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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 2 new columns ({'CustomerID', 'ProdTaken'})
This happened while the csv dataset builder was generating data using
hf://datasets/nsa9/tourism-package-prediction/tourism.csv (at revision f9c2b9c0bc68aa42423699b3fbbddc3fcf907d90)
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
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, "' + 2764
to
{'Age': Value('float64'), 'NumberOfPersonVisiting': Value('int64'), 'PreferredPropertyStar': Value('float64'), 'NumberOfTrips': Value('float64'), 'NumberOfChildrenVisiting': Value('float64'), 'MonthlyIncome': Value('float64'), 'PitchSatisfactionScore': Value('int64'), 'NumberOfFollowups': Value('float64'), 'DurationOfPitch': Value('float64'), 'TypeofContact': Value('string'), 'CityTier': Value('int64'), 'Occupation': Value('string'), 'Gender': Value('string'), 'MaritalStatus': Value('string'), 'Designation': Value('string'), 'ProductPitched': Value('string'), 'Passport': Value('int64'), 'OwnCar': 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 2 new columns ({'CustomerID', 'ProdTaken'})
This happened while the csv dataset builder was generating data using
hf://datasets/nsa9/tourism-package-prediction/tourism.csv (at revision f9c2b9c0bc68aa42423699b3fbbddc3fcf907d90)
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.
Age
float64 | NumberOfPersonVisiting
int64 | PreferredPropertyStar
float64 | NumberOfTrips
float64 | NumberOfChildrenVisiting
float64 | MonthlyIncome
float64 | PitchSatisfactionScore
int64 | NumberOfFollowups
float64 | DurationOfPitch
float64 | TypeofContact
string | CityTier
int64 | Occupation
string | Gender
string | MaritalStatus
string | Designation
string | ProductPitched
string | Passport
int64 | OwnCar
int64 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
34
| 2
| 3
| 4
| 0
| 17,979
| 1
| 4
| 9
|
Company Invited
| 1
|
Salaried
|
Male
|
Married
|
Executive
|
Basic
| 0
| 0
|
32
| 3
| 4
| 2
| 0
| 21,220
| 3
| 3
| 6
|
Self Enquiry
| 1
|
Salaried
|
Male
|
Divorced
|
Manager
|
Deluxe
| 0
| 0
|
30
| 2
| 3
| 3
| 1
| 24,419
| 4
| 3
| 11
|
Self Enquiry
| 3
|
Salaried
|
Female
|
Divorced
|
Senior Manager
|
Standard
| 0
| 1
|
39
| 3
| 4
| 2
| 2
| 26,029
| 4
| 4
| 9
|
Self Enquiry
| 3
|
Small Business
|
Male
|
Unmarried
|
Senior Manager
|
Standard
| 0
| 1
|
37
| 3
