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 3 new columns ({'Unnamed: 0', 'CustomerID', 'ProdTaken'})
This happened while the csv dataset builder was generating data using
hf://datasets/subhash33/tourism-package/tourism.csv (at revision 1e0da420ef21220ec4ba463b5ad96993c5c2faf8)
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
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
{'Age': Value('int64'), 'CityTier': Value('int64'), 'DurationOfPitch': Value('int64'), 'NumberOfPersonVisiting': Value('int64'), 'NumberOfFollowups': Value('int64'), 'PreferredPropertyStar': Value('int64'), 'NumberOfTrips': Value('int64'), 'Passport': Value('int64'), 'PitchSatisfactionScore': Value('int64'), 'OwnCar': Value('int64'), 'NumberOfChildrenVisiting': Value('int64'), 'MonthlyIncome': Value('int64'), 'TypeofContact': Value('string'), 'Occupation': Value('string'), 'Gender': Value('string'), 'ProductPitched': Value('string'), 'MaritalStatus': Value('string'), 'Designation': Value('string')}
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 3 new columns ({'Unnamed: 0', 'CustomerID', 'ProdTaken'})
This happened while the csv dataset builder was generating data using
hf://datasets/subhash33/tourism-package/tourism.csv (at revision 1e0da420ef21220ec4ba463b5ad96993c5c2faf8)
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
int64 | CityTier
int64 | DurationOfPitch
int64 | NumberOfPersonVisiting
int64 | NumberOfFollowups
int64 | PreferredPropertyStar
int64 | NumberOfTrips
int64 | Passport
int64 | PitchSatisfactionScore
int64 | OwnCar
int64 | NumberOfChildrenVisiting
int64 | MonthlyIncome
int64 | TypeofContact
string | Occupation
string | Gender
string | ProductPitched
string | MaritalStatus
string | Designation
string |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
34
| 1
| 9
| 2
| 4
| 3
| 4
| 0
| 1
| 0
| 0
| 17,979
|
Company Invited
|
Salaried
|
Male
|
Basic
|
Married
|
Executive
|
32
| 1
| 6
| 3
| 3
| 4
| 2
| 0
| 3
| 0
| 0
| 21,220
|
Self Enquiry
|
Salaried
|
Male
|
Deluxe
|
Divorced
|
Manager
|
30
| 3
| 11
| 2
| 3
| 3
| 3
| 0
| 4
| 1
| 1
| 24,419
|
Self Enquiry
|
Salaried
|
Female
|
Standard
|
Divorced
|
Senior Manager
|
39
| 3
| 9
| 3
| 4
| 4
| 2
| 0
| 4
| 1
| 2
| 26,029
|
Self Enquiry
|
Small Business
|
Male
|
Standard
|
Unmarried
|
Senior Manager
|
37
| 1
| 31
| 3
| 4
| 4
| 2
| 0
| 3
| 1
| 2
| 24,352
|
