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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 ({'252.23', '0.98', '253', '3', '0.362', '0.526', '0.474', '0.138', '0.158', '0.184', '0.240', '252.21', '0.304', '252', '0.313', '253.5', '0.484', '0.42', '0.45', '0.100', '0.391', '0.92', '0.34', '0.464', '0.305', '193', '100', '0.369', '0.206', '0.299', '0.22', '66.6', '0.513', '0.126', '0.133', '0.373', '243', '0.564', '0.431', '0.154', '250', '0.311', '0.563', '0.566', '252.36', '0.426', '0.492', '0.363', '0.204', '0.152', '248', '48', '0.72', '44', '0.586', '0.293', '0.76', '0.432', '0.449', '0.558', '0.457', '0.207', '0.528', '0.298', '66.4', '0.390', '0.499', '232.1', '252.3', '252.27', '0.166', '0.62', '0.393', '0.429', '0.328', '0.136', '0.509', '0.322', '0.343', '0.538', '252.10', '0.168', '0.153', '0.553', '0.197', '0.307', '0.357', '0.511', '0.64', '252.47', '252.43', '46.1', '0.32', '0.292', '170', '0.494', '0.279', '0.82', '0.497', '252.41', '0.70', '0.4', '0.125', '0.430', '0.502', '252.28', '0.350', '0.334', '0.151', '0.339', '6', '0.422', '82', '0.178', '0.331', '0.383', '0.466', '0.316', '0.487', '0.577', '0.3', '0.560', '159.1', '0.356', '0.436', '0.183', '0.562', '92', '0.145', '240', '0.384', '0.267', '59', '0.490', '126', '0.500', '0.20', '0.588', '0.212', '0.533', '0.177', '0.503', '0.372', '0.130', '0.231', '0.377', '252.37', '0.443', '0.79', '0.336', '0.428', '0.191', '0.8', '0.220', '0.262', '209', '0.163', '0.508', '0.404', '0.106', '0.405', '0.371', '253.1', '135.1', '0.578', '0.78', '0.39', '234', '0.338', '0.355', '0.50', '0.510', '0.342', '0.532
...
'0.536', '34.1', '0.381', '0.361', '67', '0.188', '0.448', '0.195', '249', '0.486', '252.20', '253.6', '0.13', '252.2', '0.288', '0.254', '0.222', '11', '0.263', '0.171', '0.341', '0.124', '0.241', '13', '0.245', '237', '249.1', '0.455', '177.1', '89.3', '0.150', '0.386', '79', '0.450', '16', '149', '66.7', '0.71', '0.202', '0.531', '0.155', '0.67', '0.354', '0.226', '0.189', '0.388', '0.234', '0.96', '96.1', '0.251', '0.485', '0.273', '0.47', '0.185', '0.103', '0.264', '253.4', '0.472', '0.179', '0.423', '0.389', '0.68', '0.396', '0.97', '244', '252.46', '131', '0.346', '0.312', '0.321', '252.34', '12.1', '0.349', '0.140', '252.25', '0.89', '89.1', '0.444', '0.223', '0.289', '0.529', '66.9', '0.310', '66.8', '2', '0.367', '0.576', '0.539', '67.1', '252.42', '0.285', '252.22', '0.570', '0.85', '0.111', '0.198', '0.392', '0.573', '0.5', '0.345', '0.498', '0.507', '0.471', '0.458', '0.379', '0.330', '0.352', '0.30', '0.199', '0.495', '0.244', '0.93', '246', '0.221', '0.433', '183', '0.14', '0.524', '135', '0.81', '0.134', '0.581', '0.259', '0.315', '119', '0.475', '0.2', '0.146', '0.102', '143', '5.1', '0.467', '0.35', '0.482', '0.235', '0.534', '0.424', '0.23', '0.402', '0.518', '0.110', '0.112', '89.2', '0.236', '0.277', '66', '17', '0.65', '0.568', '0.213', '0.527', '0.303', '243.1', '222', '0.365', '0.253', '0.320', '0.413', '0.370', '0.73', '0.271', '0.186', '228', '0.420', '252.35', '0.314', '0.237', '0.282', '252.8', '0.294', '0.302', '0.172', '0.323', '0.421', '0.505'}) and 9 missing columns ({'median_income', 'population', 'households', 'total_rooms', 'housing_median_age', 'latitude', 'longitude', 'median_house_value', 'total_bedrooms'}).
