.969
14.389
16.608
888.257
0
16
A
93.72
material_7
material_8
9
5
10
5
6
16.807
13.008
17.602
17.234
11.767
19.225
11.734
15.603
19.301
null
15.205
17.074
15.488
16.893
757.781
0
17
A
72.72
material_7
material_8
9
5
21
6
3
17.397
12.777
18.701
15.278
11.261
18.415
11.707
14.205
19.845
9.798
16.055
15.82
16.836
15.646
692.561
0
18
A
86.18
material_7
material_8
9
5
11
6
3
18.344
10.736
16.635
17.777
12.407
18.683
11.203
17.655
19.825
13.055
16.385
16.884
14.036
16.241
654.072
0
19
A
109.24
material_7
material_8
9
5
11
4
4
17.641
12.977
18.353
17.874
12.877
17.797
9.459
15.392
21.825
11.214
15.139
17.359
13.791
16.212
null
0
20
A
129.09
material_7
material_8
9
5
6
9
15
18.035
10.175
16.386
18.383
11.193
19.573
10.164
15.846
19.582
null
14.686
17.231
13.827
17.801
685.862
0
21
A
82.16
material_7
material_8
9
5
6
1
4
18.843
11.915
17.442
17.855
13.384
18.585
12.452
16.514
18.423
11.95
15.949
15.589
14.923
18.714
738.721
0
22
A
155.62
material_7
material_8
9
5
8
3
5
17.79
11.435
18.873
17.863
14.084
20.294
11.487
14.801
20.184
10.288
13.19
14.305
14.985
17.27
967.106
0
23
A
118.12
material_7
material_8
9
5
15
2
12
17.894
11.105
18.077
18.758
10.785
20.167
10.953
16.132
18.732
13.73
13.276
14.083
13.104
13.739
845.997
0
24
A
100.48
material_7
material_8
9
5
4
7
10
16.926
11.884
16.17
null
12.296
18.481
9.435
16.915
17.916
10.268
15.275
17.929
14.645
14.692
594.86
0
25
A
96.83
material_7
material_8
9
5
11
3
9
19.342
12.497
16.404
18.016
12.084
18.802
10.087
15.811
null
11.77
16.085
16.575
14.946
18.145
674.403
0
26
A
223.36
material_7
material_8
9
5
9
4
11
18.801
13.045
16.376
18.569
12.231
18.92
12.328
17.217
18
10.212
14.46
14.154
14.642
16.709
708.199
0
27
A
128.17
material_7
material_8
9
5
14
4
6
16.895
11.73
14.913
17.455
null
18.342
11.922
16.55
20.302
null
16.247
14.349
15.411
17.149
480.174
0
28
A
93.06
material_7
material_8
9
5
10
2
1
18.202
11.614
16.791
18.039
null
18.983
12.559
17.082
null
11.491
13.514
16.918
null
19.218
725.159
0
29
A
91.5
material_7
material_8
9
5
17
5
3
16.942
10.986
14.864
16.545
11.389
18.383
11.007
null
20.145
12.685
17.215
17.254
13.775
17.869
471.271
0
30
A
211.44
material_7
material_8
9
5
18
5
9
17.456
12.293
16.308
19.548
12.832
19.113
null
14.725
22.007
12.581
16.657
16.054
12.598
16.993
748.908
0
31
A
102.42
material_7
material_8
9
5
18
3
4
17.041
11.01
18.175
15.471
11.653
16.77
11.897
14.883
20.402
12.817
13.948
16.577
13.717
12.761
521.457
0
32
A
174.02
material_7
material_8
9
5
10
5
5
18.196
13.978
16.917
16.321
11.461
18.841
10.579
15.952
21.591
14.998
15.784
null
13.842
19.473
669.02
0
33
A
186.71
material_7
material_8
9
5
10
3
4
17.58
9.107
15.741
17.843
12.421
19.547
9.666
16.274
19.936
12.326
16.334
18.647
13.182
16.777
645.405
1
34
A
60.66
material_7
material_8
9
5
8
3
6
19.625
11.415
17.454
17.107
11.826
17.866
11.859
16.782
16.55
12.287
16.815
15.656
14.371
20.015
null
0
35
A
182.71
material_7
material_8
9
5
19
8
3
17.886
11.279
17.647
18.048
11.491
18.681
10.905
15.34
20.354
10.478
16.305
18.725
13.322
14.712
707.166
0
36
A
114.44
material_7
material_8
9
5
8
3
5
19.15
9.933
17.079
14.043
11.492
18.789
11.176
null
19.644
14.161
15.801
14.763
13.633
16.356
553.578
0
