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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 19 missing columns ({'NumberOfFollowups', 'ProductPitched', 'Passport', 'OwnCar', 'DurationOfPitch', 'Unnamed: 0', 'Occupation', 'PreferredPropertyStar', 'TypeofContact', 'Designation', 'NumberOfPersonVisiting', 'MaritalStatus', 'PitchSatisfactionScore', 'Gender', 'NumberOfTrips', 'MonthlyIncome', 'NumberOfChildrenVisiting', 'Age', 'CityTier'}).
This happened while the csv dataset builder was generating data using
hf://datasets/avatar2102/tourism-package-dataset/data_splits/ytest.csv (at revision 37f27ee5263063aa41f2327ce54836ecdb6f6381)
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, "' + 376
to
{'Unnamed: 0': Value('int64'), 'Age': Value('float64'), 'TypeofContact': Value('string'), 'CityTier': Value('int64'), 'DurationOfPitch': Value('float64'), 'Occupation': Value('string'), 'Gender': Value('string'), 'NumberOfPersonVisiting': Value('int64'), 'NumberOfFollowups': Value('float64'), '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 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 19 missing columns ({'NumberOfFollowups', 'ProductPitched', 'Passport', 'OwnCar', 'DurationOfPitch', 'Unnamed: 0', 'Occupation', 'PreferredPropertyStar', 'TypeofContact', 'Designation', 'NumberOfPersonVisiting', 'MaritalStatus', 'PitchSatisfactionScore', 'Gender', 'NumberOfTrips', 'MonthlyIncome', 'NumberOfChildrenVisiting', 'Age', 'CityTier'}).
This happened while the csv dataset builder was generating data using
hf://datasets/avatar2102/tourism-package-dataset/data_splits/ytest.csv (at revision 37f27ee5263063aa41f2327ce54836ecdb6f6381)
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 | TypeofContact
string | CityTier
int64 | DurationOfPitch
float64 | Occupation
string | Gender
string | NumberOfPersonVisiting
int64 | NumberOfFollowups
float64 | ProductPitched
string | PreferredPropertyStar
float64 | MaritalStatus
string | NumberOfTrips
float64 | Passport
int64 | PitchSatisfactionScore
int64 | OwnCar
int64 | NumberOfChildrenVisiting
float64 | Designation
string | MonthlyIncome
float64 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
2,273
| 34
|
Company Invited
| 1
| 9
|
Salaried
|
Male
| 2
| 4
|
Basic
| 3
|
Married
| 4
| 0
| 1
| 0
| 0
|
Executive
| 17,979
|
73
| 32
|
Self Enquiry
| 1
| 6
|
Salaried
|
Male
| 3
| 3
|
Deluxe
| 4
|
Divorced
| 2
| 0
| 3
| 0
| 0
|
Manager
| 21,220
|
167
| 30
|
Self Enquiry
| 3
| 11
|
Salaried
|
Female
| 2
| 3
|
Standard
| 3
|
Divorced
| 3
| 0
| 4
| 1
| 1
|
Senior Manager
