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rajoria007
/
tourpkgprediction

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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/rajoria007/tourpkgprediction/tourism.csv (at revision 9397e3092c54d12733da554ec2b890a2ea5f4078)

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: int64
              TypeofContact: string
              CityTier: int64
              DurationOfPitch: int64
              Occupation: string
              Gender: string
              NumberOfPersonVisiting: int64
              NumberOfFollowups: int64
              ProductPitched: string
              PreferredPropertyStar: int64
              MaritalStatus: string
              NumberOfTrips: int64
              Passport: int64
              PitchSatisfactionScore: int64
              OwnCar: int64
              NumberOfChildrenVisiting: int64
              Designation: string
              MonthlyIncome: int64
              -- schema metadata --
              pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 2853
              to
              {'Unnamed: 0': Value('int64'), 'CustomerID': Value('int64'), 'Age': Value('int64'), 'TypeofContact': Value('int64'), 'CityTier': Value('int64'), 'DurationOfPitch': Value('int64'), 'Occupation': Value('int64'), 'Gender': Value('int64'), 'NumberOfPersonVisiting': Value('int64'), 'NumberOfFollowups': Value('int64'), 'ProductPitched': Value('int64'), 'PreferredPropertyStar': Value('int64'), 'MaritalStatus': Value('int64'), 'NumberOfTrips': Value('int64'), 'Passport': Value('int64'), 'PitchSatisfactionScore': Value('int64'), 'OwnCar': Value('int64'), 'NumberOfChildrenVisiting': Value('int64'), 'Designation': Value('int64'), 'MonthlyIncome': Value('int64')}
              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/rajoria007/tourpkgprediction/tourism.csv (at revision 9397e3092c54d12733da554ec2b890a2ea5f4078)
              
              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
int64
TypeofContact
int64
CityTier
int64
DurationOfPitch
int64
Occupation
int64
Gender
int64
NumberOfPersonVisiting
int64
NumberOfFollowups
int64
ProductPitched
int64
PreferredPropertyStar
int64
MaritalStatus
int64
NumberOfTrips
int64
Passport
int64
PitchSatisfactionScore
int64
OwnCar
int64
NumberOfChildrenVisiting
int64
Designation
int64
MonthlyIncome
int64
1,214
201,214
44
1
1
8
2
0
3
1
3
3
1
2
1
4
1
0
3
22,879
3,829
203,829
35
1
3
20
3
1
3
4
3
3
1
3
0
1
1
2
3
27,306
2,622
202,622
47
1
3
7
3
0
4
4
3
5
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3
0
2
1
2
3
29,131
1,543
201,543
32
1
1
6
2
1
3
3
1
4
1
2
0
3
1
0
2
21,220
3,144
203,144
59
1
1
9
1
1
3
4
0
3
2
6
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2
1
2
1
21,157
907
200,907
44
1
3
11
3
1
2
3
2
4
0
1
0
5
1
1
4
33,213
1,426
201,426
32
1
1
35
2
0
2
4
0
4
2
2
0
3
1
0
1
17,837
4,269
204,269
27
1
3
7
2
1
3
4
1
3
1
3
0
5
0
2
2
23,974
261
200,261
38
0
3
8
2
1
2
4
1
3
0
4
0
5
1
1
2
20,249
4,223
204,223
32
1
1
12
1
1
3
4
0
3
1
2
1
4
1
1
1
23,499
243
200,243
40
1
1
30
1
1
3
3
1
3
1
2
0
3
1
1
2
18,319
3,533
203,533
38
1
1
20
3
1
3
4
1
3
1
3
0
1
0
1
2
22,963
228
200,228
35
0
3
6
3
0
3
3
3
3
3
2
