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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 ({'ProdTaken'})

This happened while the csv dataset builder was generating data using

hf://datasets/pavanipriyanka/tourism-project/tourism.csv (at revision cd6c6db7cbd6dac075f0ed0ddaa24abcda701cc8)

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 "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1831, in _prepare_split_single
                  writer.write_table(table)
                File "/usr/local/lib/python3.12/site-packages/datasets/arrow_writer.py", line 714, in write_table
                  pa_table = table_cast(pa_table, self._schema)
                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2272, in table_cast
                  return cast_table_to_schema(table, schema)
                         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/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
              {'Unnamed: 0': Value('int64'), 'CustomerID': 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 1339, 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 972, in convert_to_parquet
                  builder.download_and_prepare(
                File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 894, in download_and_prepare
                  self._download_and_prepare(
                File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 970, in _download_and_prepare
                  self._prepare_split(split_generator, **prepare_split_kwargs)
                File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1702, in _prepare_split
                  for job_id, done, content in self._prepare_split_single(
                                               ^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/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 ({'ProdTaken'})
              
              This happened while the csv dataset builder was generating data using
              
              hf://datasets/pavanipriyanka/tourism-project/tourism.csv (at revision cd6c6db7cbd6dac075f0ed0ddaa24abcda701cc8)
              
              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.