| 4
| 2
| 2
| 24,352
| 3
| 4
| 31
|
Company Invited
| 1
|
Salaried
|
Female
|
Married
|
Manager
|
Deluxe
| 0
| 1
|
34
| 3
| 3
| 2
| 2
| 21,178
| 3
| 4
| 9
|
Self Enquiry
| 1
|
Salaried
|
Male
|
Single
|
Executive
|
Basic
| 0
| 0
|
27
| 4
| 3
| 5
| 3
| 23,042
| 4
| 6
| 7
|
Company Invited
| 1
|
Salaried
|
Female
|
Married
|
Executive
|
Basic
| 0
| 1
|
30
| 3
| 5
| 2
| 1
| 24,714
| 4
| 4
| 6
|
Self Enquiry
| 3
|
Salaried
|
Male
|
Married
|
Manager
|
Deluxe
| 0
| 1
|
53
| 3
| 3
| 5
| 2
| 32,504
| 5
| 5
| 32
|
Company Invited
| 1
|
Small Business
|
Female
|
Married
|
AVP
|
Super Deluxe
| 0
| 0
|
55
| 3
| 3
| 2
| 2
| 29,180
| 5
| 4
| 7
|
Company Invited
| 1
|
Salaried
|
Female
|
Married
|
Senior Manager
|
Standard
| 0
| 1
|
46
| 2
| 5
| 3
| 1
| 25,673
| 2
| 4
| 6
|
Company Invited
| 1
|
Small Business
|
Male
|
Divorced
|
Senior Manager
|
Standard
| 1
| 1
|
39
| 2
| 5
| 4
| 1
| 24,966
| 5
| 5
| 19
|
Company Invited
| 1
|
Salaried
|
Male
|
Married
|
Manager
|
Deluxe
| 0
| 1
|
54
| 1
| 3
| 3
| 0
| 32,328
| 3
| 2
| 32
|
Company Invited
| 2
|
Salaried
|
Female
|
Single
|
AVP
|
Super Deluxe
| 1
| 1
|
42
| 3
| 5
| 6
| 0
| 20,538
| 4
| 1
| 19
|
Self Enquiry
| 1
|
Small Business
|
Male
|
Married
|
Manager
|
Deluxe
| 0
| 1
|
33
| 3
| 3
| 5
| 2
| 21,990
| 5
| 2
| 12
|
Self Enquiry
| 1
|
Salaried
|
Female
|
Married
|
Executive
|
Basic
| 0
| 1
|
35
| 1
| 3
| 2
| 0
| 17,859
| 4
| 4
| 6
|
Self Enquiry
| 1
|
Small Business
|
Male
|
Single
|
Executive
|
Basic
| 0
| 1
|
39
| 3
| 3
| 1
| 0
| 28,464
| 3
| 3
| 16
|
Self Enquiry
| 1
|
Small Business
|
Male
|
Unmarried
|
Senior Manager
|
Standard
| 0
| 1
|
29
| 3
| 3
| 5
| 2
| 22,338
| 4
| 4
| 17
|
Self Enquiry
| 1
|
Salaried
|
Female
|
Unmarried
|
Manager
|
Deluxe
| 0
| 1
|
23
| 3
| 3
| 7
| 1
| 22,572
| 5
| 5
| 11
|
Company Invited
| 1
|
Large Business
|
Male
|
Unmarried
|
Executive
|
Basic
| 0
| 1
|
37
| 2
| 3
| 2
| 0
| 17,326
| 2
| 3
| 15
|
Company Invited
| 1
|
Small Business
|
Male
|
Divorced
|
Executive
|
Basic
| 1
| 0
|
33
| 4
| 5
| 3
| 1
| 25,403
| 1
| 4
| 10
|
Self Enquiry
| 1
|
Small Business
|
Female
|
Married
|
Manager
|
Deluxe
| 0
| 1
|
33
| 4
| 5
| 3
| 2
| 21,634
| 1
| 4
| 7
|
Self Enquiry
| 1
|
Salaried
|
Male
|
Unmarried
|
Executive
|
Basic
| 0
| 0
|
50
| 4
| 3
| 3
| 1
| 25,482
| 1
| 4
| 25
|
Company Invited
| 1
|
Salaried
|
Male
|
Married
|
Manager
|
Deluxe
| 1
| 0
|
42
| 2
| 3
| 1
| 0
| 21,062
