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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'}) and 22 missing columns ({'DurationOfPitch', 'NumberOfPersonVisiting', 'Designation', 'Passport', 'HasChildren', 'CityTier', 'Occupation', 'MonthlyIncome', 'NumberOfChildrenVisiting', 'ProductPitched', 'PreferredPropertyStar', 'TypeofContact', 'NumberOfTrips', 'OwnCar', 'MaritalStatus', 'PitchSatisfactionScore', 'NumberOfFollowups', 'Gender', 'AgeGroup', 'IncomeCategory', 'PitchPeriodCategory', 'Age'}).
This happened while the csv dataset builder was generating data using
hf://datasets/supravab/Tourism_Package_Prediction/y_train.csv (at revision 4a74df6ebde5a60f722004af371b282ad6a6ff38)
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
ProdTaken: int64
-- schema metadata --
pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 377
to
{'Age': Value('int64'), 'TypeofContact': Value('string'), 'CityTier': Value('int64'), 'DurationOfPitch': Value('int64'), 'Occupation': Value('string'), 'Gender': Value('string'), 'NumberOfPersonVisiting': Value('int64'), 'NumberOfFollowups': Value('int64'), 'ProductPitched': Value('string'), 'PreferredPropertyStar': Value('int64'), 'MaritalStatus': Value('string'), 'NumberOfTrips': Value('int64'), 'Passport': Value('int64'), 'PitchSatisfactionScore': Value('int64'), 'OwnCar': Value('int64'), 'NumberOfChildrenVisiting': Value('int64'), 'Designation': Value('string'), 'MonthlyIncome': Value('int64'), 'HasChildren': Value('int64'), 'AgeGroup': Value('string'), 'IncomeCategory': Value('string'), 'PitchPeriodCategory': 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 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'}) and 22 missing columns ({'DurationOfPitch', 'NumberOfPersonVisiting', 'Designation', 'Passport', 'HasChildren', 'CityTier', 'Occupation', 'MonthlyIncome', 'NumberOfChildrenVisiting', 'ProductPitched', 'PreferredPropertyStar', 'TypeofContact', 'NumberOfTrips', 'OwnCar', 'MaritalStatus', 'PitchSatisfactionScore', 'NumberOfFollowups', 'Gender', 'AgeGroup', 'IncomeCategory', 'PitchPeriodCategory', 'Age'}).
This happened while the csv dataset builder was generating data using
hf://datasets/supravab/Tourism_Package_Prediction/y_train.csv (at revision 4a74df6ebde5a60f722004af371b282ad6a6ff38)
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 | 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 | HasChildren
int64 | AgeGroup
string | IncomeCategory
string | PitchPeriodCategory
