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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 10 new columns ({'education', 'looks_at', 'initial_focus_time', 'age', 'paper_type', 'visual_acuity', 'font_size', 'reading_speed', 'text_density', 'gender'}) and 9 missing columns ({'LeaveOrNot', 'PaymentTier', 'EverBenched', 'Gender', 'JoiningYear', 'Age', 'Education', 'City', 'ExperienceInCurrentDomain'}).
This happened while the csv dataset builder was generating data using
hf://datasets/dekomin/TabAdap/processed/classification/first_glance/looks_at_downsampled_2048.csv (at revision 1583e72db1f8f4634d4f460a842f2bfdbd0be30c)
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 1870, in _prepare_split_single
writer.write_table(table)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/arrow_writer.py", line 622, 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 2240, in cast_table_to_schema
raise CastError(
datasets.table.CastError: Couldn't cast
age: int64
gender: string
education: string
visual_acuity: string
reading_speed: string
text_density: string
font_size: string
paper_type: string
initial_focus_time: string
looks_at: string
-- schema metadata --
pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 1461
to
{'Education': Value(dtype='string', id=None), 'JoiningYear': Value(dtype='int64', id=None), 'City': Value(dtype='string', id=None), 'PaymentTier': Value(dtype='int64', id=None), 'Age': Value(dtype='int64', id=None), 'Gender': Value(dtype='string', id=None), 'EverBenched': Value(dtype='string', id=None), 'ExperienceInCurrentDomain': Value(dtype='int64', id=None), 'LeaveOrNot': 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 1420, 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 1052, 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 1000, 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 1741, 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 1872, 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 10 new columns ({'education', 'looks_at', 'initial_focus_time', 'age', 'paper_type', 'visual_acuity', 'font_size', 'reading_speed', 'text_density', 'gender'}) and 9 missing columns ({'LeaveOrNot', 'PaymentTier', 'EverBenched', 'Gender', 'JoiningYear', 'Age', 'Education', 'City', 'ExperienceInCurrentDomain'}).
This happened while the csv dataset builder was generating data using
hf://datasets/dekomin/TabAdap/processed/classification/first_glance/looks_at_downsampled_2048.csv (at revision 1583e72db1f8f4634d4f460a842f2bfdbd0be30c)
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.
Education
string | JoiningYear
int64 | City
string | PaymentTier
int64 | Age
int64 | Gender
string | EverBenched
string | ExperienceInCurrentDomain
int64 | LeaveOrNot
int64 |
|---|---|---|---|---|---|---|---|---|
Bachelors
| 2,017 |
Pune
| 2 | 35 |
Female
|
No
| 5 | 1 |
Bachelors
| 2,014 |
Bangalore
| 3 | 38 |
Female
|
No
| 2 | 0 |
Bachelors
| 2,014 |
Bangalore
| 3 | 27 |
