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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 ({'InvoiceNo', 'InvoiceDate', 'UnitPrice', 'Country', 'Description', 'Quantity', 'CustomerID', 'StockCode'}) and 10 missing columns ({'total_bedrooms', 'population', 'housing_median_age', 'households', 'latitude', 'longitude', 'median_income', 'ocean_proximity', 'median_house_value', 'total_rooms'}).
This happened while the csv dataset builder was generating data using
hf://datasets/habedi/feature-factory-datasets/online_retail.csv (at revision 71f9d0f2faea38db5645f5b8aff519e8ce2c0421)
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 1870, in _prepare_split_single
writer.write_table(table)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/arrow_writer.py", line 622, 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 2292, in table_cast
return cast_table_to_schema(table, schema)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2240, in cast_table_to_schema
raise CastError(
datasets.table.CastError: Couldn't cast
InvoiceNo: string
StockCode: string
Description: string
Quantity: int64
InvoiceDate: string
UnitPrice: double
CustomerID: double
Country: string
-- schema metadata --
pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 1210
to
{'longitude': Value(dtype='float64', id=None), 'latitude': Value(dtype='float64', id=None), 'housing_median_age': Value(dtype='float64', id=None), 'total_rooms': Value(dtype='float64', id=None), 'total_bedrooms': Value(dtype='float64', id=None), 'population': Value(dtype='float64', id=None), 'households': Value(dtype='float64', id=None), 'median_income': Value(dtype='float64', id=None), 'median_house_value': Value(dtype='float64', id=None), 'ocean_proximity': Value(dtype='string', 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 1438, 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 1050, in convert_to_parquet
builder.download_and_prepare(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 924, in download_and_prepare
self._download_and_prepare(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1000, 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 1741, 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 1872, 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 ({'InvoiceNo', 'InvoiceDate', 'UnitPrice', 'Country', 'Description', 'Quantity', 'CustomerID', 'StockCode'}) and 10 missing columns ({'total_bedrooms', 'population', 'housing_median_age', 'households', 'latitude', 'longitude', 'median_income', 'ocean_proximity', 'median_house_value', 'total_rooms'}).
This happened while the csv dataset builder was generating data using
hf://datasets/habedi/feature-factory-datasets/online_retail.csv (at revision 71f9d0f2faea38db5645f5b8aff519e8ce2c0421)
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.
longitude
float64 | latitude
float64 | housing_median_age
float64 | total_rooms
float64 | total_bedrooms
