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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 ({'Unnamed: 0', 'CustomerID', 'ProdTaken'})
This happened while the csv dataset builder was generating data using
hf://datasets/subhash33/tourism-package/tourism.csv (at revision 1e0da420ef21220ec4ba463b5ad96993c5c2faf8)
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('int64'), 'CityTier': Value('int64'), 'DurationOfPitch': Value('int64'), 'NumberOfPersonVisiting': Value('int64'), 'NumberOfFollowups': Value('int64'), 'PreferredPropertyStar': Value('int64'), 'NumberOfTrips': Value('int64'), 'Passport': Value('int64'), 'PitchSatisfactionScore': Value('int64'), 'OwnCar': Value('int64'), 'NumberOfChildrenVisiting': Value('int64'), 'MonthlyIncome': Value('int64'), 'TypeofContact': Value('string'), 'Occupation': Value('string'), 'Gender': Value('string'), 'ProductPitched': Value('string'), 'MaritalStatus': Value('string'), 'Designation': Value('string')}
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 ({'Unnamed: 0', 'CustomerID', 'ProdTaken'})
This happened while the csv dataset builder was generating data using
hf://datasets/subhash33/tourism-package/tourism.csv (at revision 1e0da420ef21220ec4ba463b5ad96993c5c2faf8)
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 int64 | CityTier int64 | DurationOfPitch int64 | NumberOfPersonVisiting int64 | NumberOfFollowups int64 | PreferredPropertyStar int64 | NumberOfTrips int64 | Passport int64 | PitchSatisfactionScore int64 | OwnCar int64 | NumberOfChildrenVisiting int64 | MonthlyIncome int64 | TypeofContact string | Occupation string | Gender string | ProductPitched string | MaritalStatus string | Designation string |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
34 | 1 | 9 | 2 | 4 | 3 | 4 | 0 | 1 | 0 | 0 | 17,979 | Company Invited | Salaried | Male | Basic | Married | Executive |
32 | 1 | 6 | 3 | 3 | 4 | 2 | 0 | 3 | 0 | 0 | 21,220 | Self Enquiry | Salaried | Male | Deluxe | Divorced | Manager |
30 | 3 | 11 | 2 | 3 | 3 | 3 | 0 | 4 | 1 | 1 | 24,419 | Self Enquiry | Salaried | Female | Standard | Divorced | Senior Manager |
39 | 3 | 9 | 3 | 4 | 4 | 2 | 0 | 4 | 1 | 2 | 26,029 | Self Enquiry | Small Business | Male | Standard | Unmarried | Senior Manager |
37 | 1 | 31 | 3 | 4 | 4 | 2 | 0 | 3 | 1 | 2 | 24,352 | Company Invited | Salaried | Female | Deluxe | Married | Manager |
34 | 1 | 9 | 3 | 4 | 3 | 2 | 0 | 3 | 0 | 2 | 21,178 | Self Enquiry | Salaried | Male | Basic | Single | Executive |
27 | 1 | 7 | 4 | 6 | 3 | 5 | 0 | 4 | 1 | 3 | 23,042 | Company Invited | Salaried | Female | Basic | Married | Executive |
30 | 3 | 6 | 3 | 4 | 5 | 2 | 0 | 4 | 1 | 1 | 24,714 | Self Enquiry | Salaried | Male | Deluxe | Married | Manager |
53 | 1 | 32 | 3 | 5 | 3 | 5 | 0 | 5 | 0 | 2 | 32,504 | Company Invited | Small Business | Female | Super Deluxe | Married | AVP |