Male
|
No
| 5 | 0 |
Bachelors
| 2,018 |
Bangalore
| 3 | 38 |
Male
|
No
| 0 | 1 |
Bachelors
| 2,018 |
Bangalore
| 3 | 28 |
Male
|
No
| 1 | 1 |
Masters
| 2,017 |
Bangalore
| 2 | 27 |
Male
|
No
| 5 | 0 |
Bachelors
| 2,015 |
Bangalore
| 3 | 31 |
Male
|
No
| 1 | 0 |
Bachelors
| 2,012 |
Pune
| 3 | 28 |
Male
|
No
| 3 | 0 |
Bachelors
| 2,014 |
Pune
| 3 | 36 |
Female
|
No
| 5 | 0 |
Masters
| 2,013 |
New Delhi
| 2 | 24 |
Male
|
No
| 2 | 1 |
Bachelors
| 2,014 |
Bangalore
| 3 | 22 |
Female
|
No
| 0 | 0 |
Bachelors
| 2,015 |
Bangalore
| 3 | 28 |
Male
|
No
| 1 | 0 |
PHD
| 2,017 |
Bangalore
| 3 | 27 |
Male
|
No
| 5 | 0 |
Masters
| 2,018 |
New Delhi
| 3 | 24 |
Male
|
No
| 2 | 1 |
Bachelors
| 2,016 |
Pune
| 3 | 33 |
Male
|
No
| 2 | 0 |
Bachelors
| 2,015 |
Bangalore
| 3 | 24 |
Female
|
No
| 2 | 0 |
Bachelors
| 2,017 |
New Delhi
| 3 | 25 |
Female
|
No
| 3 | 0 |
Bachelors
| 2,014 |
Pune
| 3 | 29 |
Male
|
No
| 3 | 0 |
Bachelors
| 2,013 |
Pune
| 3 | 25 |
Male
|
No
| 3 | 0 |
Bachelors
| 2,013 |
Pune
| 3 | 28 |
Female
|
No
| 2 | 1 |
Bachelors
| 2,015 |
Bangalore
| 3 | 36 |
Male
|
No
| 3 | 0 |
Masters
| 2,017 |
New Delhi
| 2 | 24 |
Male
|
Yes
| 2 | 1 |
Masters
| 2,017 |
New Delhi
| 2 | 27 |
Female
|
No
| 5 | 0 |
Masters
| 2,017 |
New Delhi
| 2 | 34 |
Female
|
No
| 4 | 0 |
Bachelors
| 2,016 |
Bangalore
| 3 | 27 |
Female
|
No
| 5 | 0 |
Masters
| 2,012 |
Pune
| 3 | 24 |
Male
|
No
| 2 | 0 |
Bachelors
| 2,015 |
Pune
| 3 | 26 |
Female
|
Yes
| 4 | 1 |
Bachelors
| 2,014 |
Pune
| 2 | 27 |
Female
|
No
| 5 | 1 |
Bachelors
| 2,016 |
Bangalore
| 3 | 26 |
Female
|
No
| 4 | 1 |
Bachelors
| 2,017 |
New Delhi
| 3 | 28 |
Male
|
No
| 2 | 0 |
Bachelors
| 2,016 |
Bangalore
| 3 | 28 |
Male
|
No
| 1 | 0 |
Bachelors
| 2,014 |
Bangalore
| 3 | 34 |
Male
|
No
| 1 | 0 |
Bachelors
| 2,017 |
New Delhi
| 2 | 26 |
Male
|
No
| 4 | 0 |
Masters
| 2,013 |
Bangalore
| 3 | 30 |
Male
|
No
| 1 | 1 |
Bachelors
| 2,017 |
Bangalore
| 1 | 28 |
Female
|
No
| 0 | 1 |
Masters
| 2,012 |
New Delhi
| 3 | 35 |
Female
|
No
| 4 | 1 |
Bachelors
| 2,017 |
New Delhi
| 3 | 37 |
Male
|
No
| 0 | 0 |
Bachelors
| 2,016 |
Pune
| 2 | 28 |
Female
|
No
| 0 | 1 |
Masters
| 2,014 |
Pune
| 3 | 39 |
Male
|
No
| 2 | 0 |
Bachelors
| 2,013 |
Pune
| 3 | 27 |
Female
|
No
| 5 | 1 |
Masters
| 2,014 |
New Delhi
| 3 | 28 |
Female
|
No
| 3 | 0 |
Bachelors
| 2,016 |
Bangalore
| 3 | 26 |
Female
|
No
| 4 | 0 |
Bachelors
| 2,016 |
Bangalore
| 3 | 32 |
Male
|
No
| 1 | 0 |
Bachelors
| 2,016 |
Bangalore
| 1 | 34 |
Male
|
Yes
| 2 | 1 |
Bachelors
| 2,013 |
New Delhi
| 3 | 38 |
Female
|
No
| 4 | 1 |
Bachelors
| 2,017 |
New Delhi
| 3 | 28 |
Female
|
No
| 3 | 0 |
Bachelors
| 2,017 |
Bangalore
| 3 | 29 |
Female
|
No
| 1 | 0 |
Bachelors
| 2,012 |
Bangalore
| 3 | 24 |
Male
|
No
| 2 | 0 |
Bachelors
| 2,013 |
Pune
| 3 | 32 |
Male
|
No
| 2 | 0 |
Bachelors
| 2,018 |
Bangalore
| 3 | 26 |
Female
|
Yes
| 4 | 1 |
Bachelors
| 2,016 |
Pune
| 3 | 38 |
Male
|
No
| 0 | 0 |
Bachelors
| 2,017 |
Bangalore
| 3 | 41 |
Male