Unnamed: 0
int64
CustomerID
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
1,214
201,214
44
Self Enquiry
1
8
Salaried
Female
3
1
Standard
3
Married
2
1
4
1
0
Senior Manager
22,879
3,829
203,829
35
Self Enquiry
3
20
Small Business
Male
3
4
Standard
3
Married
3
0
1
1
2
Senior Manager
27,306
2,622
202,622
47
Self Enquiry
3
7
Small Business
Female
4
4
Standard
5
Married
3
0
2
1
2
Senior Manager
29,131
1,543
201,543
32
Self Enquiry
1
6
Salaried
Male
3
3
Deluxe
4
Married
2
0
3
1
0
Manager
21,220
3,144
203,144
59
Self Enquiry
1
9
Large Business
Male
3
4
Basic
3
Single
6
0
2
1
2
Executive
21,157
907
200,907
44
Self Enquiry
3
11
Small Business
Male
2
3
King
4
Divorced
1
0
5
1
1
VP
33,213
1,426
201,426
32
Self Enquiry
1
35
Salaried
Female
2
4
Basic
4
Single
2
0
3
1
0
Executive
17,837
4,269
204,269
27
Self Enquiry
3
7
Salaried
Male
3
4
Deluxe
3
Married
3
0
5
0
2
Manager
23,974
261
200,261
38
Company Invited
3
8
Salaried
Male
2
4
Deluxe
3
Divorced
4
0
5
1
1
Manager
20,249
4,223
204,223
32
Self Enquiry
1
12
Large Business
Male
3
4
Basic
3
Married
2
1
4
1
1
Executive
23,499
243
200,243
40
Self Enquiry
1
30
Large Business
Male
3
3
Deluxe
3
Married
2
0
3
1
1
Manager
18,319
3,533
203,533
38
Self Enquiry
1
20
Small Business
Male
3
4
Deluxe
3
Married
3
0
1
0
1
Manager
22,963
228
200,228
35
Company Invited
3
6
Small Business
Fe Male
3
3
Standard
3
Unmarried
2
0
5
1
0
Senior Manager
23,789
1,110
201,110
35
Self Enquiry
1
8
Salaried
Female
3
3
Basic
5
Married
2
1
1
1
1
Executive
17,074
4,350
204,350
34
Self Enquiry
1
17
Small Business
Male
3
6
Basic
3
Married
2
0
5
0
1
Executive
22,086
3,870
203,870
33
Self Enquiry
1
36
Salaried
Female
3
5
Basic
4
Unmarried
3
0
3
1
1
Executive
21,515
87
200,087
51
Self Enquiry
1
15
Salaried
Male
3
3
Basic
3
Divorced
4
0
3
1
0
Executive
17,075
1,365
201,365
29
Company Invited
3
30
Large Business
Male
2
1
Basic
5
Single
2
0
3
1
1
Executive
16,091
378
200,378
34
Company Invited
3
25
Small Business
Male
3
2
Deluxe
3
Single
1
1
2
1
2
Manager
20,304
2,522
202,522
38
Self Enquiry
1
14
Small Business
Male
2
4
Standard
3
Single
6
0
2
0
1
Senior Manager
32,342
209
200,209
46
Self Enquiry
1
6
Small Business
Male
3
3
Standard
5
Married
1
0
2
0
0
Senior Manager
24,396
510
200,510
54
Self Enquiry
2
25
Small Business
Male
2
3
Standard
4
Divorced
3
0
3
1
0
Senior Manager
25,725
2,022
202,022
56
Self Enquiry
1
15
Small Business
Male
2
3
Super Deluxe
3
Married
1
0
4
0
0
AVP
26,103
385
200,385
30
Company Invited
1
10
Large Business
Male
2
3
Basic
3
Single
19
1
4
1
1
Executive
17,285
1,386
201,386
26
Self Enquiry
1
6
Small Business
Male
3
3
Basic
5
Single
1
0
5
1
2
Executive
17,867
2,060
202,060
33
Self Enquiry
1
13
Small Business
Male
2
3
Standard
3
Married
1
0
4
1
0
Senior Manager
26,691
1,946
201,946
24
Self Enquiry
1
23
Salaried
Male
3
4
Basic
4
Married
2
0
3
1
1
Executive
17,127
3,768
203,768
30
Self Enquiry
1
36
Salaried
Male
4
6
Deluxe
3
Married
2
0
5
1
3
Manager
25,062
1,253
201,253
33
Company Invited
3
8
Small Business
Female
3
3
Deluxe
4
Single
1
0
1
0
0
Manager
20,147
2,230
202,230
53
Company Invited
3
8
Small Business
Female
2
4
Standard
4
Married
3
0
1
1
0
Senior Manager
22,525
3,514
203,514
29
Company Invited
3
14
Salaried
Male
3
4
Deluxe
5
Unmarried
2
0
3
1
2
Manager
23,576
1,372
201,372
39
Self Enquiry
1
15
Small Business
Male
2
3
Deluxe
5
Married
2
0
4
1
0
Manager
20,151
4,366
204,366
46
Self Enquiry
3
9
Salaried
Male
4
4
Deluxe
4
Married
