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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 6 new columns ({'delta_pred_minus_true', 'pred_bucket', 'proba_class_1', 'abs_delta', 'pred_fwd_ret_7d', 'proba_class_0'}) and 6 missing columns ({'pred', 'score_inv_bin', 'score_raw', 'score_raw_bin', 'score_inv', 'proba_class1'}).
This happened while the csv dataset builder was generating data using
hf://datasets/miosipov/cb-data/data/processed/slow_layer_v1_1_valid_predictions.csv (at revision 130ebc4e785abca013c0602836e15ec2e8c82b67), ['hf://datasets/miosipov/cb-data@130ebc4e785abca013c0602836e15ec2e8c82b67/data/processed/slow_layer_validation_predictions_v2.csv', 'hf://datasets/miosipov/cb-data@130ebc4e785abca013c0602836e15ec2e8c82b67/data/processed/slow_layer_v1_1_valid_predictions.csv', 'hf://datasets/miosipov/cb-data@130ebc4e785abca013c0602836e15ec2e8c82b67/data/processed/slow_layer_valid_predictions.csv']
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 "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1848, in _prepare_split_single
writer.write_table(table)
~~~~~~~~~~~~~~~~~~^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/arrow_writer.py", line 784, in write_table
self._write_table(pa_table, writer_batch_size=writer_batch_size)
~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/arrow_writer.py", line 795, in _write_table
pa_table = table_cast(pa_table, self._schema)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2378, in table_cast
return cast_table_to_schema(table, schema)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2306, in cast_table_to_schema
raise CastError(
...<3 lines>...
)
datasets.table.CastError: Couldn't cast
timestamp: string
target_fwd_ret_7d: double
target_binary: int64
pred_bucket: int64
proba_class_0: double
proba_class_1: double
slow_risk_score: double
slow_bull_score: double
pred_fwd_ret_7d: double
delta_pred_minus_true: double
abs_delta: double
-- schema metadata --
pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 1683
to
{'timestamp': Value('string'), 'target_fwd_ret_7d': Value('float64'), 'target_binary': Value('int64'), 'proba_class1': Value('float64'), 'score_raw': Value('float64'), 'score_inv': Value('float64'), 'pred': Value('int64'), 'score_raw_bin': Value('int64'), 'score_inv_bin': Value('int64'), 'slow_bull_score': Value('float64'), 'slow_risk_score': Value('float64')}
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 1369, in compute_config_parquet_and_info_response
parquet_operations, partial, estimated_dataset_info = stream_convert_to_parquet(
~~~~~~~~~~~~~~~~~~~~~~~~~^
builder, max_dataset_size_bytes=max_dataset_size_bytes
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
)
^
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 948, in stream_convert_to_parquet
builder._prepare_split(split_generator=splits_generators[split], file_format="parquet")
~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1694, in _prepare_split
for job_id, done, content in self._prepare_split_single(
~~~~~~~~~~~~~~~~~~~~~~~~~~^
gen_kwargs=gen_kwargs, job_id=job_id, **_prepare_split_args
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
):
^
File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1850, in _prepare_split_single
raise DatasetGenerationCastError.from_cast_error(
...<4 lines>...
)
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 6 new columns ({'delta_pred_minus_true', 'pred_bucket', 'proba_class_1', 'abs_delta', 'pred_fwd_ret_7d', 'proba_class_0'}) and 6 missing columns ({'pred', 'score_inv_bin', 'score_raw', 'score_raw_bin', 'score_inv', 'proba_class1'}).
This happened while the csv dataset builder was generating data using
hf://datasets/miosipov/cb-data/data/processed/slow_layer_v1_1_valid_predictions.csv (at revision 130ebc4e785abca013c0602836e15ec2e8c82b67), ['hf://datasets/miosipov/cb-data@130ebc4e785abca013c0602836e15ec2e8c82b67/data/processed/slow_layer_validation_predictions_v2.csv', 'hf://datasets/miosipov/cb-data@130ebc4e785abca013c0602836e15ec2e8c82b67/data/processed/slow_layer_v1_1_valid_predictions.csv', 'hf://datasets/miosipov/cb-data@130ebc4e785abca013c0602836e15ec2e8c82b67/data/processed/slow_layer_valid_predictions.csv']
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.