float64 | population
float64 | households
float64 | median_income
float64 | median_house_value
float64 | ocean_proximity
string |
|---|---|---|---|---|---|---|---|---|---|
-122.23
| 37.88
| 41
| 880
| 129
| 322
| 126
| 8.3252
| 452,600
|
NEAR BAY
|
-122.22
| 37.86
| 21
| 7,099
| 1,106
| 2,401
| 1,138
| 8.3014
| 358,500
|
NEAR BAY
|
-122.24
| 37.85
| 52
| 1,467
| 190
| 496
| 177
| 7.2574
| 352,100
|
NEAR BAY
|
-122.25
| 37.85
| 52
| 1,274
| 235
| 558
| 219
| 5.6431
| 341,300
|
NEAR BAY
|
-122.25
| 37.85
| 52
| 1,627
| 280
| 565
| 259
| 3.8462
| 342,200
|
NEAR BAY
|
-122.25
| 37.85
| 52
| 919
| 213
| 413
| 193
| 4.0368
| 269,700
|
NEAR BAY
|
-122.25
| 37.84
| 52
| 2,535
| 489
| 1,094
| 514
| 3.6591
| 299,200
|
NEAR BAY
|
-122.25
| 37.84
| 52
| 3,104
| 687
| 1,157
| 647
| 3.12
| 241,400
|
NEAR BAY
|
-122.26
| 37.84
| 42
| 2,555
| 665
| 1,206
| 595
| 2.0804
| 226,700
|
NEAR BAY
|
-122.25
| 37.84
| 52
| 3,549
| 707
| 1,551
| 714
| 3.6912
| 261,100
|
NEAR BAY
|
-122.26
| 37.85
| 52
| 2,202
| 434
| 910
| 402
| 3.2031
| 281,500
|
NEAR BAY
|
-122.26
| 37.85
| 52
| 3,503
| 752
| 1,504
| 734
| 3.2705
| 241,800
|
NEAR BAY
|
-122.26
| 37.85
| 52
| 2,491
| 474
| 1,098
| 468
| 3.075
| 213,500
|
NEAR BAY
|
-122.26
| 37.84
| 52
| 696
| 191
| 345
| 174
| 2.6736
| 191,300
|
NEAR BAY
|
-122.26
| 37.85
| 52
| 2,643
| 626
| 1,212
| 620
| 1.9167
| 159,200
|
NEAR BAY
|
-122.26
| 37.85
| 50
| 1,120
| 283
| 697
| 264
| 2.125
| 140,000
|
NEAR BAY
|
-122.27
| 37.85
| 52
| 1,966
| 347
| 793
| 331
| 2.775
| 152,500
|
NEAR BAY
|
-122.27
| 37.85
| 52
| 1,228
| 293
| 648
| 303
| 2.1202
| 155,500
|
NEAR BAY
|
-122.26
| 37.84
| 50
| 2,239
| 455
| 990
| 419
| 1.9911
| 158,700
|
NEAR BAY
|
-122.27
| 37.84
| 52
| 1,503
| 298
| 690
| 275
| 2.6033
| 162,900
|
NEAR BAY
|
-122.27
| 37.85
| 40
| 751
| 184
| 409
| 166
| 1.3578
| 147,500
|
NEAR BAY
|
-122.27
| 37.85
| 42
| 1,639
| 367
| 929
| 366
| 1.7135
| 159,800
|
NEAR BAY
|
-122.27
| 37.84
| 52
| 2,436
| 541
| 1,015
| 478
| 1.725
| 113,900
|
NEAR BAY
|
-122.27
| 37.84
| 52
| 1,688
| 337
| 853
| 325
| 2.1806
| 99,700
|
NEAR BAY
|
-122.27
| 37.84
| 52
| 2,224
| 437
| 1,006
| 422
| 2.6
| 132,600
|
NEAR BAY
|
-122.28
| 37.85
| 41
| 535
| 123
| 317
| 119
| 2.4038
| 107,500
|
NEAR BAY
|
-122.28
| 37.85
| 49
| 1,130
| 244
| 607
| 239
| 2.4597
| 93,800
|
NEAR BAY
|
-122.28
| 37.85
| 52
| 1,898
| 421
| 1,102
| 397
| 1.808
| 105,500
|
NEAR BAY
|
-122.28
| 37.84
| 50
| 2,082
| 492
| 1,131
| 473
| 1.6424
| 108,900
|
NEAR BAY
|
-122.28
| 37.84
| 52
| 729
| 160
| 395
| 155
| 1.6875
| 132,000
|
NEAR BAY
|
-122.28
| 37.84
| 49
| 1,916
| 447
| 863
| 378
| 1.9274
| 122,300
|
NEAR BAY
|
-122.28
| 37.84
| 52
| 2,153
| 481
| 1,168
| 441
| 1.9615
| 115,200
|
NEAR BAY
|
-122.27
| 37.84
| 48
| 1,922
| 409
| 1,026
| 335
| 1.7969
| 110,400
|
NEAR BAY
|
-122.27
| 37.83
| 49
| 1,655
| 366
| 754
| 329
| 1.375
| 104,900
|
NEAR BAY
|
-122.27
| 37.83
| 51
| 2,665
| 574
| 1,258
