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akskhare
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Tourism-Packages

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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 8 new columns ({'Occupation', 'ProdTaken', 'MaritalStatus', 'ProductPitched', 'TypeofContact', 'Gender', 'Designation', 'CustomerID'}) and 23 missing columns ({'MaritalStatus_Divorced', 'Occupation_Small Business', 'ProductPitched_Super Deluxe', 'MaritalStatus_Married', 'Gender_Fe Male', 'MaritalStatus_Single', 'Occupation_Salaried', 'Occupation_Large Business', 'Gender_Female', 'Designation_Senior Manager', 'ProductPitched_King', 'TypeofContact_Company Invited', 'Occupation_Free Lancer', 'Gender_Male', 'MaritalStatus_Unmarried', 'ProductPitched_Deluxe', 'ProductPitched_Standard', 'Designation_Executive', 'Designation_AVP', 'TypeofContact_Self Enquiry', 'ProductPitched_Basic', 'Designation_Manager', 'Designation_VP'}).

This happened while the csv dataset builder was generating data using

hf://datasets/akskhare/Tourism-Packages/tourism_data.csv (at revision a165f2794aee1eea2625502eca85a93d7f97ac15)

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'), 'Age': Value('float64'), 'CityTier': Value('int64'), 'DurationOfPitch': Value('float64'), 'NumberOfPersonVisiting': Value('int64'), 'NumberOfFollowups': Value('float64'), 'PreferredPropertyStar': Value('float64'), 'NumberOfTrips': Value('float64'), 'Passport': Value('int64'), 'PitchSatisfactionScore': Value('int64'), 'OwnCar': Value('int64'), 'NumberOfChildrenVisiting': Value('float64'), 'MonthlyIncome': Value('float64'), 'TypeofContact_Company Invited': Value('float64'), 'TypeofContact_Self Enquiry': Value('float64'), 'Occupation_Free Lancer': Value('float64'), 'Occupation_Large Business': Value('float64'), 'Occupation_Salaried': Value('float64'), 'Occupation_Small Business': Value('float64'), 'Gender_Fe Male': Value('float64'), 'Gender_Female': Value('float64'), 'Gender_Male': Value('float64'), 'ProductPitched_Basic': Value('float64'), 'ProductPitched_Deluxe': Value('float64'), 'ProductPitched_King': Value('float64'), 'ProductPitched_Standard': Value('float64'), 'ProductPitched_Super Deluxe': Value('float64'), 'MaritalStatus_Divorced': Value('float64'), 'MaritalStatus_Married': Value('float64'), 'MaritalStatus_Single': Value('float64'), 'MaritalStatus_Unmarried': Value('float64'), 'Designation_AVP': Value('float64'), 'Designation_Executive': Value('float64'), 'Designation_Manager': Value('float64'), 'Designation_Senior Manager': Value('float64'), 'Designation_VP': 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 8 new columns ({'Occupation', 'ProdTaken', 'MaritalStatus', 'ProductPitched', 'TypeofContact', 'Gender', 'Designation', 'CustomerID'}) and 23 missing columns ({'MaritalStatus_Divorced', 'Occupation_Small Business', 'ProductPitched_Super Deluxe', 'MaritalStatus_Married', 'Gender_Fe Male', 'MaritalStatus_Single', 'Occupation_Salaried', 'Occupation_Large Business', 'Gender_Female', 'Designation_Senior Manager', 'ProductPitched_King', 'TypeofContact_Company Invited', 'Occupation_Free Lancer', 'Gender_Male', 'MaritalStatus_Unmarried', 'ProductPitched_Deluxe', 'ProductPitched_Standard', 'Designation_Executive', 'Designation_AVP', 'TypeofContact_Self Enquiry', 'ProductPitched_Basic', 'Designation_Manager', 'Designation_VP'}).
              
              This happened while the csv dataset builder was generating data using
              
              hf://datasets/akskhare/Tourism-Packages/tourism_data.csv (at revision a165f2794aee1eea2625502eca85a93d7f97ac15)
              
