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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 ({'looks_at', 'gender', 'text_density', 'reading_speed', 'font_size', 'education', 'paper_type', 'visual_acuity', 'age', 'initial_focus_time'}) and 9 missing columns ({'LeaveOrNot', 'Age', 'PaymentTier', 'JoiningYear', 'EverBenched', 'Education', 'City', 'ExperienceInCurrentDomain', 'Gender'}). 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 c2a31f6166547d42a1bf99d253dd8c789a554421) 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 ({'looks_at', 'gender', 'text_density', 'reading_speed', 'font_size', 'education', 'paper_type', 'visual_acuity', 'age', 'initial_focus_time'}) and 9 missing columns ({'LeaveOrNot', 'Age', 'PaymentTier', 'JoiningYear', 'EverBenched', 'Education', 'City', 'ExperienceInCurrentDomain', 'Gender'}). 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 c2a31f6166547d42a1bf99d253dd8c789a554421) 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)
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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.
This is a selection of datasets from the CARTE's public datast pool.
We created the selection to not include duplicate feature spaces and datasets will low quality in terms of feature name and it's values semantics.
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