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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/udbhav90/tourism-package-prediction/tourism.csv (at revision 3475c4c6f1df0eaed6c6b2cedbeaa78e5f4197ed)
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'), 'NumberOfPersonVisiting': Value('int64'), 'PreferredPropertyStar': Value('float64'), 'NumberOfTrips': Value('float64'), 'NumberOfChildrenVisiting': Value('float64'), 'MonthlyIncome': Value('float64'), 'PitchSatisfactionScore': Value('int64'), 'NumberOfFollowups': Value('float64'), 'DurationOfPitch': Value('float64'), 'TypeofContact': Value('string'), 'CityTier': Value('int64'), 'Occupation': Value('string'), 'Gender': Value('string'), 'MaritalStatus': Value('string'), 'Designation': Value('string'), 'ProductPitched': Value('string'), 'Passport': Value('int64'), 'OwnCar': Value('int64')}
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/udbhav90/tourism-package-prediction/tourism.csv (at revision 3475c4c6f1df0eaed6c6b2cedbeaa78e5f4197ed)
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 | NumberOfPersonVisiting int64 | PreferredPropertyStar float64 | NumberOfTrips float64 | NumberOfChildrenVisiting float64 | MonthlyIncome float64 | PitchSatisfactionScore int64 | NumberOfFollowups float64 | DurationOfPitch float64 | TypeofContact string | CityTier int64 | Occupation string | Gender string | MaritalStatus string | Designation string | ProductPitched string | Passport int64 | OwnCar int64 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
44 | 3 | 3 | 2 | 0 | 22,879 | 4 | 1 | 8 | Self Enquiry | 1 | Salaried | Female | Married | Senior Manager | Standard | 1 | 1 |
35 | 3 | 3 | 3 | 2 | 27,306 | 1 | 4 | 20 | Self Enquiry | 3 | Small Business | Male | Married | Senior Manager | Standard | 0 | 1 |
47 | 4 | 5 | 3 | 2 | 29,131 | 2 | 4 | 7 | Self Enquiry | 3 | Small Business | Female | Married | Senior Manager | Standard | 0 | 1 |
32 | 3 | 4 | 2 | 0 | 21,220 | 3 | 3 | 6 | Self Enquiry | 1 | Salaried | Male | Married | Manager | Deluxe | 0 | 1 |
59 | 3 | 3 | 6 | 2 | 21,157 | 2 | 4 | 9 | Self Enquiry | 1 | Large Business | Male | Single | Executive | Basic | 0 | 1 |
44 | 2 | 4 | 1 | 1 | 33,213 | 5 | 3 | 11 | Self Enquiry | 3 | Small Business | Male | Divorced | VP | King | 0 | 1 |
32 | 2 | 4 | 2 | 0 | 17,837 | 3 | 4 | 35 | Self Enquiry | 1 | Salaried | Female | Single | Executive | Basic | 0 | 1 |
27 | 3 | 3 | 3 | 2 | 23,974 | 5 | 4 | 7 | Self Enquiry | 3 | Salaried | Male | Married | Manager | Deluxe | 0 | 0 |
38 | 2 | 3 | 4 | 1 | 20,249 | 5 | 4 | 8 | Company Invited | 3 | Salaried | Male | Divorced | Manager | Deluxe | 0 | 1 |
32 | 3 | 3 | 2 | 1 | 23,499 | 4 | 4 | 12 | Self Enquiry | 1 | Large Business | Male | Married | Executive | Basic | 1 | 1 |
