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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 3 new columns ({'CustomerID', 'Unnamed: 0', 'ProdTaken'})
This happened while the csv dataset builder was generating data using
hf://datasets/bala-ai/tourism-package-prediction/tourism.csv (at revision 92b5c1ba81ed892999b39347c7cd5c59eef41990)
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 1831, in _prepare_split_single
writer.write_table(table)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/arrow_writer.py", line 644, 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 2272, in table_cast
return cast_table_to_schema(table, schema)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2218, in cast_table_to_schema
raise CastError(
datasets.table.CastError: Couldn't cast
Unnamed: 0: int64
CustomerID: int64
ProdTaken: int64
Age: double
TypeofContact: string
CityTier: int64
DurationOfPitch: double
Occupation: string
Gender: string
NumberOfPersonVisiting: int64
NumberOfFollowups: double
ProductPitched: string
PreferredPropertyStar: double
MaritalStatus: string
NumberOfTrips: double
Passport: int64
PitchSatisfactionScore: int64
OwnCar: int64
NumberOfChildrenVisiting: double
Designation: string
MonthlyIncome: double
-- schema metadata --
pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 2881
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 1456, 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 1055, in convert_to_parquet
builder.download_and_prepare(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 894, in download_and_prepare
self._download_and_prepare(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 970, 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 1702, 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 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 3 new columns ({'CustomerID', 'Unnamed: 0', 'ProdTaken'})
This happened while the csv dataset builder was generating data using
hf://datasets/bala-ai/tourism-package-prediction/tourism.csv (at revision 92b5c1ba81ed892999b39347c7cd5c59eef41990)
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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
34 | Company Invited | 1 | 9 | Salaried | Male | 2 | 4 | Basic | 3 | Married | 4 | 0 | 1 | 0 | 0 | Executive | 17,979 |
32 | Self Enquiry | 1 | 6 | Salaried | Male | 3 | 3 | Deluxe | 4 | Divorced | 2 | 0 | 3 | 0 | 0 | Manager | 21,220 |
30 | Self Enquiry | 3 | 11 | Salaried | Female | 2 | 3 | Standard | 3 | Divorced | 3 | 0 | 4 | 1 | 1 | Senior Manager | 24,419 |
39 | Self Enquiry | 3 | 9 | Small Business | Male | 3 | 4 | Standard | 4 | Unmarried | 2 | 0 | 4 | 1 | 2 | Senior Manager | 26,029 |
37 | Company Invited | 1 | 31 | Salaried | Female | 3 | 4 | Deluxe | 4 | Married | 2 | 0 | 3 | 1 | 2 | Manager | 24,352 |
34 | Self Enquiry | 1 | 9 | Salaried | Male | 3 | 4 | Basic | 3 | Single | 2 | 0 | 3 | 0 | 2 | Executive | 21,178 |
