The full dataset viewer is not available (click to read why). Only showing a preview of the rows.
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 ({'NumberOfFollowups'}) and 20 missing columns ({'NumberOfPersonVisiting', 'PitchSatisfactionScore', 'ProductPitched', 'ProdTaken', 'Unnamed: 0', 'NumberOfTrips', 'CustomerID', 'NumberOfChildrenVisiting', 'PreferredPropertyStar', 'CityTier', 'TypeofContact', 'Age', 'Gender', 'Occupation', 'Passport', 'DurationOfPitch', 'MonthlyIncome', 'Designation', 'OwnCar', 'MaritalStatus'}).

This happened while the csv dataset builder was generating data using

hf://datasets/Debashre2824/tourism_predicton/ytest.csv (at revision 6c324c840ccd8053d9d9cf0227543d11c31d679c)

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
              NumberOfFollowups: double
              -- schema metadata --
              pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 396
              to
              {'Unnamed: 0': Value('int64'), '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'), '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 ({'NumberOfFollowups'}) and 20 missing columns ({'NumberOfPersonVisiting', 'PitchSatisfactionScore', 'ProductPitched', 'ProdTaken', 'Unnamed: 0', 'NumberOfTrips', 'CustomerID', 'NumberOfChildrenVisiting', 'PreferredPropertyStar', 'CityTier', 'TypeofContact', 'Age', 'Gender', 'Occupation', 'Passport', 'DurationOfPitch', 'MonthlyIncome', 'Designation', 'OwnCar', 'MaritalStatus'}).
              
              This happened while the csv dataset builder was generating data using
              
              hf://datasets/Debashre2824/tourism_predicton/ytest.csv (at revision 6c324c840ccd8053d9d9cf0227543d11c31d679c)
              
              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
ProdTaken
int64
Age
float64
TypeofContact
string
CityTier
int64
DurationOfPitch
float64
Occupation
string
Gender
string
NumberOfPersonVisiting
int64
ProductPitched
string
PreferredPropertyStar
float64
MaritalStatus
string
NumberOfTrips
float64
Passport
int64
PitchSatisfactionScore
int64
OwnCar
int64
NumberOfChildrenVisiting
float64
Designation
string
MonthlyIncome
float64
1,214
201,214
0
44
Self Enquiry
1
8
Salaried
Female
3
Standard
3
Married
2
1
4
1
0
Senior Manager
22,879
3,829
203,829
0
35
Self Enquiry
3
20
Small Business
Male
3
Standard
3
Married
3
0
1
1
2
Senior Manager
27,306
2,622
202,622
0
47
Self Enquiry
3
7
Small Business
Female
4
Standard
5
Married
3
0
2
1
2
Senior Manager
29,131
1,543
201,543
0
32
Self Enquiry
1
6
Salaried
Male
3
Deluxe
4
Married
2
0
3
1
0
Manager
21,220
3,144
203,144
1
59
Self Enquiry
1
9
Large Business
Male
3
Basic
3
Single
6
0
2
1
2
Executive
21,157
907
200,907
0
44
Self Enquiry
3
11
Small Business
Male
2
King
4
Divorced
1
0
5
1
1
VP
33,213
1,426
201,426
0
32
Self Enquiry
1
35
Salaried
Female
2
Basic
4
Single
2
0
3
1
0
Executive
17,837
4,269
204,269
0
27
Self Enquiry
3
7
Salaried
Male
3
Deluxe
3
Married
3
0
5
0
2
Manager
23,974
261
200,261
0
38
Company Invited
3
8
Salaried
Male
2
Deluxe
3
Divorced
4
0
5
1
1
Manager
20,249
4,223
