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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 7 new columns ({'Unnamed: 0', 'DurationOfPitch', 'ProdTaken', 'PitchSatisfactionScore', 'ProductPitched', 'NumberOfFollowups', 'CustomerID'})
This happened while the csv dataset builder was generating data using
hf://datasets/sasipriyank/tourismlops/tourism.csv (at revision ba393ee4455b0462538facc8a2e1b7deba5d9e50)
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'), 'CityTier': Value('int64'), 'NumberOfPersonVisiting': Value('int64'), 'PreferredPropertyStar': Value('float64'), 'NumberOfTrips': Value('float64'), 'Passport': Value('int64'), 'OwnCar': Value('int64'), 'NumberOfChildrenVisiting': Value('float64'), 'MonthlyIncome': Value('float64'), 'Occupation': Value('string'), 'TypeofContact': Value('string'), 'Gender': 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 7 new columns ({'Unnamed: 0', 'DurationOfPitch', 'ProdTaken', 'PitchSatisfactionScore', 'ProductPitched', 'NumberOfFollowups', 'CustomerID'})
This happened while the csv dataset builder was generating data using
hf://datasets/sasipriyank/tourismlops/tourism.csv (at revision ba393ee4455b0462538facc8a2e1b7deba5d9e50)
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 | CityTier int64 | NumberOfPersonVisiting int64 | PreferredPropertyStar float64 | NumberOfTrips float64 | Passport int64 | OwnCar int64 | NumberOfChildrenVisiting float64 | MonthlyIncome float64 | Occupation string | TypeofContact string | Gender string | MaritalStatus string | Designation string |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
44 | 1 | 3 | 3 | 2 | 1 | 1 | 0 | 22,879 | Salaried | Self Enquiry | Female | Married | Senior Manager |
35 | 3 | 3 | 3 | 3 | 0 | 1 | 2 | 27,306 | Small Business | Self Enquiry | Male | Married | Senior Manager |
47 | 3 | 4 | 5 | 3 | 0 | 1 | 2 | 29,131 | Small Business | Self Enquiry | Female | Married | Senior Manager |
32 | 1 | 3 | 4 | 2 | 0 | 1 | 0 | 21,220 | Salaried | Self Enquiry | Male | Married | Manager |
59 | 1 | 3 | 3 | 6 | 0 | 1 | 2 | 21,157 | Large Business | Self Enquiry | Male | Single | Executive |
44 | 3 | 2 | 4 | 1 | 0 | 1 | 1 | 33,213 | Small Business | Self Enquiry | Male | Divorced | VP |
32 | 1 | 2 | 4 | 2 | 0 | 1 | 0 | 17,837 | Salaried | Self Enquiry | Female | Single | Executive |
27 | 3 | 3 | 3 | 3 | 0 | 0 | 2 | 23,974 | Salaried | Self Enquiry | Male | Married | Manager |
38 | 3 | 2 | 3 | 4 | 0 | 1 | 1 | 20,249 | Salaried | Company Invited | Male | Divorced | Manager |
32 | 1 | 3 | 3 | 2 | 1 | 1 | 1 | 23,499 | Large Business | Self Enquiry | Male | Married | Executive |
40 | 1 | 3 | 3 | 2 | 0 | 1 | 1 | 18,319 | Large Business | Self Enquiry | Male | Married | Manager |
38 | 1 | 3 | 3 | 3 | 0 | 0 | 1 | 22,963 | Small Business | Self Enquiry | Male | Married | Manager |
35 | 3 | 3 | 3 | 2 | 0 | 1 | 0 | 23,789 | Small Business | Company Invited | Fe Male | Unmarried | Senior Manager |