|
No
| 1 | 0 |
Bachelors
| 2,018 |
Pune
| 3 | 25 |
Male
|
No
| 3 | 1 |
Masters
| 2,017 |
Pune
| 2 | 39 |
Female
|
No
| 3 | 0 |
Bachelors
| 2,014 |
Bangalore
| 3 | 35 |
Female
|
No
| 2 | 0 |
Masters
| 2,017 |
New Delhi
| 2 | 24 |
Female
|
No
| 2 | 0 |
Masters
| 2,017 |
New Delhi
| 3 | 26 |
Male
|
No
| 4 | 0 |
Masters
| 2,018 |
New Delhi
| 3 | 23 |
Female
|
No
| 1 | 1 |
Bachelors
| 2,015 |
Pune
| 3 | 35 |
Female
|
No
| 1 | 1 |
Bachelors
| 2,018 |
Pune
| 3 | 28 |
Male
|
No
| 2 | 1 |
PHD
| 2,018 |
New Delhi
| 3 | 33 |
Female
|
No
| 4 | 1 |
Bachelors
| 2,018 |
Bangalore
| 3 | 24 |
Male
|
No
| 2 | 1 |
Bachelors
| 2,015 |
Bangalore
| 3 | 32 |
Female
|
No
| 4 | 0 |
Masters
| 2,013 |
New Delhi
| 3 | 31 |
Male
|
No
| 2 | 1 |
PHD
| 2,014 |
New Delhi
| 3 | 28 |
Female
|
No
| 0 | 0 |
Bachelors
| 2,014 |
Pune
| 2 | 38 |
Female
|
No
| 3 | 1 |
Masters
| 2,018 |
New Delhi
| 3 | 35 |
Male
|
No
| 2 | 1 |
Bachelors
| 2,014 |
Bangalore
| 3 | 27 |
Female
|
No
| 5 | 0 |
Masters
| 2,016 |
New Delhi
| 3 | 24 |
Male
|
No
| 2 | 1 |
Bachelors
| 2,012 |
Pune
| 2 | 35 |
Female
|
No
| 2 | 1 |
Masters
| 2,014 |
New Delhi
| 3 | 39 |
Male
|
No
| 2 | 0 |
Bachelors
| 2,014 |
New Delhi
| 3 | 23 |
Male
|
No
| 1 | 0 |
Bachelors
| 2,017 |
New Delhi
| 3 | 26 |
Male
|
No
| 4 | 0 |
Bachelors
| 2,013 |
Pune
| 3 | 28 |
Male
|
No
| 1 | 0 |
Bachelors
| 2,016 |
Pune
| 3 | 29 |
Male
|
No
| 5 | 0 |
Bachelors
| 2,013 |
Bangalore
| 3 | 35 |
Male
|
No
| 5 | 0 |
PHD
| 2,013 |
New Delhi
| 3 | 27 |
Male
|
No
| 5 | 0 |
Masters
| 2,017 |
New Delhi
| 2 | 26 |
Female
|
No
| 4 | 0 |
Bachelors
| 2,017 |
New Delhi
| 3 | 24 |
Female
|
No
| 2 | 0 |
Masters
| 2,012 |
Bangalore
| 3 | 40 |
Female
|
No
| 5 | 0 |
Bachelors
| 2,012 |
Bangalore
| 3 | 23 |
Male
|
Yes
| 1 | 0 |
Masters
| 2,017 |
New Delhi
| 1 | 26 |
Female
|
No
| 4 | 0 |
Bachelors
| 2,015 |
Pune
| 3 | 28 |
Male
|
Yes
| 2 | 0 |
Bachelors
| 2,017 |
Bangalore
| 3 | 27 |
Male
|
No
| 5 | 0 |
Bachelors
| 2,012 |
Bangalore
| 3 | 25 |
Male
|
No
| 3 | 0 |
Masters
| 2,013 |
Pune
| 2 | 28 |
Male
|
No
| 2 | 1 |
Bachelors
| 2,016 |
New Delhi
| 2 | 26 |
Female
|
No
| 4 | 1 |
Bachelors
| 2,017 |
New Delhi
| 2 | 40 |
Male
|
No
| 5 | 0 |
Bachelors
| 2,015 |
New Delhi
| 3 | 26 |
Female
|
Yes
| 4 | 0 |
Masters
| 2,015 |
New Delhi
| 3 | 26 |
Male
|
No
| 4 | 1 |
Bachelors
| 2,017 |
Bangalore
| 3 | 27 |
Male
|
No
| 5 | 0 |
Bachelors
| 2,014 |
Bangalore
| 3 | 27 |
Male
|
No
| 5 | 0 |
Bachelors
| 2,016 |
Bangalore
| 1 | 30 |
Male
|
No
| 4 | 1 |
Masters
| 2,017 |
Pune
| 2 | 39 |
Male
|
No
| 2 | 0 |
Masters
| 2,017 |
New Delhi
| 2 | 24 |
Male
|
No
| 2 | 1 |
Bachelors
| 2,016 |
Bangalore
| 3 | 33 |
Male
|
No
| 6 | 0 |
Bachelors
| 2,016 |
Bangalore
| 3 | 37 |
Female
|
No
| 1 | 0 |
Bachelors
| 2,014 |
Bangalore
| 3 | 25 |
Male
|
No
| 3 | 0 |
Bachelors
| 2,017 |
New Delhi
| 2 | 28 |
Male
|
No
| 0 | 0 |
Bachelors
| 2,013 |
Pune
| 3 | 24 |
Female
|
No
| 2 | 0 |
End of preview.
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