              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
Age
float64
CityTier
int64
DurationOfPitch
float64
NumberOfPersonVisiting
int64
NumberOfFollowups
float64
PreferredPropertyStar
float64
NumberOfTrips
float64
Passport
int64
PitchSatisfactionScore
int64
OwnCar
int64
NumberOfChildrenVisiting
float64
MonthlyIncome
float64
TypeofContact_Company Invited
float64
TypeofContact_Self Enquiry
float64
Occupation_Free Lancer
float64
Occupation_Large Business
float64
Occupation_Salaried
float64
Occupation_Small Business
float64
Gender_Fe Male
float64
Gender_Female
float64
Gender_Male
float64
ProductPitched_Basic
float64
ProductPitched_Deluxe
float64
ProductPitched_King
float64
ProductPitched_Standard
float64
ProductPitched_Super Deluxe
float64
MaritalStatus_Divorced
float64
MaritalStatus_Married
float64
MaritalStatus_Single
float64
MaritalStatus_Unmarried
float64
Designation_AVP
float64
Designation_Executive
float64
Designation_Manager
float64
Designation_Senior Manager
float64
Designation_VP
float64
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1
3
0
2
21,388
0
1
0
0
1
0
0
0
1
0
1
0
0
0
0
0
0
1
0
0
1
0
0
402
30
3
18
2
3
3
1
0
2
1
0
21,577
0
1
0
1
0
0
0
1
0
0
1
0
0
0
0
0
0
1
0
0
1
0
0
547
42
1
25
2
2
3
7
1
3
1
1
17,759
1
0
0
0
0
1
0
0
1
1
0
0
0
0
0
1
0
0
0
1
0
0
0
1,899
46
1
8
2
3
3
7
0
5
1
0
32,861
0
1
0
0
1
0
0
0
1
0
0
0
0
1
0
1
0
0
1
0
0
0
0
4,656
51
1
16
4
4
3
6
0
5
1
3
21,058
0
1
0
0
1
0
0
0
1
1
0
0
0
0
0
1
0
0
0
1
0
0
0
1,880
30
1
8
2
5
3
3
0
1
1
0
21,091
0
1
0
0
1
0
0
1
0
0
1
0
0
0
0
0
1
0
0
0
1
0
0
2,742
37
1
25
3
3
3
6
0
5
0
1
22,366
1
0
0
0
1
0
0
0
1
1
0
0
0
0
1
0
0
0
0
1
0
0
0
1,323
28
2
6
2
3
3
2
0
4
0
1
17,706
1
0
0
0
1
0
0
0
1
1
0
0
0
0
0
1
0
0
0
1
0
0
0
1,357
42
1
12
2
3
5
1
0
3
1
0
28,348
0
1
0
0
0
1
0
0
1
0
0
0
1
0
0
1
0
0
0
0
0
1
0
617
44
1
10
2
3
4
1
0
2
1
0
20,933
0
1
0
0
0
1
0
0
1
0
1
0
0
0
0
0
1
0
0
0
1
0
0
3,637
39
1
9
3
5
4
3
0
1
1
1
21,118
1
0
0
0
0
1
0
1
0
1
0
0
0
0
0
0
1
0
0
1
0
0
0
253
42
1
23
2
2
5
4
1
2
0
0
21,545
0
1
0
0
1
0
0
1
0
0
1
0
0
0
0
0
0
1
0
0
1
0
0
2,223
39
1
28
2
3
5
2
1
5
1
1
25,880
1
0
0
0
0
1
1
0
0
0
0
0
1
0
0
0
0
1
0
0
0
1
0
944
28
1
6
2
5
3
1
0
3
1
0
21,674
1
0
0
0
1
0
0
1
0
0
1
0
0
0
1
0
0
0
0
0
1
0
0
2,079
43
1
20
3
3
5
7
0
5
1
1
32,159
0
1
0
0
1
0
0
0
1
0
0
0
0
1
0
1
0
0
1
0
0
0
0
3,372
45
1
22
4
4
3
3
0
3
0
2
26,656
0
1
0
0
0
1
0
1
0
0
0
0
1
0
1
0
0
0
0
0
0
1
0
4,382
53
1
13
4
4
5
5
1
4
1
2
24,255
0
1
0
1
0
0
0
0
1
0
1
0
0
0
0
1
0
0
0
0
1
0
0
4,062
42
1
16
4
4
5
4
0
1
0
1
20,916
0
1
0
0
1
0
0
0
1
1
0
0
0
0
0
1
0
0
0
1
0
0
0
9
36
1
33
3
3
3
7
0
3
1
0
20,237
0
1
0
0
0
1
0
0
1
0
1
0
0
0
1
0
0
0
0
0
