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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 ({'PitchSatisfactionScore', 'OwnCar', 'NumberOfChildrenVisiting', 'PreferredPropertyStar', 'Occupation', 'Gender', 'NumberOfFollowups', 'MaritalStatus', 'NumberOfTrips', 'NumberOfPersonVisiting', 'Designation', 'ProductPitched', 'Passport', 'DurationOfPitch', 'TypeofContact', 'MonthlyIncome', 'CityTier', 'Age'}).
This happened while the csv dataset builder was generating data using
hf://datasets/sgpai/tourism-mlops/y_train.csv (at revision 857cef7e2da9b26c8d7708abe41c74e3e6954904)
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 ({'PitchSatisfactionScore', 'OwnCar', 'NumberOfChildrenVisiting', 'PreferredPropertyStar', 'Occupation', 'Gender', 'NumberOfFollowups', 'MaritalStatus', 'NumberOfTrips', 'NumberOfPersonVisiting', 'Designation', 'ProductPitched', 'Passport', 'DurationOfPitch', 'TypeofContact', 'MonthlyIncome', 'CityTier', 'Age'}).
This happened while the csv dataset builder was generating data using
hf://datasets/sgpai/tourism-mlops/y_train.csv (at revision 857cef7e2da9b26c8d7708abe41c74e3e6954904)
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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
28 | Company Invited | 1 | 30 | Large Business | Male | 3 | 4 | Standard | 5 | Unmarried | 2 | 0 | 2 | 0 | 0 | Senior Manager | 23,722 |
34 | Company Invited | 3 | 12 | Small Business | Female | 2 | 5 | Basic | 3 | Married | 1 | 0 | 4 | 0 | 1 | Executive | 17,351 |
26 | Self Enquiry | 3 | 11 | Salaried | Female | 3 | 5 | Deluxe | 3 | Unmarried | 3 | 1 | 2 | 0 | 2 | Manager | 23,165 |
37 | Self Enquiry | 3 | 22 | Small Business | Male | 3 | 4 | Deluxe | 3 | Married | 5 | 0 | 5 | 1 | 0 | Manager | 21,334 |
45 | Self Enquiry | 3 | 15 | Small Business | Male | 3 | 3 | Standard | 5 | Married | 5 | 1 | 1 | 0 | 0 | Senior Manager | 25,761 |
53 | Company Invited | 1 | 32 | Small Business | Female | 3 | 5 | Super Deluxe | 3 | Married | 5 | 0 | 5 | 0 | 2 | AVP | 32,504 |
33 | Company Invited | 1 | 6 | Small Business | Male | 2 | 4 | Basic | 3 | Married | 2 | 0 | 3 | 0 | 0 | Executive | 17,008 |
38 | Self Enquiry | 1 | 6 | Salaried | Female | 2 | 2 | Deluxe | 3 | Unmarried | 1 | 0 | 2 | 1 | 1 | Manager | 22,625 |
33 | Company Invited | 1 | 12 | Large Business | Male | 4 | 4 | Basic | 4 | Unmarried | 4 | 0 | 3 | 1 | 2 | Executive | 21,396 |
46 | Self Enquiry | 3 | 8 | Small Business | Female | 2 | 3 | King | 5 | Single | 4 | 0 | 1 | 1 | 1 | VP | 33,947 |
35 | Self Enquiry | 1 | 15 | Salaried | Female | 3 | 4 | Standard | 3 | Divorced | 2 | 1 | 4 | 1 | 1 | Senior Manager | 25,685 |
41 | Self Enquiry | 1 | 9 | Salaried | Male | 3 | 5 | Basic | 3 | Unmarried | 4 | 0 | 5 | 0 | 2 | Executive | 21,487 |