2
0
5
1
3
Manager
23,483
2,466
202,466
35
Self Enquiry
1
14
Salaried
Female
3
4
Standard
4
Single
2
0
3
1
1
Senior Manager
30,672
4,073
204,073
35
Company Invited
3
9
Small Business
Female
4
4
Basic
3
Married
8
0
5
0
1
Executive
20,909
4,596
204,596
33
Company Invited
1
7
Salaried
Female
4
5
Basic
4
Married
8
0
3
0
3
Executive
21,010
2,373
202,373
29
Company Invited
1
16
Salaried
Female
2
4
Basic
3
Unmarried
2
0
4
1
0
Executive
21,623
1,916
201,916
41
Company Invited
3
16
Salaried
Male
2
3
Deluxe
3
Single
1
0
1
0
1
Manager
21,230
3,268
203,268
43
Self Enquiry
1
36
Small Business
Male
3
6
Deluxe
3
Unmarried
6
0
3
1
1
Manager
22,950
4,329
204,329
35
Company Invited
3
13
Small Business
Female
3
6
Basic
3
Married
2
0
4
0
2
Executive
21,029
1,685
201,685
41
Self Enquiry
3
12
Salaried
Female
3
3
Standard
3
Single
4
1
1
0
0
Senior Manager
28,591
694
200,694
33
Self Enquiry
1
6
Salaried
Female
2
4
Deluxe
3
Unmarried
1
0
4
0
0
Manager
21,949
837
200,837
40
Company Invited
1
15
Small Business
Fe Male
2
3
Standard
3
Unmarried
1
0
4
0
0
Senior Manager
28,499
1,852
201,852
26
Company Invited
1
9
Large Business
Male
3
3
Basic
5
Single
1
0
3
0
1
Executive
18,102
1,712
201,712
41
Self Enquiry
1
25
Salaried
Male
2
3
Deluxe
5
Married
3
0
1
0
0
Manager
18,072
222
200,222
37
Company Invited
1
17
Salaried
Male
2
3
Standard
3
Married
2
1
3
0
1
Senior Manager
27,185
2,145
202,145
31
Self Enquiry
3
13
Salaried
Male
2
4
Basic
3
Married
4
0
4
1
1
Executive
17,329
4,867
204,867
45
Self Enquiry
3
8
Salaried
Male
3
6
Deluxe
4
Single
8
0
3
0
2
Manager
21,040
514
200,514
33
Company Invited
1
9
Salaried
Male
3
3
Basic
5
Single
2
1
5
1
2
Executive
18,348
2,795
202,795
33
Self Enquiry
1
9
Small Business
Female
4
4
Basic
4
Divorced
3
0
4
0
1
Executive
21,048
1,074
201,074
33
Self Enquiry
1
14
Salaried
Male
3
3
Deluxe
3
Unmarried
3
1
3
0
2
Manager
21,388
402
200,402
30
Self Enquiry
3
18
Large Business
Female
2
3
Deluxe
3
Unmarried
1
0
2
1
0
Manager
21,577
547
200,547
42
Company Invited
1
25
Small Business
Male
2
2
Basic
3
Married
7
1
3
1
1
Executive
17,759
1,899
201,899
46
Self Enquiry
1
8
Salaried
Male
2
3
Super Deluxe
3
Married
7
0
5
1
0
AVP
32,861
4,656
204,656
51
Self Enquiry
1
16
Salaried
Male
4
4
Basic
3
Married
6
0
5
1
3
Executive
21,058
1,880
201,880
30
Self Enquiry
1
8
Salaried
Female
2
5
Deluxe
3
Single
3
0
1
1
0
Manager
21,091
2,742
202,742
37
Company Invited
1
25
Salaried
Male
3
3
Basic
3
Divorced
6
0
5
0
1
Executive
22,366
1,323
201,323
28
Company Invited
2
6
Salaried
Male
2
3
Basic
3
Married
2
0
4
0
1
Executive
17,706
1,357
201,357
42
Self Enquiry
1
12
Small Business
Male
2
3
Standard
5
Married
1
0
3
1
0
Senior Manager
28,348
617
200,617
44
Self Enquiry
1
10
Small Business
Male
2
3
Deluxe
4
Single
1
0
2
1
0
Manager
20,933
3,637
203,637
39
Company Invited
1
9
Small Business
Female
3
5
Basic
4
Single
3
0
1
1
1
Executive
21,118
253
200,253
42
Self Enquiry
1
23
Salaried
Female
2
2
Deluxe
5
Unmarried
4
1
2
0
0
Manager
21,545
2,223
202,223
39
Company Invited
1
28
Small Business
Fe Male
2
3
Standard
5
Unmarried
2
1
5
1
1
Senior Manager
25,880
944
200,944
28
Company Invited
1
6
Salaried
Female
2
5
Deluxe
3
Divorced
1
0
3
1
0
Manager
21,674
2,079
202,079
43
Self Enquiry
1
20
Salaried
Male
3
3
Super Deluxe
5
Married
7
0
5
1
1
AVP
32,159
3,372
203,372
45
Self Enquiry
1
22
Small Business
Female
4
4
Standard
3
Divorced
3
0
3
0
2
Senior Manager
26,656
4,382
204,382
53
Self Enquiry
1
13