string |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
36
|
Self Enquiry
| 1
| 30
|
Small Business
|
Male
| 4
| 6
|
Basic
| 3
|
Married
| 2
| 0
| 1
| 1
| 1
|
Executive
| 21,383
| 1
|
Adult
|
Mid
|
Long
|
38
|
Company Invited
| 1
| 7
|
Small Business
|
Female
| 2
| 4
|
Standard
| 3
|
Married
| 4
| 1
| 3
| 0
| 1
|
Senior Manager
| 32,281
| 1
|
Adult
|
High
|
Short
|
54
|
Self Enquiry
| 3
| 9
|
Salaried
|
Female
| 4
| 5
|
Super Deluxe
| 3
|
Married
| 4
| 0
| 3
| 0
| 1
|
AVP
| 34,105
| 1
|
Old
|
High
|
Short
|
42
|
Self Enquiry
| 1
| 30
|
Small Business
|
Male
| 2
| 3
|
Standard
| 5
|
Married
| 2
| 1
| 1
| 1
| 0
|
Senior Manager
| 22,406
| 0
|
Old
|
Mid
|
Long
|
36
|
Self Enquiry
| 3
| 8
|
Salaried
|
Male
| 3
| 3
|
Basic
| 3
|
Unmarried
| 4
| 1
| 3
| 0
| 0
|
Executive
| 17,644
| 0
|
Adult
|
Low
|
Short
|
51
|
Company Invited
| 3
| 8
|
Small Business
|
Male
| 2
| 3
|
Standard
| 4
|
Divorced
| 3
| 0
| 4
| 0
| 0
|
Senior Manager
| 25,596
| 0
|
Old
|
Mid
|
Short
|
40
|
Self Enquiry
| 1
| 13
|
Small Business
|
Male
| 3
| 5
|
Standard
| 5
|
Married
| 6
| 0
| 4
| 1
| 1
|
Senior Manager
| 28,669
| 1
|
Adult
|
Mid
|
Long
|
34
|
Self Enquiry
| 1
| 15
|
Salaried
|
Male
| 4
| 4
|
Deluxe
| 3
|
Unmarried
| 4
| 1
| 3
| 0
| 3
|
Manager
| 25,066
| 1
|
Adult
|
Mid
|
Long
|
28
|
Self Enquiry
| 1
| 35
|
Salaried
|
Male
| 3
| 5
|
Deluxe
| 4
|
Divorced
| 2
| 0
| 1
| 1
| 2
|
Manager
| 21,549
| 1
|
Adult
|
Mid
|
High
|
53
|
Self Enquiry
| 1
| 10
|
Small Business
|
Male
| 3
| 5
|
Standard
| 3
|
Married
| 4
| 1
| 1
| 1
| 1
|
Senior Manager
| 26,647
| 1
|
Old
|
Mid
|
Short
|
46
|
Self Enquiry
| 1
| 13
|
Salaried
|
Male
| 3
| 4
|
Standard
| 5
|
Divorced
| 6
| 1
| 3
| 0
| 1
|
Senior Manager
| 31,923
| 1
|
Old
|
High
|
Long
|
36
|
Self Enquiry
| 1
| 15
|
Salaried
|
Male
| 3
| 2
|
Basic
| 3
|
Married
| 3
| 0
| 5
| 1
| 2
|
Executive
| 20,947
| 1
|
Adult
|
Mid
|
Long
|
28
|
Self Enquiry
| 1
| 13
|
Salaried
|
Male
| 3
| 5
|
Basic
| 3
|
Divorced
| 3
| 0
| 2
| 1
| 2
|
Executive
| 21,217
| 1
|
Adult
|
Mid
|
Long
|
36
|
Self Enquiry
| 1
| 16
|
Salaried
|
Female
| 4
| 5
|
Standard
| 3
|
Married
| 3
| 1
| 4
| 1
| 3
|
Senior Manager
| 29,363
| 1
|
Adult
|
Mid
|
Long
|
30
|
Company Invited
| 1
| 21
|
Salaried
|
Female
| 3
| 4
|
Standard
| 3
|
Unmarried
| 2
| 1
| 5
| 1
| 1
|
Senior Manager
| 26,231
| 1
|
Adult
|
Mid
|
Long
|
48
|
Self Enquiry
| 1
| 16
|
Salaried
|
Female
| 4
| 4
|
Basic
| 3
|
Unmarried
| 6
| 0
| 3
| 1
| 1
|
Executive
| 20,783
| 1
|
Old
|
Mid
|
Long
|
60
|
Self Enquiry
| 1
| 9
|
Salaried
|
Female
| 4
| 5
|
Super Deluxe