0
5
1
0
3
23,789
1,110
201,110
35
1
1
8
2
0
3
3
0
5
1
2
1
1
1
1
1
17,074
4,350
204,350
34
1
1
17
3
1
3
6
0
3
1
2
0
5
0
1
1
22,086
3,870
203,870
33
1
1
36
2
0
3
5
0
4
3
3
0
3
1
1
1
21,515
87
200,087
51
1
1
15
2
1
3
3
0
3
0
4
0
3
1
0
1
17,075
1,365
201,365
29
0
3
30
1
1
2
1
0
5
2
2
0
3
1
1
1
16,091
378
200,378
34
0
3
25
3
1
3
2
1
3
2
1
1
2
1
2
2
20,304
2,522
202,522
38
1
1
14
3
1
2
4
3
3
2
6
0
2
0
1
3
32,342
209
200,209
46
1
1
6
3
1
3
3
3
5
1
1
0
2
0
0
3
24,396
510
200,510
54
1
2
25
3
1
2
3
3
4
0
3
0
3
1
0
3
25,725
2,022
202,022
56
1
1
15
3
1
2
3
4
3
1
1
0
4
0
0
0
26,103
385
200,385
30
0
1
10
1
1
2
3
0
3
2
19
1
4
1
1
1
17,285
1,386
201,386
26
1
1
6
3
1
3
3
0
5
2
1
0
5
1
2
1
17,867
2,060
202,060
33
1
1
13
3
1
2
3
3
3
1
1
0
4
1
0
3
26,691
1,946
201,946
24
1
1
23
2
1
3
4
0
4
1
2
0
3
1
1
1
17,127
3,768
203,768
30
1
1
36
2
1
4
6
1
3
1
2
0
5
1
3
2
25,062
1,253
201,253
33
0
3
8
3
0
3
3
1
4
2
1
0
1
0
0
2
20,147
2,230
202,230
53
0
3
8
3
0
2
4
3
4
1
3
0
1
1
0
3
22,525
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203,514
29
0
3
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2
1
3
4
1
5
3
2
0
3
1
2
2
23,576
1,372
201,372
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1
1
15
3
1
2
3
1
5
1
2
0
4
1
0
2
20,151
4,366
204,366
46
1
3
9
2
1
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4
1
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1
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5
1
3
2
23,483
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202,466
35
1
1
14
2
0
3
4
3
4
2
2
0
3
1
1
3
30,672
4,073
204,073
35
0
3
9
3
0
4
4
0
3
1
8
0
5
0
1
1
20,909
4,596
204,596
33
0
1
7
2
0
4
5
0
4
1
8
0
3
0
3
1
21,010
2,373
202,373
29
0
1
16
2
0
2
4
0
3
3
2
0
4
1
0
1
21,623
1,916
201,916
41
0
3
16
2
1
2
3
1
3
2
1
0
1
0
1
2
21,230
3,268
203,268
43
1
1
36
3
1
3
6
1
3
3
6
0
3
1
1
2
22,950
4,329
204,329
35
0
3
13
3
0
3
6
0
3
1
2
0
4
0
2
1
21,029
1,685
201,685
41
1
3
12
2
0
3
3
3
3
2
4
1
1
0
0
3
28,591
694
200,694
33
1
1
6
2
0
2
4
1
3
3
1
0
4
0
0
2
21,949
837
200,837
40
0
1
15
3
0
2
3
3
3
3
1
0
4
0
0
3
28,499
1,852
201,852
26
0
1
9
1
1
3
3
0
5
2
1
0
3
0
1
1
18,102
1,712
201,712
41
1
1
25
2
1
2
3
1
5
1
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0
1
0
0
2
18,072
222
200,222
37
0
1
17
2
1
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3
3
3
1
2
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27,185
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31
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13
2
1
2
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0
3
1
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0
4
1
1
1
17,329
4,867
204,867
45
1
3
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2
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6
1
4
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8
0
3
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21,040
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200,514
33
0
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18,348
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33
1
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4
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1
1
21,048
1,074
201,074
33
1