49 | Self Enquiry | 3 | 9 | Small Business | Female | 3 | 4 | Deluxe | 3 | Married | 4 | 0 | 5 | 1 | 1 | Manager | 22,729 |
50 | Company Invited | 2 | 9 | Small Business | Male | 3 | 3 | King | 4 | Married | 2 | 0 | 1 | 1 | 2 | VP | 33,200 |
33 | Company Invited | 1 | 31 | Salaried | Male | 4 | 4 | Deluxe | 3 | Married | 3 | 0 | 4 | 1 | 3 | Manager | 23,987 |
32 | Self Enquiry | 1 | 14 | Small Business | Female | 3 | 1 | Deluxe | 3 | Divorced | 6 | 0 | 3 | 1 | 2 | Manager | 20,175 |
35 | Self Enquiry | 3 | 31 | Small Business | Female | 3 | 5 | Deluxe | 4 | Unmarried | 2 | 1 | 5 | 1 | 1 | Manager | 23,277 |
32 | Self Enquiry | 1 | 14 | Small Business | Female | 3 | 4 | Standard | 3 | Unmarried | 3 | 1 | 4 | 1 | 2 | Senior Manager | 25,821 |
36 | Self Enquiry | 1 | 8 | Small Business | Male | 3 | 3 | Basic | 3 | Single | 5 | 0 | 5 | 1 | 0 | Executive | 17,519 |
29 | Company Invited | 3 | 26 | Large Business | Female | 2 | 3 | Basic | 3 | Divorced | 2 | 0 | 3 | 0 | 1 | Executive | 17,157 |
36 | Self Enquiry | 3 | 6 | Salaried | Male | 2 | 3 | Deluxe | 3 | Married | 2 | 1 | 3 | 1 | 1 | Manager | 21,201 |
59 | Self Enquiry | 3 | 6 | Large Business | Male | 3 | 3 | Standard | 3 | Divorced | 4 | 1 | 2 | 0 | 1 | Senior Manager | 26,904 |
39 | Self Enquiry | 2 | 9 | Salaried | Female | 2 | 2 | Deluxe | 4 | Divorced | 1 | 0 | 2 | 1 | 0 | Manager | 21,389 |
41 | Self Enquiry | 1 | 21 | Small Business | Male | 3 | 5 | King | 3 | Single | 3 | 0 | 3 | 1 | 2 | VP | 38,304 |
55 | Self Enquiry | 1 | 6 | Small Business | Male | 2 | 3 | King | 5 | Single | 1 | 1 | 2 | 1 | 0 | VP | 34,045 |
39 | Self Enquiry | 3 | 14 | Small Business | Female | 3 | 3 | Deluxe | 5 | Married | 3 | 1 | 3 | 0 | 1 | Manager | 24,283 |
43 | Company Invited | 1 | 33 | Salaried | Female | 2 | 3 | Standard | 5 | Married | 1 | 0 | 4 | 1 | 0 | Senior Manager | 25,820 |
29 | Self Enquiry | 1 | 13 | Large Business | Female | 2 | 3 | Basic | 3 | Married | 4 | 1 | 4 | 1 | 1 | Executive | 18,339 |
30 | Company Invited | 1 | 7 | Large Business | Male | 3 | 4 | Deluxe | 3 | Married | 3 | 0 | 3 | 0 | 1 | Manager | 22,997 |
29 | Self Enquiry | 1 | 29 | Salaried | Male | 2 | 3 | Basic | 3 | Single | 1 | 0 | 3 | 0 | 0 | Executive | 17,201 |
56 | Company Invited | 1 | 25 | Small Business | Male | 4 | 4 | Deluxe | 4 | Married | 5 | 1 | 5 | 1 | 2 | Manager | 25,063 |
56 | Company Invited | 1 | 15 | Small Business | Male | 3 | 5 | Super Deluxe | 4 | Married | 3 | 1 | 3 | 1 | 2 | AVP | 32,255 |
28 | Company Invited | 1 | 10 | Small Business | Male | 4 | 5 | Basic | 3 | Married | 3 | 1 | 2 | 0 | 3 | Executive | 21,244 |
38 | Company Invited | 3 | 11 | Small Business | Male | 3 | 4 | Basic | 3 | Married | 6 | 0 | 4 | 1 | 1 | Executive | 21,471 |