| 3
|
Unmarried
| 5
| 1
| 5
| 0
| 3
|
AVP
| 32,404
| 1
|
Old
|
High
|
Short
|
40
|
Self Enquiry
| 3
| 8
|
Small Business
|
Female
| 3
| 3
|
Deluxe
| 4
|
Married
| 4
| 0
| 3
| 1
| 1
|
Manager
| 20,677
| 1
|
Adult
|
Mid
|
Short
|
38
|
Self Enquiry
| 1
| 17
|
Small Business
|
Female
| 4
| 4
|
Basic
| 4
|
Married
| 3
| 0
| 1
| 1
| 1
|
Executive
| 22,614
| 1
|
Adult
|
Mid
|
Long
|
28
|
Self Enquiry
| 1
| 33
|
Small Business
|
Female
| 2
| 5
|
Deluxe
| 5
|
Married
| 1
| 0
| 4
| 1
| 0
|
Manager
| 20,208
| 0
|
Adult
|
Mid
|
High
|
36
|
Company Invited
| 1
| 24
|
Small Business
|
Female
| 3
| 3
|
Basic
| 3
|
Unmarried
| 2
| 0
| 3
| 1
| 2
|
Executive
| 17,153
| 1
|
Adult
|
Low
|
Long
|
45
|
Self Enquiry
| 1
| 10
|
Salaried
|
Male
| 3
| 4
|
Basic
| 5
|
Divorced
| 6
| 0
| 5
| 1
| 2
|
Executive
| 21,040
| 1
|
Old
|
Mid
|
Short
|
57
|
Self Enquiry
| 1
| 14
|
Salaried
|
Male
| 3
| 6
|
Standard
| 3
|
Unmarried
| 6
| 0
| 1
| 0
| 1
|
Senior Manager
| 25,938
| 1
|
Old
|
Mid
|
Long
|
38
|
Self Enquiry
| 3
| 16
|
Small Business
|
Male
| 3
| 4
|
Standard
| 3
|
Married
| 1
| 1
| 3
| 1
| 1
|
Senior Manager
| 23,740
| 1
|
Adult
|
Mid
|
Long
|
51
|
Self Enquiry
| 1
| 7
|
Small Business
|
Male
| 3
| 5
|
Basic
| 3
|
Married
| 4
| 0
| 3
| 1
| 1
|
Executive
| 22,368
| 1
|
Old
|
Mid
|
Short
|
55
|
Self Enquiry
| 1
| 26
|
Large Business
|
Male
| 2
| 3
|
Deluxe
| 3
|
Divorced
| 4
| 1
| 2
| 1
| 1
|
Manager
| 20,415
| 1
|
Old
|
Mid
|
Long
|
27
|
Self Enquiry
| 1
| 6
|
Salaried
|
Female
| 3
| 3
|
Standard
| 5
|
Married
| 2
| 0
| 4
| 0
| 2
|
Senior Manager
| 22,412
| 1
|
Adult
|
Mid
|
Short
|
39
|
Self Enquiry
| 1
| 7
|
Large Business
|
Female
| 4
| 4
|
Standard
| 5
|
Divorced
| 3
| 0
| 4
| 1
| 3
|
Senior Manager
| 32,260
| 1
|
Adult
|
High
|
Short
|
26
|
Company Invited
| 1
| 6
|
Small Business
|
Female
| 3
| 4
|
Basic
| 3
|
Married
| 2
| 0
| 2
| 1
| 0
|
Executive
| 17,007
| 0
|
Adult
|
Low
|
Short
|
50
|
Self Enquiry
| 1
| 27
|
Small Business
|
Female
| 4
| 4
|
Deluxe
| 5
|
Married
| 3
| 0
| 1
| 1
| 1
|
Manager
| 25,245
| 1
|
Old
|
Mid
|
Long
|
41
|
Company Invited
| 1
| 33
|
Small Business
|
Female
| 3
| 4
|
Deluxe
| 4
|
Married
| 3
| 0
| 1
| 0
| 2
|
Manager
| 24,283
| 1
|
Old
|
Mid
|
High
|
25
|
Company Invited
| 1
| 11
|
Salaried
|
Male
| 3
| 5
|
Basic
| 3
|
Married
| 2
| 0
| 3
| 0
| 2
|
Executive
| 21,840
| 1
|
Adult
|
Mid
|
Long
|
51
|
Self Enquiry
| 1
| 6
|
Salaried
|
Male
| 3
| 3
|
Basic
| 3
|
Divorced
| 2
| 0
| 4
| 1
| 0
|
Executive
| 17,723
| 0
|
Old
|
Low
|
Short
|
33
|
Self Enquiry
