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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 785 new columns ({'0.534', '0.75', '0.450', '236', '0.382', '252.9', '0.576', '0.92', '249.2', '0.417', '0.425', '252.6', '0.42', '0.442', '0.266', '0.551', '252.2', '0.237', '135.1', '252.40', '252.45', '252.19', '0.574', '0.164', '152', '0.51', '0.338', '0.68', '0.529', '0.521', '0.172', '0.455', '0.547', '165', '0.281', '0.306', '0.303', '0.435', '0.240', '222', '0.260', '13', '0.85', '0.174', '0.166', '0.97', '0.205', '0.1', '0.486', '108', '252.14', '24.1', '0.411', '0.154', '143.1', '0.119', '0.331', '166', '0.320', '0.463', '0.31', '0.278', '253.1', '0.74', '255', '0.404', '19', '0.144', '0.224', '0.170', '0.401', '6', '0.359', '0.571', '0.491', '0.437', '0.48', '0.403', '0.535', '0.136', '0.570', '0.79', '66.9', '0.37', '0.564', '0.572', '17.1', '0.554', '243', '232', '0.201', '0.548', '0.277', '66.1', '0.112', '44', '0.255', '0.179', '0.419', '0.468', '0.133', '0.441', '0.301', '249.1', '0.3', '0.515', '0.175', '0.216', '0.542', '179', '252.44', '0.518', '0.339', '15.1', '0.19', '159.1', '0.271', '0.36', '0.346', '0.282', '0.120', '0.145', '0.462', '0.582', '0.43', '0.59', '0.279', '0.185', '12.2', '252.34', '0.505', '250', '0.115', '0.348', '252.35', '0.269', '0.315', '0.316', '0.433', '0.394', '0.246', '0.431', '0', '0.314', '0.55', '0.440', '0.10', '0.118', '0.80', '0.103', '18', '0.238', '0.308', '0.11', '0.214', '0.567', '0.328', '0.458', '252.12', '0.539', '0.454', '0.480', '0.82', '246', '0.558', '0.421', '0.72', '0.483', '0.129', '0.261', '0.173', '0.191', '34.1', '0.32', '0.
...
252.21', '12.3', '0.388', '0.275', '0.402', '30', '0.12', '0.524', '0.380', '0.142', '0.101', '252', '244', '239.1', '0.17', '0.398', '0.345', '0.399', '0.16', '0.53', '252.38', '0.56', '131', '252.47', '0.25', '252.13', '252.29', '0.351', '253.3', '0.501', '252.7', '0.585', '0.590', '0.532', '0.231', '0.126', '0.368', '0.265', '253.6', '0.544', '0.500', '100', '126', '0.485', '0.127', '0.226', '0.289', '0.319', '0.140', '0.94', '0.251', '0.478', '243.1', '0.414', '24', '252.4', '0.21', '0.100', '21', '0.121', '0.537', '0.218', '0.91', '0.161', '0.347', '0.189', '0.556', '0.494', '0.220', '67.1', '0.293', '0.560', '0.105', '0.190', '0.321', '0.552', '0.407', '0.527', '198', '0.389', '89', '0.333', '0.362', '0.393', '0.96', '0.557', '0.210', '0.575', '0.545', '0.444', '0.311', '184', '0.297', '0.169', '0.130', '0.420', '11.1', '0.65', '0.432', '0.553', '0.207', '0.304', '0.152', '0.30', '0.128', '0.356', '0.336', '252.16', '0.206', '0.117', '0.280', '79', '0.5', '0.60', '252.26', '26', '82', '0.484', '49', '0.342', '0.159', '0.45', '0.509', '253', '0.317', '0.33', '234', '0.335', '0.384', '0.204', '0.456', '0.27', '0.447', '22', '0.476', '0.409', '0.461', '0.235', '0.396', '0.88', '66.3', '0.436', '0.334', '0.263', '0.520', '143.2', '0.366', '0.508', '0.107', '96', '0.122', '0.533', '0.248', '2', '253.4', '0.487', '0.323', '0.286', '0.498', '0.108', '0.376', '0.234', '0.413', '252.22', '0.183', '0.276', '0.6', '235', '0.587', '0.236', '0.250', '0.499', '0.288', '0.465', '143'}) and 9 missing columns ({'total_rooms', 'longitude', 'housing_median_age', 'latitude', 'households', 'total_bedrooms', 'median_income', 'median_house_value', 'population'}).