| 24,419
|
4,725
| 39
|
Self Enquiry
| 3
| 9
|
Small Business
|
Male
| 3
| 4
|
Standard
| 4
|
Unmarried
| 2
| 0
| 4
| 1
| 2
|
Senior Manager
| 26,029
|
4,219
| 37
|
Company Invited
| 1
| 31
|
Salaried
|
Female
| 3
| 4
|
Deluxe
| 4
|
Married
| 2
| 0
| 3
| 1
| 2
|
Manager
| 24,352
|
2,620
| 34
|
Self Enquiry
| 1
| 9
|
Salaried
|
Male
| 3
| 4
|
Basic
| 3
|
Single
| 2
| 0
| 3
| 0
| 2
|
Executive
| 21,178
|
3,015
| 27
|
Company Invited
| 1
| 7
|
Salaried
|
Female
| 4
| 6
|
Basic
| 3
|
Married
| 5
| 0
| 4
| 1
| 3
|
Executive
| 23,042
|
1,106
| 30
|
Self Enquiry
| 3
| 6
|
Salaried
|
Male
| 3
| 4
|
Deluxe
| 5
|
Married
| 2
| 0
| 4
| 1
| 1
|
Manager
| 24,714
|
4,541
| 53
|
Company Invited
| 1
| 32
|
Small Business
|
Female
| 3
| 5
|
Super Deluxe
| 3
|
Married
| 5
| 0
| 5
| 0
| 2
|
AVP
| 32,504
|
3,334
| 55
|
Company Invited
| 1
| 7
|
Salaried
|
Female
| 3
| 4
|
Standard
| 3
|
Married
| 2
| 0
| 5
| 1
| 2
|
Senior Manager
| 29,180
|
93
| 46
|
Company Invited
| 1
| 6
|
Small Business
|
Male
| 2
| 4
|
Standard
| 5
|
Divorced
| 3
| 1
| 2
| 1
| 1
|
Senior Manager
| 25,673
|
4,519
| 39
|
Company Invited
| 1
| 19
|
Salaried
|
Male
| 2
| 5
|
Deluxe
| 5
|
Married
| 4
| 0
| 5
| 1
| 1
|
Manager
| 24,966
|
112
| 54
|
Company Invited
| 2
| 32
|
Salaried
|
Female
| 1
| 2
|
Super Deluxe
| 3
|
Single
| 3
| 1
| 3
| 1
| 0
|
AVP
| 32,328
|
1,287
| 42
|
Self Enquiry
| 1
| 19
|
Small Business
|
Male
| 3
| 1
|
Deluxe
| 5
|
Married
| 6
| 0
| 4
| 1
| 0
|
Manager
| 20,538
|
3,583
| 33
|
Self Enquiry
| 1
| 12
|
Salaried
|
Female
| 3
| 2
|
Basic
| 3
|
Married
| 5
| 0
| 5
| 1
| 2
|
Executive
| 21,990
|
1,551
| 35
|
Self Enquiry
| 1
| 6
|
Small Business
|
Male
| 1
| 4
|
Basic
| 3
|
Single
| 2
| 0
| 4
| 1
| 0
|
Executive
| 17,859
|
1,284
| 39
|
Self Enquiry
| 1
| 16
|
Small Business
|
Male
| 3
| 3
|
Standard
| 3
|
Unmarried
| 1
| 0
| 3
| 1
| 0
|
Senior Manager
| 28,464
|
3,232
| 29
|
Self Enquiry
| 1
| 17
|
Salaried
|
Female
| 3
| 4
|
Deluxe
| 3
|
Unmarried
| 5
| 0
| 4
| 1
| 2
|
Manager
| 22,338
|
2,887
| 23
|
Company Invited
| 1
| 11
|
Large Business
|
Male
| 3
| 5
|
Basic
| 3
|
Unmarried
| 7
| 0
| 5
| 1
| 1
|
Executive
| 22,572
|
294
| 37
|
Company Invited
| 1
| 15
|
Small Business
|
Male
| 2
| 3
|
Basic
| 3
|
Divorced
| 2
| 1
| 2
| 0
| 0
|
Executive
| 17,326
|
4,606
| 33
|
Self Enquiry
| 1
| 10
|
Small Business
|
Female
| 4
| 4
|
Deluxe
| 5
|
Married
| 3
| 0
| 1
| 1
| 1
|
Manager
| 25,403
|
4,015
| 33
|
Self Enquiry
| 1
| 7
|
Salaried
|
Male
| 4
| 4
|
Basic
| 5
|
Unmarried
| 3
| 0
| 1
| 0
| 2
|
Executive
| 21,634
|
4,115
| 50
|
Company Invited
| 1
