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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 1 new columns ({'Unnamed: 0'})

This happened while the csv dataset builder was generating data using

hf://datasets/absethi1894/Visit_with_Us/data/tourism.csv (at revision 0a90a3719c201d4a15a441d23950da0b473524c2)

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
              {'CustomerID': Value('int64'), 'ProdTaken': Value('int64'), 'Age': Value('float64'), 'TypeofContact': Value('string'), 'CityTier': Value('int64'), 'DurationOfPitch': Value('float64'), 'Occupation': Value('string'), 'Gender': Value('string'), 'NumberOfPersonVisiting': Value('int64'), 'NumberOfFollowups': Value('float64'), 'ProductPitched': Value('string'), 'PreferredPropertyStar': Value('float64'), 'MaritalStatus': Value('string'), 'NumberOfTrips': Value('float64'), 'Passport': Value('int64'), 'PitchSatisfactionScore': Value('int64'), 'OwnCar': Value('int64'), 'NumberOfChildrenVisiting': Value('float64'), 'Designation': Value('string'), 'MonthlyIncome': Value('float64')}
              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 1 new columns ({'Unnamed: 0'})
              
              This happened while the csv dataset builder was generating data using
              
              hf://datasets/absethi1894/Visit_with_Us/data/tourism.csv (at revision 0a90a3719c201d4a15a441d23950da0b473524c2)
              
              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.