Company Invited
|
Salaried
|
Female
|
Deluxe
|
Married
|
Manager
|
34
| 1
| 9
| 3
| 4
| 3
| 2
| 0
| 3
| 0
| 2
| 21,178
|
Self Enquiry
|
Salaried
|
Male
|
Basic
|
Single
|
Executive
|
27
| 1
| 7
| 4
| 6
| 3
| 5
| 0
| 4
| 1
| 3
| 23,042
|
Company Invited
|
Salaried
|
Female
|
Basic
|
Married
|
Executive
|
30
| 3
| 6
| 3
| 4
| 5
| 2
| 0
| 4
| 1
| 1
| 24,714
|
Self Enquiry
|
Salaried
|
Male
|
Deluxe
|
Married
|
Manager
|
53
| 1
| 32
| 3
| 5
| 3
| 5
| 0
| 5
| 0
| 2
| 32,504
|
Company Invited
|
Small Business
|
Female
|
Super Deluxe
|
Married
|
AVP
|
55
| 1
| 7
| 3
| 4
| 3
| 2
| 0
| 5
| 1
| 2
| 29,180
|
Company Invited
|
Salaried
|
Female
|
Standard
|
Married
|
Senior Manager
|
46
| 1
| 6
| 2
| 4
| 5
| 3
| 1
| 2
| 1
| 1
| 25,673
|
Company Invited
|
Small Business
|
Male
|
Standard
|
Divorced
|
Senior Manager
|
39
| 1
| 19
| 2
| 5
| 5
| 4
| 0
| 5
| 1
| 1
| 24,966
|
Company Invited
|
Salaried
|
Male
|
Deluxe
|
Married
|
Manager
|
54
| 2
| 32
| 1
| 2
| 3
| 3
| 1
| 3
| 1
| 0
| 32,328
|
Company Invited
|
Salaried
|
Female
|
Super Deluxe
|
Single
|
AVP
|
42
| 1
| 19
| 3
| 1
| 5
| 6
| 0
| 4
| 1
| 0
| 20,538
|
Self Enquiry
|
Small Business
|
Male
|
Deluxe
|
Married
|
Manager
|
33
| 1
| 12
| 3
| 2
| 3
| 5
| 0
| 5
| 1
| 2
| 21,990
|
Self Enquiry
|
Salaried
|
Female
|
Basic
|
Married
|
Executive
|
35
| 1
| 6
| 1
| 4
| 3
| 2
| 0
| 4
| 1
| 0
| 17,859
|
Self Enquiry
|
Small Business
|
Male
|
Basic
|
Single
|
Executive
|
39
| 1
| 16
| 3
| 3
| 3
| 1
| 0
| 3
| 1
| 0
| 28,464
|
Self Enquiry
|
Small Business
|
Male
|
Standard
|
Unmarried
|
Senior Manager
|
29
| 1
| 17
| 3
| 4
| 3
| 5
| 0
| 4
| 1
| 2
| 22,338
|
Self Enquiry
|
Salaried
|
Female
|
Deluxe
|
Unmarried
|
Manager
|
23
| 1
| 11
| 3
| 5
| 3
| 7
| 0
| 5
| 1
| 1
| 22,572
|
Company Invited
|
Large Business
|
Male
|
Basic
|
Unmarried
|
Executive
|
37
| 1
| 15
| 2
| 3
| 3
| 2
| 1
| 2
| 0
| 0
| 17,326
|
Company Invited
|
Small Business
|
Male
|
Basic
|
Divorced
|
Executive
|
33
| 1
| 10
| 4
| 4
| 5
| 3
| 0
| 1
| 1
| 1
| 25,403
|
Self Enquiry
|
Small Business
|
Female
|
Deluxe
|
Married
|
Manager
|
33
| 1
| 7
| 4
| 4
| 5
| 3
| 0
| 1
| 0
| 2
| 21,634
|
Self Enquiry
|
Salaried
|
Male
|
Basic
|
Unmarried
|
Executive
|
50
| 1
| 25
| 4
| 4
| 3
| 3
| 1
| 1
| 0
| 1
| 25,482
|
Company Invited
|
Salaried
|
Male
|
Deluxe
|
Married
|
Manager
|
42
| 1
| 6
| 2
| 4
| 3
| 1
| 1
| 3
| 0
| 0
| 21,062
|