| 3
| 4
| 6
|
Self Enquiry
| 1
|
Salaried
|
Female
|
Married
|
Manager
|
Deluxe
| 1
| 0
|
43
| 3
| 5
| 5
| 1
| 31,869
| 3
| 4
| 33
|
Company Invited
| 1
|
Small Business
|
Female
|
Married
|
Senior Manager
|
Standard
| 1
| 0
|
36
| 3
| 4
| 2
| 0
| 17,810
| 5
| 1
| 15
|
Company Invited
| 1
|
Salaried
|
Male
|
Married
|
Executive
|
Basic
| 0
| 1
|
27
| 2
| 3
| 1
| 1
| 21,500
| 1
| 1
| 8
|
Self Enquiry
| 3
|
Small Business
|
Female
|
Unmarried
|
Manager
|
Deluxe
| 0
| 0
|
29
| 4
| 3
| 3
| 2
| 23,931
| 3
| 4
| 16
|
Self Enquiry
| 3
|
Salaried
|
Male
|
Unmarried
|
Manager
|
Deluxe
| 0
| 1
|
34
| 4
| 3
| 3
| 3
| 21,589
| 2
| 5
| 12
|
Self Enquiry
| 1
|
Salaried
|
Female
|
Divorced
|
Executive
|
Basic
| 0
| 0
|
41
| 3
| 5
| 3
| 2
| 23,317
| 3
| 4
| 21
|
Self Enquiry
| 3
|
Salaried
|
Female
|
Married
|
Manager
|
Deluxe
| 0
| 0
|
32
| 4
| 5
| 7
| 1
| 20,980
| 1
| 5
| 20
|
Self Enquiry
| 3
|
Small Business
|
Male
|
Married
|
Manager
|
Deluxe
| 1
| 1
|
50
| 3
| 4
| 2
| 2
| 33,200
| 1
| 3
| 9
|
Company Invited
| 2
|
Small Business
|
Male
|
Married
|
VP
|
King
| 0
| 1
|
24
| 2
| 3
| 1
| 1
| 17,400
| 4
| 3
| 30
|
Company Invited
| 3
|
Small Business
|
Male
|
Married
|
Executive
|
Basic
| 0
| 1
|
43
| 3
| 3
| 2
| 1
| 24,740
| 3
| 5
| 7
|
Self Enquiry
| 1
|
Salaried
|
Female
|
Married
|
Manager
|
Deluxe
| 1
| 0
|
39
| 3
| 5
| 3
| 2
| 20,377
| 5
| 3
| 16
|
Self Enquiry
| 1
|
Small Business
|
Male
|
Married
|
Manager
|
Deluxe
| 0
| 1
|
55
| 2
| 5
| 1
| 1
| 34,045
| 1
| 3
| 6
|
Self Enquiry
| 1
|
Small Business
|
Male
|
Single
|
VP
|
King
| 1
| 1
|
33
| 3
| 3
| 3
| 1
| 24,887
| 4
| 4
| 10
|
Company Invited
| 1
|
Salaried
|
Fe Male
|
Unmarried
|
Executive
|
Basic
| 0
| 1
|
34
| 4
| 5
| 4
| 1
| 27,242
| 5
| 4
| 23
|
Self Enquiry
| 3
|
Salaried
|
Fe Male
|
Unmarried
|
Senior Manager
|
Standard
| 1
| 0
|
25
| 3
| 3
| 2
| 1
| 21,452
| 4
| 4
| 25
|
Self Enquiry
| 1
|
Salaried
|
Male
|
Married
|
Executive
|
Basic
| 0
| 0
|
30
| 3
| 3
| 2
| 2
| 17,632
| 1
| 3
| 24
|
Self Enquiry
| 1
|
Salaried
|
Female
|
Single
|
Executive
|
Basic
| 0
| 1
|
32
| 3
| 4
| 3
| 1
| 21,467
| 3
| 4
| 12
|
Company Invited
| 3
|
Small Business
|
Female
|
Married
|
Executive
|
Basic
| 0
| 0
|
34
| 4
| 4
| 8
| 3
| 30,556
| 3
| 4
| 12
|
Company Invited
| 1
|
Salaried
|
Female
|
Divorced
|
Senior Manager
|
Standard
| 0
| 1
|
50
| 3
| 3
| 4
| 2
| 28,973
| 4
| 3
| 30
|
Self Enquiry
| 1
|