40 | 3 | 3 | 2 | 1 | 18,319 | 3 | 3 | 30 | Self Enquiry | 1 | Large Business | Male | Married | Manager | Deluxe | 0 | 1 |
38 | 3 | 3 | 3 | 1 | 22,963 | 1 | 4 | 20 | Self Enquiry | 1 | Small Business | Male | Married | Manager | Deluxe | 0 | 0 |
35 | 3 | 3 | 2 | 0 | 23,789 | 5 | 3 | 6 | Company Invited | 3 | Small Business | Fe Male | Unmarried | Senior Manager | Standard | 0 | 1 |
35 | 3 | 5 | 2 | 1 | 17,074 | 1 | 3 | 8 | Self Enquiry | 1 | Salaried | Female | Married | Executive | Basic | 1 | 1 |
34 | 3 | 3 | 2 | 1 | 22,086 | 5 | 6 | 17 | Self Enquiry | 1 | Small Business | Male | Married | Executive | Basic | 0 | 0 |
33 | 3 | 4 | 3 | 1 | 21,515 | 3 | 5 | 36 | Self Enquiry | 1 | Salaried | Female | Unmarried | Executive | Basic | 0 | 1 |
51 | 3 | 3 | 4 | 0 | 17,075 | 3 | 3 | 15 | Self Enquiry | 1 | Salaried | Male | Divorced | Executive | Basic | 0 | 1 |
29 | 2 | 5 | 2 | 1 | 16,091 | 3 | 1 | 30 | Company Invited | 3 | Large Business | Male | Single | Executive | Basic | 0 | 1 |
34 | 3 | 3 | 1 | 2 | 20,304 | 2 | 2 | 25 | Company Invited | 3 | Small Business | Male | Single | Manager | Deluxe | 1 | 1 |
38 | 2 | 3 | 6 | 1 | 32,342 | 2 | 4 | 14 | Self Enquiry | 1 | Small Business | Male | Single | Senior Manager | Standard | 0 | 0 |
46 | 3 | 5 | 1 | 0 | 24,396 | 2 | 3 | 6 | Self Enquiry | 1 | Small Business | Male | Married | Senior Manager | Standard | 0 | 0 |
54 | 2 | 4 | 3 | 0 | 25,725 | 3 | 3 | 25 | Self Enquiry | 2 | Small Business | Male | Divorced | Senior Manager | Standard | 0 | 1 |
56 | 2 | 3 | 1 | 0 | 26,103 | 4 | 3 | 15 | Self Enquiry | 1 | Small Business | Male | Married | AVP | Super Deluxe | 0 | 0 |
30 | 2 | 3 | 19 | 1 | 17,285 | 4 | 3 | 10 | Company Invited | 1 | Large Business | Male | Single | Executive | Basic | 1 | 1 |
26 | 3 | 5 | 1 | 2 | 17,867 | 5 | 3 | 6 | Self Enquiry | 1 | Small Business | Male | Single | Executive | Basic | 0 | 1 |
33 | 2 | 3 | 1 | 0 | 26,691 | 4 | 3 | 13 | Self Enquiry | 1 | Small Business | Male | Married | Senior Manager | Standard | 0 | 1 |
24 | 3 | 4 | 2 | 1 | 17,127 | 3 | 4 | 23 | Self Enquiry | 1 | Salaried | Male | Married | Executive | Basic | 0 | 1 |
30 | 4 | 3 | 2 | 3 | 25,062 | 5 | 6 | 36 | Self Enquiry | 1 | Salaried | Male | Married | Manager | Deluxe | 0 | 1 |
33 | 3 | 4 | 1 | 0 | 20,147 | 1 | 3 | 8 | Company Invited | 3 | Small Business | Female | Single | Manager | Deluxe | 0 | 0 |
53 | 2 | 4 | 3 | 0 | 22,525 | 1 | 4 | 8 | Company Invited | 3 | Small Business | Female | Married | Senior Manager | Standard | 0 | 1 |
29 | 3 | 5 | 2 | 2 | 23,576 | 3 | 4 | 14 | Company Invited | 3 | Salaried | Male | Unmarried | Manager | Deluxe | 0 | 1 |
39 | 2 | 5 | 2 | 0 | 20,151 | 4 | 3 | 15 | Self Enquiry | 1 | Small Business | Male | Married | Manager | Deluxe | 0 | 1 |
46 | 4 | 4 | 2 | 3 | 23,483 | 5 | 4 | 9 | Self Enquiry | 3 | Salaried | Male | Married | Manager | Deluxe | 0 | 1 |
