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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 5 new columns ({'0.50500000', '23383.17000000', '1547632800.0', '0.51780000', '1547633699999'}) and 5 missing columns ({'0.49800000', '0.49800000.1', '1547639999999', '1547596800.0', '216595.03000000'}).

This happened while the csv dataset builder was generating data using

hf://datasets/TechieTeee/Chainlink_USDT_Data/15minute.csv (at revision 214387553d250080e46248556b6973222cd60718)

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
              1547632800.0: double
              0.53550000: double
              0.53550000.1: double
              0.50500000: double
              0.51780000: double
              23383.17000000: double
              1547633699999: int64
              -- schema metadata --
              pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 1128
              to
              {'1547596800.0': Value(dtype='float64', id=None), '0.53550000': Value(dtype='float64', id=None), '0.53550000.1': Value(dtype='float64', id=None), '0.49800000': Value(dtype='float64', id=None), '0.49800000.1': Value(dtype='float64', id=None), '216595.03000000': Value(dtype='float64', id=None), '1547639999999': 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 5 new columns ({'0.50500000', '23383.17000000', '1547632800.0', '0.51780000', '1547633699999'}) and 5 missing columns ({'0.49800000', '0.49800000.1', '1547639999999', '1547596800.0', '216595.03000000'}).
              
              This happened while the csv dataset builder was generating data using
              
              hf://datasets/TechieTeee/Chainlink_USDT_Data/15minute.csv (at revision 214387553d250080e46248556b6973222cd60718)
              
              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)

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1547596800.0
float64
0.53550000
float64
0.53550000.1
float64
0.49800000
float64
0.49800000.1
float64
216595.03000000
float64
1547639999999
int64
1,547,640,000
0.498
0.52
0.4668
0.4895
1,127,065.28
1,547,683,199,999
1,547,683,200
0.4895
0.4895
0.4639
0.4726
643,035.91
1,547,726,399,999
1,547,726,400
0.4734
0.4953
0.4703
0.4756
768,689.44
1,547,769,599,999
1,547,769,600
0.4762
0.48
0.4601
0.4688
342,297.95
1,547,812,799,999
1,547,812,800
0.4686
0.5112
0.4635
0.4894
642,119.64
1,547,855,999,999
1,547,856,000
0.4908
0.5
0.4673
0.4813
502,395.28
1,547,899,199,999
1,547,899,200
0.4829
0.49
0.476
0.4831
233,047.92
1,547,942,399,999
1,547,942,400
0.4803
0.4909
0.4712
0.4712
205,679.54
1,547,985,599,999
1,547,985,600
0.4773
0.492
0.459
0.4834
471,820.02
1,548,028,799,999
1,548,028,800
0.4839
0.4933
0.465
0.488
223,843.11
1,548,071,999,999
1,548,072,000
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0.5198
0.473
0.4972
673,944.73
1,548,115,199,999
1,548,115,200
0.496
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0.4956
0.526
508,549.24
1,548,158,399,999
1,548,158,400
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1,276,404.26
1,548,201,599,999
1,548,201,600
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0.5475
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756,076.04
1,548,244,799,999
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1,548,331,199,999
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0.5017
421,823.66
1,548,374,399,999
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0.5157
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340,250.62
1,548,417,599,999
1,548,417,600
0.4968
0.5009
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772,618.46
1,548,460,799,999
1,548,460,800
0.4736
0.4884
0.4732
0.4791
302,569.84
1,548,503,999,999
1,548,504,000
0.4789
0.4809
0.4624
0.4661
563,084.05
1,548,547,199,999
1,548,547,200
0.4661
0.4666
0.4313
0.4314
1,399,902.42
1,548,590,399,999
1,548,590,400
0.4314
0.4442
0.4229
0.4303
879,017.23
1,548,633,599,999
1,548,633,600
0.431
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0.3782
0.3907
1,400,669.03
1,548,676,799,999
1,548,676,800
0.3921
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0.4116
2,605,542.82
1,548,719,999,999
1,548,720,000
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0.4238
1,852,900.87
1,548,763,199,999
1,548,763,200
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0.4114
0.4505
3,337,924.5
1,548,806,399,999
1,548,806,400
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0.413
0.4325
979,957.51
1,548,849,599,999
1,548,849,600
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0.417
0.4249
1,112,412.08
1,548,892,799,999
1,548,892,800
0.425
0.441
0.391
0.4028
901,546.39
1,548,935,999,999
1,548,936,000
0.4044
0.4155
0.3811
0.3832
1,127,487.22
1,548,979,199,999
1,548,979,200
0.385
0.4135
0.38
0.4077
784,610.69
1,549,022,399,999
1,549,022,400
0.4087
0.43
0.3958
0.4147
1,114,621.87
1,549,065,599,999
1,549,065,600
0.4163
0.433
0.4099
0.4128
469,840.43
1,549,108,799,999
1,549,108,800
0.4128
0.4187
0.3985
0.4136
351,193.05
1,549,151,999,999
1,549,152,000
0.417
0.417
0.4003
0.4059
254,653.21
1,549,195,199,999
1,549,195,200
0.4026
0.403
0.386
0.3963
810,517.35
1,549,238,399,999
1,549,238,400
0.3959
0.4
0.3867
0.3941
358,868.48
1,549,281,599,999
1,549,281,600
0.3925
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0.3916
0.3943
1,090,516.48
1,549,324,799,999
1,549,324,800
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403,495.55
1,549,367,999,999
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1,549,411,199,999
1,549,411,200
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846,213.99
1,549,454,399,999
1,549,454,400
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0.4
522,332.22
1,549,497,599,999
1,549,497,600
0.4
0.4064
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0.3996
330,867.84
1,549,540,799,999
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167,974.52
1,549,583,999,999
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665,878.55
1,549,627,199,999
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335,914.13
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959,159.56
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1,549,929,600
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444,172.2
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497,131.38
1,550,015,999,999
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629,324.02
1,550,102,399,999
1,550,102,400
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480,617.79
1,550,145,599,999
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850,979.64
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1,550,750,400
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297,319.29
1,550,879,999,999
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200,895.06
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724,634.58
1,550,966,399,999
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535,439.24
1,551,009,599,999
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1,618,754.01
1,551,052,799,999
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595,651.93
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382,289.18
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471,923.27
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490,501.95
1,551,355,199,999
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1,551,398,399,999
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1,551,484,799,999
1,551,484,800
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205,394.6
1,551,527,999,999
1,551,528,000
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126,175.4
1,551,571,199,999
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110,709.13
1,551,614,399,999
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114,720.82
1,551,657,599,999
1,551,657,600
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501,014.2
1,551,700,799,999
1,551,700,800
0.4004
0.4255
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0.4036
445,367.99
1,551,743,999,999
1,551,744,000
0.4029
0.428
0.4023
0.4164
517,801.2
1,551,787,199,999
1,551,787,200
0.4159
0.4343
0.4108
0.4291
1,168,378.7
1,551,830,399,999
1,551,830,400
0.4291
0.4315
0.4186
0.4242
339,950.86
1,551,873,599,999
1,551,873,600
0.4239
0.4385
0.4227
0.4296
376,377.29
1,551,916,799,999
1,551,916,800
0.4296
0.4352
0.4256
0.4302
323,258.17
1,551,959,999,999
End of preview.