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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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