204,223
0
32
Self Enquiry
1
12
Large Business
Male
3
Basic
3
Married
2
1
4
1
1
Executive
23,499
243
200,243
0
40
Self Enquiry
1
30
Large Business
Male
3
Deluxe
3
Married
2
0
3
1
1
Manager
18,319
3,533
203,533
0
38
Self Enquiry
1
20
Small Business
Male
3
Deluxe
3
Married
3
0
1
0
1
Manager
22,963
228
200,228
0
35
Company Invited
3
6
Small Business
Fe Male
3
Standard
3
Unmarried
2
0
5
1
0
Senior Manager
23,789
1,110
201,110
1
35
Self Enquiry
1
8
Salaried
Female
3
Basic
5
Married
2
1
1
1
1
Executive
17,074
4,350
204,350
1
34
Self Enquiry
1
17
Small Business
Male
3
Basic
3
Married
2
0
5
0
1
Executive
22,086
3,870
203,870
0
33
Self Enquiry
1
36
Salaried
Female
3
Basic
4
Unmarried
3
0
3
1
1
Executive
21,515
87
200,087
0
51
Self Enquiry
1
15
Salaried
Male
3
Basic
3
Divorced
4
0
3
1
0
Executive
17,075
1,365
201,365
1
29
Company Invited
3
30
Large Business
Male
2
Basic
5
Single
2
0
3
1
1
Executive
16,091
378
200,378
1
34
Company Invited
3
25
Small Business
Male
3
Deluxe
3
Single
1
1
2
1
2
Manager
20,304
2,522
202,522
0
38
Self Enquiry
1
14
Small Business
Male
2
Standard
3
Single
6
0
2
0
1
Senior Manager
32,342
209
200,209
0
46
Self Enquiry
1
6
Small Business
Male
3
Standard
5
Married
1
0
2
0
0
Senior Manager
24,396
510
200,510
0
54
Self Enquiry
2
25
Small Business
Male
2
Standard
4
Divorced
3
0
3
1
0
Senior Manager
25,725
2,022
202,022
0
56
Self Enquiry
1
15
Small Business
Male
2
Super Deluxe
3
Married
1
0
4
0
0
AVP
26,103
385
200,385
1
30
Company Invited
1
10
Large Business
Male
2
Basic
3
Single
19
1
4
1
1
Executive
17,285
1,386
201,386
0
26
Self Enquiry
1
6
Small Business
Male
3
Basic
5
Single
1
0
5
1
2
Executive
17,867
2,060
202,060
0
33
Self Enquiry
1
13
Small Business
Male
2
Standard
3
Married
1
0
4
1
0
Senior Manager
26,691
1,946
201,946
0
24
Self Enquiry
1
23
Salaried
Male
3
Basic
4
Married
2
0
3
1
1
Executive
17,127
3,768
203,768
0
30
Self Enquiry
1
36
Salaried
Male
4
Deluxe
3
Married
2
0
5
1
3
Manager
25,062
1,253
201,253
0
33
Company Invited
3
8
Small Business
Female
3
Deluxe
4
Single
1
0
1
0
0
Manager
20,147
2,230
202,230
0
53
Company Invited
3
8
Small Business
Female
2
Standard
4
Married
3
0
1
1
0
Senior Manager
22,525
3,514
203,514
0
29
Company Invited
3
14
Salaried
Male
3
Deluxe
5
Unmarried
2
0
3
1
2
Manager
23,576
1,372
201,372
0
39
Self Enquiry
1
15
Small Business
Male
2
Deluxe
5
Married
2
0
4
1
0
Manager
20,151
4,366
204,366
0
46
Self Enquiry
3
9
Salaried
Male
4
Deluxe
4
Married
2
0
5
1
3
Manager
23,483
2,466
202,466
0
35
Self Enquiry
1
14
Salaried
Female
3
Standard
4
Single
2
0
3
1
1
Senior Manager
30,672
4,073
204,073
0
35
Company Invited
3
9
Small Business
Female
4
Basic
3
Married
8
0
5
0
1
Executive
20,909
4,596
204,596
0
33
Company Invited
1
7
Salaried
Female
4
Basic
4
Married
8
0
3
0
3
Executive
21,010
2,373
202,373
1
29
Company Invited
1
16
Salaried
Female
2
Basic
3
Unmarried
2
0
4
1
0
Executive
21,623
1,916
201,916
0
41
Company Invited
3
16
Salaried
Male
2
Deluxe
3
Single
1
0
1
0
1
Manager
21,230
3,268
203,268
0
43
Self Enquiry
1
36
Small Business
Male
3
Deluxe
3
Unmarried
6
0
3
1
1
Manager
22,950
4,329
204,329
1
35