CustomerID
int64
ProdTaken
int64
Age
float64
TypeofContact
string
CityTier
int64
DurationOfPitch
float64
Occupation
string
Gender
string
NumberOfPersonVisiting
int64
NumberOfFollowups
float64
ProductPitched
string
PreferredPropertyStar
float64
MaritalStatus
string
NumberOfTrips
float64
Passport
int64
PitchSatisfactionScore
int64
OwnCar
int64
NumberOfChildrenVisiting
float64
Designation
string
MonthlyIncome
float64
201,214
0
44
Self Enquiry
1
8
Salaried
Female
3
1
Standard
3
Married
2
1
4
1
0
Senior Manager
22,879
203,829
0
35
Self Enquiry
3
20
Small Business
Male
3
4
Standard
3
Married
3
0
1
1
2
Senior Manager
27,306
202,622
0
47
Self Enquiry
3
7
Small Business
Female
4
4
Standard
5
Married
3
0
2
1
2
Senior Manager
29,131
201,543
0
32
Self Enquiry
1
6
Salaried
Male
3
3
Deluxe
4
Married
2
0
3
1
0
Manager
21,220
203,144
1
59
Self Enquiry
1
9
Large Business
Male
3
4
Basic
3
Single
6
0
2
1
2
Executive
21,157
200,907
0
44
Self Enquiry
3
11
Small Business
Male
2
3
King
4
Divorced
1
0
5
1
1
VP
33,213
201,426
0
32
Self Enquiry
1
35
Salaried
Female
2
4
Basic
4
Single
2
0
3
1
0
Executive
17,837
204,269
0
27
Self Enquiry
3
7
Salaried
Male
3
4
Deluxe
3
Married
3
0
5
0
2
Manager
23,974
200,261
0
38
Company Invited
3
8
Salaried
Male
2
4
Deluxe
3
Divorced
4
0
5
1
1
Manager
20,249
204,223
0
32
Self Enquiry
1
12
Large Business
Male
3
4
Basic
3
Married
2
1
4
1
1
Executive
23,499
200,243
0
40
Self Enquiry
1
30
Large Business
Male
3
3
Deluxe
3
Married
2
0
3
1
1
Manager
18,319
203,533
0
38
Self Enquiry
1
20
Small Business
Male
3
4
Deluxe
3
Married
3
0
1
0
1
Manager
22,963
200,228
0
35
Company Invited
3
6
Small Business
Fe Male
3
3
Standard
3
Unmarried
2
0
5
1
0
Senior Manager
23,789
201,110
1
35
Self Enquiry
1
8
Salaried
Female
3
3
Basic
5
Married
2
1
1
1
1
Executive
17,074
204,350
1
34
Self Enquiry
1
17
Small Business
Male
3
6
Basic
3
Married
2
0
5
0
1
Executive
22,086
203,870
0
33
Self Enquiry
1
36
Salaried
Female
3
5
Basic
4
Unmarried
3
0
3
1
1
Executive
21,515
200,087
0
51
Self Enquiry
1
15
Salaried
Male
3
3
Basic
3
Divorced
4
0
3
1
0
Executive
17,075
201,365
1
29
Company Invited
3
30
Large Business
Male
2
1
Basic
5
Single
2
0
3
1
1
Executive
16,091
200,378
1
34
Company Invited
3
25
Small Business
Male
3
2
Deluxe
3
Single
1
1
2
1
2
Manager
20,304
202,522
0
38
Self Enquiry
1
14
Small Business
Male
2
4
Standard
3
Single
6
0
2
0
1
Senior Manager
32,342
200,209
0
46
Self Enquiry
1
6
Small Business
Male
3
3
Standard
5
Married
1
0
2
0
0
Senior Manager
24,396
200,510
0
54
Self Enquiry
2
25
Small Business
Male
2
3
Standard
4
Divorced
3
0
3
1
0
Senior Manager
25,725
202,022
0
56
Self Enquiry
1
15
Small Business
Male
2
3
Super Deluxe
3
Married
1
0
4
0
0
AVP
26,103
200,385
1
30
Company Invited
1
10
Large Business
Male
2
3
Basic
3
Single
19
1
4
1
1
Executive
17,285
201,386
0
26
Self Enquiry
1
6
Small Business
Male
3
3
Basic
5
Single
1
0
5
1
2
Executive
17,867
202,060
0
33
Self Enquiry
1
13
Small Business
Male
2
3
Standard
3
Married
1
0
4
1
0
Senior Manager
26,691
201,946
0
24
Self Enquiry
1
23
Salaried
Male
3
4
Basic
4
Married
2
0
3
1
1
Executive
17,127
203,768
0
30
Self Enquiry
1
36
Salaried
Male
4
6
Deluxe
3
Married
2
0
5
1
3
Manager
25,062
201,253
0
33
Company Invited
3
8
Small Business
Female
3
3
Deluxe
4
Single
1
0
1
0
0
Manager
20,147
202,230
0
53
Company Invited
3
8
Small Business
Female
2
4
Standard
4
Married
3
0
1
1
0
Senior Manager
22,525
203,514
0
29
Company Invited
3
14
Salaried