timestamp string | target_fwd_ret_7d float64 | target_binary int64 | proba_class1 float64 | score_raw float64 | score_inv float64 | pred int64 | score_raw_bin int64 | score_inv_bin int64 | slow_bull_score float64 | slow_risk_score float64 |
|---|---|---|---|---|---|---|---|---|---|---|
2025-03-18 | 0.056554 | 1 | 0.51651 | 0.51651 | 0.48349 | 1 | 2 | 2 | 0.51651 | 0.48349 |
2025-03-19 | 0.000728 | 1 | 0.51651 | 0.51651 | 0.48349 | 1 | 2 | 2 | 0.51651 | 0.48349 |
2025-03-20 | 0.035722 | 1 | 0.51651 | 0.51651 | 0.48349 | 1 | 2 | 2 | 0.51651 | 0.48349 |
2025-03-21 | 0.003991 | 1 | 0.51651 | 0.51651 | 0.48349 | 1 | 2 | 2 | 0.51651 | 0.48349 |
2025-03-22 | -0.014218 | 0 | 0.526503 | 0.526503 | 0.473497 | 1 | 3 | 1 | 0.526503 | 0.473497 |
2025-03-23 | -0.042895 | 0 | 0.51651 | 0.51651 | 0.48349 | 1 | 2 | 2 | 0.51651 | 0.48349 |
2025-03-24 | -0.056551 | 0 | 0.51651 | 0.51651 | 0.48349 | 1 | 2 | 2 | 0.51651 | 0.48349 |
2025-03-25 | -0.025569 | 0 | 0.51651 | 0.51651 | 0.48349 | 1 | 2 | 2 | 0.51651 | 0.48349 |
2025-03-26 | -0.050546 | 0 | 0.51651 | 0.51651 | 0.48349 | 1 | 2 | 2 | 0.51651 | 0.48349 |
2025-03-27 | -0.046072 | 0 | 0.586318 | 0.586318 | 0.413682 | 1 | 4 | 0 | 0.586318 | 0.413682 |
2025-03-28 | -0.006331 | 0 | 0.51651 | 0.51651 | 0.48349 | 1 | 2 | 2 | 0.51651 | 0.48349 |
2025-03-29 | 0.010762 | 1 | 0.536867 | 0.536867 | 0.463133 | 1 | 3 | 1 | 0.536867 | 0.463133 |
2025-03-30 | -0.048064 | 0 | 0.598314 | 0.598314 | 0.401686 | 1 | 4 | 0 | 0.598314 | 0.401686 |
2025-03-31 | -0.041027 | 0 | 0.598314 | 0.598314 | 0.401686 | 1 | 4 | 0 | 0.598314 | 0.401686 |
2025-04-01 | -0.103759 | 0 | 0.536867 | 0.536867 | 0.463133 | 1 | 3 | 1 | 0.536867 | 0.463133 |
2025-04-02 | 0.001199 | 1 | 0.532185 | 0.532185 | 0.467815 | 1 | 3 | 1 | 0.532185 | 0.467815 |
2025-04-03 | -0.043332 | 0 | 0.532185 | 0.532185 | 0.467815 | 1 | 3 | 1 | 0.532185 | 0.467815 |
2025-04-04 | -0.005555 | 0 | 0.579619 | 0.579619 | 0.420381 | 1 | 4 | 0 | 0.579619 | 0.420381 |
2025-04-05 | 0.020816 | 1 | 0.56983 | 0.56983 | 0.43017 | 1 | 4 | 0 | 0.56983 | 0.43017 |
2025-04-06 | 0.067959 | 1 | 0.566079 | 0.566079 | 0.433921 | 1 | 4 | 0 | 0.566079 | 0.433921 |
2025-04-07 | 0.068571 | 1 | 0.57202 | 0.57202 | 0.42798 | 1 | 4 | 0 | 0.57202 | 0.42798 |
2025-04-08 | 0.095929 | 1 | 0.597831 | 0.597831 | 0.402169 | 1 | 4 | 0 | 0.597831 | 0.402169 |
2025-04-09 | 0.01713 | 1 | 0.512606 | 0.512606 | 0.487394 | 1 | 2 | 2 | 0.512606 | 0.487394 |