1
14
2
1
3
3
1
3
3
3
1
3
0
2
2
21,388
402
200,402
30
1
3
18
1
0
2
3
1
3
3
1
0
2
1
0
2
21,577
547
200,547
42
0
1
25
3
1
2
2
0
3
1
7
1
3
1
1
1
17,759
1,899
201,899
46
1
1
8
2
1
2
3
4
3
1
7
0
5
1
0
0
32,861
4,656
204,656
51
1
1
16
2
1
4
4
0
3
1
6
0
5
1
3
1
21,058
1,880
201,880
30
1
1
8
2
0
2
5
1
3
2
3
0
1
1
0
2
21,091
2,742
202,742
37
0
1
25
2
1
3
3
0
3
0
6
0
5
0
1
1
22,366
1,323
201,323
28
0
2
6
2
1
2
3
0
3
1
2
0
4
0
1
1
17,706
1,357
201,357
42
1
1
12
3
1
2
3
3
5
1
1
0
3
1
0
3
28,348
617
200,617
44
1
1
10
3
1
2
3
1
4
2
1
0
2
1
0
2
20,933
3,637
203,637
39
0
1
9
3
0
3
5
0
4
2
3
0
1
1
1
1
21,118
253
200,253
42
1
1
23
2
0
2
2
1
5
3
4
1
2
0
0
2
21,545
2,223
202,223
39
0
1
28
3
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2
3
3
5
3
2
1
5
1
1
3
25,880
944
200,944
28
0
1
6
2
0
2
5
1
3
0
1
0
3
1
0
2
21,674
2,079
202,079
43
1
1
20
2
1
3
3
4
5
1
7
0
5
1
1
0
32,159
3,372
203,372
45
1
1
22
3
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4
3
3
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3
0
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26,656
4,382
204,382
53
1
1
13
1
1
4
4
1
5
1
5
1
4
1
2
2
24,255
4,062
204,062
42
1
1
16
2
1
4
4
0
5
1
4
0
1
0
1
1
20,916
9
200,009
36
1
1
33
3
1
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3
1
3
0
7
0
3
1
0
2
20,237
3,259
203,259
22
1
1
7
1
0
4
5
0
4
2
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1
5
0
3
1
20,748
2,664
202,664
37
1
1
12
2
1
4
4
1
4
3
2
0
2
0
3
2
24,592
3,501
203,501
30
0
3
20
1
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3
4
1
4
3
7
0
3
0
2
2
24,443
3,967
203,967
36
0
1
18
3
1
4
5
3
5
1
4
1
5
1
3
3
28,562
186
200,186
40
1
1
10
3
0
2
3
2
3
0
2
0
5
0
1
4
34,033
136
200,136
51
0
1
14
2
1
2
5
3
3
3
3
0
2
0
1
3
25,650
3,835
203,835
39
1
3
7
2
1
3
5
0
5
3
6
0
3
0
2
1
21,536
390
200,390
43
1
1
18
2
1
2
4
4
4
1
2
0
3
0
1
0
29,336
40
200,040
35
1
1
10
2
1
3
3
0
3
1
2
0
4
0
0
1
16,951
2,695
202,695
40
0
1
9
1
0
4
4
3
3
2
2
0
2
1
2
3
29,616
3,753
203,753
27
1
3
17
3
1
3
4
1
3
3
3
0
1
0
1
2
23,362
762
200,762
26
0
1
8
2
1
2
3
0
5
0
7
1
5
1
0
1
17,042
119
200,119
43
0
3
32
2
1
3
3
4
3
0
2
1
2
0
0
0
31,959
3,339
203,339
32
1
1
18
3
1
4
4
1
5
0
3
1
2
0
3
2
25,511
2,560
202,560
35
1
1
12
3
0
3
5
3
5
2
4
0
2
0
1
3
30,309
4,135
204,135
34
1
1
11
3
0
3
5
0
4
1
8
0
4
0
2
1
21,300
1,016
201,016
31
1
1
14
2
0
2
4
0
4
2
2
0
4
0
1
1
16,261
4,748
204,748
35
1
3
16
2
0
4
4
1
3
1
3
0
1
0
1
2
24,392
4,865
204,865
42
0
3
16
2
1
3
6
4
3
1
2
0
5
1
2
0
24,829
2,030
202,030
34
1
1
14
2
0
2
3
1
5
1
4
0
5
1
1
2
20,121
2,680
202,680
34
1
1
9
2
0
3
4
0
5
0
2
0
3
1
1
1
21,385
22
200,022
34
1
1
13
2
0
2
3
3
4
3
1
0
3
1
0
3
26,994
2,643
202,643
39
1
1
36
1
1
3
4
1
3
0
5
0
2
0
2
2
24,939
3,965
203,965
29
1
1
12
1
1
3
4
0
3
3
3
1
1
0
1
1
22,119
1,288
201,288
35
0
1
8
3
1
2
3
1
3
1
3
0
3
0
1
2
20,762
293
200,293
26
1
3
10
3
1
2
4
1
3
2
2
1
2
1
1
2
20,828
2,562
202,562
37
1
1
10
2
0
3
4
0
3
1
7
0
2
1
1
1
21,513
3,734
203,734
35
0
1
16
2
1
4
4
1
5
1
6
0
3
0
2
2
24,024
4,727
204,727
40
0
1
9
2
1
3
4
4
3
1
2
0
3
1
1
0
30,847
363
200,363
33
1
3
11
3
0
2
3
0
3
2
2
1
2
1
0
1
17,851
642
200,642
38
1
3
15
3
1
3
4
0
4
0
1
0
4
0
0
1
17,899
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