This happened while the csv dataset builder was generating data using

hf://datasets/luigi12345/megacursos1/mnist_train_small.csv (at revision 96fb344897a31c8a1202a0498be13bdfa2a583d8)

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 2013, 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
              6: int64
              0: int64
              0.1: int64
              0.2: int64
              0.3: int64
              0.4: int64
              0.5: int64
              0.6: int64
              0.7: int64
              0.8: int64
              0.9: int64
              0.10: int64
              0.11: int64
              0.12: int64
              0.13: int64
              0.14: int64
              0.15: int64
              0.16: int64
              0.17: int64
              0.18: int64
              0.19: int64
              0.20: int64
              0.21: int64
              0.22: int64
              0.23: int64
              0.24: int64
              0.25: int64
              0.26: int64
              0.27: int64
              0.28: int64
              0.29: int64
              0.30: int64
              0.31: int64
              0.32: int64
              0.33: int64
              0.34: int64
              0.35: int64
              0.36: int64
              0.37: int64
              0.38: int64
              0.39: int64
              0.40: int64
              0.41: int64
              0.42: int64
              0.43: int64
              0.44: int64
              0.45: int64
              0.46: int64
              0.47: int64
              0.48: int64
              0.49: int64
              0.50: int64
              0.51: int64
              0.52: int64
              0.53: int64
              0.54: int64
              0.55: int64
              0.56: int64
              0.57: int64
              0.58: int64
              0.59: int64
              0.60: int64
              0.61: int64
              0.62: int64
              0.63: int64
              0.64: int64
              0.65: int64
              0.66: int64
              0.67: int64
              0.68: int64
              0.69: int64
              0.70: int64
              0.71: int64
              0.72: int64
              0.73: int64
              0.74: int64
              0.75: int64
              0.76: int64
              0.77: int64
              0.78: int64
              0.79: int64
              0.80: int64
              0.81: int64
              0.82: int64
              0.83: int64
              0.84: int64
              0.85: int64
              0.86: int64
              0.87: int64
              0.88: int64
              0.89: int64
              0.90: int64
              0.91: int64
              0.92: int64
              0.93: int64
              0.94: int64
              0.95: int64
              0.96: int64
              0.97: int64
              0.98: int64
              0.99: int64
              0.100: int64
              0.101: int64
              0.102: int64
              0.103: int64
              0.104: int64
              0.105: int64
              0.106: int64
              0.107: int64
              0.108: int64
              0.109: int64
              0.110: int64
              0.111: int64
              0.112: int64
              0.113: int64
              0.114: int64
              0.115: int64
              0.116: int64
              0.117: int64
              0.118: int64
              0.119: int64
              0.120: int64
              0.121: int64
              24: int64
              67: int
              ...
              nt64
              0.484: int64
              0.485: int64
              0.486: int64
              0.487: int64
              0.488: int64
              0.489: int64
              0.490: int64
              0.491: int64
              0.492: int64
              0.493: int64
              0.494: int64
              0.495: int64
              0.496: int64
              0.497: int64
              0.498: int64
              0.499: int64
              0.500: int64
              0.501: int64
              0.502: int64
              0.503: int64
              0.504: int64
              0.505: int64
              0.506: int64
              0.507: int64
              0.508: int64
              0.509: int64
              0.510: int64
              0.511: int64
              0.512: int64
              0.513: int64
              0.514: int64
              0.515: int64
              0.516: int64
              0.517: int64
              0.518: int64
              0.519: int64
              0.520: int64
              0.521: int64
              0.522: int64
              0.523: int64
              0.524: int64
              0.525: int64
              0.526: int64
              0.527: int64
              0.528: int64
              0.529: int64
              0.530: int64
              0.531: int64
              0.532: int64
              0.533: int64
              0.534: int64
              0.535: int64
              0.536: int64
              0.537: int64
              0.538: int64
              0.539: int64
              0.540: int64
              0.541: int64
              0.542: int64
              0.543: int64
              0.544: int64