| 25
|
Salaried
|
Male
| 4
| 4
|
Deluxe
| 3
|
Married
| 3
| 1
| 1
| 0
| 1
|
Manager
| 25,482
|
2,067
| 42
|
Self Enquiry
| 1
| 6
|
Salaried
|
Female
| 2
| 4
|
Deluxe
| 3
|
Married
| 1
| 1
| 3
| 0
| 0
|
Manager
| 21,062
|
4,801
| 43
|
Company Invited
| 1
| 33
|
Small Business
|
Female
| 3
| 4
|
Standard
| 5
|
Married
| 5
| 1
| 3
| 0
| 1
|
Senior Manager
| 31,869
|
1,383
| 36
|
Company Invited
| 1
| 15
|
Salaried
|
Male
| 3
| 1
|
Basic
| 4
|
Married
| 2
| 0
| 5
| 1
| 0
|
Executive
| 17,810
|
1,350
| 27
|
Self Enquiry
| 3
| 8
|
Small Business
|
Female
| 2
| 1
|
Deluxe
| 3
|
Unmarried
| 1
| 0
| 1
| 0
| 1
|
Manager
| 21,500
|
4,288
| 29
|
Self Enquiry
| 3
| 16
|
Salaried
|
Male
| 4
| 4
|
Deluxe
| 3
|
Unmarried
| 3
| 0
| 3
| 1
| 2
|
Manager
| 23,931
|
2,690
| 34
|
Self Enquiry
| 1
| 12
|
Salaried
|
Female
| 4
| 5
|
Basic
| 3
|
Divorced
| 3
| 0
| 2
| 0
| 3
|
Executive
| 21,589
|
3,576
| 41
|
Self Enquiry
| 3
| 21
|
Salaried
|
Female
| 3
| 4
|
Deluxe
| 5
|
Married
| 3
| 0
| 3
| 0
| 2
|
Manager
| 23,317
|
4,866
| 32
|
Self Enquiry
| 3
| 20
|
Small Business
|
Male
| 4
| 5
|
Deluxe
| 5
|
Married
| 7
| 1
| 1
| 1
| 1
|
Manager
| 20,980
|
1,947
| 50
|
Company Invited
| 2
| 9
|
Small Business
|
Male
| 3
| 3
|
King
| 4
|
Married
| 2
| 0
| 1
| 1
| 2
|
VP
| 33,200
|
1,940
| 24
|
Company Invited
| 3
| 30
|
Small Business
|
Male
| 2
| 3
|
Basic
| 3
|
Married
| 1
| 0
| 4
| 1
| 1
|
Executive
| 17,400
|
4,511
| 43
|
Self Enquiry
| 1
| 7
|
Salaried
|
Female
| 3
| 5
|
Deluxe
| 3
|
Married
| 2
| 1
| 3
| 0
| 1
|
Manager
| 24,740
|
1,148
| 39
|
Self Enquiry
| 1
| 16
|
Small Business
|
Male
| 3
| 3
|
Deluxe
| 5
|
Married
| 3
| 0
| 5
| 1
| 2
|
Manager
| 20,377
|
1,740
| 55
|
Self Enquiry
| 1
| 6
|
Small Business
|
Male
| 2
| 3
|
King
| 5
|
Single
| 1
| 1
| 1
| 1
| 1
|
VP
| 34,045
|
4,849
| 33
|
Company Invited
| 1
| 10
|
Salaried
|
Fe Male
| 3
| 4
|
Basic
| 3
|
Unmarried
| 3
| 0
| 4
| 1
| 1
|
Executive
| 24,887
|
3,699
| 34
|
Self Enquiry
| 3
| 23
|
Salaried
|
Fe Male
| 4
| 4
|
Standard
| 5
|
Unmarried
| 4
| 1
| 5
| 0
| 1
|
Senior Manager
| 27,242
|
4,027
| 25
|
Self Enquiry
| 1
| 25
|
Salaried
|
Male
| 3
| 4
|
Basic
| 3
|
Married
| 2
| 0
| 4
| 0
| 1
|
Executive
| 21,452
|
1,613
| 30
|
Self Enquiry
| 1
| 24
|
Salaried
|
Female
| 3
| 3
|
Basic
| 3
|
Single
| 2
| 0
| 1
| 1
| 2
|
Executive
| 17,632
|
4,206
| 32
|
Company Invited
| 3
| 12
|
Small Business
|
Female
| 3
| 4
|
Basic
| 4
|
Married
| 3
| 0
| 3
| 0
| 1
|
Executive
| 21,467
|
2,757
| 34
|
Company Invited
| 1
| 12
|
Salaried
|
Female
| 4
| 4
|
Standard
| 4
|
Divorced
| 8
| 0
| 3
| 1