| 1
| 8
|
Salaried
|
Male
| 2
| 3
|
Basic
| 3
|
Unmarried
| 1
| 0
| 3
| 1
| 0
|
Executive
| 17,500
| 0
|
Adult
|
Low
|
Short
|
29
|
Self Enquiry
| 1
| 14
|
Salaried
|
Male
| 3
| 5
|
Basic
| 5
|
Divorced
| 2
| 1
| 3
| 1
| 1
|
Executive
| 17,119
| 1
|
Adult
|
Low
|
Long
|
31
|
Company Invited
| 3
| 32
|
Large Business
|
Female
| 3
| 4
|
Deluxe
| 3
|
Married
| 2
| 1
| 3
| 1
| 2
|
Manager
| 23,414
| 1
|
Adult
|
Mid
|
High
|
49
|
Self Enquiry
| 1
| 27
|
Small Business
|
Male
| 3
| 4
|
Basic
| 3
|
Divorced
| 6
| 0
| 2
| 0
| 1
|
Executive
| 20,937
| 1
|
Old
|
Mid
|
Long
|
29
|
Company Invited
| 1
| 7
|
Small Business
|
Male
| 3
| 5
|
Basic
| 4
|
Married
| 3
| 0
| 4
| 1
| 1
|
Executive
| 21,274
| 1
|
Adult
|
Mid
|
Short
|
31
|
Self Enquiry
| 3
| 13
|
Large Business
|
Male
| 3
| 2
|
Deluxe
| 3
|
Divorced
| 5
| 0
| 2
| 1
| 0
|
Manager
| 21,929
| 0
|
Adult
|
Mid
|
Long
|
35
|
Self Enquiry
| 1
| 22
|
Small Business
|
Male
| 2
| 2
|
Basic
| 4
|
Divorced
| 1
| 0
| 3
| 1
| 1
|
Executive
| 17,426
| 1
|
Adult
|
Low
|
Long
|
38
|
Self Enquiry
| 2
| 6
|
Salaried
|
Male
| 2
| 1
|
Basic
| 3
|
Divorced
| 2
| 0
| 4
| 1
| 0
|
Executive
| 17,844
| 0
|
Adult
|
Low
|
Short
|
41
|
Self Enquiry
| 3
| 9
|
Small Business
|
Female
| 4
| 4
|
Deluxe
| 4
|
Married
| 5
| 0
| 3
| 1
| 2
|
Manager
| 24,355
| 1
|
Old
|
Mid
|
Short
|
31
|
Self Enquiry
| 1
| 15
|
Salaried
|
Male
| 2
| 3
|
Standard
| 4
|
Married
| 2
| 0
| 3
| 0
| 0
|
Senior Manager
| 25,648
| 0
|
Adult
|
Mid
|
Long
|
55
|
Self Enquiry
| 1
| 14
|
Small Business
|
Female
| 4
| 4
|
Deluxe
| 3
|
Married
| 6
| 0
| 3
| 1
| 2
|
Manager
| 25,532
| 1
|
Old
|
Mid
|
Long
|
44
|
Company Invited
| 1
| 16
|
Small Business
|
Male
| 4
| 4
|
Deluxe
| 3
|
Married
| 5
| 1
| 3
| 1
| 1
|
Manager
| 24,357
| 1
|
Old
|
Mid
|
Long
|
47
|
Self Enquiry
| 1
| 25
|
Small Business
|
Female
| 3
| 4
|
Deluxe
| 3
|
Married
| 4
| 0
| 5
| 0
| 1
|
Manager
| 23,488
| 1
|
Old
|
Mid
|
Long
|
31
|
Self Enquiry
| 1
| 9
|
Salaried
|
Male
| 5
| 5
|
Deluxe
| 3
|
Married
| 3
| 0
| 4
| 1
| 2
|
Manager
| 22,830
| 1
|
Adult
|
Mid
|
Short
|
50
|
Self Enquiry
| 1
| 14
|
Salaried
|
Male
| 3
| 5
|
Standard
| 3
|
Unmarried
| 2
| 0
| 1
| 1
| 1
|
Senior Manager
| 29,643
| 1
|
Old
|
Mid
|
Long
|
41
|
Self Enquiry
| 1
| 21
|
Small Business
|
Male
| 3
| 5
|
King
| 3
|
Unmarried
| 3
| 0
| 3
| 1
| 2
|
VP
| 38,304
| 1
|
Old
|
High
|
Long
|
58
|
Self Enquiry
| 1
| 29
|
Small Business
|
Female
| 3
| 3
|
Standard
| 3
|
Married
| 2
| 0
| 3
| 1
| 0
|
Senior Manager
| 25,312
| 0
|
Old
|
Mid
|
Long
|
33
|
