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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 1 new columns ({'ProdTaken'}) and 18 missing columns ({'OwnCar', 'ProductPitched', 'MaritalStatus', 'NumberOfChildrenVisiting', 'Designation', 'TypeofContact', 'PreferredPropertyStar', 'DurationOfPitch', 'PitchSatisfactionScore', 'NumberOfTrips', 'Passport', 'Gender', 'NumberOfFollowups', 'Age', 'MonthlyIncome', 'NumberOfPersonVisiting', 'Occupation', 'CityTier'}).
This happened while the csv dataset builder was generating data using
hf://datasets/nilanjanadevc/tourism-wellness-dataset/y_train.csv (at revision 741c2c9ad9c6a4302c2f92d977d6284171298b3a)
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 "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1831, in _prepare_split_single
writer.write_table(table)
File "/usr/local/lib/python3.12/site-packages/datasets/arrow_writer.py", line 714, in write_table
pa_table = table_cast(pa_table, self._schema)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2272, in table_cast
return cast_table_to_schema(table, schema)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2218, in cast_table_to_schema
raise CastError(
datasets.table.CastError: Couldn't cast
ProdTaken: int64
-- schema metadata --
pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 377
to
{'Age': Value('float64'), 'TypeofContact': Value('string'), 'CityTier': Value('int64'), 'DurationOfPitch': Value('float64'), 'Occupation': Value('string'), 'Gender': Value('string'), 'NumberOfPersonVisiting': Value('int64'), 'NumberOfFollowups': Value('float64'), 'ProductPitched': Value('string'), 'PreferredPropertyStar': Value('float64'), 'MaritalStatus': Value('string'), 'NumberOfTrips': Value('float64'), 'Passport': Value('int64'), 'PitchSatisfactionScore': Value('int64'), 'OwnCar': Value('int64'), 'NumberOfChildrenVisiting': Value('float64'), 'Designation': Value('string'), 'MonthlyIncome': Value('float64')}
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 1339, 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 972, in convert_to_parquet
builder.download_and_prepare(
File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 894, in download_and_prepare
self._download_and_prepare(
File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 970, in _download_and_prepare
self._prepare_split(split_generator, **prepare_split_kwargs)
File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1702, in _prepare_split
for job_id, done, content in self._prepare_split_single(
^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1833, 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 1 new columns ({'ProdTaken'}) and 18 missing columns ({'OwnCar', 'ProductPitched', 'MaritalStatus', 'NumberOfChildrenVisiting', 'Designation', 'TypeofContact', 'PreferredPropertyStar', 'DurationOfPitch', 'PitchSatisfactionScore', 'NumberOfTrips', 'Passport', 'Gender', 'NumberOfFollowups', 'Age', 'MonthlyIncome', 'NumberOfPersonVisiting', 'Occupation', 'CityTier'}).
This happened while the csv dataset builder was generating data using
hf://datasets/nilanjanadevc/tourism-wellness-dataset/y_train.csv (at revision 741c2c9ad9c6a4302c2f92d977d6284171298b3a)
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.