35 | 3 | 4 | 2 | 1 | 30,672 | 3 | 4 | 14 | Self Enquiry | 1 | Salaried | Female | Single | Senior Manager | Standard | 0 | 1 |
35 | 4 | 3 | 8 | 1 | 20,909 | 5 | 4 | 9 | Company Invited | 3 | Small Business | Female | Married | Executive | Basic | 0 | 0 |
33 | 4 | 4 | 8 | 3 | 21,010 | 3 | 5 | 7 | Company Invited | 1 | Salaried | Female | Married | Executive | Basic | 0 | 0 |
29 | 2 | 3 | 2 | 0 | 21,623 | 4 | 4 | 16 | Company Invited | 1 | Salaried | Female | Unmarried | Executive | Basic | 0 | 1 |
41 | 2 | 3 | 1 | 1 | 21,230 | 1 | 3 | 16 | Company Invited | 3 | Salaried | Male | Single | Manager | Deluxe | 0 | 0 |
43 | 3 | 3 | 6 | 1 | 22,950 | 3 | 6 | 36 | Self Enquiry | 1 | Small Business | Male | Unmarried | Manager | Deluxe | 0 | 1 |
35 | 3 | 3 | 2 | 2 | 21,029 | 4 | 6 | 13 | Company Invited | 3 | Small Business | Female | Married | Executive | Basic | 0 | 0 |
41 | 3 | 3 | 4 | 0 | 28,591 | 1 | 3 | 12 | Self Enquiry | 3 | Salaried | Female | Single | Senior Manager | Standard | 1 | 0 |
33 | 2 | 3 | 1 | 0 | 21,949 | 4 | 4 | 6 | Self Enquiry | 1 | Salaried | Female | Unmarried | Manager | Deluxe | 0 | 0 |
40 | 2 | 3 | 1 | 0 | 28,499 | 4 | 3 | 15 | Company Invited | 1 | Small Business | Fe Male | Unmarried | Senior Manager | Standard | 0 | 0 |
26 | 3 | 5 | 1 | 1 | 18,102 | 3 | 3 | 9 | Company Invited | 1 | Large Business | Male | Single | Executive | Basic | 0 | 0 |
41 | 2 | 5 | 3 | 0 | 18,072 | 1 | 3 | 25 | Self Enquiry | 1 | Salaried | Male | Married | Manager | Deluxe | 0 | 0 |
37 | 2 | 3 | 2 | 1 | 27,185 | 3 | 3 | 17 | Company Invited | 1 | Salaried | Male | Married | Senior Manager | Standard | 1 | 0 |
31 | 2 | 3 | 4 | 1 | 17,329 | 4 | 4 | 13 | Self Enquiry | 3 | Salaried | Male | Married | Executive | Basic | 0 | 1 |
45 | 3 | 4 | 8 | 2 | 21,040 | 3 | 6 | 8 | Self Enquiry | 3 | Salaried | Male | Single | Manager | Deluxe | 0 | 0 |
33 | 3 | 5 | 2 | 2 | 18,348 | 5 | 3 | 9 | Company Invited | 1 | Salaried | Male | Single | Executive | Basic | 1 | 1 |
33 | 4 | 4 | 3 | 1 | 21,048 | 4 | 4 | 9 | Self Enquiry | 1 | Small Business | Female | Divorced | Executive | Basic | 0 | 0 |
33 | 3 | 3 | 3 | 2 | 21,388 | 3 | 3 | 14 | Self Enquiry | 1 | Salaried | Male | Unmarried | Manager | Deluxe | 1 | 0 |
30 | 2 | 3 | 1 | 0 | 21,577 | 2 | 3 | 18 | Self Enquiry | 3 | Large Business | Female | Unmarried | Manager | Deluxe | 0 | 1 |
42 | 2 | 3 | 7 | 1 | 17,759 | 3 | 2 | 25 | Company Invited | 1 | Small Business | Male | Married | Executive | Basic | 1 | 1 |
46 | 2 | 3 | 7 | 0 | 32,861 | 5 | 3 | 8 | Self Enquiry | 1 | Salaried | Male | Married | AVP | Super Deluxe | 0 | 1 |
51 | 4 | 3 | 6 | 3 | 21,058 | 5 | 4 | 16 | Self Enquiry | 1 | Salaried | Male | Married | Executive | Basic | 0 | 1 |