Large Business
Male
4
4
Deluxe
5
Married
5
1
4
1
2
Manager
24,255
4,062
204,062
42
Self Enquiry
1
16
Salaried
Male
4
4
Basic
5
Married
4
0
1
0
1
Executive
20,916
9
200,009
36
Self Enquiry
1
33
Small Business
Male
3
3
Deluxe
3
Divorced
7
0
3
1
0
Manager
20,237
3,259
203,259
22
Self Enquiry
1
7
Large Business
Female
4
5
Basic
4
Single
3
1
5
0
3
Executive
20,748
2,664
202,664
37
Self Enquiry
1
12
Salaried
Male
4
4
Deluxe
4
Unmarried
2
0
2
0
3
Manager
24,592
3,501
203,501
30
Company Invited
3
20
Large Business
Fe Male
3
4
Deluxe
4
Unmarried
7
0
3
0
2
Manager
24,443
3,967
203,967
36
Company Invited
1
18
Small Business
Male
4
5
Standard
5
Married
4
1
5
1
3
Senior Manager
28,562
186
200,186
40
Self Enquiry
1
10
Small Business
Female
2
3
King
3
Divorced
2
0
5
0
1
VP
34,033
136
200,136
51
Company Invited
1
14
Salaried
Male
2
5
Standard
3
Unmarried
3
0
2
0
1
Senior Manager
25,650
3,835
203,835
39
Self Enquiry
3
7
Salaried
Male
3
5
Basic
5
Unmarried
6
0
3
0
2
Executive
21,536
390
200,390
43
Self Enquiry
1
18
Salaried
Male
2
4
Super Deluxe
4
Married
2
0
3
0
1
AVP
29,336
40
200,040
35
Self Enquiry
1
10
Salaried
Male
3
3
Basic
3
Married
2
0
4
0
0
Executive
16,951
2,695
202,695
40
Company Invited
1
9
Large Business
Female
4
4
Standard
3
Single
2
0
2
1
2
Senior Manager
29,616
3,753
203,753
27
Self Enquiry
3
17
Small Business
Male
3
4
Deluxe
3
Unmarried
3
0
1
0
1
Manager
23,362
762
200,762
26
Company Invited
1
8
Salaried
Male
2
3
Basic
5
Divorced
7
1
5
1
0
Executive
17,042
119
200,119
43
Company Invited
3
32
Salaried
Male
3
3
Super Deluxe
3
Divorced
2
1
2
0
0
AVP
31,959
3,339
203,339
32
Self Enquiry
1
18
Small Business
Male
4
4
Deluxe
5
Divorced
3
1
2
0
3
Manager
25,511
2,560
202,560
35
Self Enquiry
1
12
Small Business
Female
3
5
Standard
5
Single
4
0
2
0
1
Senior Manager
30,309
4,135
204,135
34
Self Enquiry
1
11
Small Business
Female
3
5
Basic
4
Married
8
0
4
0
2
Executive
21,300
1,016
201,016
31
Self Enquiry
1
14
Salaried
Female
2
4
Basic
4
Single
2
0
4
0
1
Executive
16,261
4,748
204,748
35
Self Enquiry
3
16
Salaried
Female
4
4
Deluxe
3
Married
3
0
1
0
1
Manager
24,392
4,865
204,865
42
Company Invited
3
16
Salaried
Male
3
6
Super Deluxe
3
Married
2
0
5
1
2
AVP
24,829
2,030
202,030
34
Self Enquiry
1
14
Salaried
Female
2
3
Deluxe
5
Married
4
0
5
1
1
Manager
20,121
2,680
202,680
34
Self Enquiry
1
9
Salaried
Female
3
4
Basic
5
Divorced
2
0
3
1
1
Executive
21,385
22
200,022
34
Self Enquiry
1
13
Salaried
Fe Male
2
3
Standard
4
Unmarried
1
0
3
1
0
Senior Manager
26,994
2,643
202,643
39
Self Enquiry
1
36
Large Business
Male
3
4
Deluxe
3
Divorced
5
0
2
0
2
Manager
24,939
3,965
203,965
29
Self Enquiry
1
12
Large Business
Male
3
4
Basic
3
Unmarried
3
1
1
0
1
Executive
22,119
1,288
201,288
35
Company Invited
1
8
Small Business
Male
2
3
Deluxe
3
Married
3
0
3
0
1
Manager
20,762
293
200,293
26
Self Enquiry
3
10
Small Business
Male
2
4
Deluxe
3
Single
2
1
2
1
1
Manager
20,828
2,562
202,562
37
Self Enquiry
1
10
Salaried
Female
3
4
Basic
3
Married
7
0
2
1
1
Executive
21,513
3,734
203,734
35
Company Invited
1
16
Salaried
Male
4
4
Deluxe
5
Married
6
0
3
0
2
Manager
24,024
4,727
204,727
40
Company Invited
1
9
Salaried
Male
3
4
Super Deluxe
3
Married
2
0
3
1
1
AVP
30,847
363
200,363
33
Self Enquiry
3
11
Small Business
Female
2
3
Basic
3
Single
2
1
2
1
0
Executive
17,851
642
200,642
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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