35 | 1 | 3 | 5 | 2 | 1 | 1 | 1 | 17,074 | Salaried | Self Enquiry | Female | Married | Executive |
34 | 1 | 3 | 3 | 2 | 0 | 0 | 1 | 22,086 | Small Business | Self Enquiry | Male | Married | Executive |
33 | 1 | 3 | 4 | 3 | 0 | 1 | 1 | 21,515 | Salaried | Self Enquiry | Female | Unmarried | Executive |
51 | 1 | 3 | 3 | 4 | 0 | 1 | 0 | 17,075 | Salaried | Self Enquiry | Male | Divorced | Executive |
29 | 3 | 2 | 5 | 2 | 0 | 1 | 1 | 16,091 | Large Business | Company Invited | Male | Single | Executive |
34 | 3 | 3 | 3 | 1 | 1 | 1 | 2 | 20,304 | Small Business | Company Invited | Male | Single | Manager |
38 | 1 | 2 | 3 | 6 | 0 | 0 | 1 | 32,342 | Small Business | Self Enquiry | Male | Single | Senior Manager |
46 | 1 | 3 | 5 | 1 | 0 | 0 | 0 | 24,396 | Small Business | Self Enquiry | Male | Married | Senior Manager |
54 | 2 | 2 | 4 | 3 | 0 | 1 | 0 | 25,725 | Small Business | Self Enquiry | Male | Divorced | Senior Manager |
56 | 1 | 2 | 3 | 1 | 0 | 0 | 0 | 26,103 | Small Business | Self Enquiry | Male | Married | AVP |
30 | 1 | 2 | 3 | 19 | 1 | 1 | 1 | 17,285 | Large Business | Company Invited | Male | Single | Executive |
26 | 1 | 3 | 5 | 1 | 0 | 1 | 2 | 17,867 | Small Business | Self Enquiry | Male | Single | Executive |
33 | 1 | 2 | 3 | 1 | 0 | 1 | 0 | 26,691 | Small Business | Self Enquiry | Male | Married | Senior Manager |
24 | 1 | 3 | 4 | 2 | 0 | 1 | 1 | 17,127 | Salaried | Self Enquiry | Male | Married | Executive |
30 | 1 | 4 | 3 | 2 | 0 | 1 | 3 | 25,062 | Salaried | Self Enquiry | Male | Married | Manager |
33 | 3 | 3 | 4 | 1 | 0 | 0 | 0 | 20,147 | Small Business | Company Invited | Female | Single | Manager |
53 | 3 | 2 | 4 | 3 | 0 | 1 | 0 | 22,525 | Small Business | Company Invited | Female | Married | Senior Manager |
29 | 3 | 3 | 5 | 2 | 0 | 1 | 2 | 23,576 | Salaried | Company Invited | Male | Unmarried | Manager |
39 | 1 | 2 | 5 | 2 | 0 | 1 | 0 | 20,151 | Small Business | Self Enquiry | Male | Married | Manager |
46 | 3 | 4 | 4 | 2 | 0 | 1 | 3 | 23,483 | Salaried | Self Enquiry | Male | Married | Manager |
35 | 1 | 3 | 4 | 2 | 0 | 1 | 1 | 30,672 | Salaried | Self Enquiry | Female | Single | Senior Manager |
35 | 3 | 4 | 3 | 8 | 0 | 0 | 1 | 20,909 | Small Business | Company Invited | Female | Married | Executive |
33 | 1 | 4 | 4 | 8 | 0 | 0 | 3 | 21,010 | Salaried | Company Invited | Female | Married | Executive |
29 | 1 | 2 | 3 | 2 | 0 | 1 | 0 | 21,623 | Salaried | Company Invited | Female | Unmarried | Executive |
41 | 3 | 2 | 3 | 1 | 0 | 0 | 1 | 21,230 | Salaried | Company Invited | Male | Single | Manager |
43 | 1 | 3 | 3 | 6 | 0 | 1 | 1 | 22,950 | Small Business | Self Enquiry | Male | Unmarried | Manager |
35 | 3 | 3 | 3 | 2 | 0 | 0 | 2 | 21,029 | Small Business | Company Invited | Female | Married | Executive |
41 | 3 | 3 | 3 | 4 | 1 | 0 | 0 | 28,591 | Salaried | Self Enquiry | Female | Single | Senior Manager |
33 | 1 | 2 | 3 | 1 | 0 | 0 | 0 | 21,949 | Salaried | Self Enquiry | Female | Unmarried | Manager |