Age float64 | TypeofContact string | CityTier int64 | DurationOfPitch float64 | Occupation string | Gender string | NumberOfPersonVisiting int64 | NumberOfFollowups float64 | ProductPitched string | PreferredPropertyStar float64 | MaritalStatus string | NumberOfTrips float64 | Passport int64 | PitchSatisfactionScore int64 | OwnCar int64 | NumberOfChildrenVisiting float64 | Designation string | MonthlyIncome float64 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
55 | Self Enquiry | 1 | 17 | Small Business | Female | 4 | 4 | Deluxe | 5 | Unmarried | 8 | 1 | 1 | 0 | 1 | Manager | 23,118 |
39 | Self Enquiry | 1 | 9 | Salaried | Male | 3 | 4 | Basic | 3 | Unmarried | 7 | 1 | 4 | 0 | 2 | Executive | 22,622 |
42 | Company Invited | 2 | 8 | Small Business | Male | 3 | 1 | Deluxe | 5 | Divorced | 1 | 0 | 2 | 0 | 2 | Manager | 21,272 |
37 | Self Enquiry | 1 | 12 | Salaried | Female | 3 | 5 | Basic | 5 | Divorced | 2 | 1 | 2 | 1 | 1 | Executive | 98,678 |
23 | Self Enquiry | 1 | 7 | Salaried | Male | 3 | 5 | Deluxe | 3 | Divorced | 8 | 0 | 2 | 1 | 1 | Manager | 23,453 |
33 | Company Invited | 1 | 31 | Salaried | Male | 4 | 4 | Deluxe | 3 | Divorced | 3 | 0 | 4 | 1 | 1 | Manager | 23,987 |
38 | Self Enquiry | 1 | 24 | Small Business | Male | 2 | 5 | Deluxe | 3 | Married | 4 | 1 | 5 | 0 | 1 | Manager | 20,811 |
60 | Self Enquiry | 1 | 9 | Salaried | Female | 4 | 5 | Super Deluxe | 3 | Single | 5 | 1 | 5 | 0 | 3 | AVP | 32,404 |
53 | Company Invited | 3 | 8 | Small Business | Female | 2 | 4 | Standard | 4 | Married | 3 | 0 | 1 | 1 | 0 | Senior Manager | 22,525 |
37 | Self Enquiry | 1 | 33 | Salaried | Male | 4 | 4 | Deluxe | 3 | Married | 8 | 0 | 3 | 1 | 1 | Manager | 24,025 |
60 | Company Invited | 3 | 34 | Small Business | Female | 3 | 4 | Standard | 5 | Married | 5 | 0 | 1 | 1 | 0 | Senior Manager | 25,266 |
43 | Self Enquiry | 1 | 36 | Small Business | Male | 3 | 6 | Deluxe | 3 | Unmarried | 6 | 0 | 3 | 1 | 2 | Manager | 22,950 |
35 | Self Enquiry | 1 | 22 | Small Business | Male | 2 | 1 | Basic | 4 | Married | 1 | 0 | 4 | 1 | 1 | Executive | 17,426 |
43 | Self Enquiry | 1 | 10 | Salaried | Female | 4 | 2 | Deluxe | 3 | Married | 4 | 1 | 5 | 1 | 1 | Manager | 23,909 |
52 | Company Invited | 1 | 34 | Small Business | Female | 2 | 1 | Super Deluxe | 3 | Divorced | 3 | 1 | 4 | 0 | 0 | AVP | 28,247 |
59 | Company Invited | 1 | 9 | Salaried | Male | 3 | 5 | Basic | 3 | Married | 2 | 1 | 2 | 0 | 1 | Executive | 21,058 |
36 | Self Enquiry | 1 | 33 | Small Business | Male | 3 | 3 | Deluxe | 3 | Divorced | 7 | 0 | 3 | 1 | 0 | Manager | 20,237 |