37
A
88
material_7
material_8
9
5
19
7
1
18.39
13.55
19.053
17.408
11.499
20.23
12.245
17.131
21.899
13.434
14.476
14.926
16.347
18.029
927.606
0
38
A
103.49
material_7
material_8
9
5
13
2
3
17.11
13.184
16.659
17.814
10.628
18.602
8.946
16.729
21.136
null
15.107
17.436
15.646
15.887
641.698
0
39
A
144.15
material_7
material_8
9
5
16
3
1
17.172
12.303
15.873
17.606
13.055
18.206
12.042
16.342
22.389
13.931
15.705
13.341
15.226
18.369
606.519
1
40
A
136.29
material_7
material_8
9
5
8
7
3
16.704
11.588
16.984
16.009
11.897
19.872
10.626
15.983
18.572
null
15.386
18.777
17.379
18.873
719.904
0
41
A
138.41
material_7
material_8
9
5
13
2
4
18.086
12.572
16.743
17.572
11.886
18.191
10.801
14.658
18.056
11.531
15.423
15.472
14.067
null
631.067
0
42
A
98.01
material_7
material_8
9
5
14
3
0
16.973
11.512
16.375
17.419
12.516
null
14.034
16.85
17.642
14.419
15.228
14.023
null
15.741
811.245
0
43
A
178.81
material_7
material_8
9
5
11
4
3
17.742
12.331
15.535
null
13.735
18.296
11.625
15.31
22.941
10.436
15.561
17.667
15.048
17.63
631.167
0
44
A
191.18
material_7
material_8
9
5
5
4
12
19.052
11.209
17.071
18.044
10.32
19.2
11.47
15.342
18.671
12.935
15.797
13.664
null
17.74
682.064
0
45
A
211.2
material_7
material_8
9
5
8
9
3
17.626
11.935
17.463
16.413
12.673
20.174
11.097
16.323
20.621
11.157
15.937
17.057
15.079
16.129
807.674
1
46
A
164.47
material_7
material_8
9
5
11
3
5
19.877
12.02
18.826
16.775
10.967
18.668
11.874
16.149
19.59
13.101
15.133
18.654
16.409
17.779
740.611
0
47
A
215.05
material_7
material_8
9
5
14
7
7
17.873
13.361
19.204
15.899
11.85
19.41
11.08
15.789
15.495
11.044
15.269
14.92
15.927
13.917
839.468
0
48
A
228.32
material_7
material_8
9
5
8
1
4
17.252
11.486
17.373
15.98
11.066
18.722
9.662
null
20.762
12.28
15.584
16.659
15.018
null
630.769
0
49
A
150.48
material_7
material_8
9
5
13
3
2
18.057
11.393
17.064
16.497
11.744
21.543
11.946
17.513
17.948
12.866
14.786
15.201
13.501
16.626
860.434
0
50
A
158.69
material_7
material_8
9
5
12
2
10
17.699
13.003
17.998
17.933
11.362
19.24
11.195
16.862
20.949
14.83
17.48
15.492
16.232
19.039
790.748
0
51
A
145.07
material_7
material_8
9
5
13
7
6
18.231
11.04
17.056
17.351
11.452
20.053
11.134
16.575
18.205
null
null
14.412
13.364
18.958
754.881
1
52
A
143.74
material_7
material_8
9
5
4
5
3
17.75
10.414
18.662
17.593
10.751
18.071
13.838
14.944
null
11.878
13.309
20.071
17.032
14.628
null
0
53
A
157.84
material_7
material_8
9
5
11
2
4
17.981
12.07
16.252
17.582
10.906
18.218
10.922
17.087
19.037
12.986
16.549
15.746
12.546
16.901
571.376
0
54
A
72.96
material_7
material_8
9
5
12
3
1
18.144
11.998
16.155
17.827
11.644
20.021
12.099
16.749
18.264
11.824
15.857
15.285
14.053
13.88
729.64
0
55
A
110.55
material_7
material_8
9
5
10
4
4
17.214
11.73
null
19.267
null
18.428
10.875
16.42
20.386
13.123
15.503
18.642
12.356
13.209
843.56
1
56
A
141.03
material_7
material_8
9
5
6
4
3
16.673
11.794
16.51
19.619
11.651
18.242
13.125
17.157
21.126
11.224
15.377
17.848
15.367
18.183
659.105
0
57
A
64.74
material_7
material_8
9
5
12
6
3
15.426
11.818
16.432
17.398
12.744
20.018
12.719
15.383
22.3
12.265
16.975
null
18.422
16.404
null
0
58
A
79.05
material_7
material_8
9
5