40 | 1 | 2 | 3 | 1 | 0 | 0 | 0 | 28,499 | Small Business | Company Invited | Fe Male | Unmarried | Senior Manager |
26 | 1 | 3 | 5 | 1 | 0 | 0 | 1 | 18,102 | Large Business | Company Invited | Male | Single | Executive |
41 | 1 | 2 | 5 | 3 | 0 | 0 | 0 | 18,072 | Salaried | Self Enquiry | Male | Married | Manager |
37 | 1 | 2 | 3 | 2 | 1 | 0 | 1 | 27,185 | Salaried | Company Invited | Male | Married | Senior Manager |
31 | 3 | 2 | 3 | 4 | 0 | 1 | 1 | 17,329 | Salaried | Self Enquiry | Male | Married | Executive |
45 | 3 | 3 | 4 | 8 | 0 | 0 | 2 | 21,040 | Salaried | Self Enquiry | Male | Single | Manager |
33 | 1 | 3 | 5 | 2 | 1 | 1 | 2 | 18,348 | Salaried | Company Invited | Male | Single | Executive |
33 | 1 | 4 | 4 | 3 | 0 | 0 | 1 | 21,048 | Small Business | Self Enquiry | Female | Divorced | Executive |
33 | 1 | 3 | 3 | 3 | 1 | 0 | 2 | 21,388 | Salaried | Self Enquiry | Male | Unmarried | Manager |
30 | 3 | 2 | 3 | 1 | 0 | 1 | 0 | 21,577 | Large Business | Self Enquiry | Female | Unmarried | Manager |
42 | 1 | 2 | 3 | 7 | 1 | 1 | 1 | 17,759 | Small Business | Company Invited | Male | Married | Executive |
46 | 1 | 2 | 3 | 7 | 0 | 1 | 0 | 32,861 | Salaried | Self Enquiry | Male | Married | AVP |
51 | 1 | 4 | 3 | 6 | 0 | 1 | 3 | 21,058 | Salaried | Self Enquiry | Male | Married | Executive |
30 | 1 | 2 | 3 | 3 | 0 | 1 | 0 | 21,091 | Salaried | Self Enquiry | Female | Single | Manager |
37 | 1 | 3 | 3 | 6 | 0 | 0 | 1 | 22,366 | Salaried | Company Invited | Male | Divorced | Executive |
28 | 2 | 2 | 3 | 2 | 0 | 0 | 1 | 17,706 | Salaried | Company Invited | Male | Married | Executive |
42 | 1 | 2 | 5 | 1 | 0 | 1 | 0 | 28,348 | Small Business | Self Enquiry | Male | Married | Senior Manager |
44 | 1 | 2 | 4 | 1 | 0 | 1 | 0 | 20,933 | Small Business | Self Enquiry | Male | Single | Manager |
39 | 1 | 3 | 4 | 3 | 0 | 1 | 1 | 21,118 | Small Business | Company Invited | Female | Single | Executive |
42 | 1 | 2 | 5 | 4 | 1 | 0 | 0 | 21,545 | Salaried | Self Enquiry | Female | Unmarried | Manager |
39 | 1 | 2 | 5 | 2 | 1 | 1 | 1 | 25,880 | Small Business | Company Invited | Fe Male | Unmarried | Senior Manager |
28 | 1 | 2 | 3 | 1 | 0 | 1 | 0 | 21,674 | Salaried | Company Invited | Female | Divorced | Manager |
43 | 1 | 3 | 5 | 7 | 0 | 1 | 1 | 32,159 | Salaried | Self Enquiry | Male | Married | AVP |
45 | 1 | 4 | 3 | 3 | 0 | 0 | 2 | 26,656 | Small Business | Self Enquiry | Female | Divorced | Senior Manager |
53 | 1 | 4 | 5 | 5 | 1 | 1 | 2 | 24,255 | Large Business | Self Enquiry | Male | Married | Manager |
42 | 1 | 4 | 5 | 4 | 0 | 0 | 1 | 20,916 | Salaried | Self Enquiry | Male | Married | Executive |
36 | 1 | 3 | 3 | 7 | 0 | 1 | 0 | 20,237 | Small Business | Self Enquiry | Male | Divorced | Manager |
22 | 1 | 4 | 4 | 3 | 1 | 0 | 3 | 20,748 | Large Business | Self Enquiry | Female | Single | Executive |
37 | 1 | 4 | 4 | 2 | 0 | 0 | 3 | 24,592 | Salaried | Self Enquiry | Male | Unmarried | Manager |