Self Enquiry
| 1
| 7
|
Salaried
|
Male
| 4
| 4
|
Basic
| 5
|
Unmarried
| 3
| 0
| 2
| 0
| 3
|
Executive
| 21,634
| 1
|
Adult
|
Mid
|
Short
|
45
|
Company Invited
| 1
| 31
|
Salaried
|
Male
| 3
| 4
|
Basic
| 3
|
Married
| 5
| 1
| 5
| 0
| 2
|
Executive
| 21,839
| 1
|
Old
|
Mid
|
High
|
31
|
Company Invited
| 3
| 11
|
Small Business
|
Female
| 2
| 3
|
Basic
| 4
|
Married
| 2
| 0
| 3
| 0
| 0
|
Executive
| 17,789
| 0
|
Adult
|
Low
|
Long
|
42
|
Company Invited
| 2
| 11
|
Salaried
|
Male
| 3
| 6
|
Deluxe
| 4
|
Married
| 8
| 0
| 5
| 0
| 2
|
Manager
| 25,108
| 1
|
Old
|
Mid
|
Long
|
58
|
Self Enquiry
| 1
| 13
|
Small Business
|
Female
| 2
| 4
|
Standard
| 5
|
Divorced
| 1
| 1
| 4
| 1
| 0
|
Senior Manager
| 25,008
| 0
|
Old
|
Mid
|
Long
|
29
|
Self Enquiry
| 1
| 9
|
Small Business
|
Male
| 3
| 4
|
Basic
| 3
|
Unmarried
| 8
| 0
| 3
| 1
| 2
|
Executive
| 23,060
| 1
|
Adult
|
Mid
|
Short
|
42
|
Self Enquiry
| 1
| 12
|
Small Business
|
Male
| 2
| 3
|
Standard
| 5
|
Married
| 1
| 0
| 3
| 1
| 0
|
Senior Manager
| 28,348
| 0
|
Old
|
Mid
|
Long
|
22
|
Self Enquiry
| 1
| 17
|
Small Business
|
Female
| 2
| 3
|
Basic
| 4
|
Married
| 2
| 0
| 1
| 1
| 1
|
Executive
| 17,244
| 1
|
Adult
|
Low
|
Long
|
40
|
Self Enquiry
| 3
| 16
|
Small Business
|
Male
| 3
| 4
|
Standard
| 4
|
Married
| 3
| 0
| 4
| 0
| 0
|
Senior Manager
| 24,705
| 0
|
Adult
|
Mid
|
Long
|
39
|
Company Invited
| 1
| 5
|
Small Business
|
Male
| 2
| 4
|
King
| 3
|
Divorced
| 2
| 0
| 5
| 1
| 1
|
VP
| 34,272
| 1
|
Adult
|
High
|
Short
|
24
|
Self Enquiry
| 3
| 6
|
Large Business
|
Female
| 3
| 3
|
Basic
| 4
|
Unmarried
| 2
| 1
| 4
| 0
| 0
|
Executive
| 18,202
| 0
|
Adult
|
Low
|
Short
|
38
|
Self Enquiry
| 3
| 16
|
Small Business
|
Male
| 3
| 5
|
Deluxe
| 4
|
Married
| 3
| 0
| 4
| 0
| 2
|
Manager
| 22,867
| 1
|
Adult
|
Mid
|
Long
|
28
|
Company Invited
| 1
| 8
|
Small Business
|
Male
| 2
| 4
|
Basic
| 5
|
Unmarried
| 1
| 0
| 4
| 0
| 0
|
Executive
| 17,561
| 0
|
Adult
|
Low
|
Short
|
23
|
Company Invited
| 1
| 23
|
Small Business
|
Male
| 4
| 2
|
Basic
| 3
|
Married
| 3
| 1
| 3
| 0
| 3
|
Executive
| 21,613
| 1
|
Adult
|
Mid
|
Long
|
30
|
Self Enquiry
| 3
| 17
|
Small Business
|
Female
| 3
| 5
|
Deluxe
| 4
|
Married
| 3
| 1
| 5
| 1
| 1
|
Manager
| 26,946
| 1
|
Adult
|
Mid
|
Long
|
26
|
Self Enquiry
| 1
| 26
|
Small Business
|
Male
| 4
| 4
|
Basic
| 3
|
Divorced
| 5
| 0
| 5
| 1
| 3
|
Executive
| 22,347
| 1
|
Adult
|
Mid
|
Long
|
56
|
Self Enquiry
| 1
| 11
|
Salaried
|
Male
| 2
| 4
|
Deluxe
| 3
|
Divorced
| 2
| 1
| 4
| 0
| 1
|