27 | Company Invited | 1 | 7 | Salaried | Female | 4 | 6 | Basic | 3 | Married | 5 | 0 | 4 | 1 | 3 | Executive | 23,042 |
30 | Self Enquiry | 3 | 6 | Salaried | Male | 3 | 4 | Deluxe | 5 | Married | 2 | 0 | 4 | 1 | 1 | Manager | 24,714 |
53 | Company Invited | 1 | 32 | Small Business | Female | 3 | 5 | Super Deluxe | 3 | Married | 5 | 0 | 5 | 0 | 2 | AVP | 32,504 |
55 | Company Invited | 1 | 7 | Salaried | Female | 3 | 4 | Standard | 3 | Married | 2 | 0 | 5 | 1 | 2 | Senior Manager | 29,180 |
46 | Company Invited | 1 | 6 | Small Business | Male | 2 | 4 | Standard | 5 | Divorced | 3 | 1 | 2 | 1 | 1 | Senior Manager | 25,673 |
39 | Company Invited | 1 | 19 | Salaried | Male | 2 | 5 | Deluxe | 5 | Married | 4 | 0 | 5 | 1 | 1 | Manager | 24,966 |
54 | Company Invited | 2 | 32 | Salaried | Female | 1 | 2 | Super Deluxe | 3 | Single | 3 | 1 | 3 | 1 | 0 | AVP | 32,328 |
42 | Self Enquiry | 1 | 19 | Small Business | Male | 3 | 1 | Deluxe | 5 | Married | 6 | 0 | 4 | 1 | 0 | Manager | 20,538 |
33 | Self Enquiry | 1 | 12 | Salaried | Female | 3 | 2 | Basic | 3 | Married | 5 | 0 | 5 | 1 | 2 | Executive | 21,990 |
35 | Self Enquiry | 1 | 6 | Small Business | Male | 1 | 4 | Basic | 3 | Single | 2 | 0 | 4 | 1 | 0 | Executive | 17,859 |
39 | Self Enquiry | 1 | 16 | Small Business | Male | 3 | 3 | Standard | 3 | Unmarried | 1 | 0 | 3 | 1 | 0 | Senior Manager | 28,464 |
29 | Self Enquiry | 1 | 17 | Salaried | Female | 3 | 4 | Deluxe | 3 | Unmarried | 5 | 0 | 4 | 1 | 2 | Manager | 22,338 |
23 | Company Invited | 1 | 11 | Large Business | Male | 3 | 5 | Basic | 3 | Unmarried | 7 | 0 | 5 | 1 | 1 | Executive | 22,572 |
37 | Company Invited | 1 | 15 | Small Business | Male | 2 | 3 | Basic | 3 | Divorced | 2 | 1 | 2 | 0 | 0 | Executive | 17,326 |
33 | Self Enquiry | 1 | 10 | Small Business | Female | 4 | 4 | Deluxe | 5 | Married | 3 | 0 | 1 | 1 | 1 | Manager | 25,403 |
33 | Self Enquiry | 1 | 7 | Salaried | Male | 4 | 4 | Basic | 5 | Unmarried | 3 | 0 | 1 | 0 | 2 | Executive | 21,634 |
50 | Company Invited | 1 | 25 | Salaried | Male | 4 | 4 | Deluxe | 3 | Married | 3 | 1 | 1 | 0 | 1 | Manager | 25,482 |
42 | Self Enquiry | 1 | 6 | Salaried | Female | 2 | 4 | Deluxe | 3 | Married | 1 | 1 | 3 | 0 | 0 | Manager | 21,062 |
43 | Company Invited | 1 | 33 | Small Business | Female | 3 | 4 | Standard | 5 | Married | 5 | 1 | 3 | 0 | 1 | Senior Manager | 31,869 |
36 | Company Invited | 1 | 15 | Salaried | Male | 3 | 1 | Basic | 4 | Married | 2 | 0 | 5 | 1 | 0 | Executive | 17,810 |
27 | Self Enquiry | 3 | 8 | Small Business | Female | 2 | 1 | Deluxe | 3 | Unmarried | 1 | 0 | 1 | 0 | 1 | Manager | 21,500 |
29 | Self Enquiry | 3 | 16 | Salaried | Male | 4 | 4 | Deluxe | 3 | Unmarried | 3 | 0 | 3 | 1 | 2 | Manager | 23,931 |
34 | Self Enquiry | 1 | 12 | Salaried | Female | 4 | 5 | Basic | 3 | Divorced | 3 | 0 | 2 | 0 | 3 | Executive | 21,589 |