Self Enquiry
|
Salaried
|
Female
|
Deluxe
|
Married
|
Manager
|
43
| 1
| 33
| 3
| 4
| 5
| 5
| 1
| 3
| 0
| 1
| 31,869
|
Company Invited
|
Small Business
|
Female
|
Standard
|
Married
|
Senior Manager
|
36
| 1
| 15
| 3
| 1
| 4
| 2
| 0
| 5
| 1
| 0
| 17,810
|
Company Invited
|
Salaried
|
Male
|
Basic
|
Married
|
Executive
|
27
| 3
| 8
| 2
| 1
| 3
| 1
| 0
| 1
| 0
| 1
| 21,500
|
Self Enquiry
|
Small Business
|
Female
|
Deluxe
|
Unmarried
|
Manager
|
29
| 3
| 16
| 4
| 4
| 3
| 3
| 0
| 3
| 1
| 2
| 23,931
|
Self Enquiry
|
Salaried
|
Male
|
Deluxe
|
Unmarried
|
Manager
|
34
| 1
| 12
| 4
| 5
| 3
| 3
| 0
| 2
| 0
| 3
| 21,589
|
Self Enquiry
|
Salaried
|
Female
|
Basic
|
Divorced
|
Executive
|
41
| 3
| 21
| 3
| 4
| 5
| 3
| 0
| 3
| 0
| 2
| 23,317
|
Self Enquiry
|
Salaried
|
Female
|
Deluxe
|
Married
|
Manager
|
32
| 3
| 20
| 4
| 5
| 5
| 7
| 1
| 1
| 1
| 1
| 20,980
|
Self Enquiry
|
Small Business
|
Male
|
Deluxe
|
Married
|
Manager
|
50
| 2
| 9
| 3
| 3
| 4
| 2
| 0
| 1
| 1
| 2
| 33,200
|
Company Invited
|
Small Business
|
Male
|
King
|
Married
|
VP
|
24
| 3
| 30
| 2
| 3
| 3
| 1
| 0
| 4
| 1
| 1
| 17,400
|
Company Invited
|
Small Business
|
Male
|
Basic
|
Married
|
Executive
|
43
| 1
| 7
| 3
| 5
| 3
| 2
| 1
| 3
| 0
| 1
| 24,740
|
Self Enquiry
|
Salaried
|
Female
|
Deluxe
|
Married
|
Manager
|
39
| 1
| 16
| 3
| 3
| 5
| 3
| 0
| 5
| 1
| 2
| 20,377
|
Self Enquiry
|
Small Business
|
Male
|
Deluxe
|
Married
|
Manager
|
55
| 1
| 6
| 2
| 3
| 5
| 1
| 1
| 1
| 1
| 1
| 34,045
|
Self Enquiry
|
Small Business
|
Male
|
King
|
Single
|
VP
|
33
| 1
| 10
| 3
| 4
| 3
| 3
| 0
| 4
| 1
| 1
| 24,887
|
Company Invited
|
Salaried
|
Female
|
Basic
|
Unmarried
|
Executive
|
34
| 3
| 23
| 4
| 4
| 5
| 4
| 1
| 5
| 0
| 1
| 27,242
|
Self Enquiry
|
Salaried
|
Female
|
Standard
|
Unmarried
|
Senior Manager
|
25
| 1
| 25
| 3
| 4
| 3
| 2
| 0
| 4
| 0
| 1
| 21,452
|
Self Enquiry
|
Salaried
|
Male
|
Basic
|
Married
|
Executive
|
30
| 1
| 24
| 3
| 3
| 3
| 2
| 0
| 1
| 1
| 2
| 17,632
|
Self Enquiry
|
Salaried
|
Female
|
Basic
|
Single
|
Executive
|
32
| 3
| 12
| 3
| 4
| 4
| 3
| 0
| 3
| 0
| 1
| 21,467
|
Company Invited
|
Small Business
|
Female
|
Basic
|
Married
|
Executive
|
34
| 1
| 12
| 4
| 4
| 4
| 8
| 0
| 3
| 1
| 3
| 30,556
|
Company Invited
|
Salaried
|
Female
|
Standard
|
Divorced
|
Senior Manager
|
50
| 1
| 30
| 3
| 3
| 3
| 4
| 1
| 4
| 1
| 2
| 28,973
|
Self Enquiry
|
Salaried
|