30 | 2 | 3 | 3 | 0 | 21,091 | 1 | 5 | 8 | Self Enquiry | 1 | Salaried | Female | Single | Manager | Deluxe | 0 | 1 |
37 | 3 | 3 | 6 | 1 | 22,366 | 5 | 3 | 25 | Company Invited | 1 | Salaried | Male | Divorced | Executive | Basic | 0 | 0 |
28 | 2 | 3 | 2 | 1 | 17,706 | 4 | 3 | 6 | Company Invited | 2 | Salaried | Male | Married | Executive | Basic | 0 | 0 |
42 | 2 | 5 | 1 | 0 | 28,348 | 3 | 3 | 12 | Self Enquiry | 1 | Small Business | Male | Married | Senior Manager | Standard | 0 | 1 |
44 | 2 | 4 | 1 | 0 | 20,933 | 2 | 3 | 10 | Self Enquiry | 1 | Small Business | Male | Single | Manager | Deluxe | 0 | 1 |
39 | 3 | 4 | 3 | 1 | 21,118 | 1 | 5 | 9 | Company Invited | 1 | Small Business | Female | Single | Executive | Basic | 0 | 1 |
42 | 2 | 5 | 4 | 0 | 21,545 | 2 | 2 | 23 | Self Enquiry | 1 | Salaried | Female | Unmarried | Manager | Deluxe | 1 | 0 |
39 | 2 | 5 | 2 | 1 | 25,880 | 5 | 3 | 28 | Company Invited | 1 | Small Business | Fe Male | Unmarried | Senior Manager | Standard | 1 | 1 |
28 | 2 | 3 | 1 | 0 | 21,674 | 3 | 5 | 6 | Company Invited | 1 | Salaried | Female | Divorced | Manager | Deluxe | 0 | 1 |
43 | 3 | 5 | 7 | 1 | 32,159 | 5 | 3 | 20 | Self Enquiry | 1 | Salaried | Male | Married | AVP | Super Deluxe | 0 | 1 |
45 | 4 | 3 | 3 | 2 | 26,656 | 3 | 4 | 22 | Self Enquiry | 1 | Small Business | Female | Divorced | Senior Manager | Standard | 0 | 0 |
53 | 4 | 5 | 5 | 2 | 24,255 | 4 | 4 | 13 | Self Enquiry | 1 | Large Business | Male | Married | Manager | Deluxe | 1 | 1 |
42 | 4 | 5 | 4 | 1 | 20,916 | 1 | 4 | 16 | Self Enquiry | 1 | Salaried | Male | Married | Executive | Basic | 0 | 0 |
36 | 3 | 3 | 7 | 0 | 20,237 | 3 | 3 | 33 | Self Enquiry | 1 | Small Business | Male | Divorced | Manager | Deluxe | 0 | 1 |
22 | 4 | 4 | 3 | 3 | 20,748 | 5 | 5 | 7 | Self Enquiry | 1 | Large Business | Female | Single | Executive | Basic | 1 | 0 |
37 | 4 | 4 | 2 | 3 | 24,592 | 2 | 4 | 12 | Self Enquiry | 1 | Salaried | Male | Unmarried | Manager | Deluxe | 0 | 0 |
30 | 3 | 4 | 7 | 2 | 24,443 | 3 | 4 | 20 | Company Invited | 3 | Large Business | Fe Male | Unmarried | Manager | Deluxe | 0 | 0 |
36 | 4 | 5 | 4 | 3 | 28,562 | 5 | 5 | 18 | Company Invited | 1 | Small Business | Male | Married | Senior Manager | Standard | 1 | 1 |
40 | 2 | 3 | 2 | 1 | 34,033 | 5 | 3 | 10 | Self Enquiry | 1 | Small Business | Female | Divorced | VP | King | 0 | 0 |
51 | 2 | 3 | 3 | 1 | 25,650 | 2 | 5 | 14 | Company Invited | 1 | Salaried | Male | Unmarried | Senior Manager | Standard | 0 | 0 |
39 | 3 | 5 | 6 | 2 | 21,536 | 3 | 5 | 7 | Self Enquiry | 3 | Salaried | Male | Unmarried | Executive | Basic | 0 | 0 |
43 | 2 | 4 | 2 | 1 | 29,336 | 3 | 4 | 18 | Self Enquiry | 1 | Salaried | Male | Married | AVP | Super Deluxe | 0 | 0 |
35 | 3 | 3 | 2 | 0 | 16,951 | 4 | 3 | 10 | Self Enquiry | 1 | Salaried | Male | Married | Executive | Basic | 0 | 0 |