55 | 1 | 7 | 3 | 4 | 3 | 2 | 0 | 5 | 1 | 2 | 29,180 | Company Invited | Salaried | Female | Standard | Married | Senior Manager |
46 | 1 | 6 | 2 | 4 | 5 | 3 | 1 | 2 | 1 | 1 | 25,673 | Company Invited | Small Business | Male | Standard | Divorced | Senior Manager |
39 | 1 | 19 | 2 | 5 | 5 | 4 | 0 | 5 | 1 | 1 | 24,966 | Company Invited | Salaried | Male | Deluxe | Married | Manager |
54 | 2 | 32 | 1 | 2 | 3 | 3 | 1 | 3 | 1 | 0 | 32,328 | Company Invited | Salaried | Female | Super Deluxe | Single | AVP |
42 | 1 | 19 | 3 | 1 | 5 | 6 | 0 | 4 | 1 | 0 | 20,538 | Self Enquiry | Small Business | Male | Deluxe | Married | Manager |
33 | 1 | 12 | 3 | 2 | 3 | 5 | 0 | 5 | 1 | 2 | 21,990 | Self Enquiry | Salaried | Female | Basic | Married | Executive |
35 | 1 | 6 | 1 | 4 | 3 | 2 | 0 | 4 | 1 | 0 | 17,859 | Self Enquiry | Small Business | Male | Basic | Single | Executive |
39 | 1 | 16 | 3 | 3 | 3 | 1 | 0 | 3 | 1 | 0 | 28,464 | Self Enquiry | Small Business | Male | Standard | Unmarried | Senior Manager |
29 | 1 | 17 | 3 | 4 | 3 | 5 | 0 | 4 | 1 | 2 | 22,338 | Self Enquiry | Salaried | Female | Deluxe | Unmarried | Manager |
23 | 1 | 11 | 3 | 5 | 3 | 7 | 0 | 5 | 1 | 1 | 22,572 | Company Invited | Large Business | Male | Basic | Unmarried | Executive |
37 | 1 | 15 | 2 | 3 | 3 | 2 | 1 | 2 | 0 | 0 | 17,326 | Company Invited | Small Business | Male | Basic | Divorced | Executive |
33 | 1 | 10 | 4 | 4 | 5 | 3 | 0 | 1 | 1 | 1 | 25,403 | Self Enquiry | Small Business | Female | Deluxe | Married | Manager |
33 | 1 | 7 | 4 | 4 | 5 | 3 | 0 | 1 | 0 | 2 | 21,634 | Self Enquiry | Salaried | Male | Basic | Unmarried | Executive |
50 | 1 | 25 | 4 | 4 | 3 | 3 | 1 | 1 | 0 | 1 | 25,482 | Company Invited | Salaried | Male | Deluxe | Married | Manager |
42 | 1 | 6 | 2 | 4 | 3 | 1 | 1 | 3 | 0 | 0 | 21,062 | Self Enquiry | Salaried | Female | Deluxe | Married | Manager |
43 | 1 | 33 | 3 | 4 | 5 | 5 | 1 | 3 | 0 | 1 | 31,869 | Company Invited | Small Business | Female | Standard | Married | Senior Manager |
36 | 1 | 15 | 3 | 1 | 4 | 2 | 0 | 5 | 1 | 0 | 17,810 | Company Invited | Salaried | Male | Basic | Married | Executive |
27 | 3 | 8 | 2 | 1 | 3 | 1 | 0 | 1 | 0 | 1 | 21,500 | Self Enquiry | Small Business | Female | Deluxe | Unmarried | Manager |
29 | 3 | 16 | 4 | 4 | 3 | 3 | 0 | 3 | 1 | 2 | 23,931 | Self Enquiry | Salaried | Male | Deluxe | Unmarried | Manager |
34 | 1 | 12 | 4 | 5 | 3 | 3 | 0 | 2 | 0 | 3 | 21,589 | Self Enquiry | Salaried | Female | Basic | Divorced | Executive |
41 | 3 | 21 | 3 | 4 | 5 | 3 | 0 | 3 | 0 | 2 | 23,317 | Self Enquiry | Salaried | Female | Deluxe | Married | Manager |
32 | 3 | 20 | 4 | 5 | 5 | 7 | 1 | 1 | 1 | 1 | 20,980 | Self Enquiry | Small Business | Male | Deluxe | Married | Manager |
50 | 2 | 9 | 3 | 3 | 4 | 2 | 0 | 1 | 1 | 2 | 33,200 | Company Invited | Small Business | Male | King | Married | VP |
