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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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