2025-04-10 | 0.067087 | 1 | 0.602865 | 0.602865 | 0.397135 | 1 | 4 | 0 | 0.602865 | 0.397135 |
2025-04-11 | 0.012597 | 1 | 0.537843 | 0.537843 | 0.462157 | 1 | 3 | 1 | 0.537843 | 0.462157 |
2025-04-12 | -0.002344 | 0 | 0.521888 | 0.521888 | 0.478112 | 1 | 3 | 1 | 0.521888 | 0.478112 |
2025-04-13 | 0.016944 | 1 | 0.542673 | 0.542673 | 0.457327 | 1 | 3 | 1 | 0.542673 | 0.457327 |
2025-04-14 | 0.034574 | 1 | 0.531041 | 0.531041 | 0.468959 | 1 | 3 | 1 | 0.531041 | 0.468959 |
2025-04-15 | 0.117151 | 1 | 0.531041 | 0.531041 | 0.468959 | 1 | 3 | 1 | 0.531041 | 0.468959 |
2025-04-16 | 0.114967 | 1 | 0.517052 | 0.517052 | 0.482948 | 1 | 2 | 2 | 0.517052 | 0.482948 |
2025-04-17 | 0.106331 | 1 | 0.505361 | 0.505361 | 0.494639 | 1 | 2 | 2 | 0.505361 | 0.494639 |
2025-04-18 | 0.12032 | 1 | 0.505361 | 0.505361 | 0.494639 | 1 | 2 | 2 | 0.505361 | 0.494639 |
2025-04-19 | 0.112263 | 1 | 0.586318 | 0.586318 | 0.413682 | 1 | 4 | 0 | 0.586318 | 0.413682 |
2025-04-20 | 0.100612 | 1 | 0.586318 | 0.586318 | 0.413682 | 1 | 4 | 0 | 0.586318 | 0.413682 |
2025-04-21 | 0.085641 | 1 | 0.597618 | 0.597618 | 0.402382 | 1 | 4 | 0 | 0.597618 | 0.402382 |
2025-04-22 | 0.008709 | 1 | 0.506953 | 0.506953 | 0.493047 | 1 | 2 | 2 | 0.506953 | 0.493047 |
2025-04-23 | 0.005133 | 1 | 0.506953 | 0.506953 | 0.493047 | 1 | 2 | 2 | 0.506953 | 0.493047 |
2025-04-24 | 0.026702 | 1 | 0.506953 | 0.506953 | 0.493047 | 1 | 2 | 2 | 0.506953 | 0.493047 |
2025-04-25 | 0.023758 | 1 | 0.506953 | 0.506953 | 0.493047 | 1 | 2 | 2 | 0.506953 | 0.493047 |
2025-04-26 | 0.012982 | 1 | 0.513243 | 0.513243 | 0.486757 | 1 | 2 | 2 | 0.513243 | 0.486757 |
2025-04-27 | 0.005635 | 1 | 0.513243 | 0.513243 | 0.486757 | 1 | 2 | 2 | 0.513243 | 0.486757 |
2025-04-28 | -0.002921 | 0 | 0.513243 | 0.513243 | 0.486757 | 1 | 2 | 2 | 0.513243 | 0.486757 |
2025-04-29 | 0.027342 | 1 | 0.607916 | 0.607916 | 0.392084 | 1 | 4 | 0 | 0.607916 | 0.392084 |
2025-04-30 | 0.030354 | 1 | 0.627805 | 0.627805 | 0.372195 | 1 | 4 | 0 | 0.627805 | 0.372195 |
2025-05-01 | 0.07018 | 1 | 0.623256 | 0.623256 | 0.376744 | 1 | 4 | 0 | 0.623256 | 0.376744 |
2025-05-02 | 0.062803 | 1 | 0.634245 | 0.634245 | 0.365755 | 1 | 4 | 0 | 0.634245 | 0.365755 |
2025-05-03 | 0.093401 | 1 | 0.566545 | 0.566545 | 0.433455 | 1 | 4 | 0 | 0.566545 | 0.433455 |
2025-05-04 | 0.104377 | 1 | 0.531505 | 0.531505 | 0.468496 | 1 | 3 | 1 | 0.531505 | 0.468496 |
2025-05-05 | 0.085056 | 1 | 0.525811 | 0.525811 | 0.474189 | 1 | 3 | 1 | 0.525811 | 0.474189 |
