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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/praneeth232/tourism/tourism.csv (at revision 00e1be0d7d099a286669920e1bde867960899ed4)

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'), 'DurationOfPitch': Value('float64'), 'NumberOfPersonVisiting': Value('int64'), 'NumberOfFollowups': Value('float64'), 'PreferredPropertyStar': Value('float64'), 'NumberOfTrips': Value('float64'), 'PitchSatisfactionScore': Value('int64'), 'NumberOfChildrenVisiting': Value('float64'), 'MonthlyIncome': Value('float64'), 'Passport': Value('int64'), 'OwnCar': 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/praneeth232/tourism/tourism.csv (at revision 00e1be0d7d099a286669920e1bde867960899ed4)
              
              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
DurationOfPitch
float64
NumberOfPersonVisiting
int64
NumberOfFollowups
float64
PreferredPropertyStar
float64
NumberOfTrips
float64
PitchSatisfactionScore
int64
NumberOfChildrenVisiting
float64
MonthlyIncome
float64
Passport
int64
OwnCar
int64
TypeofContact
string
Occupation
string
Gender
string
ProductPitched
string
MaritalStatus
string
Designation
string
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27,306
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1
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47
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29,131
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Married
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Basic
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Executive
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11
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33,213
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King
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VP
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1
35
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4
2
3
0
17,837
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1
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Basic
Single
Executive
27
3
7
3
4
3
3
5
2
23,974
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0
Self Enquiry
Salaried
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Deluxe
Married
Manager
38
3
8
2
4
3
4
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1
20,249
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1
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Salaried
Male
Deluxe
Divorced
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1
12
3
4
3
2
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1
23,499
1
1
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Basic
Married
Executive
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30
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3
3
2
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1
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Large Business
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Deluxe
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38
1
20
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3
3
1
1
22,963
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Small Business
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Deluxe
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Manager
35
3
6
3
3
3
2
5
0
23,789
0
1
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Small Business
Fe Male
Standard
Unmarried
Senior Manager
35
1
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3
3
5
2
1
1
17,074
1
1
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Basic
Married
Executive
34
1
17
3
6
3
2
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1
22,086
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Executive
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1
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1
15
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3
3
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3
0
17,075
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30
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1
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2
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1
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Executive
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25
3
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3
1
2
2
20,304
1
1
Company Invited
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Deluxe
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Manager
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3
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Standard
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Senior Manager
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1
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Small Business
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Standard
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Senior Manager
54
2
25
2
3
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3
3
0
25,725
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1
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Small Business
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Standard
Divorced
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56
1
15
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1
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0
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Super Deluxe
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10
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3
19
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1
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3
5
1
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17,867
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1
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Executive
33
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13
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1
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0
26,691
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1
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Small Business
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Standard
Married
Senior Manager
24
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23
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1
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Basic
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Executive
30
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36
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3
25,062
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Deluxe
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1
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Super Deluxe
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45
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22
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Super Deluxe
Married
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Basic
Married
Executive
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Deluxe
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Salaried
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Basic
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Executive
43
3
32
3
3
3
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2
0
31,959
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Salaried
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Super Deluxe
Divorced
AVP
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4
4
5
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3
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Self Enquiry
Small Business
Male
Deluxe
Divorced
Manager
35
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5
5
4
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30,309
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Self Enquiry
Small Business
Female
Standard
Single
Senior Manager
34
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11
3
5
4
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4
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Small Business
Female
Basic
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Basic
Single
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Deluxe
Married
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Salaried
Female
Deluxe
Married
Manager
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Salaried
Female
Basic
Divorced
Executive
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1
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Unmarried
Senior Manager
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36
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Large Business
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Deluxe
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1
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Self Enquiry
Large Business
Male
Basic
Unmarried
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3
3
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1
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Company Invited
Small Business
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Deluxe
Married
Manager
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10
2
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3
2
2
1
20,828
1
1
Self Enquiry
Small Business
Male
Deluxe
Single
Manager
37
1
10
3
4
3
7
2
1
21,513
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1
Self Enquiry
Salaried
Female
Basic
Married
Executive
35
1
16
4
4
5
6
3
2
24,024
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Company Invited
Salaried
Male
Deluxe
Married
Manager
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1
9
3
4
3
2
3
1
30,847
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1
Company Invited
Salaried
Male
Super Deluxe
Married
AVP
33
3
11
2
3
3
2
2
0
17,851
1
1
Self Enquiry
Small Business
Female
Basic
Single
Executive
38
3
15
3
4
4
1
4
0
17,899
0
0
Self Enquiry
Small Business
Male
Basic
Divorced
Executive
End of preview.