Male
|
Super Deluxe
|
Married
|
AVP
|
33
| 1
| 6
| 3
| 4
| 5
| 4
| 1
| 4
| 0
| 0
| 17,799
|
Self Enquiry
|
Salaried
|
Male
|
Basic
|
Single
|
Executive
|
36
| 3
| 18
| 3
| 4
| 3
| 3
| 0
| 5
| 0
| 1
| 23,646
|
Company Invited
|
Small Business
|
Male
|
Deluxe
|
Married
|
Manager
|
50
| 1
| 25
| 4
| 4
| 3
| 3
| 1
| 2
| 0
| 2
| 25,482
|
Company Invited
|
Salaried
|
Male
|
Deluxe
|
Married
|
Manager
|
49
| 3
| 14
| 4
| 4
| 3
| 4
| 1
| 4
| 1
| 2
| 21,333
|
Company Invited
|
Small Business
|
Female
|
Basic
|
Married
|
Executive
|
37
| 3
| 14
| 3
| 2
| 5
| 4
| 0
| 1
| 1
| 1
| 23,317
|
Company Invited
|
Small Business
|
Female
|
Deluxe
|
Divorced
|
Manager
|
30
| 1
| 24
| 3
| 3
| 3
| 2
| 0
| 2
| 1
| 0
| 17,632
|
Self Enquiry
|
Salaried
|
Female
|
Basic
|
Single
|
Executive
|
23
| 1
| 7
| 4
| 4
| 3
| 2
| 0
| 3
| 0
| 3
| 22,053
|
Self Enquiry
|
Salaried
|
Male
|
Basic
|
Unmarried
|
Executive
|
34
| 1
| 33
| 3
| 3
| 4
| 3
| 0
| 3
| 0
| 0
| 17,311
|
Self Enquiry
|
Small Business
|
Female
|
Basic
|
Single
|
Executive
|
52
| 3
| 28
| 4
| 4
| 3
| 2
| 1
| 5
| 0
| 3
| 24,119
|
Self Enquiry
|
Small Business
|
Male
|
Deluxe
|
Unmarried
|
Manager
|
27
| 3
| 36
| 4
| 6
| 5
| 2
| 0
| 3
| 0
| 1
| 23,647
|
Company Invited
|
Small Business
|
Male
|
Deluxe
|
Unmarried
|
Manager
|
40
| 3
| 30
| 3
| 1
| 4
| 5
| 1
| 3
| 1
| 2
| 28,194
|
Company Invited
|
Salaried
|
Female
|
Super Deluxe
|
Unmarried
|
AVP
|
44
| 1
| 8
| 3
| 1
| 3
| 2
| 0
| 4
| 1
| 0
| 17,011
|
Self Enquiry
|
Salaried
|
Female
|
Basic
|
Divorced
|
Executive
|
27
| 1
| 9
| 3
| 4
| 5
| 8
| 1
| 5
| 0
| 1
| 20,720
|
Company Invited
|
Salaried
|
Male
|
Basic
|
Married
|
Executive
|
42
| 1
| 12
| 4
| 5
| 5
| 8
| 0
| 3
| 1
| 1
| 20,785
|
Company Invited
|
Salaried
|
Male
|
Basic
|
Married
|
Executive
|
28
| 3
| 9
| 3
| 4
| 5
| 2
| 0
| 5
| 0
| 2
| 21,719
|
Self Enquiry
|
Small Business
|
Male
|
Basic
|
Married
|
Executive
|
59
| 1
| 12
| 3
| 5
| 4
| 4
| 1
| 5
| 1
| 2
| 29,230
|
Self Enquiry
|
Large Business
|
Female
|
Standard
|
Married
|
Senior Manager
|
40
| 3
| 28
| 3
| 5
| 3
| 5
| 1
| 1
| 0
| 2
| 24,798
|
Self Enquiry
|
Salaried
|
Male
|
Deluxe
|
Divorced
|
Manager
|
29
| 2
| 7
| 3
| 4
| 3
| 3
| 0
| 4
| 0
| 2
| 21,384
|
Company Invited
|
Salaried
|
Male
|
Basic
|
Married
|
Executive
|
35
| 1
| 15
| 3
| 4
| 5
| 5
| 0
| 5
| 1
| 1
| 23,799
|
Self Enquiry
|
Salaried
|
Female
|
Deluxe
|