              0.545: int64
              0.546: int64
              0.547: int64
              0.548: int64
              0.549: int64
              0.550: int64
              0.551: int64
              0.552: int64
              0.553: int64
              0.554: int64
              0.555: int64
              0.556: int64
              0.557: int64
              0.558: int64
              0.559: int64
              0.560: int64
              0.561: int64
              0.562: int64
              0.563: int64
              0.564: int64
              0.565: int64
              0.566: int64
              0.567: int64
              0.568: int64
              0.569: int64
              0.570: int64
              0.571: int64
              0.572: int64
              0.573: int64
              0.574: int64
              0.575: int64
              0.576: int64
              0.577: int64
              0.578: int64
              0.579: int64
              0.580: int64
              0.581: int64
              0.582: int64
              0.583: int64
              0.584: int64
              0.585: int64
              0.586: int64
              0.587: int64
              0.588: int64
              0.589: int64
              0.590: int64
              -- schema metadata --
              pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 83572
              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)}
              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 1396, 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 1045, in convert_to_parquet
                  builder.download_and_prepare(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1029, in download_and_prepare
                  self._download_and_prepare(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1124, 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 1884, 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 2015, 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 785 new columns ({'0.534', '0.75', '0.450', '236', '0.382', '252.9', '0.576', '0.92', '249.2', '0.417', '0.425', '252.6', '0.42', '0.442', '0.266', '0.551', '252.2', '0.237', '135.1', '252.40', '252.45', '252.19', '0.574', '0.164', '152', '0.51', '0.338', '0.68', '0.529', '0.521', '0.172', '0.455', '0.547', '165', '0.281', '0.306', '0.303', '0.435', '0.240', '222', '0.260', '13', '0.85', '0.174', '0.166', '0.97', '0.205', '0.1', '0.486', '108', '252.14', '24.1', '0.411', '0.154', '143.1', '0.119', '0.331', '166', '0.320', '0.463', '0.31', '0.278', '253.1', '0.74', '255', '0.404', '19', '0.144', '0.224', '0.170', '0.401', '6', '0.359', '0.571', '0.491', '0.437', '0.48', '0.403', '0.535', '0.136', '0.570', '0.79', '66.9', '0.37', '0.564', '0.572', '17.1', '0.554', '243', '232', '0.201', '0.548', '0.277', '66.1', '0.112', '44', '0.255', '0.179', '0.419', '0.468', '0.133', '0.441', '0.301', '249.1', '0.3', '0.515', '0.175', '0.216', '0.542', '179', '252.44', '0.518', '0.339', '15.1', '0.19', '159.1', '0.271', '0.36', '0.346', '0.282', '0.120', '0.145', '0.462', '0.582', '0.43', '0.59', '0.279', '0.185', '12.2', '252.34', '0.505', '250', '0.115', '0.348', '252.35', '0.269', '0.315', '0.316', '0.433', '0.394', '0.246', '0.431', '0', '0.314', '0.55', '0.440', '0.10', '0.118', '0.80', '0.103', '18', '0.238', '0.308', '0.11', '0.214', '0.567', '0.328', '0.458', '252.12', '0.539', '0.454', '0.480', '0.82', '246', '0.558', '0.421', '0.72', '0.483', '0.129', '0.261', '0.173', '0.191', '34.1', '0.32', '0.
              ...
              252.21', '12.3', '0.388', '0.275', '0.402', '30', '0.12', '0.524', '0.380', '0.142', '0.101', '252', '244', '239.1', '0.17', '0.398', '0.345', '0.399', '0.16', '0.53', '252.38', '0.56', '131', '252.47', '0.25', '252.13', '252.29', '0.351', '253.3', '0.501', '252.7', '0.585', '0.590', '0.532', '0.231', '0.126', '0.368', '0.265', '253.6', '0.544', '0.500', '100', '126', '0.485', '0.127', '0.226', '0.289', '0.319', '0.140', '0.94', '0.251', '0.478', '243.1', '0.414', '24', '252.4', '0.21', '0.100', '21', '0.121', '0.537', '0.218', '0.91', '0.161', '0.347', '0.189', '0.556', '0.494', '0.220', '67.1', '0.293', '0.560', '0.105', '0.190', '0.321', '0.552', '0.407', '0.527', '198', '0.389', '89', '0.333', '0.362', '0.393', '0.96', '0.557', '0.210', '0.575', '0.545', '0.444', '0.311', '184', '0.297', '0.169', '0.130', '0.420', '11.1', '0.65', '0.432', '0.553', '0.207', '0.304', '0.152', '0.30', '0.128', '0.356', '0.336', '252.16', '0.206', '0.117', '0.280', '79', '0.5', '0.60', '252.26', '26', '82', '0.484', '49', '0.342', '0.159', '0.45', '0.509', '253', '0.317', '0.33', '234', '0.335', '0.384', '0.204', '0.456', '0.27', '0.447', '22', '0.476', '0.409', '0.461', '0.235', '0.396', '0.88', '66.3', '0.436', '0.334', '0.263', '0.520', '143.2', '0.366', '0.508', '0.107', '96', '0.122', '0.533', '0.248', '2', '253.4', '0.487', '0.323', '0.286', '0.498', '0.108', '0.376', '0.234', '0.413', '252.22', '0.183', '0.276', '0.6', '235', '0.587', '0.236', '0.250', '0.499', '0.288', '0.465', '143'}) and 9 missing columns ({'total_rooms', 'longitude', 'housing_median_age', 'latitude', 'households', 'total_bedrooms', 'median_income', 'median_house_value', 'population'}).