39 | Self Enquiry | 3 | 17 | Small Business | Male | 4 | 5 | Standard | 3 | Married | 2 | 1 | 3 | 1 | 2 | Senior Manager | 27,418 |
29 | Self Enquiry | 1 | 6 | Salaried | Female | 2 | 4 | Basic | 5 | Married | 2 | 1 | 1 | 0 | 0 | Executive | 17,319 |
56 | Self Enquiry | 1 | 27 | Large Business | Male | 3 | 4 | Deluxe | 3 | Married | 5 | 1 | 1 | 0 | 1 | Manager | 24,093 |
59 | Self Enquiry | 1 | 9 | Large Business | Male | 3 | 4 | Basic | 3 | Single | 6 | 0 | 2 | 1 | 2 | Executive | 21,157 |
49 | Company Invited | 1 | 8 | Salaried | Male | 2 | 3 | King | 3 | Married | 4 | 0 | 3 | 1 | 0 | VP | 34,161 |
35 | Self Enquiry | 1 | 7 | Salaried | Female | 4 | 2 | Basic | 3 | Unmarried | 4 | 0 | 2 | 0 | 1 | Executive | 21,958 |
37 | Company Invited | 1 | 25 | Salaried | Male | 3 | 2 | Basic | 3 | Married | 6 | 0 | 5 | 1 | 2 | Executive | 22,366 |
26 | Company Invited | 1 | 6 | Salaried | Female | 2 | 3 | Deluxe | 4 | Married | 2 | 0 | 5 | 1 | 1 | Manager | 21,397 |
56 | Self Enquiry | 1 | 30 | Salaried | Male | 3 | 3 | Basic | 3 | Single | 2 | 0 | 3 | 0 | 0 | Executive | 17,587 |
32 | Self Enquiry | 1 | 9 | Salaried | Female | 2 | 3 | Standard | 3 | Unmarried | 4 | 0 | 1 | 1 | 0 | Senior Manager | 26,159 |
34 | Self Enquiry | 1 | 6 | Salaried | Female | 2 | 4 | Basic | 4 | Divorced | 6 | 0 | 1 | 1 | 1 | Executive | 18,294 |
31 | Self Enquiry | 1 | 24 | Small Business | Female | 4 | 4 | Standard | 5 | Divorced | 3 | 1 | 4 | 0 | 3 | Senior Manager | 30,594 |
37 | Company Invited | 1 | 16 | Small Business | Male | 3 | 3 | Standard | 3 | Married | 7 | 0 | 3 | 0 | 2 | Senior Manager | 25,048 |
48 | Self Enquiry | 3 | 21 | Small Business | Female | 4 | 4 | Deluxe | 3 | Divorced | 5 | 1 | 5 | 1 | 1 | Manager | 23,269 |
38 | Company Invited | 1 | 16 | Small Business | Male | 3 | 3 | Basic | 3 | Divorced | 1 | 0 | 5 | 0 | 2 | Executive | 17,684 |
33 | Company Invited | 3 | 18 | Salaried | Male | 3 | 3 | Deluxe | 3 | Divorced | 2 | 0 | 3 | 1 | 2 | Manager | 23,385 |
36 | Self Enquiry | 3 | 19 | Small Business | Male | 3 | 4 | Deluxe | 5 | Married | 6 | 1 | 1 | 1 | 0 | Manager | 21,134 |
45 | Self Enquiry | 1 | 15 | Salaried | Male | 4 | 2 | Basic | 3 | Married | 4 | 1 | 3 | 1 | 1 | Executive | 21,496 |
37 | Self Enquiry | 3 | 7 | Salaried | Male | 3 | 4 | Deluxe | 3 | Divorced | 3 | 1 | 3 | 1 | 2 | Manager | 24,879 |
41 | Self Enquiry | 3 | 6 | Salaried | Female | 3 | 3 | Deluxe | 3 | Single | 1 | 1 | 2 | 1 | 0 | Manager | 20,993 |
36 | Company Invited | 1 | 29 | Small Business | Male | 2 | 1 | Deluxe | 3 | Married | 5 | 0 | 3 | 0 | 0 | Manager | 17,571 |
30 | Company Invited | 3 | 9 | Salaried | Male | 3 | 4 | Deluxe | 3 | Unmarried | 3 | 0 | 1 | 0 | 2 | Manager | 23,232 |