| 536
| 2.7303
| 109,700
|
NEAR BAY
|
-122.27
| 37.83
| 49
| 1,215
| 282
| 570
| 264
| 1.4861
| 97,200
|
NEAR BAY
|
-122.27
| 37.83
| 48
| 1,798
| 432
| 987
| 374
| 1.0972
| 104,500
|
NEAR BAY
|
-122.28
| 37.83
| 52
| 1,511
| 390
| 901
| 403
| 1.4103
| 103,900
|
NEAR BAY
|
-122.26
| 37.83
| 52
| 1,470
| 330
| 689
| 309
| 3.48
| 191,400
|
NEAR BAY
|
-122.26
| 37.83
| 52
| 2,432
| 715
| 1,377
| 696
| 2.5898
| 176,000
|
NEAR BAY
|
-122.26
| 37.83
| 52
| 1,665
| 419
| 946
| 395
| 2.0978
| 155,400
|
NEAR BAY
|
-122.26
| 37.83
| 51
| 936
| 311
| 517
| 249
| 1.2852
| 150,000
|
NEAR BAY
|
-122.26
| 37.84
| 49
| 713
| 202
| 462
| 189
| 1.025
| 118,800
|
NEAR BAY
|
-122.26
| 37.84
| 52
| 950
| 202
| 467
| 198
| 3.9643
| 188,800
|
NEAR BAY
|
-122.26
| 37.83
| 52
| 1,443
| 311
| 660
| 292
| 3.0125
| 184,400
|
NEAR BAY
|
-122.26
| 37.83
| 52
| 1,656
| 420
| 718
| 382
| 2.6768
| 182,300
|
NEAR BAY
|
-122.26
| 37.83
| 50
| 1,125
| 322
| 616
| 304
| 2.026
| 142,500
|
NEAR BAY
|
-122.27
| 37.82
| 43
| 1,007
| 312
| 558
| 253
| 1.7348
| 137,500
|
NEAR BAY
|
-122.26
| 37.82
| 40
| 624
| 195
| 423
| 160
| 0.9506
| 187,500
|
NEAR BAY
|
-122.27
| 37.82
| 40
| 946
| 375
| 700
| 352
| 1.775
| 112,500
|
NEAR BAY
|
-122.27
| 37.82
| 21
| 896
| 453
| 735
| 438
| 0.9218
| 171,900
|
NEAR BAY
|
-122.27
| 37.82
| 43
| 1,868
| 456
| 1,061
| 407
| 1.5045
| 93,800
|
NEAR BAY
|
-122.27
| 37.82
| 41
| 3,221
| 853
| 1,959
| 720
| 1.1108
| 97,500
|
NEAR BAY
|
-122.27
| 37.82
| 52
| 1,630
| 456
| 1,162
| 400
| 1.2475
| 104,200
|
NEAR BAY
|
-122.28
| 37.82
| 52
| 1,170
| 235
| 701
| 233
| 1.6098
| 87,500
|
NEAR BAY
|
-122.28
| 37.82
| 52
| 945
| 243
| 576
| 220
| 1.4113
| 83,100
|
NEAR BAY
|
-122.28
| 37.82
| 52
| 1,238
| 288
| 622
| 259
| 1.5057
| 87,500
|
NEAR BAY
|
-122.28
| 37.82
| 52
| 1,489
| 335
| 728
| 244
| 0.8172
| 85,300
|
NEAR BAY
|
-122.28
| 37.82
| 52
| 1,387
| 341
| 1,074
| 304
| 1.2171
| 80,300
|
NEAR BAY
|
-122.29
| 37.82
| 2
| 158
| 43
| 94
| 57
| 2.5625
| 60,000
|
NEAR BAY
|
-122.29
| 37.83
| 52
| 1,121
| 211
| 554
| 187
| 3.3929
| 75,700
|
NEAR BAY
|
-122.29
| 37.82
| 49
| 135
| 29
| 86
| 23
| 6.1183
| 75,000
|
NEAR BAY
|
-122.29
| 37.81
| 50
| 760
| 190
| 377
| 122
| 0.9011
| 86,100
|
NEAR BAY
|
-122.3
| 37.81
| 52
| 1,224
| 237
| 521
| 159
| 1.191
| 76,100
|
NEAR BAY
|
-122.3
| 37.81
| 48
| 828
| 182
| 392
| 133
| 2.5938
| 73,500
|
NEAR BAY
|
-122.3
| 37.81
| 52
| 1,010
| 209
| 604
| 187
| 1.1667
| 78,400
|
NEAR BAY
|
-122.3
| 37.81
| 48
| 1,455
| 354
| 788
| 332
| 0.8056
| 84,400
|
NEAR BAY
|
-122.29
| 37.8
| 52
| 1,027
| 244
| 492
| 147
| 2.6094
| 81,300
|
NEAR BAY
|
-122.3
| 37.81
| 52
| 572
| 109
| 274
| 82
| 1.8516
| 85,000
|
NEAR BAY
|
-122.29
| 37.81
| 46
| 2,801
| 644
| 1,823
| 611
| 0.9802
| 129,200
|
NEAR BAY
|
-122.29
| 37.81
| 26
| 768
| 152
| 392
| 127
| 1.7719
| 82,500
|
NEAR BAY
|
-122.29
| 37.81
| 46
| 935
| 297
| 582
| 277
| 0.7286
| 95,200
|
NEAR BAY
|
-122.29
