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IceMasterT
/
autotrain-data-bam-v2

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The dataset generation failed
Error code:   DatasetGenerationError
Exception:    ArrowNotImplementedError
Message:      Cannot write struct type '_format_kwargs' with no child field to Parquet. Consider adding a dummy child field.
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 583, in write_table
                  self._build_writer(inferred_schema=pa_table.schema)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/arrow_writer.py", line 404, in _build_writer
                  self.pa_writer = self._WRITER_CLASS(self.stream, schema)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/pyarrow/parquet/core.py", line 1010, in __init__
                  self.writer = _parquet.ParquetWriter(
                File "pyarrow/_parquet.pyx", line 2157, in pyarrow._parquet.ParquetWriter.__cinit__
                File "pyarrow/error.pxi", line 154, in pyarrow.lib.pyarrow_internal_check_status
                File "pyarrow/error.pxi", line 91, in pyarrow.lib.check_status
              pyarrow.lib.ArrowNotImplementedError: Cannot write struct type '_format_kwargs' with no child field to Parquet. Consider adding a dummy child field.
              
              During handling of the above exception, another exception occurred:
              
              Traceback (most recent call last):
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 2027, in _prepare_split_single
                  num_examples, num_bytes = writer.finalize()
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/arrow_writer.py", line 602, in finalize
                  self._build_writer(self.schema)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/arrow_writer.py", line 404, in _build_writer
                  self.pa_writer = self._WRITER_CLASS(self.stream, schema)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/pyarrow/parquet/core.py", line 1010, in __init__
                  self.writer = _parquet.ParquetWriter(
                File "pyarrow/_parquet.pyx", line 2157, in pyarrow._parquet.ParquetWriter.__cinit__
                File "pyarrow/error.pxi", line 154, in pyarrow.lib.pyarrow_internal_check_status
                File "pyarrow/error.pxi", line 91, in pyarrow.lib.check_status
              pyarrow.lib.ArrowNotImplementedError: Cannot write struct type '_format_kwargs' with no child field to Parquet. Consider adding a dummy child field.
              
              The above exception was the direct cause of the following exception:
              
              Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1529, 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 1154, 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 2038, in _prepare_split_single
                  raise DatasetGenerationError("An error occurred while generating the dataset") from e
              datasets.exceptions.DatasetGenerationError: An error occurred while generating the dataset

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_data_files
list
_fingerprint
string
_format_columns
sequence
_format_kwargs
dict
_format_type
null
_output_all_columns
bool
_split
null
[ { "filename": "data-00000-of-00001.arrow" } ]
f3d1ae7d3c94d6ca
[ "feat_Adj Close", "feat_Date", "feat_High", "feat_Low", "feat_Open", "feat_Volume", "feat_Volume BTC", "feat_Volume U", "feat_Volume USD", "feat_date", "feat_high", "feat_low", "feat_open", "feat_unix", "id", "target" ]
{}
null
false
null

AutoTrain Dataset for project: bam-v2

Dataset Description

This dataset has been automatically processed by AutoTrain for project bam-v2.

Languages

The BCP-47 code for the dataset's language is unk.

Dataset Structure

Data Instances

A sample from this dataset looks as follows:

[
  {
    "feat_unix": 1548158400,
    "feat_date": "2019-01-22 12:00:00",
    "id": "BTC/USD",
    "feat_open": 3543.58,
    "feat_high": 3590.0,
    "feat_low": 3523.1,
    "target": 3557.860107421875,
    "feat_Volume BTC": 3593298.05,
    "feat_Volume USD": 1009.88,
    "feat_Volume U": null,
    "feat_Date": null,
    "feat_Open": null,
    "feat_High": null,
    "feat_Low": null,
    "feat_Adj Close": null,
    "feat_Volume": null
  },
  {
    "feat_unix": 1627473600,
    "feat_date": "2021-07-28 12:00:00",
    "id": "BTC/USD",
    "feat_open": 40786.1,
    "feat_high": 40900.0,
    "feat_low": 39601.35,
    "target": 39708.12109375,
    "feat_Volume BTC": 265.2041301,
    "feat_Volume USD": 10530757.42,
    "feat_Volume U": null,
    "feat_Date": null,
    "feat_Open": null,
    "feat_High": null,
    "feat_Low": null,
    "feat_Adj Close": null,
    "feat_Volume": null
  }
]

Dataset Fields

The dataset has the following fields (also called "features"):

{
  "feat_unix": "Value(dtype='int64', id=None)",
  "feat_date": "Value(dtype='string', id=None)",
  "id": "Value(dtype='string', id=None)",
  "feat_open": "Value(dtype='float64', id=None)",
  "feat_high": "Value(dtype='float64', id=None)",
  "feat_low": "Value(dtype='float64', id=None)",
  "target": "Value(dtype='float32', id=None)",
  "feat_Volume BTC": "Value(dtype='float64', id=None)",
  "feat_Volume USD": "Value(dtype='float64', id=None)",
  "feat_Volume U": "Value(dtype='float64', id=None)",
  "feat_Date": "Value(dtype='string', id=None)",
  "feat_Open": "Value(dtype='float64', id=None)",
  "feat_High": "Value(dtype='float64', id=None)",
  "feat_Low": "Value(dtype='float64', id=None)",
  "feat_Adj Close": "Value(dtype='float64', id=None)",
  "feat_Volume": "Value(dtype='int64', id=None)"
}

Dataset Splits

This dataset is split into a train and validation split. The split sizes are as follow:

Split name Num samples
train 41362
valid 10349
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