41 | Self Enquiry | 3 | 21 | Salaried | Female | 3 | 4 | Deluxe | 5 | Married | 3 | 0 | 3 | 0 | 2 | Manager | 23,317 |
32 | Self Enquiry | 3 | 20 | Small Business | Male | 4 | 5 | Deluxe | 5 | Married | 7 | 1 | 1 | 1 | 1 | Manager | 20,980 |
50 | Company Invited | 2 | 9 | Small Business | Male | 3 | 3 | King | 4 | Married | 2 | 0 | 1 | 1 | 2 | VP | 33,200 |
24 | Company Invited | 3 | 30 | Small Business | Male | 2 | 3 | Basic | 3 | Married | 1 | 0 | 4 | 1 | 1 | Executive | 17,400 |
43 | Self Enquiry | 1 | 7 | Salaried | Female | 3 | 5 | Deluxe | 3 | Married | 2 | 1 | 3 | 0 | 1 | Manager | 24,740 |
39 | Self Enquiry | 1 | 16 | Small Business | Male | 3 | 3 | Deluxe | 5 | Married | 3 | 0 | 5 | 1 | 2 | Manager | 20,377 |
55 | Self Enquiry | 1 | 6 | Small Business | Male | 2 | 3 | King | 5 | Single | 1 | 1 | 1 | 1 | 1 | VP | 34,045 |
33 | Company Invited | 1 | 10 | Salaried | Female | 3 | 4 | Basic | 3 | Unmarried | 3 | 0 | 4 | 1 | 1 | Executive | 24,887 |
34 | Self Enquiry | 3 | 23 | Salaried | Female | 4 | 4 | Standard | 5 | Unmarried | 4 | 1 | 5 | 0 | 1 | Senior Manager | 27,242 |
25 | Self Enquiry | 1 | 25 | Salaried | Male | 3 | 4 | Basic | 3 | Married | 2 | 0 | 4 | 0 | 1 | Executive | 21,452 |
30 | Self Enquiry | 1 | 24 | Salaried | Female | 3 | 3 | Basic | 3 | Single | 2 | 0 | 1 | 1 | 2 | Executive | 17,632 |
32 | Company Invited | 3 | 12 | Small Business | Female | 3 | 4 | Basic | 4 | Married | 3 | 0 | 3 | 0 | 1 | Executive | 21,467 |
34 | Company Invited | 1 | 12 | Salaried | Female | 4 | 4 | Standard | 4 | Divorced | 8 | 0 | 3 | 1 | 3 | Senior Manager | 30,556 |
50 | Self Enquiry | 1 | 30 | Salaried | Male | 3 | 3 | Super Deluxe | 3 | Married | 4 | 1 | 4 | 1 | 2 | AVP | 28,973 |
33 | Self Enquiry | 1 | 6 | Salaried | Male | 3 | 4 | Basic | 5 | Single | 4 | 1 | 4 | 0 | 0 | Executive | 17,799 |
36 | Company Invited | 3 | 18 | Small Business | Male | 3 | 4 | Deluxe | 3 | Married | 3 | 0 | 5 | 0 | 1 | Manager | 23,646 |
50 | Company Invited | 1 | 25 | Salaried | Male | 4 | 4 | Deluxe | 3 | Married | 3 | 1 | 2 | 0 | 2 | Manager | 25,482 |
49 | Company Invited | 3 | 14 | Small Business | Female | 4 | 4 | Basic | 3 | Married | 4 | 1 | 4 | 1 | 2 | Executive | 21,333 |
37 | Company Invited | 3 | 14 | Small Business | Female | 3 | 2 | Deluxe | 5 | Divorced | 4 | 0 | 1 | 1 | 1 | Manager | 23,317 |
30 | Self Enquiry | 1 | 24 | Salaried | Female | 3 | 3 | Basic | 3 | Single | 2 | 0 | 2 | 1 | 0 | Executive | 17,632 |
23 | Self Enquiry | 1 | 7 | Salaried | Male | 4 | 4 | Basic | 3 | Unmarried | 2 | 0 | 3 | 0 | 3 | Executive | 22,053 |
34 | Self Enquiry | 1 | 33 | Small Business | Female | 3 | 3 | Basic | 4 | Single | 3 | 0 | 3 | 0 | 0 | Executive | 17,311 |
52 | Self Enquiry | 3 | 28 | Small Business | Male | 4 | 4 | Deluxe | 3 | Unmarried | 2 | 1 | 5 | 0 | 3 | Manager | 24,119 |
27 | Company Invited | 3 | 36 | Small Business | Male | 4 | 6 | Deluxe | 5 | Unmarried | 2 | 0 | 3 | 0 | 1 | Manager | 23,647 |
