The full dataset viewer is not available (click to read why). Only showing a preview of the rows.
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.