              
              This happened while the csv dataset builder was generating data using
              
              hf://datasets/luigi12345/megacursos1/mnist_train_small.csv (at revision 96fb344897a31c8a1202a0498be13bdfa2a583d8)
              
              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
-114.31
34.19
15
5,612
1,283
1,015
472
1.4936
66,900
-114.47
34.4
19
7,650
1,901
1,129
463
1.82
80,100
-114.56
33.69
17
720
174
333
117
1.6509
85,700
-114.57
33.64
14
1,501
337
515
226
3.1917
73,400
-114.57
33.57
20
1,454
326
624
262
1.925
65,500
-114.58
33.63
29
1,387
236
671
239
3.3438
74,000
-114.58
33.61
25
2,907
680
1,841
633
2.6768
82,400
-114.59
34.83
41
812
168
375
158
1.7083
48,500
-114.59
33.61
34
4,789
1,175
3,134
1,056
2.1782
58,400
-114.6
34.83
46
1,497
309
787
271
2.1908
48,100
-114.6
33.62
16
3,741
801
2,434
824
2.6797
86,500
-114.6
33.6
21
1,988
483
1,182
437
1.625
62,000
-114.61
34.84
48
1,291
248
580
211
2.1571
48,600
-114.61
34.83
31
2,478
464
1,346
479
3.212
70,400
-114.63
32.76
15
1,448
378
949
300
0.8585
45,000
-114.65
34.89
17
2,556
587
1,005
401
1.6991
69,100
-114.65
33.6
28
1,678
322
666
256
2.9653
94,900
-114.65
32.79
21
44
33
64
27
0.8571
25,000
-114.66
32.74
17
1,388
386
775
320
1.2049
44,000
-114.67
33.92
17
97
24
29
15
1.2656
27,500
-114.68
33.49
20
1,491
360
1,135
303
1.6395
44,400
-114.73
33.43
24
796
243
227
139
0.8964
59,200
-114.94
34.55
20
350
95
119
58
1.625
50,000
-114.98
33.82
15
644
129
137
52
3.2097
71,300
-115.22
33.54
18
1,706
397
3,424
283
1.625
53,500
-115.32
32.82
34
591
139
327
89
3.6528
100,000
-115.37
32.82
30
1,602
322
1,130
335
3.5735
71,100
-115.37
32.82
14
1,276
270
867
261
1.9375
80,900
-115.37
32.81
32
741
191
623
169
1.7604
68,600
-115.37
32.81
23
1,458
294
866
275
2.3594
74,300
-115.38
32.82
38
1,892
394
1,175
374
1.9939
65,800
-115.38
32.81
35
1,263
262
950
241
1.8958
67,500
-115.39
32.76
16
1,136
196
481
185
6.2558
146,300
-115.4
32.86
19
1,087
171
649
173
3.3182
113,800
-115.4
32.7
19
583
113
531
134
1.6838
95,800
-115.41
32.99
29
1,141
220
684
194
3.4038
107,800
-115.46
33.19
33
1,234
373
777
298
1
40,000
-115.48
32.8
21
1,260
246
805
239
2.6172
88,500
-115.48
32.68
15
3,414
666
2,097
622
2.3319
91,200
-115.49
32.87
19
541
104
457
106
3.3583
102,800
-115.49
32.69
17
1,960
389
1,691
356
1.899
64,000
-115.49
32.67
29
1,523
440
1,302
393
1.1311
84,700
-115.49
32.67
25
2,322
573
2,185
602
1.375
70,100
-115.5
32.75
13
330
72
822
64
3.4107
142,500
-115.5
32.68
18
3,631
913
3,565
924
1.5931
88,400
-115.5
32.67
35
2,159
492
1,694
475
2.1776
75,500
-115.51
33.24
32
1,995
523
1,069
410
1.6552
43,300
-115.51
33.12
21
1,024
218
890
232
2.101
