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Datasets:
Plashkar
/
diabetes-predict-db

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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
_indexes
dict
_output_all_columns
bool
_split
null
[ { "filename": "dataset.arrow" } ]
8b9e5f2e307c548a
[ "feat_Age", "feat_AnyHealthcare", "feat_BMI", "feat_CholCheck", "feat_DiffWalk", "feat_Education", "feat_Fruits", "feat_GenHlth", "feat_HeartDiseaseorAttack", "feat_HighBP", "feat_HighChol", "feat_HvyAlcoholConsump", "feat_Income", "feat_MentHlth", "feat_NoDocbcCost", "feat_PhysActivity", "feat_PhysHlth", "feat_Sex", "feat_Smoker", "feat_Stroke", "feat_Veggies", "target" ]
{}
null
{}
false
null

AutoTrain Dataset for project: sample-diabetes-predict

Dataset Descritpion

This dataset has been automatically processed by AutoTrain for project sample-diabetes-predict.

Languages

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

Dataset Structure

Data Instances

A sample from this dataset looks as follows:

[
  {
    "target": 0,
    "feat_HighBP": 0.0,
    "feat_HighChol": 0.0,
    "feat_CholCheck": 1.0,
    "feat_BMI": 34.0,
    "feat_Smoker": 1.0,
    "feat_Stroke": 0.0,
    "feat_HeartDiseaseorAttack": 0.0,
    "feat_PhysActivity": 1.0,
    "feat_Fruits": 1.0,
    "feat_Veggies": 1.0,
    "feat_HvyAlcoholConsump": 0.0,
    "feat_AnyHealthcare": 1.0,
    "feat_NoDocbcCost": 0.0,
    "feat_GenHlth": 3.0,
    "feat_MentHlth": 0.0,
    "feat_PhysHlth": 0.0,
    "feat_DiffWalk": 0.0,
    "feat_Sex": 0.0,
    "feat_Age": 6.0,
    "feat_Education": 6.0,
    "feat_Income": 7.0
  },
  {
    "target": 1,
    "feat_HighBP": 0.0,
    "feat_HighChol": 0.0,
    "feat_CholCheck": 1.0,
    "feat_BMI": 46.0,
    "feat_Smoker": 1.0,
    "feat_Stroke": 0.0,
    "feat_HeartDiseaseorAttack": 0.0,
    "feat_PhysActivity": 1.0,
    "feat_Fruits": 1.0,
    "feat_Veggies": 1.0,
    "feat_HvyAlcoholConsump": 0.0,
    "feat_AnyHealthcare": 1.0,
    "feat_NoDocbcCost": 0.0,
    "feat_GenHlth": 2.0,
    "feat_MentHlth": 1.0,
    "feat_PhysHlth": 0.0,
    "feat_DiffWalk": 0.0,
    "feat_Sex": 1.0,
    "feat_Age": 10.0,
    "feat_Education": 6.0,
    "feat_Income": 5.0
  }
]

Dataset Fields

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

{
  "target": "ClassLabel(num_classes=2, names=['0.0', '1.0'], id=None)",
  "feat_HighBP": "Value(dtype='float64', id=None)",
  "feat_HighChol": "Value(dtype='float64', id=None)",
  "feat_CholCheck": "Value(dtype='float64', id=None)",
  "feat_BMI": "Value(dtype='float64', id=None)",
  "feat_Smoker": "Value(dtype='float64', id=None)",
  "feat_Stroke": "Value(dtype='float64', id=None)",
  "feat_HeartDiseaseorAttack": "Value(dtype='float64', id=None)",
  "feat_PhysActivity": "Value(dtype='float64', id=None)",
  "feat_Fruits": "Value(dtype='float64', id=None)",
  "feat_Veggies": "Value(dtype='float64', id=None)",
  "feat_HvyAlcoholConsump": "Value(dtype='float64', id=None)",
  "feat_AnyHealthcare": "Value(dtype='float64', id=None)",
  "feat_NoDocbcCost": "Value(dtype='float64', id=None)",
  "feat_GenHlth": "Value(dtype='float64', id=None)",
  "feat_MentHlth": "Value(dtype='float64', id=None)",
  "feat_PhysHlth": "Value(dtype='float64', id=None)",
  "feat_DiffWalk": "Value(dtype='float64', id=None)",
  "feat_Sex": "Value(dtype='float64', id=None)",
  "feat_Age": "Value(dtype='float64', id=None)",
  "feat_Education": "Value(dtype='float64', id=None)",
  "feat_Income": "Value(dtype='float64', 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 56552
valid 14140
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