2025-05-06 | 0.075074 | 1 | 0.566525 | 0.566525 | 0.433475 | 1 | 4 | 0 | 0.566525 | 0.433475 |
2025-05-07 | 0.066756 | 1 | 0.57563 | 0.57563 | 0.42437 | 1 | 4 | 0 | 0.57563 | 0.42437 |
2025-05-08 | 0.004863 | 1 | 0.582876 | 0.582876 | 0.417124 | 1 | 4 | 0 | 0.582876 | 0.417124 |
2025-05-09 | 0.004777 | 1 | 0.612387 | 0.612387 | 0.387613 | 1 | 4 | 0 | 0.612387 | 0.387613 |
2025-05-10 | -0.016057 | 0 | 0.699285 | 0.699285 | 0.300715 | 1 | 4 | 0 | 0.699285 | 0.300715 |
2025-05-11 | 0.022439 | 1 | 0.742364 | 0.742364 | 0.257636 | 1 | 4 | 0 | 0.742364 | 0.257636 |
2025-05-12 | 0.027069 | 1 | 0.671067 | 0.671067 | 0.328933 | 1 | 4 | 0 | 0.671067 | 0.328933 |
2025-05-13 | 0.02638 | 1 | 0.676648 | 0.676648 | 0.323352 | 1 | 4 | 0 | 0.676648 | 0.323352 |
2025-05-14 | 0.059282 | 1 | 0.648954 | 0.648954 | 0.351046 | 1 | 4 | 0 | 0.648954 | 0.351046 |
2025-05-15 | 0.076448 | 1 | 0.666202 | 0.666202 | 0.333798 | 1 | 4 | 0 | 0.666202 | 0.333798 |
2025-05-16 | 0.037254 | 1 | 0.666202 | 0.666202 | 0.333798 | 1 | 4 | 0 | 0.666202 | 0.333798 |
2025-05-17 | 0.044947 | 1 | 0.726874 | 0.726874 | 0.273126 | 1 | 4 | 0 | 0.726874 | 0.273126 |
2025-05-18 | 0.023953 | 1 | 0.65905 | 0.65905 | 0.34095 | 1 | 4 | 0 | 0.65905 | 0.34095 |
2025-05-19 | 0.036572 | 1 | 0.652808 | 0.652808 | 0.347192 | 1 | 4 | 0 | 0.652808 | 0.347192 |
2025-05-20 | 0.019543 | 1 | 0.652808 | 0.652808 | 0.347192 | 1 | 4 | 0 | 0.652808 | 0.347192 |
2025-05-21 | -0.016984 | 0 | 0.670567 | 0.670567 | 0.329433 | 1 | 4 | 0 | 0.670567 | 0.329433 |
2025-05-22 | -0.05467 | 0 | 0.651257 | 0.651257 | 0.348743 | 1 | 4 | 0 | 0.651257 | 0.348743 |
2025-05-23 | -0.031055 | 0 | 0.535708 | 0.535708 | 0.464292 | 1 | 3 | 1 | 0.535708 | 0.464292 |
2025-05-24 | -0.029417 | 0 | 0.535708 | 0.535708 | 0.464292 | 1 | 3 | 1 | 0.535708 | 0.464292 |
2025-05-25 | -0.030836 | 0 | 0.529221 | 0.529221 | 0.470779 | 1 | 3 | 1 | 0.529221 | 0.470779 |
2025-05-26 | -0.032684 | 0 | 0.555398 | 0.555398 | 0.444602 | 1 | 4 | 0 | 0.555398 | 0.444602 |
2025-05-27 | -0.032691 | 0 | 0.479932 | 0.479932 | 0.520068 | 0 | 0 | 4 | 0.479932 | 0.520068 |
2025-05-28 | -0.028622 | 0 | 0.494628 | 0.494628 | 0.505372 | 0 | 1 | 3 | 0.494628 | 0.505372 |
2025-05-29 | -0.03865 | 0 | 0.529801 | 0.529801 | 0.470199 | 1 | 3 | 1 | 0.529801 | 0.470199 |
2025-05-30 | 0.002913 | 1 | 0.537763 | 0.537763 | 0.462237 | 1 | 3 | 1 | 0.537763 | 0.462237 |
2025-05-31 | 0.009181 | 1 | 0.50587 | 0.50587 | 0.49413 | 1 | 2 | 2 | 0.50587 | 0.49413 |