11
4
0
18.056
12.116
16.787
16.608
11.227
18.714
null
16.158
19.053
12.255
15.305
17.135
12.486
15.15
625.406
0
59
A
195.96
material_7
material_8
9
5
25
2
1
18.452
12.046
15.419
18.309
11.527
18.17
11.126
16.359
19.096
10.705
null
14.521
15.497
15.382
551.914
1
60
A
88.66
material_7
material_8
9
5
11
4
2
17.091
10.692
17.459
15.144
11.661
18.25
12.413
15.903
null
14.214
14.843
15.632
12.208
16.404
579.645
0
61
A
105.98
material_7
material_8
9
5
6
6
6
17.523
11.637
17.729
18.822
11.299
19.631
11.93
15.86
21.36
null
15.781
17.776
14.927
16.554
806.565
0
62
A
136.34
material_7
material_8
9
5
12
4
6
17.969
10.95
18.04
17.987
11.091
19.325
13.163
17.537
17.562
12.44
16.026
15.696
14.671
16.132
763.738
0
63
A
105.61
material_7
material_8
9
5
7
5
4
18.213
null
15.102
17.087
10.576
20.244
10.62
19.07
null
11.756
16.932
19.095
15.759
17.421
648.561
0
64
A
94.1
material_7
material_8
9
5
12
6
3
18.177
11.557
16.195
19.583
10.439
18.71
12.638
18.089
null
11.413
14.911
18.792
18.037
14.851
null
0
65
A
104.35
material_7
material_8
9
5
8
9
5
18.192
12.263
18.474
17.286
9.978
18.295
12.783
17.128
18.363
10.714
14.357
19.056
12.554
14.37
682.616
0
66
A
107.14
material_7
material_8
9
5
3
8
7
19.201
11.162
17.632
17.445
11.38
19.66
12.031
16.226
20.429
13.177
16.848
18.041
13.449
16.51
760.846
0
67
A
102.38
material_7
material_8
9
5
3
0
5
19.938
12.676
16.561
17.819
10.487
20.483
11.394
null
17.839
12.666
15.586
15.325
14.906
16.323
null
1
68
A
128.68
material_7
material_8
9
5
19
4
5
18.741
13.006
17.494
18.608
11.552
18.559
11.528
17.293
18.637
9.173
null
12.244
12.146
16.049
730.396
0
69
A
197.46
material_7
material_8
9
5
13
1
9
19.446
12.972
17.408
19.551
11.97
18.505
10.25
15.944
18.628
13.395
14.995
15.386
15.576
16.995
755.809
1
70
A
135.57
material_7
material_8
9
5
9
1
7
18.289
10.581
17.343
17.915
12.824
19.46
12.629
16.729
22.138
11.264
14.206
19.354
16.608
16.882
768.254
0
71
A
198.35
material_7
material_8
9
5
7
1
3
16.313
11.81
17.934
17.616
11.897
18.579
12.268
17.89
20.311
12.393
15.177
12.767
12.667
14.717
722.617
0
72
A
152.09
material_7
material_8
9
5
19
5
2
16.772
10.267
17.527
16.924
null
17.361
10.104
15.674
20.985
12.226
17.838
14.615
15.915
18.154
509.304
1
73
A
156.56
material_7
material_8
9
5
6
5
9
18.417
11.879
17.304
16.814
12.242
18.148
11.866
16.386
20.387
12.569
null
16.691
16.448
15.265
640.662
0
74
A
145.27
material_7
material_8
9
5
7
2
5
18.5
12.445
15.312
16.492
10.501
20.221
12.413
16.912
null
12.608
15.66
14.637
12.733
14.428
636.96
1
75
A
111.38
material_7
material_8
9
5
14
1
2
17.587
11.801
19.027
15.445
12.577
19.383
11.926
16.472
22.005
12.7
null
19.744
15.352
15.584
809.012
0
76
A
138.25
material_7
material_8
9
5
16
2
8
18.554
11.465
19.248
15.828
9.946
17.999
11.948
14.99
18.849
12.072
13.927
18.485
11.906
13.578
655.256
0
77
A
133.41
material_7
material_8
9
5
7
10
3
17.141
null
17.207
15.864
12.826
19.454
12.236
null
16.379
14.191
16.844
14.635
12.993
null
735.877
0
78
A
87.26
material_7
material_8
9
5
5
5
10
17.887
10.029
16.357
17.981
10.356
20.458
null
17.331
19.603
13.419
null
14.879
12.963
null
718.723
0
79
A
152.48
material_7
material_8
9
5
11
12
4
17.458
11.969
16.151
18.566
10.35