40 | 4 | 3 | 2 | 2 | 29,616 | 2 | 4 | 9 | Company Invited | 1 | Large Business | Female | Single | Senior Manager | Standard | 0 | 1 |
27 | 3 | 3 | 3 | 1 | 23,362 | 1 | 4 | 17 | Self Enquiry | 3 | Small Business | Male | Unmarried | Manager | Deluxe | 0 | 0 |
26 | 2 | 5 | 7 | 0 | 17,042 | 5 | 3 | 8 | Company Invited | 1 | Salaried | Male | Divorced | Executive | Basic | 1 | 1 |
43 | 3 | 3 | 2 | 0 | 31,959 | 2 | 3 | 32 | Company Invited | 3 | Salaried | Male | Divorced | AVP | Super Deluxe | 1 | 0 |
32 | 4 | 5 | 3 | 3 | 25,511 | 2 | 4 | 18 | Self Enquiry | 1 | Small Business | Male | Divorced | Manager | Deluxe | 1 | 0 |
35 | 3 | 5 | 4 | 1 | 30,309 | 2 | 5 | 12 | Self Enquiry | 1 | Small Business | Female | Single | Senior Manager | Standard | 0 | 0 |
34 | 3 | 4 | 8 | 2 | 21,300 | 4 | 5 | 11 | Self Enquiry | 1 | Small Business | Female | Married | Executive | Basic | 0 | 0 |
31 | 2 | 4 | 2 | 1 | 16,261 | 4 | 4 | 14 | Self Enquiry | 1 | Salaried | Female | Single | Executive | Basic | 0 | 0 |
35 | 4 | 3 | 3 | 1 | 24,392 | 1 | 4 | 16 | Self Enquiry | 3 | Salaried | Female | Married | Manager | Deluxe | 0 | 0 |
42 | 3 | 3 | 2 | 2 | 24,829 | 5 | 6 | 16 | Company Invited | 3 | Salaried | Male | Married | AVP | Super Deluxe | 0 | 1 |
34 | 2 | 5 | 4 | 1 | 20,121 | 5 | 3 | 14 | Self Enquiry | 1 | Salaried | Female | Married | Manager | Deluxe | 0 | 1 |
34 | 3 | 5 | 2 | 1 | 21,385 | 3 | 4 | 9 | Self Enquiry | 1 | Salaried | Female | Divorced | Executive | Basic | 0 | 1 |
34 | 2 | 4 | 1 | 0 | 26,994 | 3 | 3 | 13 | Self Enquiry | 1 | Salaried | Fe Male | Unmarried | Senior Manager | Standard | 0 | 1 |
39 | 3 | 3 | 5 | 2 | 24,939 | 2 | 4 | 36 | Self Enquiry | 1 | Large Business | Male | Divorced | Manager | Deluxe | 0 | 0 |
29 | 3 | 3 | 3 | 1 | 22,119 | 1 | 4 | 12 | Self Enquiry | 1 | Large Business | Male | Unmarried | Executive | Basic | 1 | 0 |
35 | 2 | 3 | 3 | 1 | 20,762 | 3 | 3 | 8 | Company Invited | 1 | Small Business | Male | Married | Manager | Deluxe | 0 | 0 |
26 | 2 | 3 | 2 | 1 | 20,828 | 2 | 4 | 10 | Self Enquiry | 3 | Small Business | Male | Single | Manager | Deluxe | 1 | 1 |
37 | 3 | 3 | 7 | 1 | 21,513 | 2 | 4 | 10 | Self Enquiry | 1 | Salaried | Female | Married | Executive | Basic | 0 | 1 |
35 | 4 | 5 | 6 | 2 | 24,024 | 3 | 4 | 16 | Company Invited | 1 | Salaried | Male | Married | Manager | Deluxe | 0 | 0 |
40 | 3 | 3 | 2 | 1 | 30,847 | 3 | 4 | 9 | Company Invited | 1 | Salaried | Male | Married | AVP | Super Deluxe | 0 | 1 |
33 | 2 | 3 | 2 | 0 | 17,851 | 2 | 3 | 11 | Self Enquiry | 3 | Small Business | Female | Single | Executive | Basic | 1 | 1 |
38 | 3 | 4 | 1 | 0 | 17,899 | 4 | 4 | 15 | Self Enquiry | 3 | Small Business | Male | Divorced | Executive | Basic | 0 | 0 |
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