29 | Company Invited | 1 | 23 | Small Business | Male | 3 | 4 | Basic | 3 | Single | 3 | 0 | 3 | 0 | 1 | Executive | 20,822 |
37 | Self Enquiry | 1 | 16 | Small Business | Male | 3 | 5 | Deluxe | 4 | Married | 4 | 1 | 4 | 0 | 2 | Manager | 27,525 |
38 | Self Enquiry | 1 | 8 | Salaried | Male | 2 | 3 | Deluxe | 3 | Divorced | 1 | 0 | 2 | 0 | 1 | Manager | 21,553 |
31 | Company Invited | 3 | 6 | Salaried | Female | 2 | 5 | Basic | 3 | Single | 2 | 0 | 3 | 1 | 1 | Executive | 16,359 |
46 | Self Enquiry | 3 | 16 | Small Business | Male | 4 | 4 | Standard | 5 | Married | 6 | 1 | 2 | 1 | 1 | Senior Manager | 29,439 |
41 | Self Enquiry | 3 | 14 | Small Business | Male | 3 | 4 | Basic | 4 | Unmarried | 3 | 0 | 5 | 0 | 1 | Executive | 23,339 |
35 | Self Enquiry | 1 | 13 | Salaried | Male | 3 | 3 | Basic | 4 | Single | 2 | 1 | 3 | 1 | 1 | Executive | 20,363 |
29 | Self Enquiry | 3 | 16 | Salaried | Male | 3 | 3 | Basic | 3 | Single | 2 | 0 | 4 | 1 | 0 | Executive | 17,642 |
51 | Self Enquiry | 3 | 27 | Small Business | Male | 3 | 3 | Deluxe | 3 | Single | 1 | 1 | 5 | 0 | 2 | Manager | 20,441 |
39 | Self Enquiry | 1 | 6 | Small Business | Male | 2 | 2 | Standard | 3 | Married | 1 | 0 | 3 | 1 | 0 | Senior Manager | 24,613 |
37 | Self Enquiry | 3 | 22 | Small Business | Male | 3 | 4 | Deluxe | 3 | Married | 5 | 0 | 5 | 1 | 2 | Manager | 21,334 |
33 | Company Invited | 3 | 23 | Salaried | Male | 2 | 3 | Super Deluxe | 3 | Single | 2 | 0 | 3 | 1 | 1 | AVP | 32,444 |
51 | Company Invited | 3 | 19 | Small Business | Female | 4 | 4 | Standard | 3 | Unmarried | 6 | 0 | 5 | 1 | 3 | Senior Manager | 27,886 |
42 | Self Enquiry | 1 | 12 | Salaried | Male | 3 | 2 | Deluxe | 4 | Unmarried | 5 | 0 | 5 | 1 | 1 | Manager | 25,548 |
33 | Self Enquiry | 3 | 15 | Large Business | Female | 4 | 5 | Deluxe | 4 | Divorced | 3 | 1 | 2 | 1 | 1 | Manager | 23,906 |
30 | Company Invited | 1 | 17 | Salaried | Female | 4 | 4 | Basic | 4 | Married | 2 | 0 | 5 | 1 | 1 | Executive | 21,969 |
41 | Self Enquiry | 3 | 7 | Small Business | Male | 3 | 6 | Deluxe | 3 | Divorced | 4 | 1 | 3 | 1 | 1 | Manager | 26,135 |
38 | Company Invited | 1 | 12 | Large Business | Male | 3 | 2 | Basic | 3 | Unmarried | 2 | 0 | 5 | 1 | 1 | Executive | 22,178 |
28 | Company Invited | 3 | 9 | Salaried | Male | 3 | 6 | Deluxe | 3 | Unmarried | 5 | 0 | 4 | 1 | 2 | Manager | 23,749 |
27 | Self Enquiry | 1 | 24 | Small Business | Male | 4 | 6 | Basic | 3 | Married | 3 | 0 | 3 | 0 | 3 | Executive | 20,983 |
27 | Self Enquiry | 1 | 11 | Salaried | Female | 2 | 3 | Basic | 4 | Single | 2 | 1 | 3 | 0 | 1 | Executive | 17,478 |