40 | Company Invited | 3 | 30 | Salaried | Female | 3 | 1 | Super Deluxe | 4 | Unmarried | 5 | 1 | 3 | 1 | 2 | AVP | 28,194 |
44 | Self Enquiry | 1 | 8 | Salaried | Female | 3 | 1 | Basic | 3 | Divorced | 2 | 0 | 4 | 1 | 0 | Executive | 17,011 |
27 | Company Invited | 1 | 9 | Salaried | Male | 3 | 4 | Basic | 5 | Married | 8 | 1 | 5 | 0 | 1 | Executive | 20,720 |
42 | Company Invited | 1 | 12 | Salaried | Male | 4 | 5 | Basic | 5 | Married | 8 | 0 | 3 | 1 | 1 | Executive | 20,785 |
28 | Self Enquiry | 3 | 9 | Small Business | Male | 3 | 4 | Basic | 5 | Married | 2 | 0 | 5 | 0 | 2 | Executive | 21,719 |
59 | Self Enquiry | 1 | 12 | Large Business | Female | 3 | 5 | Standard | 4 | Married | 4 | 1 | 5 | 1 | 2 | Senior Manager | 29,230 |
40 | Self Enquiry | 3 | 28 | Salaried | Male | 3 | 5 | Deluxe | 3 | Divorced | 5 | 1 | 1 | 0 | 2 | Manager | 24,798 |
29 | Company Invited | 2 | 7 | Salaried | Male | 3 | 4 | Basic | 3 | Married | 3 | 0 | 4 | 0 | 2 | Executive | 21,384 |
35 | Self Enquiry | 1 | 15 | Salaried | Female | 3 | 4 | Deluxe | 5 | Married | 5 | 0 | 5 | 1 | 1 | Manager | 23,799 |
34 | Self Enquiry | 2 | 15 | Large Business | Female | 2 | 3 | Basic | 3 | Divorced | 2 | 0 | 1 | 1 | 0 | Executive | 17,742 |
36 | Self Enquiry | 1 | 10 | Salaried | Male | 2 | 4 | Deluxe | 3 | Single | 2 | 0 | 5 | 1 | 1 | Manager | 20,810 |
41 | Company Invited | 1 | 16 | Salaried | Male | 3 | 4 | Super Deluxe | 5 | Married | 5 | 0 | 2 | 1 | 0 | AVP | 32,181 |
46 | Company Invited | 1 | 6 | Small Business | Male | 2 | 4 | Standard | 5 | Married | 3 | 1 | 1 | 1 | 1 | Senior Manager | 25,673 |
27 | Self Enquiry | 3 | 36 | Small Business | Male | 3 | 4 | Deluxe | 3 | Married | 7 | 0 | 5 | 1 | 1 | Manager | 22,984 |
32 | Company Invited | 3 | 27 | Salaried | Male | 4 | 2 | Basic | 3 | Married | 2 | 0 | 5 | 1 | 1 | Executive | 21,469 |
38 | Self Enquiry | 1 | 26 | Salaried | Male | 4 | 4 | Basic | 4 | Married | 6 | 0 | 4 | 0 | 2 | Executive | 21,700 |
34 | Company Invited | 3 | 29 | Small Business | Male | 4 | 4 | Deluxe | 4 | Married | 2 | 0 | 1 | 0 | 1 | Manager | 24,824 |
51 | Self Enquiry | 2 | 11 | Salaried | Male | 2 | 3 | Super Deluxe | 4 | Married | 2 | 1 | 3 | 1 | 1 | AVP | 29,026 |
40 | Self Enquiry | 1 | 8 | Small Business | Female | 2 | 4 | Basic | 3 | Single | 1 | 1 | 3 | 1 | 1 | Executive | 17,342 |
49 | Self Enquiry | 1 | 13 | Salaried | Male | 2 | 4 | Standard | 3 | Unmarried | 1 | 0 | 1 | 1 | 0 | Senior Manager | 25,965 |
48 | Self Enquiry | 1 | 16 | Salaried | Female | 4 | 4 | Basic | 3 | Single | 6 | 0 | 3 | 1 | 1 | Executive | 20,783 |
29 | Self Enquiry | 3 | 26 | Small Business | Male | 2 | 3 | Deluxe | 3 | Married | 3 | 0 | 1 | 1 | 0 | Manager | 21,931 |
25 | Company Invited | 3 | 31 | Small Business | Male | 3 | 4 | Basic | 3 | Married | 2 | 0 | 4 | 1 | 2 | Executive | 21,078 |
35 | Self Enquiry | 3 | 23 | Salaried | Male | 3 | 3 | Deluxe | 5 | Married | 4 | 1 | 3 | 0 | 2 | Manager | 23,966 |