24 | 3 | 30 | 2 | 3 | 3 | 1 | 0 | 4 | 1 | 1 | 17,400 | Company Invited | Small Business | Male | Basic | Married | Executive |
43 | 1 | 7 | 3 | 5 | 3 | 2 | 1 | 3 | 0 | 1 | 24,740 | Self Enquiry | Salaried | Female | Deluxe | Married | Manager |
39 | 1 | 16 | 3 | 3 | 5 | 3 | 0 | 5 | 1 | 2 | 20,377 | Self Enquiry | Small Business | Male | Deluxe | Married | Manager |
55 | 1 | 6 | 2 | 3 | 5 | 1 | 1 | 1 | 1 | 1 | 34,045 | Self Enquiry | Small Business | Male | King | Single | VP |
33 | 1 | 10 | 3 | 4 | 3 | 3 | 0 | 4 | 1 | 1 | 24,887 | Company Invited | Salaried | Female | Basic | Unmarried | Executive |
34 | 3 | 23 | 4 | 4 | 5 | 4 | 1 | 5 | 0 | 1 | 27,242 | Self Enquiry | Salaried | Female | Standard | Unmarried | Senior Manager |
25 | 1 | 25 | 3 | 4 | 3 | 2 | 0 | 4 | 0 | 1 | 21,452 | Self Enquiry | Salaried | Male | Basic | Married | Executive |
30 | 1 | 24 | 3 | 3 | 3 | 2 | 0 | 1 | 1 | 2 | 17,632 | Self Enquiry | Salaried | Female | Basic | Single | Executive |
32 | 3 | 12 | 3 | 4 | 4 | 3 | 0 | 3 | 0 | 1 | 21,467 | Company Invited | Small Business | Female | Basic | Married | Executive |
34 | 1 | 12 | 4 | 4 | 4 | 8 | 0 | 3 | 1 | 3 | 30,556 | Company Invited | Salaried | Female | Standard | Divorced | Senior Manager |
50 | 1 | 30 | 3 | 3 | 3 | 4 | 1 | 4 | 1 | 2 | 28,973 | Self Enquiry | Salaried | Male | Super Deluxe | Married | AVP |
33 | 1 | 6 | 3 | 4 | 5 | 4 | 1 | 4 | 0 | 0 | 17,799 | Self Enquiry | Salaried | Male | Basic | Single | Executive |
36 | 3 | 18 | 3 | 4 | 3 | 3 | 0 | 5 | 0 | 1 | 23,646 | Company Invited | Small Business | Male | Deluxe | Married | Manager |
50 | 1 | 25 | 4 | 4 | 3 | 3 | 1 | 2 | 0 | 2 | 25,482 | Company Invited | Salaried | Male | Deluxe | Married | Manager |
49 | 3 | 14 | 4 | 4 | 3 | 4 | 1 | 4 | 1 | 2 | 21,333 | Company Invited | Small Business | Female | Basic | Married | Executive |
37 | 3 | 14 | 3 | 2 | 5 | 4 | 0 | 1 | 1 | 1 | 23,317 | Company Invited | Small Business | Female | Deluxe | Divorced | Manager |
30 | 1 | 24 | 3 | 3 | 3 | 2 | 0 | 2 | 1 | 0 | 17,632 | Self Enquiry | Salaried | Female | Basic | Single | Executive |
23 | 1 | 7 | 4 | 4 | 3 | 2 | 0 | 3 | 0 | 3 | 22,053 | Self Enquiry | Salaried | Male | Basic | Unmarried | Executive |
34 | 1 | 33 | 3 | 3 | 4 | 3 | 0 | 3 | 0 | 0 | 17,311 | Self Enquiry | Small Business | Female | Basic | Single | Executive |
52 | 3 | 28 | 4 | 4 | 3 | 2 | 1 | 5 | 0 | 3 | 24,119 | Self Enquiry | Small Business | Male | Deluxe | Unmarried | Manager |
27 | 3 | 36 | 4 | 6 | 5 | 2 | 0 | 3 | 0 | 1 | 23,647 | Company Invited | Small Business | Male | Deluxe | Unmarried | Manager |
40 | 3 | 30 | 3 | 1 | 4 | 5 | 1 | 3 | 1 | 2 | 28,194 | Company Invited | Salaried | Female | Super Deluxe | Unmarried | AVP |