24 | Self Enquiry | 1 | 11 | Small Business | Male | 3 | 2 | Basic | 5 | Married | 4 | 0 | 4 | 0 | 2 | Executive | 21,497 |
34 | Company Invited | 1 | 22 | Salaried | Female | 3 | 4 | Basic | 3 | Single | 2 | 0 | 5 | 1 | 2 | Executive | 17,553 |
37 | Self Enquiry | 3 | 17 | Small Business | Male | 3 | 5 | Standard | 5 | Married | 2 | 0 | 5 | 0 | 1 | Senior Manager | 25,772 |
34 | Company Invited | 1 | 7 | Small Business | Male | 3 | 4 | Deluxe | 5 | Single | 1 | 0 | 1 | 0 | 0 | Manager | 20,343 |
30 | Company Invited | 3 | 32 | Small Business | Female | 2 | 4 | Deluxe | 5 | Unmarried | 6 | 0 | 2 | 0 | 1 | Manager | 21,696 |
27 | Self Enquiry | 1 | 23 | Large Business | Male | 2 | 3 | Basic | 4 | Married | 1 | 1 | 4 | 0 | 0 | Executive | 18,058 |
36 | Self Enquiry | 1 | 9 | Salaried | Male | 3 | 5 | Standard | 4 | Married | 4 | 0 | 4 | 1 | 1 | Senior Manager | 28,952 |
40 | Self Enquiry | 1 | 30 | Large Business | Male | 3 | 3 | Deluxe | 3 | Married | 2 | 0 | 3 | 1 | 1 | Manager | 18,319 |
38 | Self Enquiry | 1 | 7 | Large Business | Female | 3 | 4 | Standard | 3 | Unmarried | 6 | 0 | 5 | 1 | 2 | Senior Manager | 26,169 |
33 | Self Enquiry | 3 | 9 | Small Business | Male | 3 | 5 | Deluxe | 4 | Single | 2 | 1 | 1 | 1 | 1 | Manager | 28,585 |
30 | Self Enquiry | 1 | 16 | Salaried | Male | 2 | 5 | Basic | 3 | Unmarried | 2 | 0 | 1 | 1 | 1 | Executive | 22,661 |
52 | Self Enquiry | 1 | 6 | Salaried | Male | 3 | 3 | Super Deluxe | 3 | Married | 3 | 0 | 1 | 1 | 2 | AVP | 32,099 |
33 | Self Enquiry | 3 | 7 | Salaried | Male | 3 | 6 | Deluxe | 4 | Unmarried | 8 | 0 | 3 | 0 | 2 | Manager | 25,413 |
20 | Company Invited | 1 | 17 | Small Business | Female | 4 | 5 | Basic | 4 | Single | 3 | 1 | 5 | 0 | 3 | Executive | 20,537 |
38 | Company Invited | 1 | 29 | Salaried | Male | 2 | 4 | Standard | 3 | Unmarried | 1 | 0 | 3 | 0 | 0 | Senior Manager | 24,526 |
31 | Self Enquiry | 1 | 17 | Salaried | Male | 2 | 3 | Basic | 3 | Married | 4 | 1 | 3 | 0 | 0 | Executive | 17,356 |
52 | Self Enquiry | 1 | 11 | Salaried | Male | 3 | 4 | Basic | 3 | Divorced | 2 | 1 | 2 | 1 | 2 | Executive | 21,139 |
39 | Self Enquiry | 1 | 10 | Large Business | Female | 3 | 4 | Deluxe | 3 | Unmarried | 5 | 1 | 5 | 1 | 1 | Manager | 22,995 |
40 | Self Enquiry | 3 | 11 | Salaried | Female | 3 | 5 | Deluxe | 3 | Married | 6 | 0 | 5 | 1 | 2 | Manager | 24,580 |
26 | Self Enquiry | 1 | 26 | Small Business | Male | 4 | 4 | Basic | 3 | Divorced | 5 | 0 | 5 | 1 | 3 | Executive | 22,347 |
47 | Company Invited | 3 | 15 | Salaried | Male | 2 | 5 | Super Deluxe | 3 | Married | 1 | 0 | 5 | 1 | 1 | AVP | 27,936 |