1
0
0
3,259
22
1
7
4
5
4
3
1
5
0
3
20,748
0
1
0
1
0
0
0
1
0
1
0
0
0
0
0
0
1
0
0
1
0
0
0
2,664
37
1
12
4
4
4
2
0
2
0
3
24,592
0
1
0
0
1
0
0
0
1
0
1
0
0
0
0
0
0
1
0
0
1
0
0
3,501
30
3
20
3
4
4
7
0
3
0
2
24,443
1
0
0
1
0
0
1
0
0
0
1
0
0
0
0
0
0
1
0
0
1
0
0
3,967
36
1
18
4
5
5
4
1
5
1
3
28,562
1
0
0
0
0
1
0
0
1
0
0
0
1
0
0
1
0
0
0
0
0
1
0
186
40
1
10
2
3
3
2
0
5
0
1
34,033
0
1
0
0
0
1
0
1
0
0
0
1
0
0
1
0
0
0
0
0
0
0
1
136
51
1
14
2
5
3
3
0
2
0
1
25,650
1
0
0
0
1
0
0
0
1
0
0
0
1
0
0
0
0
1
0
0
0
1
0
3,835
39
3
7
3
5
5
6
0
3
0
2
21,536
0
1
0
0
1
0
0
0
1
1
0
0
0
0
0
0
0
1
0
1
0
0
0
390
43
1
18
2
4
4
2
0
3
0
1
29,336
0
1
0
0
1
0
0
0
1
0
0
0
0
1
0
1
0
0
1
0
0
0
0
40
35
1
10
3
3
3
2
0
4
0
0
16,951
0
1
0
0
1
0
0
0
1
1
0
0
0
0
0
1
0
0
0
1
0
0
0
2,695
40
1
9
4
4
3
2
0
2
1
2
29,616
1
0
0
1
0
0
0
1
0
0
0
0
1
0
0
0
1
0
0
0
0
1
0
3,753
27
3
17
3
4
3
3
0
1
0
1
23,362
0
1
0
0
0
1
0
0
1
0
1
0
0
0
0
0
0
1
0
0
1
0
0
762
26
1
8
2
3
5
7
1
5
1
0
17,042
1
0
0
0
1
0
0
0
1
1
0
0
0
0
1
0
0
0
0
1
0
0
0
119
43
3
32
3
3
3
2
1
2
0
0
31,959
1
0
0
0
1
0
0
0
1
0
0
0
0
1
1
0
0
0
1
0
0
0
0
3,339
32
1
18
4
4
5
3
1
2
0
3
25,511
0
1
0
0
0
1
0
0
1
0
1
0
0
0
1
0
0
0
0
0
1
0
0
2,560
35
1
12
3
5
5
4
0
2
0
1
30,309
0
1
0
0
0
1
0
1
0
0
0
0
1
0
0
0
1
0
0
0
0
1
0
4,135
34
1
11
3
5
4
8
0
4
0
2
21,300
0
1
0
0
0
1
0
1
0
1
0
0
0
0
0
1
0
0
0
1
0
0
0
1,016
31
1
14
2
4
4
2
0
4
0
1
16,261
0
1
0
0
1
0
0
1
0
1
0
0
0
0
0
0
1
0
0
1
0
0
0
4,748
35
3
16
4
4
3
3
0
1
0
1
24,392
0
1
0
0
1
0
0
1
0
0
1
0
0
0
0
1
0
0
0
0
1
0
0
4,865
42
3
16
3
6
3
2
0
5
1
2
24,829
1
0
0
0
1
0
0
0
1
0
0
0
0
1
0
1
0
0
1
0
0
0
0
2,030
34
1
14
2
3
5
4
0
5
1
1
20,121
0
1
0
0
1
0
0
1
0
0
1
0
0
0
0
1
0
0
0
0
1
0
0
2,680
34
1
9
3
4
5
2
0
3
1
1
21,385
0
1
0
0
1
0
0
1
0
1
0
0
0
0
1
0
0
0
0
1
0
0
0
22
34
1
13
2
3
4
1
0
3
1
0
26,994
0
1
0
0
1
0
1
0
0
0
0
0
1
0
0
0
0
1
0
0
0
1
0
2,643
39
1
36
3
4
3
5
0
2
0
2
24,939
0
1
0
1
0
0
0
0
1
0
1
0
0
0
1
0
0
0
0
0
1
0
0
3,965
29
1
12
3
4
3
3
1
1
0
1
22,119
0
1
0
1
0
0
0
0
1
1
0
0
0
0
0
0
0
1
0
1
0
0
0
1,288
35
1
8
2
3
3
3
0
3
0
1
20,762
1
0
0
0
0
1
0
0
1
0
1
0
0
0
0
1
0
0
0
0
1
0
0
293
26
3
10
2
4
3
2
1
2
1
1
20,828
0
1
0
0
0
1
0
0
1
0
1
0
0
0
0
0
1
0
0
0
1
0
0
2,562
37
1
10
3
4
3
7
0
2
1
1
21,513
0
1
0
0
1
0
0
1
0
1
0
0
0
0
0
1
0
0
0
1
0
0
0
3,734
35
1
16
4
4
5
6
0
3
0
2
24,024
1
0
0
0
1
0
0
0
1
0
1
0
0
0
0
1
0
0
0
0
1
0
0
4,727
40
1
9
3
4
3
2
0
3
1
1
30,847
1
0
0
0
1
0
0
0
1
0
0
0
0
1
0
1
0
0
1
0
0
0
0
363
33
3
11
2
3
3
2
1
2
1
0
17,851
0
1
0
0
0
1
0
1
0
1
0
0
0
0
0
0
1
0
0
1
0
0
0
642
38
3
15
3
4
4
1
0
4
0
0
17,899
0
1
0
0
0
1
0
0
1
1
0
0
0
0
1
0
0
0
0
1
0
0
0
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