46,700
-115.51
32.99
20
1,402
287
1,104
317
1.9088
63,700
-115.51
32.68
11
2,872
610
2,644
581
2.625
72,700
-115.52
34.22
30
540
136
122
63
1.3333
42,500
-115.52
33.13
18
1,109
283
1,006
253
2.163
53,400
-115.52
33.12
38
1,327
262
784
231
1.8793
60,800
-115.52
32.98
32
1,615
382
1,307
345
1.4583
58,600
-115.52
32.97
24
1,617
366
1,416
401
1.975
66,400
-115.52
32.97
10
1,879
387
1,376
337
1.9911
67,500
-115.52
32.77
18
1,715
337
1,166
333
2.2417
79,200
-115.52
32.73
17
1,190
275
1,113
258
2.3571
63,100
-115.52
32.67
6
2,804
581
2,807
594
2.0625
67,700
-115.53
34.91
12
807
199
246
102
2.5391
40,000
-115.53
32.99
25
2,578
634
2,082
565
1.7159
62,200
-115.53
32.97
35
1,583
340
933
318
2.4063
70,700
-115.53
32.97
34
2,231
545
1,568
510
1.5217
60,300
-115.53
32.73
14
1,527
325
1,453
332
1.735
61,200
-115.54
32.99
23
1,459
373
1,148
388
1.5372
69,400
-115.54
32.99
17
1,697
268
911
254
4.3523
96,000
-115.54
32.98
27
1,513
395
1,121
381
1.9464
60,600
-115.54
32.97
41
2,429
454
1,188
430
3.0091
70,800
-115.54
32.79
23
1,712
403
1,370
377
1.275
60,400
-115.55
32.98
33
2,266
365
952
360
5.4349
143,000
-115.55
32.98
24
2,565
530
1,447
473
3.2593
80,800
-115.55
32.82
34
1,540
316
1,013
274
2.5664
67,500
-115.55
32.8
23
666
142
580
160
2.1136
61,000
-115.55
32.79
23
1,004
221
697
201
1.6351
59,600
-115.55
32.79
22
565
162
692
141
1.2083
53,600
-115.55
32.78
5
2,652
606
1,767
536
2.8025
84,300
-115.56
32.96
21
2,164
480
1,164
421
3.8177
107,200
-115.56
32.8
28
1,672
416
1,335
397
1.5987
59,400
-115.56
32.8
25
1,311
375
1,193
351
2.1979
63,900
-115.56
32.8
15
1,171
328
1,024
298
1.3882
69,400
-115.56
32.79
20
2,372
835
2,283
767
1.1707
62,500
-115.56
32.79
18
1,178
438
1,377
429
1.3373
58,300
-115.56
32.78
46
2,511
490
1,583
469
3.0603
70,800
-115.56
32.78
35
1,185
202
615
191
4.6154
86,200
-115.56
32.78
29
1,568
283
848
245
3.1597
76,200
-115.56
32.76
15
1,278
217
653
185
4.4821
140,300
-115.57
32.85
33
1,365
269
825
250
3.2396
62,300
-115.57
32.85
17
1,039
256
728
246
1.7411
63,500
-115.57
32.84
29
1,207
301
804
288
1.9531
61,100
-115.57
32.83
31
1,494
289
959
284
3.5282
67,500
-115.57
32.8
16
2,276
594
1,184
513
1.875
93,800
-115.57
32.79
34
1,152
208
621
208
3.6042
73,600
-115.57
32.78
20
1,534
235
871
222
6.2715
97,200
-115.57
32.78
15
1,413
279
803
277
4.3021
87,500
-115.58
33.88
21
1,161
282
724
186
3.1827
71,700
-115.58
32.81
5
805
143
458
143
4.475
96,300
-115.58
32.81
10
1,088
203
533
201
3.6597
87,500
-115.58
32.79
14
1,687
507
762
451
1.6635
64,400
-115.58
32.78
5
2,494
414
1,416
421
5.7843
110,100
-115.59
32.85
20
1,608
274
862
248
4.875
90,800
End of preview.
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