Male
3
4
Deluxe
5
Unmarried
2
0
3
1
2
Manager
23,576
201,372
0
39
Self Enquiry
1
15
Small Business
Male
2
3
Deluxe
5
Married
2
0
4
1
0
Manager
20,151
204,366
0
46
Self Enquiry
3
9
Salaried
Male
4
4
Deluxe
4
Married
2
0
5
1
3
Manager
23,483
202,466
0
35
Self Enquiry
1
14
Salaried
Female
3
4
Standard
4
Single
2
0
3
1
1
Senior Manager
30,672
204,073
0
35
Company Invited
3
9
Small Business
Female
4
4
Basic
3
Married
8
0
5
0
1
Executive
20,909
204,596
0
33
Company Invited
1
7
Salaried
Female
4
5
Basic
4
Married
8
0
3
0
3
Executive
21,010
202,373
1
29
Company Invited
1
16
Salaried
Female
2
4
Basic
3
Unmarried
2
0
4
1
0
Executive
21,623
201,916
0
41
Company Invited
3
16
Salaried
Male
2
3
Deluxe
3
Single
1
0
1
0
1
Manager
21,230
203,268
0
43
Self Enquiry
1
36
Small Business
Male
3
6
Deluxe
3
Unmarried
6
0
3
1
1
Manager
22,950
204,329
1
35
Company Invited
3
13
Small Business
Female
3
6
Basic
3
Married
2
0
4
0
2
Executive
21,029
201,685
0
41
Self Enquiry
3
12
Salaried
Female
3
3
Standard
3
Single
4
1
1
0
0
Senior Manager
28,591
200,694
0
33
Self Enquiry
1
6
Salaried
Female
2
4
Deluxe
3
Unmarried
1
0
4
0
0
Manager
21,949
200,837
0
40
Company Invited
1
15
Small Business
Fe Male
2
3
Standard
3
Unmarried
1
0
4
0
0
Senior Manager
28,499
201,852
1
26
Company Invited
1
9
Large Business
Male
3
3
Basic
5
Single
1
0
3
0
1
Executive
18,102
201,712
0
41
Self Enquiry
1
25
Salaried
Male
2
3
Deluxe
5
Married
3
0
1
0
0
Manager
18,072
200,222
0
37
Company Invited
1
17
Salaried
Male
2
3
Standard
3
Married
2
1
3
0
1
Senior Manager
27,185
202,145
0
31
Self Enquiry
3
13
Salaried
Male
2
4
Basic
3
Married
4
0
4
1
1
Executive
17,329
204,867
1
45
Self Enquiry
3
8
Salaried
Male
3
6
Deluxe
4
Single
8
0
3
0
2
Manager
21,040
200,514
1
33
Company Invited
1
9
Salaried
Male
3
3
Basic
5
Single
2
1
5
1
2
Executive
18,348
202,795
0
33
Self Enquiry
1
9
Small Business
Female
4
4
Basic
4
Divorced
3
0
4
0
1
Executive
21,048
201,074
0
33
Self Enquiry
1
14
Salaried
Male
3
3
Deluxe
3
Unmarried
3
1
3
0
2
Manager
21,388
200,402
0
30
Self Enquiry
3
18
Large Business
Female
2
3
Deluxe
3
Unmarried
1
0
2
1
0
Manager
21,577
200,547
1
42
Company Invited
1
25
Small Business
Male
2
2
Basic
3
Married
7
1
3
1
1
Executive
17,759
201,899
0
46
Self Enquiry
1
8
Salaried
Male
2
3
Super Deluxe
3
Married
7
0
5
1
0
AVP
32,861
204,656
0
51
Self Enquiry
1
16
Salaried
Male
4
4
Basic
3
Married
6
0
5
1
3
Executive
21,058
201,880
0
30
Self Enquiry
1
8
Salaried
Female
2
5
Deluxe
3
Single
3
0
1
1
0
Manager
21,091
202,742
0
37
Company Invited
1
25
Salaried
Male
3
3
Basic
3
Divorced
6
0
5
0
1
Executive
22,366
201,323
0
28
Company Invited
2
6
Salaried
Male
2
3
Basic
3
Married
2
0
4
0
1
Executive
17,706
201,357
0
42
Self Enquiry
1
12
Small Business
Male
2
3
Standard
5
Married
1
0
3
1
0
Senior Manager
28,348
200,617
0
44
Self Enquiry
1
10
Small Business
Male
2
3
Deluxe
4
Single
1
0
2
1
0
Manager
20,933
203,637
0
39
Company Invited
1
9
Small Business
Female
3
5
Basic
4
Single
3
0
1
1
1
Executive
21,118
200,253
0
42
Self Enquiry
1
23
Salaried
Female
2
2
Deluxe
5
Unmarried
4
1
2
0
0
Manager
21,545
202,223
0
39
Company Invited
1
28
Small Business
Fe Male
2
3
Standard
5
Unmarried
2
1
5
1
1
Senior Manager
25,880
200,944
0
28
Company Invited
1
6
Salaried
Female
2
5
Deluxe
3
Divorced
1
0
3
1
0
Manager
21,674
202,079
0
43
Self Enquiry
1
20
Salaried
Male
3
3
Super Deluxe
5
Married
7
0
5
1
1
AVP
32,159
203,372
1
45
Self Enquiry
1
22
Small Business
Female
4
4