Salaried
|
Male
|
Married
|
AVP
|
Super Deluxe
| 1
| 1
|
33
| 3
| 5
| 4
| 0
| 17,799
| 4
| 4
| 6
|
Self Enquiry
| 1
|
Salaried
|
Male
|
Single
|
Executive
|
Basic
| 1
| 0
|
36
| 3
| 3
| 3
| 1
| 23,646
| 5
| 4
| 18
|
Company Invited
| 3
|
Small Business
|
Male
|
Married
|
Manager
|
Deluxe
| 0
| 0
|
50
| 4
| 3
| 3
| 2
| 25,482
| 2
| 4
| 25
|
Company Invited
| 1
|
Salaried
|
Male
|
Married
|
Manager
|
Deluxe
| 1
| 0
|
49
| 4
| 3
| 4
| 2
| 21,333
| 4
| 4
| 14
|
Company Invited
| 3
|
Small Business
|
Female
|
Married
|
Executive
|
Basic
| 1
| 1
|
37
| 3
| 5
| 4
| 1
| 23,317
| 1
| 2
| 14
|
Company Invited
| 3
|
Small Business
|
Female
|
Divorced
|
Manager
|
Deluxe
| 0
| 1
|
30
| 3
| 3
| 2
| 0
| 17,632
| 2
| 3
| 24
|
Self Enquiry
| 1
|
Salaried
|
Female
|
Single
|
Executive
|
Basic
| 0
| 1
|
23
| 4
| 3
| 2
| 3
| 22,053
| 3
| 4
| 7
|
Self Enquiry
| 1
|
Salaried
|
Male
|
Unmarried
|
Executive
|
Basic
| 0
| 0
|
34
| 3
| 4
| 3
| 0
| 17,311
| 3
| 3
| 33
|
Self Enquiry
| 1
|
Small Business
|
Female
|
Single
|
Executive
|
Basic
| 0
| 0
|
52
| 4
| 3
| 2
| 3
| 24,119
| 5
| 4
| 28
|
Self Enquiry
| 3
|
Small Business
|
Male
|
Unmarried
|
Manager
|
Deluxe
| 1
| 0
|
27
| 4
| 5
| 2
| 1
| 23,647
| 3
| 6
| 36
|
Company Invited
| 3
|
Small Business
|
Male
|
Unmarried
|
Manager
|
Deluxe
| 0
| 0
|
40
| 3
| 4
| 5
| 2
| 28,194
| 3
| 1
| 30
|
Company Invited
| 3
|
Salaried
|
Fe Male
|
Unmarried
|
AVP
|
Super Deluxe
| 1
| 1
|
44
| 3
| 3
| 2
| 0
| 17,011
| 4
| 1
| 8
|
Self Enquiry
| 1
|
Salaried
|
Female
|
Divorced
|
Executive
|
Basic
| 0
| 1
|
27
| 3
| 5
| 8
| 1
| 20,720
| 5
| 4
| 9
|
Company Invited
| 1
|
Salaried
|
Male
|
Married
|
Executive
|
Basic
| 1
| 0
|
42
| 4
| 5
| 8
| 1
| 20,785
| 3
| 5
| 12
|
Company Invited
| 1
|
Salaried
|
Male
|
Married
|
Executive
|
Basic
| 0
| 1
|
28
| 3
| 5
| 2
| 2
| 21,719
| 5
| 4
| 9
|
Self Enquiry
| 3
|
Small Business
|
Male
|
Married
|
Executive
|
Basic
| 0
| 0
|
59
| 3
| 4
| 4
| 2
| 29,230
| 5
| 5
| 12
|
Self Enquiry
| 1
|
Large Business
|
Female
|
Married
|
Senior Manager
|
Standard
| 1
| 1
|
40
| 3
| 3
| 5
| 2
| 24,798
| 1
| 5
| 28
|
Self Enquiry
| 3
|
Salaried
|
Male
|
Divorced
|
Manager
|
Deluxe
| 1
| 0
|
29
| 3
| 3
| 3
| 2
| 21,384
| 4
| 4
| 7
|
Company Invited
| 2
|
Salaried
|
Male
|
Married
|
Executive
|
Basic
| 0
| 0
|
35
| 3
| 5
| 5
| 1
| 23,799
| 5
| 4
| 15
|
Self Enquiry
| 1
|
Salaried
|
Female
|
Married
|
Manager
|