30 | 3 | 3 | 4 | 7 | 0 | 0 | 2 | 24,443 | Large Business | Company Invited | Fe Male | Unmarried | Manager |
36 | 1 | 4 | 5 | 4 | 1 | 1 | 3 | 28,562 | Small Business | Company Invited | Male | Married | Senior Manager |
40 | 1 | 2 | 3 | 2 | 0 | 0 | 1 | 34,033 | Small Business | Self Enquiry | Female | Divorced | VP |
51 | 1 | 2 | 3 | 3 | 0 | 0 | 1 | 25,650 | Salaried | Company Invited | Male | Unmarried | Senior Manager |
39 | 3 | 3 | 5 | 6 | 0 | 0 | 2 | 21,536 | Salaried | Self Enquiry | Male | Unmarried | Executive |
43 | 1 | 2 | 4 | 2 | 0 | 0 | 1 | 29,336 | Salaried | Self Enquiry | Male | Married | AVP |
35 | 1 | 3 | 3 | 2 | 0 | 0 | 0 | 16,951 | Salaried | Self Enquiry | Male | Married | Executive |
40 | 1 | 4 | 3 | 2 | 0 | 1 | 2 | 29,616 | Large Business | Company Invited | Female | Single | Senior Manager |
27 | 3 | 3 | 3 | 3 | 0 | 0 | 1 | 23,362 | Small Business | Self Enquiry | Male | Unmarried | Manager |
26 | 1 | 2 | 5 | 7 | 1 | 1 | 0 | 17,042 | Salaried | Company Invited | Male | Divorced | Executive |
43 | 3 | 3 | 3 | 2 | 1 | 0 | 0 | 31,959 | Salaried | Company Invited | Male | Divorced | AVP |
32 | 1 | 4 | 5 | 3 | 1 | 0 | 3 | 25,511 | Small Business | Self Enquiry | Male | Divorced | Manager |
35 | 1 | 3 | 5 | 4 | 0 | 0 | 1 | 30,309 | Small Business | Self Enquiry | Female | Single | Senior Manager |
34 | 1 | 3 | 4 | 8 | 0 | 0 | 2 | 21,300 | Small Business | Self Enquiry | Female | Married | Executive |
31 | 1 | 2 | 4 | 2 | 0 | 0 | 1 | 16,261 | Salaried | Self Enquiry | Female | Single | Executive |
35 | 3 | 4 | 3 | 3 | 0 | 0 | 1 | 24,392 | Salaried | Self Enquiry | Female | Married | Manager |
42 | 3 | 3 | 3 | 2 | 0 | 1 | 2 | 24,829 | Salaried | Company Invited | Male | Married | AVP |
34 | 1 | 2 | 5 | 4 | 0 | 1 | 1 | 20,121 | Salaried | Self Enquiry | Female | Married | Manager |
34 | 1 | 3 | 5 | 2 | 0 | 1 | 1 | 21,385 | Salaried | Self Enquiry | Female | Divorced | Executive |
34 | 1 | 2 | 4 | 1 | 0 | 1 | 0 | 26,994 | Salaried | Self Enquiry | Fe Male | Unmarried | Senior Manager |
39 | 1 | 3 | 3 | 5 | 0 | 0 | 2 | 24,939 | Large Business | Self Enquiry | Male | Divorced | Manager |
29 | 1 | 3 | 3 | 3 | 1 | 0 | 1 | 22,119 | Large Business | Self Enquiry | Male | Unmarried | Executive |
35 | 1 | 2 | 3 | 3 | 0 | 0 | 1 | 20,762 | Small Business | Company Invited | Male | Married | Manager |
26 | 3 | 2 | 3 | 2 | 1 | 1 | 1 | 20,828 | Small Business | Self Enquiry | Male | Single | Manager |
37 | 1 | 3 | 3 | 7 | 0 | 1 | 1 | 21,513 | Salaried | Self Enquiry | Female | Married | Executive |
35 | 1 | 4 | 5 | 6 | 0 | 0 | 2 | 24,024 | Salaried | Company Invited | Male | Married | Manager |
40 | 1 | 3 | 3 | 2 | 0 | 1 | 1 | 30,847 | Salaried | Company Invited | Male | Married | AVP |
33 | 3 | 2 | 3 | 2 | 1 | 1 | 0 | 17,851 | Small Business | Self Enquiry | Female | Single | Executive |
38 | 3 | 3 | 4 | 1 | 0 | 0 | 0 | 17,899 | Small Business | Self Enquiry | Male | Divorced | Executive |
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