44 | 1 | 8 | 3 | 1 | 3 | 2 | 0 | 4 | 1 | 0 | 17,011 | Self Enquiry | Salaried | Female | Basic | Divorced | Executive |
27 | 1 | 9 | 3 | 4 | 5 | 8 | 1 | 5 | 0 | 1 | 20,720 | Company Invited | Salaried | Male | Basic | Married | Executive |
42 | 1 | 12 | 4 | 5 | 5 | 8 | 0 | 3 | 1 | 1 | 20,785 | Company Invited | Salaried | Male | Basic | Married | Executive |
28 | 3 | 9 | 3 | 4 | 5 | 2 | 0 | 5 | 0 | 2 | 21,719 | Self Enquiry | Small Business | Male | Basic | Married | Executive |
59 | 1 | 12 | 3 | 5 | 4 | 4 | 1 | 5 | 1 | 2 | 29,230 | Self Enquiry | Large Business | Female | Standard | Married | Senior Manager |
40 | 3 | 28 | 3 | 5 | 3 | 5 | 1 | 1 | 0 | 2 | 24,798 | Self Enquiry | Salaried | Male | Deluxe | Divorced | Manager |
29 | 2 | 7 | 3 | 4 | 3 | 3 | 0 | 4 | 0 | 2 | 21,384 | Company Invited | Salaried | Male | Basic | Married | Executive |
35 | 1 | 15 | 3 | 4 | 5 | 5 | 0 | 5 | 1 | 1 | 23,799 | Self Enquiry | Salaried | Female | Deluxe | Married | Manager |
34 | 2 | 15 | 2 | 3 | 3 | 2 | 0 | 1 | 1 | 0 | 17,742 | Self Enquiry | Large Business | Female | Basic | Divorced | Executive |
36 | 1 | 10 | 2 | 4 | 3 | 2 | 0 | 5 | 1 | 1 | 20,810 | Self Enquiry | Salaried | Male | Deluxe | Single | Manager |
41 | 1 | 16 | 3 | 4 | 5 | 5 | 0 | 2 | 1 | 0 | 32,181 | Company Invited | Salaried | Male | Super Deluxe | Married | AVP |
46 | 1 | 6 | 2 | 4 | 5 | 3 | 1 | 1 | 1 | 1 | 25,673 | Company Invited | Small Business | Male | Standard | Married | Senior Manager |
27 | 3 | 36 | 3 | 4 | 3 | 7 | 0 | 5 | 1 | 1 | 22,984 | Self Enquiry | Small Business | Male | Deluxe | Married | Manager |
32 | 3 | 27 | 4 | 2 | 3 | 2 | 0 | 5 | 1 | 1 | 21,469 | Company Invited | Salaried | Male | Basic | Married | Executive |
38 | 1 | 26 | 4 | 4 | 4 | 6 | 0 | 4 | 0 | 2 | 21,700 | Self Enquiry | Salaried | Male | Basic | Married | Executive |
34 | 3 | 29 | 4 | 4 | 4 | 2 | 0 | 1 | 0 | 1 | 24,824 | Company Invited | Small Business | Male | Deluxe | Married | Manager |
51 | 2 | 11 | 2 | 3 | 4 | 2 | 1 | 3 | 1 | 1 | 29,026 | Self Enquiry | Salaried | Male | Super Deluxe | Married | AVP |
40 | 1 | 8 | 2 | 4 | 3 | 1 | 1 | 3 | 1 | 1 | 17,342 | Self Enquiry | Small Business | Female | Basic | Single | Executive |
49 | 1 | 13 | 2 | 4 | 3 | 1 | 0 | 1 | 1 | 0 | 25,965 | Self Enquiry | Salaried | Male | Standard | Unmarried | Senior Manager |
48 | 1 | 16 | 4 | 4 | 3 | 6 | 0 | 3 | 1 | 1 | 20,783 | Self Enquiry | Salaried | Female | Basic | Single | Executive |
29 | 3 | 26 | 2 | 3 | 3 | 3 | 0 | 1 | 1 | 0 | 21,931 | Self Enquiry | Small Business | Male | Deluxe | Married | Manager |
25 | 3 | 31 | 3 | 4 | 3 | 2 | 0 | 4 | 1 | 2 | 21,078 | Company Invited | Small Business | Male | Basic | Married | Executive |
35 | 3 | 23 | 3 | 3 | 5 | 4 | 1 | 3 | 0 | 2 | 23,966 | Self Enquiry | Salaried | Male | Deluxe | Married | Manager |
30 | 3 | 17 | 3 | 5 | 4 | 3 | 1 | 5 | 1 | 1 | 26,946 | Self Enquiry | Small Business | Female | Deluxe | Married | Manager |