Deluxe
| 0
| 1
|
34
| 2
| 3
| 2
| 0
| 17,742
| 1
| 3
| 15
|
Self Enquiry
| 2
|
Large Business
|
Female
|
Divorced
|
Executive
|
Basic
| 0
| 1
|
36
| 2
| 3
| 2
| 1
| 20,810
| 5
| 4
| 10
|
Self Enquiry
| 1
|
Salaried
|
Male
|
Single
|
Manager
|
Deluxe
| 0
| 1
|
41
| 3
| 5
| 5
| 0
| 32,181
| 2
| 4
| 16
|
Company Invited
| 1
|
Salaried
|
Male
|
Married
|
AVP
|
Super Deluxe
| 0
| 1
|
46
| 2
| 5
| 3
| 1
| 25,673
| 1
| 4
| 6
|
Company Invited
| 1
|
Small Business
|
Male
|
Married
|
Senior Manager
|
Standard
| 1
| 1
|
27
| 3
| 3
| 7
| 1
| 22,984
| 5
| 4
| 36
|
Self Enquiry
| 3
|
Small Business
|
Male
|
Married
|
Manager
|
Deluxe
| 0
| 1
|
32
| 4
| 3
| 2
| 1
| 21,469
| 5
| 2
| 27
|
Company Invited
| 3
|
Salaried
|
Male
|
Married
|
Executive
|
Basic
| 0
| 1
|
38
| 4
| 4
| 6
| 2
| 21,700
| 4
| 4
| 26
|
Self Enquiry
| 1
|
Salaried
|
Male
|
Married
|
Executive
|
Basic
| 0
| 0
|
34
| 4
| 4
| 2
| 1
| 24,824
| 1
| 4
| 29
|
Company Invited
| 3
|
Small Business
|
Male
|
Married
|
Manager
|
Deluxe
| 0
| 0
|
51
| 2
| 4
| 2
| 1
| 29,026
| 3
| 3
| 11
|
Self Enquiry
| 2
|
Salaried
|
Male
|
Married
|
AVP
|
Super Deluxe
| 1
| 1
|
40
| 2
| 3
| 1
| 1
| 17,342
| 3
| 4
| 8
|
Self Enquiry
| 1
|
Small Business
|
Female
|
Single
|
Executive
|
Basic
| 1
| 1
|
49
| 2
| 3
| 1
| 0
| 25,965
| 1
| 4
| 13
|
Self Enquiry
| 1
|
Salaried
|
Male
|
Unmarried
|
Senior Manager
|
Standard
| 0
| 1
|
48
| 4
| 3
| 6
| 1
| 20,783
| 3
| 4
| 16
|
Self Enquiry
| 1
|
Salaried
|
Female
|
Single
|
Executive
|
Basic
| 0
| 1
|
29
| 2
| 3
| 3
| 0
| 21,931
| 1
| 3
| 26
|
Self Enquiry
| 3
|
Small Business
|
Male
|
Married
|
Manager
|
Deluxe
| 0
| 1
|
25
| 3
| 3
| 2
| 2
| 21,078
| 4
| 4
| 31
|
Company Invited
| 3
|
Small Business
|
Male
|
Married
|
Executive
|
Basic
| 0
| 1
|
35
| 3
| 5
| 4
| 2
| 23,966
| 3
| 3
| 23
|
Self Enquiry
| 3
|
Salaried
|
Male
|
Married
|
Manager
|
Deluxe
| 1
| 0
|
30
| 3
| 4
| 3
| 1
| 26,946
| 5
| 5
| 17
|
Self Enquiry
| 3
|
Small Business
|
Female
|
Married
|
Manager
|
Deluxe
| 1
| 1
|
35
| 2
| 3
| 4
| 0
| 20,916
| 4
| 4
| 29
|
Self Enquiry
| 1
|
Salaried
|
Male
|
Married
|
Manager
|
Deluxe
| 1
| 1
|
36
| 3
| 3
| 5
| 0
| 17,543
| 5
| 3
| 8
|
Self Enquiry
| 1
|
Salaried
|
Female
|
Married
|
Executive
|
Basic
| 0
| 1
|
50
| 2
| 3
| 5
| 1
| 34,331
| 5
| 3
| 5
|
Self Enquiry
| 3
|
Small Business
|
Male
|
Married
|
VP
|
King
| 1
| 0
|
44
| 4
| 3
| 7
| 2
| 29,476
| 4
| 5
| 32