2025-06-01 | 0.000862 | 1 | 0.536816 | 0.536816 | 0.463184 | 1 | 3 | 1 | 0.536816 | 0.463184 |
2025-06-02 | 0.041613 | 1 | 0.510509 | 0.510509 | 0.489491 | 1 | 2 | 2 | 0.510509 | 0.489491 |
2025-06-03 | 0.046476 | 1 | 0.477958 | 0.477958 | 0.522042 | 0 | 0 | 4 | 0.477958 | 0.522042 |
2025-06-04 | 0.037711 | 1 | 0.502046 | 0.502046 | 0.497954 | 1 | 2 | 2 | 0.502046 | 0.497954 |
2025-06-05 | 0.041012 | 1 | 0.549751 | 0.549751 | 0.450249 | 1 | 3 | 1 | 0.549751 | 0.450249 |
2025-06-06 | 0.01705 | 1 | 0.491972 | 0.491972 | 0.508028 | 0 | 1 | 3 | 0.491972 | 0.508028 |
2025-06-07 | -0.001303 | 0 | 0.449697 | 0.449697 | 0.550303 | 0 | 0 | 4 | 0.449697 | 0.550303 |
2025-06-08 | -0.001324 | 0 | 0.464803 | 0.464803 | 0.535197 | 0 | 0 | 4 | 0.464803 | 0.535197 |
2025-06-09 | -0.031457 | 0 | 0.464803 | 0.464803 | 0.535197 | 0 | 0 | 4 | 0.464803 | 0.535197 |
2025-06-10 | -0.0519 | 0 | 0.464803 | 0.464803 | 0.535197 | 0 | 0 | 4 | 0.464803 | 0.535197 |
2025-06-11 | -0.034593 | 0 | 0.518336 | 0.518336 | 0.481664 | 1 | 3 | 1 | 0.518336 | 0.481664 |
2025-06-12 | -0.009588 | 0 | 0.529464 | 0.529464 | 0.470536 | 1 | 3 | 1 | 0.529464 | 0.470536 |
2025-06-13 | -0.026102 | 0 | 0.560195 | 0.560195 | 0.439805 | 1 | 4 | 0 | 0.560195 | 0.439805 |
2025-06-14 | -0.031254 | 0 | 0.549175 | 0.549175 | 0.450825 | 1 | 3 | 1 | 0.549175 | 0.450825 |
2025-06-15 | -0.043849 | 0 | 0.560195 | 0.560195 | 0.439805 | 1 | 4 | 0 | 0.560195 | 0.439805 |
2025-06-16 | -0.013677 | 0 | 0.549751 | 0.549751 | 0.450249 | 1 | 3 | 1 | 0.549751 | 0.450249 |
2025-06-17 | 0.014651 | 1 | 0.55959 | 0.55959 | 0.44041 | 1 | 4 | 0 | 0.55959 | 0.44041 |
2025-06-18 | 0.023395 | 1 | 0.55123 | 0.55123 | 0.44877 | 1 | 3 | 1 | 0.55123 | 0.44877 |
2025-06-19 | 0.021866 | 1 | 0.58798 | 0.58798 | 0.41202 | 1 | 4 | 0 | 0.58798 | 0.41202 |
2025-06-20 | 0.036299 | 1 | 0.58798 | 0.58798 | 0.41202 | 1 | 4 | 0 | 0.58798 | 0.41202 |
2025-06-21 | 0.050693 | 1 | 0.58798 | 0.58798 | 0.41202 | 1 | 4 | 0 | 0.58798 | 0.41202 |
2025-06-22 | 0.073225 | 1 | 0.535248 | 0.535248 | 0.464752 | 1 | 3 | 1 | 0.535248 | 0.464752 |
2025-06-23 | 0.017208 | 1 | 0.496317 | 0.496317 | 0.503683 | 0 | 1 | 3 | 0.496317 | 0.503683 |
2025-06-24 | -0.003788 | 0 | 0.475917 | 0.475917 | 0.524083 | 0 | 0 | 4 | 0.475917 | 0.524083 |
2025-06-25 | 0.014058 | 1 | 0.475917 | 0.475917 | 0.524083 | 0 | 0 | 4 | 0.475917 | 0.524083 |
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