30 | Self Enquiry | 3 | 17 | Small Business | Female | 3 | 5 | Deluxe | 4 | Married | 3 | 1 | 5 | 1 | 1 | Manager | 26,946 |
35 | Self Enquiry | 1 | 29 | Salaried | Male | 2 | 4 | Deluxe | 3 | Married | 4 | 1 | 4 | 1 | 0 | Manager | 20,916 |
36 | Self Enquiry | 1 | 8 | Salaried | Female | 3 | 3 | Basic | 3 | Married | 5 | 0 | 5 | 1 | 0 | Executive | 17,543 |
50 | Self Enquiry | 3 | 5 | Small Business | Male | 2 | 3 | King | 3 | Married | 5 | 1 | 5 | 0 | 1 | VP | 34,331 |
44 | Self Enquiry | 3 | 32 | Small Business | Male | 4 | 5 | Standard | 3 | Married | 7 | 0 | 4 | 1 | 2 | Senior Manager | 29,476 |
38 | Self Enquiry | 3 | 8 | Small Business | Male | 2 | 3 | Standard | 4 | Unmarried | 1 | 0 | 4 | 1 | 0 | Senior Manager | 22,351 |
37 | Self Enquiry | 1 | 14 | Salaried | Male | 4 | 4 | Basic | 4 | Single | 4 | 0 | 1 | 0 | 3 | Executive | 20,691 |
32 | Self Enquiry | 2 | 9 | Salaried | Male | 4 | 5 | Deluxe | 5 | Divorced | 5 | 0 | 3 | 0 | 2 | Manager | 25,088 |
42 | Company Invited | 3 | 17 | Salaried | Male | 3 | 4 | Deluxe | 3 | Unmarried | 2 | 0 | 2 | 0 | 2 | Manager | 24,908 |
50 | Self Enquiry | 1 | 34 | Small Business | Male | 3 | 2 | Basic | 3 | Divorced | 2 | 1 | 2 | 1 | 2 | Executive | 18,221 |
25 | Company Invited | 1 | 14 | Salaried | Female | 3 | 4 | Basic | 3 | Married | 3 | 1 | 4 | 0 | 1 | Executive | 21,564 |
19 | Self Enquiry | 1 | 15 | Salaried | Male | 2 | 3 | Basic | 5 | Single | 2 | 0 | 3 | 0 | 0 | Executive | 17,552 |
41 | Self Enquiry | 3 | 17 | Small Business | Male | 4 | 5 | Standard | 4 | Married | 4 | 0 | 4 | 0 | 1 | Senior Manager | 28,383 |
47 | Company Invited | 1 | 25 | Small Business | Female | 3 | 4 | Standard | 3 | Divorced | 7 | 0 | 3 | 1 | 1 | Senior Manager | 29,205 |
32 | Company Invited | 3 | 27 | Small Business | Female | 3 | 4 | Deluxe | 3 | Divorced | 3 | 0 | 2 | 1 | 1 | Manager | 25,610 |
44 | Self Enquiry | 3 | 34 | Small Business | Female | 2 | 1 | Super Deluxe | 3 | Divorced | 4 | 1 | 2 | 1 | 1 | AVP | 28,320 |
51 | Self Enquiry | 3 | 15 | Small Business | Male | 3 | 4 | Basic | 4 | Divorced | 2 | 0 | 2 | 1 | 1 | Executive | 22,553 |
37 | Self Enquiry | 1 | 7 | Salaried | Female | 2 | 4 | Deluxe | 3 | Married | 2 | 0 | 1 | 0 | 0 | Manager | 21,474 |
36 | Self Enquiry | 1 | 7 | Small Business | Male | 4 | 5 | Basic | 5 | Single | 3 | 0 | 1 | 0 | 3 | Executive | 21,128 |
30 | Self Enquiry | 1 | 15 | Salaried | Male | 4 | 6 | Basic | 5 | Divorced | 3 | 1 | 3 | 1 | 2 | Executive | 20,797 |
43 | Self Enquiry | 3 | 21 | Small Business | Female | 4 | 5 | Deluxe | 3 | Unmarried | 2 | 0 | 3 | 1 | 1 | Manager | 24,922 |
28 | Self Enquiry | 3 | 9 | Salaried | Male | 4 | 4 | Deluxe | 3 | Unmarried | 3 | 1 | 4 | 0 | 2 | Manager | 23,156 |
33 | Self Enquiry | 1 | 9 | Large Business | Male | 3 | 5 | Deluxe | 5 | Single | 6 | 0 | 4 | 0 | 2 | Manager | 20,854 |
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