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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 24 new columns ({'MaritalStatus_Divorced', 'MaritalStatus_Unmarried', 'Gender_Fe Male', 'Designation_Executive', 'ProductPitched_Basic', 'ProductPitched_Standard', 'MaritalStatus_Married', 'Occupation_Small Business', 'ProductPitched_Deluxe', 'TypeofContact_Self Enquiry', 'Occupation_Free Lancer', 'Designation_Manager', 'Occupation_Large Business', 'Designation_Senior Manager', 'Occupation_Salaried', 'Gender_Female', 'MaritalStatus_Single', 'Designation_AVP', 'Designation_VP', 'TypeofContact_Company Invited', 'Unnamed: 0', 'Gender_Male', 'ProductPitched_Super Deluxe', 'ProductPitched_King'}) and 6 missing columns ({'Occupation', 'Gender', 'ProductPitched', 'Designation', 'TypeofContact', 'MaritalStatus'}).
This happened while the csv dataset builder was generating data using
hf://datasets/Prashantbhat1607/wellness-tourism-data/train.csv (at revision e4db24c1c908086f4157af3654a9b023cd105f5f)
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
ProdTaken: int64
Age: double
CityTier: int64
DurationOfPitch: double
NumberOfPersonVisiting: int64
NumberOfFollowups: double
PreferredPropertyStar: double
NumberOfTrips: double
Passport: int64
PitchSatisfactionScore: int64
OwnCar: int64
NumberOfChildrenVisiting: double
MonthlyIncome: double
TypeofContact_Company Invited: bool
TypeofContact_Self Enquiry: bool
Occupation_Free Lancer: bool
Occupation_Large Business: bool
Occupation_Salaried: bool
Occupation_Small Business: bool
Gender_Fe Male: bool
Gender_Female: bool
Gender_Male: bool
ProductPitched_Basic: bool
ProductPitched_Deluxe: bool
ProductPitched_King: bool
ProductPitched_Standard: bool
ProductPitched_Super Deluxe: bool
MaritalStatus_Divorced: bool
MaritalStatus_Married: bool
MaritalStatus_Single: bool
MaritalStatus_Unmarried: bool
Designation_AVP: bool
Designation_Executive: bool
Designation_Manager: bool
Designation_Senior Manager: bool
Designation_VP: bool
-- schema metadata --
pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 5165
to
{'ProdTaken': 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 24 new columns ({'MaritalStatus_Divorced', 'MaritalStatus_Unmarried', 'Gender_Fe Male', 'Designation_Executive', 'ProductPitched_Basic', 'ProductPitched_Standard', 'MaritalStatus_Married', 'Occupation_Small Business', 'ProductPitched_Deluxe', 'TypeofContact_Self Enquiry', 'Occupation_Free Lancer', 'Designation_Manager', 'Occupation_Large Business', 'Designation_Senior Manager', 'Occupation_Salaried', 'Gender_Female', 'MaritalStatus_Single', 'Designation_AVP', 'Designation_VP', 'TypeofContact_Company Invited', 'Unnamed: 0', 'Gender_Male', 'ProductPitched_Super Deluxe', 'ProductPitched_King'}) and 6 missing columns ({'Occupation', 'Gender', 'ProductPitched', 'Designation', 'TypeofContact', 'MaritalStatus'}).
This happened while the csv dataset builder was generating data using
hf://datasets/Prashantbhat1607/wellness-tourism-data/train.csv (at revision e4db24c1c908086f4157af3654a9b023cd105f5f)
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.
ProdTaken
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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
0
| 55
|
Self Enquiry
| 1
| 17
|
Small Business
|
Female
| 4
| 4
|
Deluxe
| 5
|
Unmarried
| 8
| 1
| 1
| 0
| 1
|
Manager
| 23,118
|
0
| 39
|
Self Enquiry