|
Self Enquiry
| 3
|
Small Business
|
Male
|
Married
|
Senior Manager
|
Standard
| 0
| 1
|
38
| 2
| 4
| 1
| 0
| 22,351
| 4
| 3
| 8
|
Self Enquiry
| 3
|
Small Business
|
Male
|
Unmarried
|
Senior Manager
|
Standard
| 0
| 1
|
37
| 4
| 4
| 4
| 3
| 20,691
| 1
| 4
| 14
|
Self Enquiry
| 1
|
Salaried
|
Male
|
Single
|
Executive
|
Basic
| 0
| 0
|
32
| 4
| 5
| 5
| 2
| 25,088
| 3
| 5
| 9
|
Self Enquiry
| 2
|
Salaried
|
Male
|
Divorced
|
Manager
|
Deluxe
| 0
| 0
|
42
| 3
| 3
| 2
| 2
| 24,908
| 2
| 4
| 17
|
Company Invited
| 3
|
Salaried
|
Male
|
Unmarried
|
Manager
|
Deluxe
| 0
| 0
|
50
| 3
| 3
| 2
| 2
| 18,221
| 2
| 2
| 34
|
Self Enquiry
| 1
|
Small Business
|
Male
|
Divorced
|
Executive
|
Basic
| 1
| 1
|
25
| 3
| 3
| 3
| 1
| 21,564
| 4
| 4
| 14
|
Company Invited
| 1
|
Salaried
|
Female
|
Married
|
Executive
|
Basic
| 1
| 0
|
19
| 2
| 5
| 2
| 0
| 17,552
| 3
| 3
| 15
|
Self Enquiry
| 1
|
Salaried
|
Male
|
Single
|
Executive
|
Basic
| 0
| 0
|
41
| 4
| 4
| 4
| 1
| 28,383
| 4
| 5
| 17
|
Self Enquiry
| 3
|
Small Business
|
Male
|
Married
|
Senior Manager
|
Standard
| 0
| 0
|
47
| 3
| 3
| 7
| 1
| 29,205
| 3
| 4
| 25
|
Company Invited
| 1
|
Small Business
|
Female
|
Divorced
|
Senior Manager
|
Standard
| 0
| 1
|
32
| 3
| 3
| 3
| 1
| 25,610
| 2
| 4
| 27
|
Company Invited
| 3
|
Small Business
|
Female
|
Divorced
|
Manager
|
Deluxe
| 0
| 1
|
44
| 2
| 3
| 4
| 1
| 28,320
| 2
| 1
| 34
|
Self Enquiry
| 3
|
Small Business
|
Female
|
Divorced
|
AVP
|
Super Deluxe
| 1
| 1
|
51
| 3
| 4
| 2
| 1
| 22,553
| 2
| 4
| 15
|
Self Enquiry
| 3
|
Small Business
|
Male
|
Divorced
|
Executive
|
Basic
| 0
| 1
|
37
| 2
| 3
| 2
| 0
| 21,474
| 1
| 4
| 7
|
Self Enquiry
| 1
|
Salaried
|
Female
|
Married
|
Manager
|
Deluxe
| 0
| 0
|
36
| 4
| 5
| 3
| 3
| 21,128
| 1
| 5
| 7
|
Self Enquiry
| 1
|
Small Business
|
Male
|
Single
|
Executive
|
Basic
| 0
| 0
|
30
| 4
| 5
| 3
| 2
| 20,797
| 3
| 6
| 15
|
Self Enquiry
| 1
|
Salaried
|
Male
|
Divorced
|
Executive
|
Basic
| 1
| 1
|
43
| 4
| 3
| 2
| 1
| 24,922
| 3
| 5
| 21
|
Self Enquiry
| 3
|
Small Business
|
Fe Male
|
Unmarried
|
Manager
|
Deluxe
| 0
| 1
|
28
| 4
| 3
| 3
| 2
| 23,156
| 4
| 4
| 9
|
Self Enquiry
| 3
|
Salaried
|
Male
|
Unmarried
|
Manager
|
Deluxe
| 1
| 0
|
33
| 3
| 5
| 6
| 2
| 20,854
| 4
| 5
| 9
|
Self Enquiry
| 1
|
Large Business
|
Male
|
Single
|
Manager
|
Deluxe
| 0
| 0
|
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