Manager
| 22,713
| 1
|
Old
|
Mid
|
Long
|
30
|
Self Enquiry
| 1
| 17
|
Salaried
|
Female
| 4
| 5
|
Basic
| 5
|
Unmarried
| 8
| 1
| 5
| 1
| 1
|
Executive
| 21,082
| 1
|
Adult
|
Mid
|
Long
|
42
|
Self Enquiry
| 3
| 18
|
Small Business
|
Male
| 3
| 3
|
Deluxe
| 3
|
Married
| 4
| 1
| 1
| 0
| 0
|
Manager
| 20,087
| 0
|
Old
|
Mid
|
Long
|
51
|
Self Enquiry
| 1
| 31
|
Salaried
|
Male
| 4
| 4
|
Super Deluxe
| 3
|
Married
| 5
| 1
| 4
| 1
| 3
|
AVP
| 32,651
| 1
|
Old
|
High
|
High
|
42
|
Self Enquiry
| 1
| 19
|
Salaried
|
Male
| 3
| 4
|
Basic
| 3
|
Divorced
| 5
| 1
| 3
| 1
| 1
|
Executive
| 23,444
| 1
|
Old
|
Mid
|
Long
|
31
|
Company Invited
| 1
| 21
|
Small Business
|
Male
| 3
| 3
|
Basic
| 3
|
Married
| 2
| 0
| 4
| 1
| 0
|
Executive
| 17,610
| 0
|
Adult
|
Low
|
Long
|
37
|
Self Enquiry
| 3
| 9
|
Salaried
|
Female
| 3
| 4
|
Deluxe
| 3
|
Unmarried
| 5
| 0
| 4
| 1
| 2
|
Manager
| 23,180
| 1
|
Adult
|
Mid
|
Short
|
26
|
Self Enquiry
| 1
| 11
|
Large Business
|
Male
| 3
| 4
|
Basic
| 3
|
Divorced
| 3
| 1
| 3
| 1
| 1
|
Executive
| 22,369
| 1
|
Adult
|
Mid
|
Long
|
54
|
Company Invited
| 1
| 17
|
Small Business
|
Female
| 2
| 3
|
Super Deluxe
| 3
|
Married
| 4
| 0
| 3
| 1
| 0
|
AVP
| 31,032
| 0
|
Old
|
High
|
Long
|
30
|
Self Enquiry
| 1
| 14
|
Small Business
|
Female
| 4
| 5
|
Basic
| 3
|
Married
| 8
| 0
| 5
| 1
| 2
|
Executive
| 21,210
| 1
|
Adult
|
Mid
|
Long
|
33
|
Company Invited
| 1
| 7
|
Salaried
|
Female
| 4
| 5
|
Basic
| 4
|
Divorced
| 8
| 0
| 3
| 1
| 1
|
Executive
| 21,010
| 1
|
Adult
|
Mid
|
Short
|
27
|
Self Enquiry
| 1
| 9
|
Small Business
|
Male
| 3
| 5
|
Basic
| 3
|
Unmarried
| 2
| 0
| 3
| 0
| 1
|
Executive
| 22,582
| 1
|
Adult
|
Mid
|
Short
|
31
|
Self Enquiry
| 1
| 10
|
Large Business
|
Female
| 3
| 4
|
Basic
| 5
|
Unmarried
| 7
| 1
| 4
| 0
| 1
|
Executive
| 21,335
| 1
|
Adult
|
Mid
|
Short
|
35
|
Self Enquiry
| 3
| 8
|
Small Business
|
Female
| 3
| 3
|
Basic
| 3
|
Married
| 2
| 0
| 1
| 1
| 2
|
Executive
| 17,014
| 1
|
Adult
|
Low
|
Short
|
29
|
Self Enquiry
| 3
| 12
|
Small Business
|
Male
| 4
| 4
|
Deluxe
| 3
|
Unmarried
| 3
| 0
| 3
| 1
| 1
|
Manager
| 23,586
| 1
|
Adult
|
Mid
|
Long
|
38
|
Self Enquiry
| 1
| 8
|
Small Business
|
Male
| 3
| 3
|
Basic
| 3
|
Married
| 7
| 1
| 4
| 0
| 2
|
Executive
| 18,057
| 1
|
Adult
|
Low
|
Short
|
52
|
Company Invited
| 1
| 15
|
Salaried
|
Male
| 3
| 6
|
Standard
| 3
|
Unmarried
| 4
| 0
| 1
| 1
| 1
|
Senior Manager
| 29,328
| 1
|
Old
|
Mid
|
Long
|
42
|
Self Enquiry
| 1
| 26
|
Salaried
|
Male
| 3
| 4
|
Deluxe
| 5
|
Married
| 4