Company Invited
3
13
Small Business
Female
3
Basic
3
Married
2
0
4
0
2
Executive
21,029
1,685
201,685
0
41
Self Enquiry
3
12
Salaried
Female
3
Standard
3
Single
4
1
1
0
0
Senior Manager
28,591
694
200,694
0
33
Self Enquiry
1
6
Salaried
Female
2
Deluxe
3
Unmarried
1
0
4
0
0
Manager
21,949
837
200,837
0
40
Company Invited
1
15
Small Business
Fe Male
2
Standard
3
Unmarried
1
0
4
0
0
Senior Manager
28,499
1,852
201,852
1
26
Company Invited
1
9
Large Business
Male
3
Basic
5
Single
1
0
3
0
1
Executive
18,102
1,712
201,712
0
41
Self Enquiry
1
25
Salaried
Male
2
Deluxe
5
Married
3
0
1
0
0
Manager
18,072
222
200,222
0
37
Company Invited
1
17
Salaried
Male
2
Standard
3
Married
2
1
3
0
1
Senior Manager
27,185
2,145
202,145
0
31
Self Enquiry
3
13
Salaried
Male
2
Basic
3
Married
4
0
4
1
1
Executive
17,329
4,867
204,867
1
45
Self Enquiry
3
8
Salaried
Male
3
Deluxe
4
Single
8
0
3
0
2
Manager
21,040
514
200,514
1
33
Company Invited
1
9
Salaried
Male
3
Basic
5
Single
2
1
5
1
2
Executive
18,348
2,795
202,795
0
33
Self Enquiry
1
9
Small Business
Female
4
Basic
4
Divorced
3
0
4
0
1
Executive
21,048
1,074
201,074
0
33
Self Enquiry
1
14
Salaried
Male
3
Deluxe
3
Unmarried
3
1
3
0
2
Manager
21,388
402
200,402
0
30
Self Enquiry
3
18
Large Business
Female
2
Deluxe
3
Unmarried
1
0
2
1
0
Manager
21,577
547
200,547
1
42
Company Invited
1
25
Small Business
Male
2
Basic
3
Married
7
1
3
1
1
Executive
17,759
1,899
201,899
0
46
Self Enquiry
1
8
Salaried
Male
2
Super Deluxe
3
Married
7
0
5
1
0
AVP
32,861
4,656
204,656
0
51
Self Enquiry
1
16
Salaried
Male
4
Basic
3
Married
6
0
5
1
3
Executive
21,058
1,880
201,880
0
30
Self Enquiry
1
8
Salaried
Female
2
Deluxe
3
Single
3
0
1
1
0
Manager
21,091
2,742
202,742
0
37
Company Invited
1
25
Salaried
Male
3
Basic
3
Divorced
6
0
5
0
1
Executive
22,366
1,323
201,323
0
28
Company Invited
2
6
Salaried
Male
2
Basic
3
Married
2
0
4
0
1
Executive
17,706
1,357
201,357
0
42
Self Enquiry
1
12
Small Business
Male
2
Standard
5
Married
1
0
3
1
0
Senior Manager
28,348
617
200,617
0
44
Self Enquiry
1
10
Small Business
Male
2
Deluxe
4
Single
1
0
2
1
0
Manager
20,933
3,637
203,637
0
39
Company Invited
1
9
Small Business
Female
3
Basic
4
Single
3
0
1
1
1
Executive
21,118
253
200,253
0
42
Self Enquiry
1
23
Salaried
Female
2
Deluxe
5
Unmarried
4
1
2
0
0
Manager
21,545
2,223
202,223
0
39
Company Invited
1
28
Small Business
Fe Male
2
Standard
5
Unmarried
2
1
5
1
1
Senior Manager
25,880
944
200,944
0
28
Company Invited
1
6
Salaried
Female
2
Deluxe
3
Divorced
1
0
3
1
0
Manager
21,674
2,079
202,079
0
43
Self Enquiry
1
20
Salaried
Male
3
Super Deluxe
5
Married
7
0
5
1
1
AVP
32,159
3,372
203,372
1
45
Self Enquiry
1
22
Small Business
Female
4
Standard
3
Divorced
3
0
3
0
2
Senior Manager
26,656
4,382
204,382
0
53
Self Enquiry
1
13
Large Business
Male
4
Deluxe
5
Married
5
1
4
1
2
Manager
24,255
4,062
204,062
0
42
Self Enquiry
1
16
Salaried
Male
4
Basic
5
Married
4
0
1
0
1
Executive
20,916
9
200,009
0
36
Self Enquiry
1
33
Small Business
Male
3
Deluxe
3
Divorced
7
0
3
1
0
Manager
20,237
3,259
203,259
0
22
Self Enquiry
1
7
Large Business
Female
4
Basic
4