| 37.81
| 49
| 844
| 204
| 560
| 152
| 1.75
| 75,000
|
NEAR BAY
|
-122.29
| 37.81
| 46
| 12
| 4
| 18
| 7
| 0.4999
| 67,500
|
NEAR BAY
|
-122.29
| 37.81
| 20
| 835
| 161
| 290
| 133
| 2.483
| 137,500
|
NEAR BAY
|
-122.28
| 37.81
| 17
| 1,237
| 462
| 762
| 439
| 0.9241
| 177,500
|
NEAR BAY
|
-122.28
| 37.81
| 36
| 2,914
| 562
| 1,236
| 509
| 2.4464
| 102,100
|
NEAR BAY
|
-122.28
| 37.81
| 19
| 1,207
| 243
| 721
| 207
| 1.1111
| 108,300
|
NEAR BAY
|
-122.29
| 37.81
| 23
| 1,745
| 374
| 1,054
| 325
| 0.8026
| 112,500
|
NEAR BAY
|
-122.28
| 37.8
| 38
| 684
| 176
| 344
| 155
| 2.0114
| 131,300
|
NEAR BAY
|
-122.28
| 37.81
| 17
| 924
| 289
| 609
| 289
| 1.5
| 162,500
|
NEAR BAY
|
-122.27
| 37.81
| 52
| 210
| 56
| 183
| 56
| 1.1667
| 112,500
|
NEAR BAY
|
-122.28
| 37.81
| 52
| 340
| 97
| 200
| 87
| 1.5208
| 112,500
|
NEAR BAY
|
-122.28
| 37.81
| 52
| 386
| 164
| 346
| 155
| 0.8075
| 137,500
|
NEAR BAY
|
-122.28
| 37.81
| 35
| 948
| 184
| 467
| 169
| 1.8088
| 118,800
|
NEAR BAY
|
-122.28
| 37.81
| 52
| 773
| 143
| 377
| 115
| 2.4083
| 98,200
|
NEAR BAY
|
-122.27
| 37.81
| 40
| 880
| 451
| 582
| 380
| 0.977
| 118,800
|
NEAR BAY
|
-122.27
| 37.81
| 10
| 875
| 348
| 546
| 330
| 0.76
| 162,500
|
NEAR BAY
|
-122.27
| 37.8
| 10
| 105
| 42
| 125
| 39
| 0.9722
| 137,500
|
NEAR BAY
|
-122.27
| 37.8
| 52
| 249
| 78
| 396
| 85
| 1.2434
| 500,001
|
NEAR BAY
|
-122.27
| 37.8
| 16
| 994
| 392
| 800
| 362
| 2.0938
| 162,500
|
NEAR BAY
|
-122.28
| 37.8
| 52
| 215
| 87
| 904
| 88
| 0.8668
| 137,500
|
NEAR BAY
|
-122.28
| 37.8
| 52
| 96
| 31
| 191
| 34
| 0.75
| 162,500
|
NEAR BAY
|
-122.27
| 37.79
| 27
| 1,055
| 347
| 718
| 302
| 2.6354
| 187,500
|
NEAR BAY
|
-122.27
| 37.8
| 39
| 1,715
| 623
| 1,327
| 467
| 1.8477
| 179,200
|
NEAR BAY
|
-122.26
| 37.8
| 36
| 5,329
| 2,477
| 3,469
| 2,323
| 2.0096
| 130,000
|
NEAR BAY
|
-122.26
| 37.82
| 31
| 4,596
| 1,331
| 2,048
| 1,180
| 2.8345
| 183,800
|
NEAR BAY
|
-122.26
| 37.81
| 29
| 335
| 107
| 202
| 91
| 2.0062
| 125,000
|
NEAR BAY
|
-122.26
| 37.82
| 22
| 3,682
| 1,270
| 2,024
| 1,250
| 1.2185
| 170,000
|
NEAR BAY
|
-122.26
| 37.82
| 37
| 3,633
| 1,085
| 1,838
| 980
| 2.6104
| 193,100
|
NEAR BAY
|
End of preview.
Tabular Datasets
The datasets are used in this project: Feature Factory
| Index | Dataset Name | File Name | Data Type | #Records (Approx.) | Format | Source |
|---|---|---|---|---|---|---|
| 1 | Wine Quality (Red Wine) | winequality-red.csv | Tabular | 1,599 | CSV | Link |
| 2 | NYC Yellow Taxi Trip (Jan 2019) | yellow_tripdata_2019.parquet | Taxi Trip Data | ~7M | Parquet | Link |
| 3 | NYC Green Taxi Trip (Jan 2019) | green_tripdata_2019.parquet | Taxi Trip Data | ~1M | Parquet | Link |
| 4 | California Housing Prices | california_housing.csv | Real Estate Prices | ~20,640 | CSV | Link |
| 6 | Retail Sales Transactions | retail_sales.csv | Sales Transactions | ~500K | CSV | Link |
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