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The dataset generation failed
Error code:   DatasetGenerationError
Exception:    ArrowInvalid
Message:      Float value 17.29 was truncated converting to int64
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1869, in _prepare_split_single
                  writer.write_table(table)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/arrow_writer.py", line 580, 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 2292, in table_cast
                  return cast_table_to_schema(table, schema)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2245, in cast_table_to_schema
                  arrays = [
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2246, in <listcomp>
                  cast_array_to_feature(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 1795, in wrapper
                  return pa.chunked_array([func(chunk, *args, **kwargs) for chunk in array.chunks])
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 1795, in <listcomp>
                  return pa.chunked_array([func(chunk, *args, **kwargs) for chunk in array.chunks])
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2102, in cast_array_to_feature
                  return array_cast(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 1797, in wrapper
                  return func(array, *args, **kwargs)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 1949, in array_cast
                  return array.cast(pa_type)
                File "pyarrow/array.pxi", line 996, in pyarrow.lib.Array.cast
                File "/src/services/worker/.venv/lib/python3.9/site-packages/pyarrow/compute.py", line 404, in cast
                  return call_function("cast", [arr], options, memory_pool)
                File "pyarrow/_compute.pyx", line 590, in pyarrow._compute.call_function
                File "pyarrow/_compute.pyx", line 385, in pyarrow._compute.Function.call
                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.ArrowInvalid: Float value 17.29 was truncated converting to int64
              
              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 1392, 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 1041, in convert_to_parquet
                  builder.download_and_prepare(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 924, in download_and_prepare
                  self._download_and_prepare(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 999, 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 1740, 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 1896, 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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age
int64
sex
string
bmi
float64
children
int64
smoker
string
region
string
prediction
float64
60
male
72
2
no
northwest
28,219.275589
44
female
23
0
yes
southwest
29,970.170203
30
female
30
2
no
southwest
5,931.586896
30
female
30
2
no
southwest
5,931.586896
30
female
30
2
no
southwest
5,931.586896
30
female
30
2
no
southwest
5,931.586896
30
female
30
2
no
southwest
5,931.586896
30
female
30
2
no
southwest
5,931.586896
30
female
30
2
no
southwest
5,931.586896
30
female
30
2
no
southwest
5,931.586896
30
female
30
2
no
southwest
5,931.586896
30
female
30
2
no
southwest
5,931.586896
30
female
30
2
no
southwest
5,931.586896
30
female
30
2
no
southwest
5,931.586896
30
female
30
2
no
southwest
5,931.586896
30
female
30
2
no
southwest
5,931.586896
30
female
30
2
no
southwest
5,931.586896
30
female
30
2
no
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5,931.586896
30
female
30
2
no
southwest
5,931.586896
30
female
30
2
no
southwest
5,931.586896
30
female
30
2
no
southwest
5,931.586896
30
female
30
2
no
southwest
5,931.586896
30
female
30
2
no
southwest
5,931.586896
30
female
30
2
no
southwest
5,931.586896
30
female
30
2
no
southwest
5,931.586896
30
female
30
2
no
southwest
5,931.586896
30
female
30
2
no
southwest
5,931.586896
30
female
30
2
no
southwest
5,931.586896
30
female
30
2
no
southwest
5,931.586896
30
female
30
2
no
southwest
5,931.586896
30
female
30
2
no
southwest
5,931.586896
30
female
30
2
no
southwest
5,931.586896
30
female
30
2
no
southwest
5,931.586896
30
female
30
2
no
southwest
5,931.586896
30
female
30
2
no
southwest
5,931.586896
30
female
30
2
no
southwest
5,931.586896
30
female
30
2
no
southwest
5,931.586896
30
female
30
2
no
southwest
5,931.586896
30
female
30
2
no
southwest
5,931.586896
30
female
30
2
no
southwest
5,931.586896
30
female
30
2
no
southwest
5,931.586896
30
female
30
2
no
southwest
5,931.586896
30
female
30
2
no
southwest
5,931.586896
30
female
30
2
no
southwest
5,931.586896
30
female
30
2
no
southwest
5,931.586896
30
female
30
2
no
southwest
5,931.586896
30
female
30
2
no
southwest
5,931.586896
30
female
30
2
no
southwest
5,931.586896
30
female
30
2
no
southwest
5,931.586896
30
female
30
2
no
southwest
5,931.586896
30
female
30
2
no
southwest
5,931.586896
30
female
30
2
no
southwest
5,931.586896
30
female
30
2
no
southwest
5,931.586896
30
female
30
2
no
southwest
5,931.586896
30
female
30
2
no
southwest
5,931.586896
30
female
30
2
no
southwest
5,931.586896
30
female
30
2
no
southwest
5,931.586896
30
female
30
2
no
southwest
5,931.586896
30
female
30
2
no
southwest
5,931.586896
30
female
30
2
no
southwest
5,931.586896
30
female
30
2
no
southwest
5,931.586896
30
female
30
2
no
southwest
5,931.586896
30
female
30
2
no
southwest
5,931.586896
30
female
30
2
no
southwest
5,931.586896
30
female
30
2
no
southwest
5,931.586896
30
female
30
2
no
southwest
5,931.586896
30
female
30
2
no
southwest
5,931.586896
30
female
30
2
no
southwest
5,931.586896
30
female
30
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no
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5,931.586896
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30
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no
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5,931.586896
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female
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2
no
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5,931.586896
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30
2
no
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5,931.586896
30
female
30
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no
southwest
5,931.586896
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no
southwest
5,931.586896
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no
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5,931.586896
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female
30
2
no
southwest
5,931.586896
30
female
30
2
no
southwest
5,931.586896
30
female
30
2
no
southwest
5,931.586896
30
female
30
2
no
southwest
5,931.586896
30
female
30
2
no
southwest
5,931.586896
30
female
30
2
no
southwest
5,931.586896
30
female
30
2
no
southwest
5,931.586896
30
female
30
2
no
southwest
5,931.586896
30
female
30
2
no
southwest
5,931.586896
30
female
30
2
no
southwest
5,931.586896
30
female
30
2
no
southwest
5,931.586896
30
female
30
2
no
southwest
5,931.586896
30
female
30
2
no
southwest
5,931.586896
30
female
30
2
no
southwest
5,931.586896
30
female
30
2
no
southwest
5,931.586896
30
female
30
2
no
southwest
5,931.586896
30
female
30
2
no
southwest
5,931.586896
30
female
30
2
no
southwest
5,931.586896
30
female
30
2
no
southwest
5,931.586896
30
female
30
2
no
southwest
5,931.586896
30
female
30
2
no
southwest
5,931.586896
30
female
30
2
no
southwest
5,931.586896
30
female
30
2
no
southwest
5,931.586896
30
female
30
2
no
southwest
5,931.586896
30
female
30
2
no
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5,931.586896
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