| 3
|
Senior Manager
| 30,556
|
2,191
| 50
|
Self Enquiry
| 1
| 30
|
Salaried
|
Male
| 3
| 3
|
Super Deluxe
| 3
|
Married
| 4
| 1
| 4
| 1
| 2
|
AVP
| 28,973
|
673
| 33
|
Self Enquiry
| 1
| 6
|
Salaried
|
Male
| 3
| 4
|
Basic
| 5
|
Single
| 4
| 1
| 4
| 0
| 0
|
Executive
| 17,799
|
3,264
| 36
|
Company Invited
| 3
| 18
|
Small Business
|
Male
| 3
| 4
|
Deluxe
| 3
|
Married
| 3
| 0
| 5
| 0
| 1
|
Manager
| 23,646
|
2,645
| 50
|
Company Invited
| 1
| 25
|
Salaried
|
Male
| 4
| 4
|
Deluxe
| 3
|
Married
| 3
| 1
| 2
| 0
| 2
|
Manager
| 25,482
|
3,648
| 49
|
Company Invited
| 3
| 14
|
Small Business
|
Female
| 4
| 4
|
Basic
| 3
|
Married
| 4
| 1
| 4
| 1
| 2
|
Executive
| 21,333
|
3,412
| 37
|
Company Invited
| 3
| 14
|
Small Business
|
Female
| 3
| 2
|
Deluxe
| 5
|
Divorced
| 4
| 0
| 1
| 1
| 1
|
Manager
| 23,317
|
143
| 30
|
Self Enquiry
| 1
| 24
|
Salaried
|
Female
| 3
| 3
|
Basic
| 3
|
Single
| 2
| 0
| 2
| 1
| 0
|
Executive
| 17,632
|
3,867
| 23
|
Self Enquiry
| 1
| 7
|
Salaried
|
Male
| 4
| 4
|
Basic
| 3
|
Unmarried
| 2
| 0
| 3
| 0
| 3
|
Executive
| 22,053
|
1,651
| 34
|
Self Enquiry
| 1
| 33
|
Small Business
|
Female
| 3
| 3
|
Basic
| 4
|
Single
| 3
| 0
| 3
| 0
| 0
|
Executive
| 17,311
|
4,005
| 52
|
Self Enquiry
| 3
| 28
|
Small Business
|
Male
| 4
| 4
|
Deluxe
| 3
|
Unmarried
| 2
| 1
| 5
| 0
| 3
|
Manager
| 24,119
|
3,192
| 27
|
Company Invited
| 3
| 36
|
Small Business
|
Male
| 4
| 6
|
Deluxe
| 5
|
Unmarried
| 2
| 0
| 3
| 0
| 1
|
Manager
| 23,647
|
706
| 40
|
Company Invited
| 3
| 30
|
Salaried
|
Fe Male
| 3
| 1
|
Super Deluxe
| 4
|
Unmarried
| 5
| 1
| 3
| 1
| 2
|
AVP
| 28,194
|
891
| 44
|
Self Enquiry
| 1
| 8
|
Salaried
|
Female
| 3
| 1
|
Basic
| 3
|
Divorced
| 2
| 0
| 4
| 1
| 0
|
Executive
| 17,011
|
4,676
| 27
|
Company Invited
| 1
| 9
|
Salaried
|
Male
| 3
| 4
|
Basic
| 5
|
Married
| 8
| 1
| 5
| 0
| 1
|
Executive
| 20,720
|
3,308
| 42
|
Company Invited
| 1
| 12
|
Salaried
|
Male
| 4
| 5
|
Basic
| 5
|
Married
| 8
| 0
| 3
| 1
| 1
|
Executive
| 20,785
|
2,939
| 28
|
Self Enquiry
| 3
| 9
|
Small Business
|
Male
| 3
| 4
|
Basic
| 5
|
Married
| 2
| 0
| 5
| 0
| 2
|
Executive
| 21,719
|
4,588
| 59
|
Self Enquiry
| 1
| 12
|
Large Business
|
Female
| 3
| 5
|
Standard
| 4
|
Married
| 4
| 1
| 5
| 1
| 2
|
Senior Manager
| 29,230
|
3,430
| 40
|
Self Enquiry
| 3
| 28
|
Salaried
|
Male
| 3
| 5
|
Deluxe
| 3
|
Divorced
| 5
| 1
| 1
| 0
| 2
|
Manager
| 24,798
|
3,767
| 29
|
Company Invited
| 2
| 7
|
Salaried
|
Male
| 3
| 4
|
Basic
| 3
|
Married
| 3
| 0
| 4
| 0
| 2
|
Executive
| 21,384
|
3,004
| 35
|
Self Enquiry
| 1
| 15
|
Salaried