35 | 1 | 29 | 2 | 4 | 3 | 4 | 1 | 4 | 1 | 0 | 20,916 | Self Enquiry | Salaried | Male | Deluxe | Married | Manager |
36 | 1 | 8 | 3 | 3 | 3 | 5 | 0 | 5 | 1 | 0 | 17,543 | Self Enquiry | Salaried | Female | Basic | Married | Executive |
50 | 3 | 5 | 2 | 3 | 3 | 5 | 1 | 5 | 0 | 1 | 34,331 | Self Enquiry | Small Business | Male | King | Married | VP |
44 | 3 | 32 | 4 | 5 | 3 | 7 | 0 | 4 | 1 | 2 | 29,476 | Self Enquiry | Small Business | Male | Standard | Married | Senior Manager |
38 | 3 | 8 | 2 | 3 | 4 | 1 | 0 | 4 | 1 | 0 | 22,351 | Self Enquiry | Small Business | Male | Standard | Unmarried | Senior Manager |
37 | 1 | 14 | 4 | 4 | 4 | 4 | 0 | 1 | 0 | 3 | 20,691 | Self Enquiry | Salaried | Male | Basic | Single | Executive |
32 | 2 | 9 | 4 | 5 | 5 | 5 | 0 | 3 | 0 | 2 | 25,088 | Self Enquiry | Salaried | Male | Deluxe | Divorced | Manager |
42 | 3 | 17 | 3 | 4 | 3 | 2 | 0 | 2 | 0 | 2 | 24,908 | Company Invited | Salaried | Male | Deluxe | Unmarried | Manager |
50 | 1 | 34 | 3 | 2 | 3 | 2 | 1 | 2 | 1 | 2 | 18,221 | Self Enquiry | Small Business | Male | Basic | Divorced | Executive |
25 | 1 | 14 | 3 | 4 | 3 | 3 | 1 | 4 | 0 | 1 | 21,564 | Company Invited | Salaried | Female | Basic | Married | Executive |
19 | 1 | 15 | 2 | 3 | 5 | 2 | 0 | 3 | 0 | 0 | 17,552 | Self Enquiry | Salaried | Male | Basic | Single | Executive |
41 | 3 | 17 | 4 | 5 | 4 | 4 | 0 | 4 | 0 | 1 | 28,383 | Self Enquiry | Small Business | Male | Standard | Married | Senior Manager |
47 | 1 | 25 | 3 | 4 | 3 | 7 | 0 | 3 | 1 | 1 | 29,205 | Company Invited | Small Business | Female | Standard | Divorced | Senior Manager |
32 | 3 | 27 | 3 | 4 | 3 | 3 | 0 | 2 | 1 | 1 | 25,610 | Company Invited | Small Business | Female | Deluxe | Divorced | Manager |
44 | 3 | 34 | 2 | 1 | 3 | 4 | 1 | 2 | 1 | 1 | 28,320 | Self Enquiry | Small Business | Female | Super Deluxe | Divorced | AVP |
51 | 3 | 15 | 3 | 4 | 4 | 2 | 0 | 2 | 1 | 1 | 22,553 | Self Enquiry | Small Business | Male | Basic | Divorced | Executive |
37 | 1 | 7 | 2 | 4 | 3 | 2 | 0 | 1 | 0 | 0 | 21,474 | Self Enquiry | Salaried | Female | Deluxe | Married | Manager |
36 | 1 | 7 | 4 | 5 | 5 | 3 | 0 | 1 | 0 | 3 | 21,128 | Self Enquiry | Small Business | Male | Basic | Single | Executive |
30 | 1 | 15 | 4 | 6 | 5 | 3 | 1 | 3 | 1 | 2 | 20,797 | Self Enquiry | Salaried | Male | Basic | Divorced | Executive |
43 | 3 | 21 | 4 | 5 | 3 | 2 | 0 | 3 | 1 | 1 | 24,922 | Self Enquiry | Small Business | Female | Deluxe | Unmarried | Manager |
28 | 3 | 9 | 4 | 4 | 3 | 3 | 1 | 4 | 0 | 2 | 23,156 | Self Enquiry | Salaried | Male | Deluxe | Unmarried | Manager |
33 | 1 | 9 | 3 | 5 | 5 | 6 | 0 | 4 | 0 | 2 | 20,854 | Self Enquiry | Large Business | Male | Deluxe | Single | Manager |
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