28 | Self Enquiry | 3 | 16 | Small Business | Male | 3 | 3 | Basic | 4 | Married | 2 | 0 | 5 | 0 | 2 | Executive | 16,052 |
19 | Company Invited | 1 | 15 | Small Business | Male | 4 | 4 | Basic | 3 | Single | 3 | 0 | 5 | 0 | 1 | Executive | 20,582 |
52 | Self Enquiry | 3 | 9 | Small Business | Male | 2 | 4 | Super Deluxe | 5 | Married | 2 | 0 | 5 | 1 | 0 | AVP | 31,856 |
20 | Company Invited | 3 | 7 | Large Business | Female | 4 | 6 | Basic | 5 | Single | 2 | 0 | 3 | 1 | 2 | Executive | 21,003 |
43 | Self Enquiry | 3 | 15 | Small Business | Male | 3 | 4 | Deluxe | 4 | Divorced | 2 | 0 | 3 | 0 | 2 | Manager | 25,503 |
30 | Self Enquiry | 1 | 8 | Salaried | Female | 4 | 4 | Basic | 3 | Married | 3 | 0 | 1 | 1 | 3 | Executive | 22,438 |
51 | Company Invited | 3 | 7 | Salaried | Male | 4 | 4 | Deluxe | 3 | Married | 2 | 0 | 3 | 1 | 2 | Manager | 25,406 |
41 | Company Invited | 1 | 16 | Salaried | Male | 4 | 5 | Deluxe | 3 | Married | 2 | 0 | 5 | 0 | 2 | Manager | 23,554 |
33 | Company Invited | 3 | 15 | Small Business | Female | 3 | 4 | Standard | 3 | Unmarried | 3 | 0 | 4 | 1 | 2 | Senior Manager | 27,676 |
22 | Company Invited | 3 | 16 | Small Business | Male | 3 | 4 | Basic | 3 | Unmarried | 3 | 0 | 4 | 0 | 1 | Executive | 21,288 |
40 | Self Enquiry | 1 | 16 | Salaried | Female | 2 | 1 | Basic | 3 | Married | 4 | 1 | 3 | 0 | 1 | Executive | 17,213 |
53 | Self Enquiry | 3 | 6 | Small Business | Female | 2 | 3 | Deluxe | 5 | Unmarried | 1 | 0 | 1 | 1 | 1 | Manager | 23,381 |
29 | Company Invited | 1 | 9 | Small Business | Male | 3 | 5 | Basic | 5 | Single | 2 | 0 | 4 | 0 | 1 | Executive | 21,239 |
44 | Company Invited | 1 | 16 | Small Business | Male | 4 | 4 | Deluxe | 3 | Married | 5 | 1 | 3 | 1 | 3 | Manager | 24,357 |
23 | Self Enquiry | 1 | 13 | Small Business | Male | 4 | 4 | Basic | 3 | Divorced | 2 | 0 | 2 | 1 | 1 | Executive | 21,451 |
43 | Self Enquiry | 1 | 36 | Small Business | Male | 3 | 6 | Deluxe | 3 | Unmarried | 6 | 0 | 3 | 1 | 1 | Manager | 22,950 |
33 | Company Invited | 3 | 23 | Salaried | Male | 2 | 3 | Super Deluxe | 3 | Single | 2 | 0 | 3 | 1 | 0 | AVP | 32,444 |
37 | Company Invited | 3 | 7 | Small Business | Female | 3 | 4 | Deluxe | 3 | Unmarried | 6 | 0 | 1 | 1 | 2 | Manager | 25,331 |
37 | Self Enquiry | 1 | 16 | Salaried | Female | 2 | 1 | Standard | 3 | Married | 2 | 1 | 1 | 0 | 1 | Senior Manager | 28,744 |
40 | Self Enquiry | 3 | 10 | Small Business | Female | 3 | 4 | Deluxe | 3 | Married | 6 | 1 | 4 | 1 | 2 | Manager | 23,916 |
36 | Self Enquiry | 1 | 7 | Salaried | Female | 3 | 2 | Basic | 3 | Single | 5 | 0 | 3 | 1 | 2 | Executive | 21,184 |