Married
|
Manager
|
34
| 2
| 15
| 2
| 3
| 3
| 2
| 0
| 1
| 1
| 0
| 17,742
|
Self Enquiry
|
Large Business
|
Female
|
Basic
|
Divorced
|
Executive
|
36
| 1
| 10
| 2
| 4
| 3
| 2
| 0
| 5
| 1
| 1
| 20,810
|
Self Enquiry
|
Salaried
|
Male
|
Deluxe
|
Single
|
Manager
|
41
| 1
| 16
| 3
| 4
| 5
| 5
| 0
| 2
| 1
| 0
| 32,181
|
Company Invited
|
Salaried
|
Male
|
Super Deluxe
|
Married
|
AVP
|
46
| 1
| 6
| 2
| 4
| 5
| 3
| 1
| 1
| 1
| 1
| 25,673
|
Company Invited
|
Small Business
|
Male
|
Standard
|
Married
|
Senior Manager
|
27
| 3
| 36
| 3
| 4
| 3
| 7
| 0
| 5
| 1
| 1
| 22,984
|
Self Enquiry
|
Small Business
|
Male
|
Deluxe
|
Married
|
Manager
|
32
| 3
| 27
| 4
| 2
| 3
| 2
| 0
| 5
| 1
| 1
| 21,469
|
Company Invited
|
Salaried
|
Male
|
Basic
|
Married
|
Executive
|
38
| 1
| 26
| 4
| 4
| 4
| 6
| 0
| 4
| 0
| 2
| 21,700
|
Self Enquiry
|
Salaried
|
Male
|
Basic
|
Married
|
Executive
|
34
| 3
| 29
| 4
| 4
| 4
| 2
| 0
| 1
| 0
| 1
| 24,824
|
Company Invited
|
Small Business
|
Male
|
Deluxe
|
Married
|
Manager
|
51
| 2
| 11
| 2
| 3
| 4
| 2
| 1
| 3
| 1
| 1
| 29,026
|
Self Enquiry
|
Salaried
|
Male
|
Super Deluxe
|
Married
|
AVP
|
40
| 1
| 8
| 2
| 4
| 3
| 1
| 1
| 3
| 1
| 1
| 17,342
|
Self Enquiry
|
Small Business
|
Female
|
Basic
|
Single
|
Executive
|
49
| 1
| 13
| 2
| 4
| 3
| 1
| 0
| 1
| 1
| 0
| 25,965
|
Self Enquiry
|
Salaried
|
Male
|
Standard
|
Unmarried
|
Senior Manager
|
48
| 1
| 16
| 4
| 4
| 3
| 6
| 0
| 3
| 1
| 1
| 20,783
|
Self Enquiry
|
Salaried
|
Female
|
Basic
|
Single
|
Executive
|
29
| 3
| 26
| 2
| 3
| 3
| 3
| 0
| 1
| 1
| 0
| 21,931
|
Self Enquiry
|
Small Business
|
Male
|
Deluxe
|
Married
|
Manager
|
25
| 3
| 31
| 3
| 4
| 3
| 2
| 0
| 4
| 1
| 2
| 21,078
|
Company Invited
|
Small Business
|
Male
|
Basic
|
Married
|
Executive
|
35
| 3
| 23
| 3
| 3
| 5
| 4
| 1
| 3
| 0
| 2
| 23,966
|
Self Enquiry
|
Salaried
|
Male
|
Deluxe
|
Married
|
Manager
|
30
| 3
| 17
| 3
| 5
| 4
| 3
| 1
| 5
| 1
| 1
| 26,946
|
Self Enquiry
|
Small Business
|
Female
|
Deluxe
|
Married
|
Manager
|
35
| 1
| 29
| 2
| 4
| 3
| 4
| 1
| 4
| 1
| 0
| 20,916
|
Self Enquiry
|
Salaried
|
Male
|
Deluxe
|
Married
|
Manager
|
36
| 1
| 8
| 3
| 3
| 3
| 5
| 0
| 5
| 1
| 0
| 17,543
|
Self Enquiry
|
Salaried
|
Female
|
Basic
|
Married
|
Executive
|
50
| 3
| 5
| 2
| 3
| 3
| 5
| 1
| 5
| 0
| 1
| 34,331
|
Self Enquiry
|
Small Business
|
Male
|
King
|
Married
|
VP
|
44
| 3
| 32
| 4
| 5