| 0
| 2
| 1
| 1
|
Manager
| 21,750
| 1
|
Old
|
Mid
|
Long
|
35
|
Company Invited
| 1
| 10
|
Salaried
|
Male
| 3
| 5
|
Basic
| 3
|
Divorced
| 5
| 0
| 2
| 1
| 1
|
Executive
| 21,657
| 1
|
Adult
|
Mid
|
Short
|
36
|
Self Enquiry
| 1
| 28
|
Salaried
|
Female
| 3
| 4
|
Deluxe
| 3
|
Divorced
| 3
| 1
| 3
| 0
| 2
|
Manager
| 22,692
| 1
|
Adult
|
Mid
|
Long
|
36
|
Self Enquiry
| 3
| 8
|
Small Business
|
Male
| 3
| 4
|
Standard
| 3
|
Divorced
| 2
| 0
| 2
| 1
| 0
|
Senior Manager
| 22,596
| 0
|
Adult
|
Mid
|
Short
|
33
|
Self Enquiry
| 1
| 9
|
Small Business
|
Female
| 4
| 2
|
Deluxe
| 3
|
Unmarried
| 2
| 0
| 3
| 0
| 1
|
Manager
| 23,733
| 1
|
Adult
|
Mid
|
Short
|
60
|
Company Invited
| 3
| 7
|
Salaried
|
Female
| 3
| 5
|
Deluxe
| 3
|
Unmarried
| 2
| 0
| 5
| 1
| 1
|
Manager
| 24,151
| 1
|
Old
|
Mid
|
Short
|
48
|
Self Enquiry
| 1
| 10
|
Salaried
|
Male
| 3
| 4
|
Standard
| 3
|
Unmarried
| 1
| 0
| 5
| 1
| 0
|
Senior Manager
| 25,999
| 0
|
Old
|
Mid
|
Short
|
41
|
Company Invited
| 1
| 16
|
Salaried
|
Male
| 4
| 5
|
Deluxe
| 3
|
Married
| 2
| 0
| 5
| 0
| 2
|
Manager
| 23,554
| 1
|
Old
|
Mid
|
Long
|
35
|
Self Enquiry
| 1
| 6
|
Small Business
|
Male
| 2
| 4
|
Basic
| 3
|
Married
| 7
| 0
| 1
| 1
| 1
|
Executive
| 17,258
| 1
|
Adult
|
Low
|
Short
|
25
|
Self Enquiry
| 1
| 9
|
Salaried
|
Male
| 2
| 3
|
Basic
| 5
|
Married
| 5
| 0
| 5
| 1
| 0
|
Executive
| 16,118
| 0
|
Adult
|
Low
|
Short
|
27
|
Company Invited
| 1
| 10
|
Large Business
|
Male
| 4
| 4
|
Basic
| 5
|
Unmarried
| 2
| 0
| 3
| 0
| 3
|
Executive
| 21,780
| 1
|
Adult
|
Mid
|
Short
|
33
|
Self Enquiry
| 2
| 9
|
Salaried
|
Male
| 2
| 3
|
Basic
| 4
|
Married
| 4
| 1
| 5
| 0
| 1
|
Executive
| 17,277
| 1
|
Adult
|
Low
|
Short
|
34
|
Self Enquiry
| 1
| 13
|
Salaried
|
Female
| 2
| 3
|
Standard
| 4
|
Unmarried
| 1
| 0
| 3
| 1
| 0
|
Senior Manager
| 26,994
| 0
|
Adult
|
Mid
|
Long
|
39
|
Self Enquiry
| 1
| 16
|
Small Business
|
Male
| 3
| 3
|
Super Deluxe
| 5
|
Married
| 2
| 1
| 3
| 1
| 2
|
AVP
| 32,068
| 1
|
Adult
|
High
|
Long
|
39
|
Self Enquiry
| 1
| 25
|
Small Business
|
Male
| 3
| 6
|
Deluxe
| 3
|
Married
| 5
| 1
| 5
| 0
| 2
|
Manager
| 24,489
| 1
|
Adult
|
Mid
|
Long
|
49
|
Self Enquiry
| 1
| 13
|
Salaried
|
Male
| 2
| 4
|
Standard
| 3
|
Unmarried
| 1
| 0
| 2
| 1
| 1
|
Senior Manager
| 25,965
| 1
|
Old
|
Mid
|
Long
|
36
|
Self Enquiry
| 2
| 33
|
Salaried
|
Female
| 3
| 4
|
Standard
| 3
|
Unmarried
| 3
| 1
| 1
| 1
| 1
|
Senior Manager
| 27,515
| 1
|
Adult
|
Mid
|
High
|
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