This happened while the csv dataset builder was generating data using
hf://datasets/Chandrasrishti/pdf_chatbot_book3/embeddings/sample_data/mnist_train_small.csv (at revision 640b158f5419db8a8ea252e8912cde5ef747a26e)
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
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 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 785 new columns ({'252.23', '0.98', '253', '3', '0.362', '0.526', '0.474', '0.138', '0.158', '0.184', '0.240', '252.21', '0.304', '252', '0.313', '253.5', '0.484', '0.42', '0.45', '0.100', '0.391', '0.92', '0.34', '0.464', '0.305', '193', '100', '0.369', '0.206', '0.299', '0.22', '66.6', '0.513', '0.126', '0.133', '0.373', '243', '0.564', '0.431', '0.154', '250', '0.311', '0.563', '0.566', '252.36', '0.426', '0.492', '0.363', '0.204', '0.152', '248', '48', '0.72', '44', '0.586', '0.293', '0.76', '0.432', '0.449', '0.558', '0.457', '0.207', '0.528', '0.298', '66.4', '0.390', '0.499', '232.1', '252.3', '252.27', '0.166', '0.62', '0.393', '0.429', '0.328', '0.136', '0.509', '0.322', '0.343', '0.538', '252.10', '0.168', '0.153', '0.553', '0.197', '0.307', '0.357', '0.511', '0.64', '252.47', '252.43', '46.1', '0.32', '0.292', '170', '0.494', '0.279', '0.82', '0.497', '252.41', '0.70', '0.4', '0.125', '0.430', '0.502', '252.28', '0.350', '0.334', '0.151', '0.339', '6', '0.422', '82', '0.178', '0.331', '0.383', '0.466', '0.316', '0.487', '0.577', '0.3', '0.560', '159.1', '0.356', '0.436', '0.183', '0.562', '92', '0.145', '240', '0.384', '0.267', '59', '0.490', '126', '0.500', '0.20', '0.588', '0.212', '0.533', '0.177', '0.503', '0.372', '0.130', '0.231', '0.377', '252.37', '0.443', '0.79', '0.336', '0.428', '0.191', '0.8', '0.220', '0.262', '209', '0.163', '0.508', '0.404', '0.106', '0.405', '0.371', '253.1', '135.1', '0.578', '0.78', '0.39', '234', '0.338', '0.355', '0.50', '0.510', '0.342', '0.532
...
'0.536', '34.1', '0.381', '0.361', '67', '0.188', '0.448', '0.195', '249', '0.486', '252.20', '253.6', '0.13', '252.2', '0.288', '0.254', '0.222', '11', '0.263', '0.171', '0.341', '0.124', '0.241', '13', '0.245', '237', '249.1', '0.455', '177.1', '89.3', '0.150', '0.386', '79', '0.450', '16', '149', '66.7', '0.71', '0.202', '0.531', '0.155', '0.67', '0.354', '0.226', '0.189', '0.388', '0.234', '0.96', '96.1', '0.251', '0.485', '0.273', '0.47', '0.185', '0.103', '0.264', '253.4', '0.472', '0.179', '0.423', '0.389', '0.68', '0.396', '0.97', '244', '252.46', '131', '0.346', '0.312', '0.321', '252.34', '12.1', '0.349', '0.140', '252.25', '0.89', '89.1', '0.444', '0.223', '0.289', '0.529', '66.9', '0.310', '66.8', '2', '0.367', '0.576', '0.539', '67.1', '252.42', '0.285', '252.22', '0.570', '0.85', '0.111', '0.198', '0.392', '0.573', '0.5', '0.345', '0.498', '0.507', '0.471', '0.458', '0.379', '0.330', '0.352', '0.30', '0.199', '0.495', '0.244', '0.93', '246', '0.221', '0.433', '183', '0.14', '0.524', '135', '0.81', '0.134', '0.581', '0.259', '0.315', '119', '0.475', '0.2', '0.146', '0.102', '143', '5.1', '0.467', '0.35', '0.482', '0.235', '0.534', '0.424', '0.23', '0.402', '0.518', '0.110', '0.112', '89.2', '0.236', '0.277', '66', '17', '0.65', '0.568', '0.213', '0.527', '0.303', '243.1', '222', '0.365', '0.253', '0.320', '0.413', '0.370', '0.73', '0.271', '0.186', '228', '0.420', '252.35', '0.314', '0.237', '0.282', '252.8', '0.294', '0.302', '0.172', '0.323', '0.421', '0.505'}) and 9 missing columns ({'median_income', 'population', 'households', 'total_rooms', 'housing_median_age', 'latitude', 'longitude', 'median_house_value', 'total_bedrooms'}).
This happened while the csv dataset builder was generating data using
hf://datasets/Chandrasrishti/pdf_chatbot_book3/embeddings/sample_data/mnist_train_small.csv (at revision 640b158f5419db8a8ea252e8912cde5ef747a26e)
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
|
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