50 | Self Enquiry | 1 | 23 | Small Business | Female | 4 | 4 | Basic | 5 | Married | 6 | 1 | 1 | 1 | 2 | Executive | 21,265 |
21 | Company Invited | 3 | 6 | Large Business | Female | 3 | 4 | Basic | 4 | Single | 2 | 1 | 5 | 1 | 2 | Executive | 17,174 |
28 | Self Enquiry | 3 | 9 | Small Business | Female | 4 | 6 | King | 4 | Single | 4 | 1 | 5 | 1 | 2 | VP | 21,195 |
52 | Self Enquiry | 1 | 15 | Salaried | Male | 3 | 5 | Standard | 4 | Divorced | 7 | 0 | 3 | 1 | 2 | Senior Manager | 31,168 |
40 | Self Enquiry | 1 | 14 | Small Business | Male | 3 | 4 | Basic | 3 | Unmarried | 2 | 1 | 4 | 1 | 2 | Executive | 24,094 |
29 | Self Enquiry | 1 | 12 | Small Business | Female | 2 | 3 | Basic | 3 | Married | 2 | 0 | 3 | 0 | 1 | Executive | 18,131 |
35 | Company Invited | 1 | 17 | Small Business | Male | 3 | 4 | Standard | 5 | Divorced | 3 | 1 | 5 | 1 | 1 | Senior Manager | 24,884 |
38 | Self Enquiry | 3 | 13 | Small Business | Male | 4 | 4 | Deluxe | 3 | Married | 6 | 0 | 3 | 1 | 1 | Manager | 25,180 |
51 | Company Invited | 1 | 6 | Small Business | Female | 1 | 4 | Standard | 5 | Unmarried | 4 | 0 | 2 | 1 | 0 | Senior Manager | 22,484 |
22 | Company Invited | 3 | 16 | Small Business | Male | 3 | 4 | Basic | 3 | Unmarried | 3 | 0 | 4 | 1 | 1 | Executive | 21,288 |
36 | Self Enquiry | 2 | 19 | Salaried | Male | 2 | 3 | Basic | 4 | Married | 5 | 0 | 3 | 1 | 1 | Executive | 17,143 |
31 | Self Enquiry | 1 | 17 | Small Business | Male | 3 | 3 | Deluxe | 5 | Married | 2 | 1 | 1 | 1 | 1 | Manager | 21,833 |
28 | Self Enquiry | 3 | 16 | Small Business | Male | 3 | 4 | Deluxe | 3 | Unmarried | 3 | 0 | 1 | 0 | 2 | Manager | 22,783 |
50 | Self Enquiry | 1 | 7 | Large Business | Female | 3 | 5 | Super Deluxe | 3 | Single | 2 | 1 | 3 | 0 | 1 | AVP | 32,642 |
28 | Self Enquiry | 1 | 13 | Salaried | Male | 3 | 5 | Basic | 3 | Married | 3 | 0 | 1 | 1 | 2 | Executive | 21,217 |
40 | Self Enquiry | 1 | 14 | Salaried | Female | 3 | 3 | Deluxe | 5 | Married | 3 | 1 | 1 | 0 | 0 | Manager | 21,516 |
29 | Self Enquiry | 1 | 21 | Salaried | Male | 2 | 3 | Basic | 3 | Single | 2 | 0 | 3 | 0 | 0 | Executive | 17,340 |
40 | Self Enquiry | 1 | 17 | Small Business | Male | 4 | 4 | Standard | 3 | Single | 2 | 0 | 3 | 1 | 1 | Senior Manager | 32,142 |
29 | Company Invited | 1 | 7 | Small Business | Male | 3 | 4 | Basic | 3 | Single | 2 | 1 | 4 | 0 | 1 | Executive | 20,832 |
31 | Self Enquiry | 1 | 8 | Small Business | Male | 4 | 4 | Basic | 4 | Married | 2 | 1 | 4 | 1 | 3 | Executive | 22,257 |
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