|
Female
| 3
| 4
|
Deluxe
| 5
|
Married
| 5
| 0
| 5
| 1
| 1
|
Manager
| 23,799
|
1,039
| 34
|
Self Enquiry
| 2
| 15
|
Large Business
|
Female
| 2
| 3
|
Basic
| 3
|
Divorced
| 2
| 0
| 1
| 1
| 0
|
Executive
| 17,742
|
1,018
| 36
|
Self Enquiry
| 1
| 10
|
Salaried
|
Male
| 2
| 4
|
Deluxe
| 3
|
Single
| 2
| 0
| 5
| 1
| 1
|
Manager
| 20,810
|
147
| 41
|
Company Invited
| 1
| 16
|
Salaried
|
Male
| 3
| 4
|
Super Deluxe
| 5
|
Married
| 5
| 0
| 2
| 1
| 0
|
AVP
| 32,181
|
1,563
| 46
|
Company Invited
| 1
| 6
|
Small Business
|
Male
| 2
| 4
|
Standard
| 5
|
Married
| 3
| 1
| 1
| 1
| 1
|
Senior Manager
| 25,673
|
2,904
| 27
|
Self Enquiry
| 3
| 36
|
Small Business
|
Male
| 3
| 4
|
Deluxe
| 3
|
Married
| 7
| 0
| 5
| 1
| 1
|
Manager
| 22,984
|
4,732
| 32
|
Company Invited
| 3
| 27
|
Salaried
|
Male
| 4
| 2
|
Basic
| 3
|
Married
| 2
| 0
| 5
| 1
| 1
|
Executive
| 21,469
|
3,961
| 38
|
Self Enquiry
| 1
| 26
|
Salaried
|
Male
| 4
| 4
|
Basic
| 4
|
Married
| 6
| 0
| 4
| 0
| 2
|
Executive
| 21,700
|
4,035
| 34
|
Company Invited
| 3
| 29
|
Small Business
|
Male
| 4
| 4
|
Deluxe
| 4
|
Married
| 2
| 0
| 1
| 0
| 1
|
Manager
| 24,824
|
962
| 51
|
Self Enquiry
| 2
| 11
|
Salaried
|
Male
| 2
| 3
|
Super Deluxe
| 4
|
Married
| 2
| 1
| 3
| 1
| 1
|
AVP
| 29,026
|
553
| 40
|
Self Enquiry
| 1
| 8
|
Small Business
|
Female
| 2
| 4
|
Basic
| 3
|
Single
| 1
| 1
| 3
| 1
| 1
|
Executive
| 17,342
|
1,845
| 49
|
Self Enquiry
| 1
| 13
|
Salaried
|
Male
| 2
| 4
|
Standard
| 3
|
Unmarried
| 1
| 0
| 1
| 1
| 0
|
Senior Manager
| 25,965
|
3,765
| 48
|
Self Enquiry
| 1
| 16
|
Salaried
|
Female
| 4
| 4
|
Basic
| 3
|
Single
| 6
| 0
| 3
| 1
| 1
|
Executive
| 20,783
|
1,724
| 29
|
Self Enquiry
| 3
| 26
|
Small Business
|
Male
| 2
| 3
|
Deluxe
| 3
|
Married
| 3
| 0
| 1
| 1
| 0
|
Manager
| 21,931
|
4,384
| 25
|
Company Invited
| 3
| 31
|
Small Business
|
Male
| 3
| 4
|
Basic
| 3
|
Married
| 2
| 0
| 4
| 1
| 2
|
Executive
| 21,078
|
2,340
| 35
|
Self Enquiry
| 3
| 23
|
Salaried
|
Male
| 3
| 3
|
Deluxe
| 5
|
Married
| 4
| 1
| 3
| 0
| 2
|
Manager
| 23,966
|
4,257
| 30
|
Self Enquiry
| 3
| 17
|
Small Business
|
Female
| 3
| 5
|
Deluxe
| 4
|
Married
| 3
| 1
| 5
| 1
| 1
|
Manager
| 26,946
|
1,662
| 35
|
Self Enquiry
| 1
| 29
|
Salaried
|
Male
| 2
| 4
|
Deluxe
| 3
|
Married
| 4
| 1
| 4
| 1
| 0
|
Manager
| 20,916
|
1,847
| 36
|
Self Enquiry
| 1
| 8
|
Salaried
|
Female
| 3
| 3
|
Basic
| 3
|
Married
| 5
| 0
| 5
| 1
| 0
|
Executive
| 17,543
|
1,126
| 50
|
Self Enquiry
| 3
| 5
|
Small Business
|
Male
| 2
| 3
|
King
| 3
|
Married
| 5
| 1
| 5
| 0
| 1
|
VP
| 34,331
|
4,689