| 3
| 7
| 0
| 4
| 1
| 2
| 29,476
|
Self Enquiry
|
Small Business
|
Male
|
Standard
|
Married
|
Senior Manager
|
38
| 3
| 8
| 2
| 3
| 4
| 1
| 0
| 4
| 1
| 0
| 22,351
|
Self Enquiry
|
Small Business
|
Male
|
Standard
|
Unmarried
|
Senior Manager
|
37
| 1
| 14
| 4
| 4
| 4
| 4
| 0
| 1
| 0
| 3
| 20,691
|
Self Enquiry
|
Salaried
|
Male
|
Basic
|
Single
|
Executive
|
32
| 2
| 9
| 4
| 5
| 5
| 5
| 0
| 3
| 0
| 2
| 25,088
|
Self Enquiry
|
Salaried
|
Male
|
Deluxe
|
Divorced
|
Manager
|
42
| 3
| 17
| 3
| 4
| 3
| 2
| 0
| 2
| 0
| 2
| 24,908
|
Company Invited
|
Salaried
|
Male
|
Deluxe
|
Unmarried
|
Manager
|
50
| 1
| 34
| 3
| 2
| 3
| 2
| 1
| 2
| 1
| 2
| 18,221
|
Self Enquiry
|
Small Business
|
Male
|
Basic
|
Divorced
|
Executive
|
25
| 1
| 14
| 3
| 4
| 3
| 3
| 1
| 4
| 0
| 1
| 21,564
|
Company Invited
|
Salaried
|
Female
|
Basic
|
Married
|
Executive
|
19
| 1
| 15
| 2
| 3
| 5
| 2
| 0
| 3
| 0
| 0
| 17,552
|
Self Enquiry
|
Salaried
|
Male
|
Basic
|
Single
|
Executive
|
41
| 3
| 17
| 4
| 5
| 4
| 4
| 0
| 4
| 0
| 1
| 28,383
|
Self Enquiry
|
Small Business
|
Male
|
Standard
|
Married
|
Senior Manager
|
47
| 1
| 25
| 3
| 4
| 3
| 7
| 0
| 3
| 1
| 1
| 29,205
|
Company Invited
|
Small Business
|
Female
|
Standard
|
Divorced
|
Senior Manager
|
32
| 3
| 27
| 3
| 4
| 3
| 3
| 0
| 2
| 1
| 1
| 25,610
|
Company Invited
|
Small Business
|
Female
|
Deluxe
|
Divorced
|
Manager
|
44
| 3
| 34
| 2
| 1
| 3
| 4
| 1
| 2
| 1
| 1
| 28,320
|
Self Enquiry
|
Small Business
|
Female
|
Super Deluxe
|
Divorced
|
AVP
|
51
| 3
| 15
| 3
| 4
| 4
| 2
| 0
| 2
| 1
| 1
| 22,553
|
Self Enquiry
|
Small Business
|
Male
|
Basic
|
Divorced
|
Executive
|
37
| 1
| 7
| 2
| 4
| 3
| 2
| 0
| 1
| 0
| 0
| 21,474
|
Self Enquiry
|
Salaried
|
Female
|
Deluxe
|
Married
|
Manager
|
36
| 1
| 7
| 4
| 5
| 5
| 3
| 0
| 1
| 0
| 3
| 21,128
|
Self Enquiry
|
Small Business
|
Male
|
Basic
|
Single
|
Executive
|
30
| 1
| 15
| 4
| 6
| 5
| 3
| 1
| 3
| 1
| 2
| 20,797
|
Self Enquiry
|
Salaried
|
Male
|
Basic
|
Divorced
|
Executive
|
43
| 3
| 21
| 4
| 5
| 3
| 2
| 0
| 3
| 1
| 1
| 24,922
|
Self Enquiry
|
Small Business
|
Female
|
Deluxe
|
Unmarried
|
Manager
|
28
| 3
| 9
| 4
| 4
| 3
| 3
| 1
| 4
| 0
| 2
| 23,156
|
Self Enquiry
|
Salaried
|
Male
|
Deluxe
|
Unmarried
|
Manager
|
33
| 1
| 9
| 3
| 5
| 5
| 6
| 0
| 4
| 0
| 2
| 20,854
|
Self Enquiry
|
Large Business
|
Male
|
Deluxe
|
Single
|
Manager
|
End of preview.