Standard
3
Divorced
3
0
3
0
2
Senior Manager
26,656
204,382
0
53
Self Enquiry
1
13
Large Business
Male
4
4
Deluxe
5
Married
5
1
4
1
2
Manager
24,255
204,062
0
42
Self Enquiry
1
16
Salaried
Male
4
4
Basic
5
Married
4
0
1
0
1
Executive
20,916
200,009
0
36
Self Enquiry
1
33
Small Business
Male
3
3
Deluxe
3
Divorced
7
0
3
1
0
Manager
20,237
203,259
0
22
Self Enquiry
1
7
Large Business
Female
4
5
Basic
4
Single
3
1
5
0
3
Executive
20,748
202,664
0
37
Self Enquiry
1
12
Salaried
Male
4
4
Deluxe
4
Unmarried
2
0
2
0
3
Manager
24,592
203,501
1
30
Company Invited
3
20
Large Business
Fe Male
3
4
Deluxe
4
Unmarried
7
0
3
0
2
Manager
24,443
203,967
0
36
Company Invited
1
18
Small Business
Male
4
5
Standard
5
Married
4
1
5
1
3
Senior Manager
28,562
200,186
0
40
Self Enquiry
1
10
Small Business
Female
2
3
King
3
Divorced
2
0
5
0
1
VP
34,033
200,136
1
51
Company Invited
1
14
Salaried
Male
2
5
Standard
3
Unmarried
3
0
2
0
1
Senior Manager
25,650
203,835
0
39
Self Enquiry
3
7
Salaried
Male
3
5
Basic
5
Unmarried
6
0
3
0
2
Executive
21,536
200,390
0
43
Self Enquiry
1
18
Salaried
Male
2
4
Super Deluxe
4
Married
2
0
3
0
1
AVP
29,336
200,040
0
35
Self Enquiry
1
10
Salaried
Male
3
3
Basic
3
Married
2
0
4
0
0
Executive
16,951
202,695
0
40
Company Invited
1
9
Large Business
Female
4
4
Standard
3
Single
2
0
2
1
2
Senior Manager
29,616
203,753
0
27
Self Enquiry
3
17
Small Business
Male
3
4
Deluxe
3
Unmarried
3
0
1
0
1
Manager
23,362
200,762
1
26
Company Invited
1
8
Salaried
Male
2
3
Basic
5
Divorced
7
1
5
1
0
Executive
17,042
200,119
0
43
Company Invited
3
32
Salaried
Male
3
3
Super Deluxe
3
Divorced
2
1
2
0
0
AVP
31,959
203,339
0
32
Self Enquiry
1
18
Small Business
Male
4
4
Deluxe
5
Divorced
3
1
2
0
3
Manager
25,511
202,560
0
35
Self Enquiry
1
12
Small Business
Female
3
5
Standard
5
Single
4
0
2
0
1
Senior Manager
30,309
204,135
0
34
Self Enquiry
1
11
Small Business
Female
3
5
Basic
4
Married
8
0
4
0
2
Executive
21,300
201,016
1
31
Self Enquiry
1
14
Salaried
Female
2
4
Basic
4
Single
2
0
4
0
1
Executive
16,261
204,748
0
35
Self Enquiry
3
16
Salaried
Female
4
4
Deluxe
3
Married
3
0
1
0
1
Manager
24,392
204,865
1
42
Company Invited
3
16
Salaried
Male
3
6
Super Deluxe
3
Married
2
0
5
1
2
AVP
24,829
202,030
0
34
Self Enquiry
1
14
Salaried
Female
2
3
Deluxe
5
Married
4
0
5
1
1
Manager
20,121
202,680
1
34
Self Enquiry
1
9
Salaried
Female
3
4
Basic
5
Divorced
2
0
3
1
1
Executive
21,385
200,022
0
34
Self Enquiry
1
13
Salaried
Fe Male
2
3
Standard
4
Unmarried
1
0
3
1
0
Senior Manager
26,994
202,643
0
39
Self Enquiry
1
36
Large Business
Male
3
4
Deluxe
3
Divorced
5
0
2
0
2
Manager
24,939
203,965
1
29
Self Enquiry
1
12
Large Business
Male
3
4
Basic
3
Unmarried
3
1
1
0
1
Executive
22,119
201,288
0
35
Company Invited
1
8
Small Business
Male
2
3
Deluxe
3
Married
3
0
3
0
1
Manager
20,762
200,293
1
26
Self Enquiry
3
10
Small Business
Male
2
4
Deluxe
3
Single
2
1
2
1
1
Manager
20,828
202,562
0
37
Self Enquiry
1
10
Salaried
Female
3
4
Basic
3
Married
7
0
2
1
1
Executive
21,513
203,734
1
35
Company Invited
1
16
Salaried
Male
4
4
Deluxe
5
Married
6
0
3
0
2
Manager
24,024
204,727
1
40
Company Invited
1
9
Salaried
Male
3
4
Super Deluxe
3
Married
2
0
3
1
1
AVP
30,847
200,363
1
33
Self Enquiry
3
11
Small Business
Female
2
3
Basic
3
Single
2
1
2
1
0
Executive
17,851
200,642
0
38
Self Enquiry
3
15
Small Business
Male
3
4
Basic
4
Divorced
1
0
4
0
0
Executive
17,899
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