42 | Self Enquiry | 1 | 14 | Large Business | Female | 3 | 2 | Basic | 3 | Married | 3 | 0 | 3 | 0 | 1 | Executive | 22,054 |
33 | Self Enquiry | 1 | 12 | Salaried | Female | 3 | 2 | Basic | 3 | Married | 5 | 0 | 5 | 1 | 2 | Executive | 21,990 |
48 | Self Enquiry | 3 | 9 | Small Business | Female | 3 | 4 | Deluxe | 3 | Divorced | 2 | 1 | 2 | 1 | 1 | Manager | 23,215 |
29 | Self Enquiry | 1 | 34 | Salaried | Female | 3 | 3 | Basic | 3 | Married | 5 | 0 | 5 | 1 | 0 | Executive | 17,514 |
31 | Self Enquiry | 3 | 13 | Large Business | Male | 3 | 2 | Deluxe | 3 | Divorced | 5 | 0 | 2 | 1 | 0 | Manager | 21,929 |
34 | Self Enquiry | 1 | 22 | Small Business | Male | 3 | 4 | Standard | 3 | Divorced | 2 | 1 | 5 | 0 | 1 | Senior Manager | 32,288 |
58 | Company Invited | 1 | 21 | Salaried | Male | 2 | 3 | Super Deluxe | 3 | Married | 3 | 1 | 1 | 1 | 0 | AVP | 30,787 |
30 | Self Enquiry | 1 | 30 | Salaried | Male | 3 | 2 | Basic | 3 | Divorced | 3 | 0 | 2 | 1 | 2 | Executive | 21,378 |
34 | Self Enquiry | 1 | 35 | Salaried | Male | 4 | 4 | Deluxe | 3 | Married | 3 | 1 | 1 | 1 | 1 | Manager | 23,885 |
28 | Self Enquiry | 3 | 19 | Small Business | Female | 2 | 3 | Deluxe | 3 | Unmarried | 4 | 1 | 5 | 1 | 1 | Manager | 24,854 |
20 | Self Enquiry | 3 | 29 | Small Business | Male | 3 | 4 | Basic | 3 | Single | 3 | 1 | 1 | 1 | 1 | Executive | 20,353 |
34 | Company Invited | 3 | 15 | Salaried | Female | 3 | 5 | Basic | 3 | Single | 2 | 0 | 2 | 1 | 2 | Executive | 21,020 |
37 | Company Invited | 1 | 25 | Salaried | Male | 4 | 4 | Deluxe | 3 | Unmarried | 4 | 0 | 3 | 1 | 1 | Manager | 26,457 |
36 | Company Invited | 1 | 24 | Salaried | Male | 3 | 3 | Deluxe | 3 | Unmarried | 3 | 0 | 3 | 1 | 0 | Manager | 22,779 |
20 | Self Enquiry | 3 | 29 | Small Business | Male | 3 | 4 | Basic | 3 | Single | 3 | 1 | 2 | 0 | 2 | Executive | 20,353 |
35 | Self Enquiry | 1 | 7 | Salaried | Female | 4 | 2 | Basic | 3 | Unmarried | 4 | 0 | 1 | 1 | 2 | Executive | 21,958 |
52 | Self Enquiry | 1 | 10 | Small Business | Female | 4 | 4 | Super Deluxe | 4 | Single | 5 | 0 | 5 | 1 | 2 | AVP | 32,412 |
31 | Self Enquiry | 1 | 10 | Large Business | Female | 3 | 4 | Basic | 5 | Unmarried | 7 | 1 | 4 | 1 | 2 | Executive | 21,335 |
45 | Company Invited | 3 | 12 | Small Business | Female | 2 | 4 | Standard | 3 | Unmarried | 7 | 0 | 4 | 1 | 0 | Senior Manager | 23,865 |
29 | Self Enquiry | 3 | 16 | Small Business | Female | 2 | 4 | Deluxe | 4 | Married | 2 | 1 | 5 | 0 | 1 | Manager | 23,268 |
34 | Self Enquiry | 1 | 22 | Small Business | Female | 4 | 4 | Deluxe | 3 | Married | 2 | 1 | 1 | 1 | 2 | Manager | 23,556 |
39 | Self Enquiry | 1 | 9 | Small Business | Male | 4 | 4 | Basic | 3 | Divorced | 8 | 1 | 4 | 0 | 1 | Executive | 21,735 |