19.746
10.616
16.522
16.994
12.912
14.103
17.982
15.197
18.354
695.779
0
80
A
144.88
material_7
material_8
9
5
11
1
2
16.707
11.393
16.165
17.292
10.959
19.149
12.383
16.623
18.916
13.887
15.694
15.91
13.706
16.729
622.716
0
81
A
136.07
material_7
material_8
9
5
11
3
5
18.87
12.229
15.476
17.28
10.672
18.893
12.976
16.461
null
11.912
15.998
19.227
17.103
null
566.318
0
82
A
103.03
material_7
material_8
9
5
6
5
8
18.732
12.863
17.289
18.993
12.52
19.336
12.214
16.722
17.412
13.935
16.3
15.989
14.773
17.327
810.747
0
83
A
55.29
material_7
material_8
9
5
8
0
4
17.492
13.157
19.336
16.516
11.734
19.707
10.777
16.76
18.229
14.523
14.6
15.347
13.242
15.565
880.573
0
84
A
189.2
material_7
material_8
9
5
10
3
3
18.083
11.567
17.054
17.717
11.884
18.794
10.369
14.962
19.661
null
15.547
17.865
13.184
null
685.746
0
85
A
119.28
material_7
material_8
9
5
15
1
1
18.875
11.419
18.822
18.445
11.581
19.228
12.595
17.159
18.116
13.804
16.243
14.974
11.346
15.177
833.558
0
86
A
63.39
material_7
material_8
9
5
5
10
5
19.941
11.821
18.417
18.197
11.852
18.046
11.848
18.238
18.417
12.672
16.369
16.6
null
19.121
725.064
0
87
A
148.04
material_7
material_8
9
5
8
2
9
18.444
11.883
18.433
18.091
12.47
19.976
10.183
17.182
16.354
9.302
15.393
16.724
17.032
17.465
888.393
0
88
A
98.77
material_7
material_8
9
5
8
5
3
18.648
10.577
17.9
16.94
12.392
18.347
11.292
16.142
21.241
11.72
15.201
12.082
12.94
17.404
678.734
0
89
A
149.7
material_7
material_8
9
5
11
4
8
19.803
10.29
null
18.374
null
17.473
13.55
18.695
21.765
11.659
15.102
14.622
15.88
18.269
595.175
0
90
A
118.16
material_7
material_8
9
5
12
6
4
17.176
12.2
17.904
20.147
10.261
20.044
null
14.556
18.039
null
15.163
14.882
14.037
14.706
866.091
0
91
A
171.21
material_7
material_8
9
5
11
4
5
17.02
11.797
16.475
17.853
10.895
20.342
11.052
16.458
19.115
12.487
15.236
14.76
14.05
16.661
752.42
0
92
A
130.66
material_7
material_8
9
5
9
2
2
18.797
12.437
19.376
18.224
12.559
19.67
9.479
null
20.365
12.564
13.854
14.766
16.58
14.562
936.198
1
93
A
132.48
material_7
material_8
9
5
15
8
5
17.284
11.451
18.255
17.137
12.382
18.399
11.309
17.282
19.334
11.978
13.829
15.159
14.007
17.324
722.006
0
94
A
127.43
material_7
material_8
9
5
11
4
3
19.543
10.925
16.295
16.699
11.161
19.045
12.451
15.294
19.426
9.439
16.749
14.07
14.589
15.176
605.448
0
95
A
176.23
material_7
material_8
9
5
3
3
5
18.95
12.985
17.003
16.989
10.987
18.407
11.024
16.921
18.462
11.869
15.342
15.995
12.613
14.991
631.304
1
96
A
82.58
material_7
material_8
9
5
9
6
7
17.323
10.73
18.033
16.578
13.128
18.257
9.9
15.659
20.923
14.235
17.031
15.713
9.869
18
690.442
0
97
A
173.41
material_7
material_8
9
5
5
7
4
18.03
11.915
16.569
18.839
13.203
19.597
11.956
null
17.175
14.902
15.292
13.431
12.688
15.612
788.538
0
98
A
149.79
material_7
material_8
9
5
21
1
3
18.197
12.151
18.463
null
10.428
18.45
13.658
14.828
18.225
12.931
14.433
14.378
13.83
null
728.899
0
99
A
103.16
material_7
material_8
9
5
11
2
1
18.693
12.105
17.347
null
13.083
18.063
10.086
15.706
20.944
12.236
14.775
17.291
15.209
17.805
643.647
1
End of preview.
README.md exists but content is empty. Use the Edit dataset card button to edit it.
Downloads last month
37