| 44
|
Self Enquiry
| 3
| 32
|
Small Business
|
Male
| 4
| 5
|
Standard
| 3
|
Married
| 7
| 0
| 4
| 1
| 2
|
Senior Manager
| 29,476
|
811
| 38
|
Self Enquiry
| 3
| 8
|
Small Business
|
Male
| 2
| 3
|
Standard
| 4
|
Unmarried
| 1
| 0
| 4
| 1
| 0
|
Senior Manager
| 22,351
|
3,624
| 37
|
Self Enquiry
| 1
| 14
|
Salaried
|
Male
| 4
| 4
|
Basic
| 4
|
Single
| 4
| 0
| 1
| 0
| 3
|
Executive
| 20,691
|
2,754
| 32
|
Self Enquiry
| 2
| 9
|
Salaried
|
Male
| 4
| 5
|
Deluxe
| 5
|
Divorced
| 5
| 0
| 3
| 0
| 2
|
Manager
| 25,088
|
2,890
| 42
|
Company Invited
| 3
| 17
|
Salaried
|
Male
| 3
| 4
|
Deluxe
| 3
|
Unmarried
| 2
| 0
| 2
| 0
| 2
|
Manager
| 24,908
|
523
| 50
|
Self Enquiry
| 1
| 34
|
Small Business
|
Male
| 3
| 2
|
Basic
| 3
|
Divorced
| 2
| 1
| 2
| 1
| 2
|
Executive
| 18,221
|
4,393
| 25
|
Company Invited
| 1
| 14
|
Salaried
|
Female
| 3
| 4
|
Basic
| 3
|
Married
| 3
| 1
| 4
| 0
| 1
|
Executive
| 21,564
|
853
| 19
|
Self Enquiry
| 1
| 15
|
Salaried
|
Male
| 2
| 3
|
Basic
| 5
|
Single
| 2
| 0
| 3
| 0
| 0
|
Executive
| 17,552
|
4,598
| 41
|
Self Enquiry
| 3
| 17
|
Small Business
|
Male
| 4
| 5
|
Standard
| 4
|
Married
| 4
| 0
| 4
| 0
| 1
|
Senior Manager
| 28,383
|
2,909
| 47
|
Company Invited
| 1
| 25
|
Small Business
|
Female
| 3
| 4
|
Standard
| 3
|
Divorced
| 7
| 0
| 3
| 1
| 1
|
Senior Manager
| 29,205
|
3,123
| 32
|
Company Invited
| 3
| 27
|
Small Business
|
Female
| 3
| 4
|
Deluxe
| 3
|
Divorced
| 3
| 0
| 2
| 1
| 1
|
Manager
| 25,610
|
750
| 44
|
Self Enquiry
| 3
| 34
|
Small Business
|
Female
| 2
| 1
|
Super Deluxe
| 3
|
Divorced
| 4
| 1
| 2
| 1
| 1
|
AVP
| 28,320
|
2,983
| 51
|
Self Enquiry
| 3
| 15
|
Small Business
|
Male
| 3
| 4
|
Basic
| 4
|
Divorced
| 2
| 0
| 2
| 1
| 1
|
Executive
| 22,553
|
2,325
| 37
|
Self Enquiry
| 1
| 7
|
Salaried
|
Female
| 2
| 4
|
Deluxe
| 3
|
Married
| 2
| 0
| 1
| 0
| 0
|
Manager
| 21,474
|
3,552
| 36
|
Self Enquiry
| 1
| 7
|
Small Business
|
Male
| 4
| 5
|
Basic
| 5
|
Single
| 3
| 0
| 1
| 0
| 3
|
Executive
| 21,128
|
2,780
| 30
|
Self Enquiry
| 1
| 15
|
Salaried
|
Male
| 4
| 6
|
Basic
| 5
|
Divorced
| 3
| 1
| 3
| 1
| 2
|
Executive
| 20,797
|
4,586
| 43
|
Self Enquiry
| 3
| 21
|
Small Business
|
Fe Male
| 4
| 5
|
Deluxe
| 3
|
Unmarried
| 2
| 0
| 3
| 1
| 1
|
Manager
| 24,922
|
4,234
| 28
|
Self Enquiry
| 3
| 9
|
Salaried
|
Male
| 4
| 4
|
Deluxe
| 3
|
Unmarried
| 3
| 1
| 4
| 0
| 2
|
Manager
| 23,156
|
4,176
| 33
|
Self Enquiry
| 1
| 9
|
Large Business
|
Male
| 3
| 5
|
Deluxe
| 5
|
Single
| 6
| 0
| 4
| 0
| 2
|
Manager
| 20,854
|
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