Single
3
1
5
0
3
Executive
20,748
2,664
202,664
0
37
Self Enquiry
1
12
Salaried
Male
4
Deluxe
4
Unmarried
2
0
2
0
3
Manager
24,592
3,501
203,501
1
30
Company Invited
3
20
Large Business
Fe Male
3
Deluxe
4
Unmarried
7
0
3
0
2
Manager
24,443
3,967
203,967
0
36
Company Invited
1
18
Small Business
Male
4
Standard
5
Married
4
1
5
1
3
Senior Manager
28,562
186
200,186
0
40
Self Enquiry
1
10
Small Business
Female
2
King
3
Divorced
2
0
5
0
1
VP
34,033
136
200,136
1
51
Company Invited
1
14
Salaried
Male
2
Standard
3
Unmarried
3
0
2
0
1
Senior Manager
25,650
3,835
203,835
0
39
Self Enquiry
3
7
Salaried
Male
3
Basic
5
Unmarried
6
0
3
0
2
Executive
21,536
390
200,390
0
43
Self Enquiry
1
18
Salaried
Male
2
Super Deluxe
4
Married
2
0
3
0
1
AVP
29,336
40
200,040
0
35
Self Enquiry
1
10
Salaried
Male
3
Basic
3
Married
2
0
4
0
0
Executive
16,951
2,695
202,695
0
40
Company Invited
1
9
Large Business
Female
4
Standard
3
Single
2
0
2
1
2
Senior Manager
29,616
3,753
203,753
0
27
Self Enquiry
3
17
Small Business
Male
3
Deluxe
3
Unmarried
3
0
1
0
1
Manager
23,362
762
200,762
1
26
Company Invited
1
8
Salaried
Male
2
Basic
5
Divorced
7
1
5
1
0
Executive
17,042
119
200,119
0
43
Company Invited
3
32
Salaried
Male
3
Super Deluxe
3
Divorced
2
1
2
0
0
AVP
31,959
3,339
203,339
0
32
Self Enquiry
1
18
Small Business
Male
4
Deluxe
5
Divorced
3
1
2
0
3
Manager
25,511
2,560
202,560
0
35
Self Enquiry
1
12
Small Business
Female
3
Standard
5
Single
4
0
2
0
1
Senior Manager
30,309
4,135
204,135
0
34
Self Enquiry
1
11
Small Business
Female
3
Basic
4
Married
8
0
4
0
2
Executive
21,300
1,016
201,016
1
31
Self Enquiry
1
14
Salaried
Female
2
Basic
4
Single
2
0
4
0
1
Executive
16,261
4,748
204,748
0
35
Self Enquiry
3
16
Salaried
Female
4
Deluxe
3
Married
3
0
1
0
1
Manager
24,392
4,865
204,865
1
42
Company Invited
3
16
Salaried
Male
3
Super Deluxe
3
Married
2
0
5
1
2
AVP
24,829
2,030
202,030
0
34
Self Enquiry
1
14
Salaried
Female
2
Deluxe
5
Married
4
0
5
1
1
Manager
20,121
2,680
202,680
1
34
Self Enquiry
1
9
Salaried
Female
3
Basic
5
Divorced
2
0
3
1
1
Executive
21,385
22
200,022
0
34
Self Enquiry
1
13
Salaried
Fe Male
2
Standard
4
Unmarried
1
0
3
1
0
Senior Manager
26,994
2,643
202,643
0
39
Self Enquiry
1
36
Large Business
Male
3
Deluxe
3
Divorced
5
0
2
0
2
Manager
24,939
3,965
203,965
1
29
Self Enquiry
1
12
Large Business
Male
3
Basic
3
Unmarried
3
1
1
0
1
Executive
22,119
1,288
201,288
0
35
Company Invited
1
8
Small Business
Male
2
Deluxe
3
Married
3
0
3
0
1
Manager
20,762
293
200,293
1
26
Self Enquiry
3
10
Small Business
Male
2
Deluxe
3
Single
2
1
2
1
1
Manager
20,828
2,562
202,562
0
37
Self Enquiry
1
10
Salaried
Female
3
Basic
3
Married
7
0
2
1
1
Executive
21,513
3,734
203,734
1
35
Company Invited
1
16
Salaried
Male
4
Deluxe
5
Married
6
0
3
0
2
Manager
24,024
4,727
204,727
1
40
Company Invited
1
9
Salaried
Male
3
Super Deluxe
3
Married
2
0
3
1
1
AVP
30,847
363
200,363
1
33
Self Enquiry
3
11
Small Business
Female
2
Basic
3
Single
2
1
2
1
0
Executive
17,851
642
200,642
0
38
Self Enquiry
3
15
Small Business
Male
3
Basic
4
Divorced
1
0
4
0
0
Executive
17,899
End of preview.