47 | Company Invited | 3 | 10 | Small Business | Male | 3 | 3 | Deluxe | 3 | Single | 4 | 0 | 4 | 0 | 2 | Manager | 17,976 |
45 | Self Enquiry | 1 | 36 | Salaried | Male | 3 | 4 | Deluxe | 3 | Unmarried | 3 | 0 | 5 | 1 | 2 | Manager | 23,219 |
38 | Self Enquiry | 1 | 21 | Salaried | Female | 4 | 4 | Basic | 5 | Married | 3 | 0 | 4 | 1 | 2 | Executive | 21,712 |
34 | Company Invited | 1 | 9 | Salaried | Male | 2 | 3 | Deluxe | 3 | Unmarried | 1 | 0 | 1 | 1 | 0 | Manager | 22,756 |
24 | Self Enquiry | 1 | 23 | Salaried | Female | 3 | 3 | Basic | 4 | Divorced | 2 | 0 | 2 | 0 | 1 | Executive | 17,210 |
37 | Self Enquiry | 1 | 9 | Small Business | Male | 4 | 4 | Basic | 3 | Single | 6 | 0 | 5 | 1 | 1 | Executive | 21,197 |
23 | Self Enquiry | 1 | 10 | Small Business | Male | 2 | 2 | Basic | 5 | Divorced | 3 | 0 | 4 | 0 | 1 | Executive | 17,819 |
33 | Self Enquiry | 1 | 10 | Small Business | Female | 2 | 4 | Basic | 4 | Married | 7 | 0 | 4 | 0 | 1 | Executive | 17,622 |
36 | Self Enquiry | 1 | 12 | Salaried | Male | 2 | 3 | Basic | 3 | Divorced | 1 | 0 | 5 | 1 | 1 | Executive | 18,210 |
29 | Self Enquiry | 1 | 31 | Small Business | Male | 3 | 4 | Basic | 4 | Married | 3 | 1 | 1 | 0 | 1 | Executive | 21,086 |
51 | Company Invited | 3 | 19 | Small Business | Female | 4 | 4 | Standard | 3 | Unmarried | 6 | 0 | 5 | 0 | 1 | Senior Manager | 27,886 |
37 | Self Enquiry | 2 | 15 | Salaried | Male | 4 | 5 | Basic | 5 | Married | 2 | 0 | 1 | 0 | 2 | Executive | 21,020 |
39 | Self Enquiry | 3 | 7 | Salaried | Male | 3 | 5 | Basic | 5 | Unmarried | 6 | 0 | 3 | 0 | 2 | Executive | 21,536 |
34 | Self Enquiry | 1 | 32 | Small Business | Male | 3 | 5 | Basic | 4 | Single | 6 | 1 | 4 | 1 | 1 | Executive | 20,991 |
20 | Company Invited | 3 | 15 | Small Business | Female | 2 | 3 | Basic | 3 | Single | 2 | 1 | 4 | 1 | 0 | Executive | 17,323 |
34 | Company Invited | 3 | 14 | Salaried | Female | 2 | 4 | Deluxe | 4 | Married | 2 | 0 | 4 | 0 | 1 | Manager | 22,980 |
20 | Self Enquiry | 1 | 32 | Salaried | Female | 3 | 2 | Basic | 3 | Unmarried | 3 | 1 | 5 | 1 | 1 | Executive | 21,672 |
46 | Self Enquiry | 3 | 10 | Small Business | Female | 2 | 4 | King | 4 | Divorced | 3 | 0 | 5 | 1 | 0 | VP | 33,789 |
19 | Company Invited | 1 | 7 | Salaried | Female | 4 | 4 | Basic | 3 | Single | 3 | 0 | 5 | 1 | 2 | Executive | 20,289 |
26 | Self Enquiry | 3 | 33 | Small Business | Female | 3 | 4 | Deluxe | 3 | Unmarried | 3 | 0 | 4 | 0 | 1 | Manager | 24,858 |
47 | Company Invited | 1 | 6 | Small Business | Female | 3 | 3 | Standard | 4 | Married | 1 | 0 | 5 | 0 | 0 | Senior Manager | 26,957 |
32 | Self Enquiry | 1 | 9 | Small Business | Female | 3 | 3 | Deluxe | 5 | Married | 2 | 0 | 1 | 1 | 0 | Manager | 21,725 |
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