| 1
| 9
|
Salaried
|
Male
| 3
| 4
|
Basic
| 3
|
Unmarried
| 7
| 1
| 4
| 0
| 2
|
Executive
| 22,622
|
0
| 42
|
Company Invited
| 2
| 8
|
Small Business
|
Male
| 3
| 1
|
Deluxe
| 5
|
Divorced
| 1
| 0
| 2
| 0
| 2
|
Manager
| 21,272
|
0
| 37
|
Self Enquiry
| 1
| 12
|
Salaried
|
Female
| 3
| 5
|
Basic
| 5
|
Divorced
| 2
| 1
| 2
| 1
| 1
|
Executive
| 98,678
|
0
| 23
|
Self Enquiry
| 1
| 7
|
Salaried
|
Male
| 3
| 5
|
Deluxe
| 3
|
Divorced
| 8
| 0
| 2
| 1
| 1
|
Manager
| 23,453
|
0
| 33
|
Company Invited
| 1
| 31
|
Salaried
|
Male
| 4
| 4
|
Deluxe
| 3
|
Divorced
| 3
| 0
| 4
| 1
| 1
|
Manager
| 23,987
|
0
| 38
|
Self Enquiry
| 1
| 24
|
Small Business
|
Male
| 2
| 5
|
Deluxe
| 3
|
Married
| 4
| 1
| 5
| 0
| 1
|
Manager
| 20,811
|
0
| 60
|
Self Enquiry
| 1
| 9
|
Salaried
|
Female
| 4
| 5
|
Super Deluxe
| 3
|
Single
| 5
| 1
| 5
| 0
| 3
|
AVP
| 32,404
|
0
| 53
|
Company Invited
| 3
| 8
|
Small Business
|
Female
| 2
| 4
|
Standard
| 4
|
Married
| 3
| 0
| 1
| 1
| 0
|
Senior Manager
| 22,525
|
0
| 37
|
Self Enquiry
| 1
| 33
|
Salaried
|
Male
| 4
| 4
|
Deluxe
| 3
|
Married
| 8
| 0
| 3
| 1
| 1
|
Manager
| 24,025
|
0
| 60
|
Company Invited
| 3
| 34
|
Small Business
|
Female
| 3
| 4
|
Standard
| 5
|
Married
| 5
| 0
| 1
| 1
| 0
|
Senior Manager
| 25,266
|
0
| 43
|
Self Enquiry
| 1
| 36
|
Small Business
|
Male
| 3
| 6
|
Deluxe
| 3
|
Unmarried
| 6
| 0
| 3
| 1
| 2
|
Manager
| 22,950
|
0
| 35
|
Self Enquiry
| 1
| 22
|
Small Business
|
Male
| 2
| 1
|
Basic
| 4
|
Married
| 1
| 0
| 4
| 1
| 1
|
Executive
| 17,426
|
0
| 43
|
Self Enquiry
| 1
| 10
|
Salaried
|
Female
| 4
| 2
|
Deluxe
| 3
|
Married
| 4
| 1
| 5
| 1
| 1
|
Manager
| 23,909
|
0
| 52
|
Company Invited
| 1
| 34
|
Small Business
|
Female
| 2
| 1
|
Super Deluxe
| 3
|
Divorced
| 3
| 1
| 4
| 0
| 0
|
AVP
| 28,247
|
1
| 59
|
Company Invited
| 1
| 9
|
Salaried
|
Male
| 3
| 5
|
Basic
| 3
|
Married
| 2
| 1
| 2
| 0
| 1
|
Executive
| 21,058
|
0
| 36
|
Self Enquiry
| 1
| 33
|
Small Business
|
Male
| 3
| 3
|
Deluxe
| 3
|
Divorced
| 7
| 0
| 3
| 1
| 0
|
Manager
| 20,237
|
0
| 29
|
Company Invited
| 1
| 23
|
Small Business
|
Male
| 3
| 4
|
Basic
| 3
|
Single
| 3
| 0
| 3
| 0
| 1
|
Executive
| 20,822
|
0
| 37
|
Self Enquiry
| 1
| 16
|
Small Business
|
Male
| 3
| 5
|
Deluxe
| 4
|
Married
| 4
| 1
| 4
| 0
| 2
|
Manager
| 27,525
|
0
| 38
|
Self Enquiry
| 1
| 8
|
Salaried
|
Male
| 2
| 3
|
Deluxe
| 3
|
Divorced
| 1
| 0
| 2
| 0
| 1
|
Manager
| 21,553
|
1
| 31
|
Company Invited
| 3
| 6
|
Salaried
|
Female
| 2
| 5
|
Basic
| 3
|
Single
| 2
| 0
| 3
| 1
| 1
|
Executive
| 16,359
|
0
| 46
|
Self Enquiry
| 3
| 16
|
Small Business
|
Male
| 4
| 4
|
Standard
| 5
|
Married
| 6
| 1
| 2
| 1
| 1
|
Senior Manager
| 29,439
|
1
| 41
|
Self Enquiry
| 3
| 14
|
Small Business
|
Male
| 3
| 4
|
Basic
| 4
|
Unmarried
| 3
| 0
| 5
| 0
| 1
|
Executive
| 23,339
|
1
| 35
|
Self Enquiry
| 1
| 13
|
Salaried
|
Male
| 3
| 3
|
Basic
| 4
|
Single
| 2
| 1
| 3
| 1
| 1
|
Executive
| 20,363
|
0
| 29
|
Self Enquiry
| 3
| 16
|
Salaried
|
Male
| 3
| 3
|
Basic
| 3
|
Single
| 2
| 0
| 4
| 1
| 0
|
Executive
| 17,642
|
0
| 51
|
Self Enquiry
| 3
| 27
|
Small Business
|
Male
| 3
| 3
|
Deluxe
| 3
|
Single
| 1
| 1
| 5
| 0
| 2
|
Manager
| 20,441
|
0
| 39
|
Self Enquiry
| 1
| 6
|
Small Business
|
Male
| 2
| 2
|
Standard
| 3
|
Married
| 1
| 0
| 3
| 1
| 0
|
Senior Manager
| 24,613
|
0
| 37
|
Self Enquiry
| 3
| 22
|
Small Business
|
Male
| 3
| 4
|
Deluxe
| 3
|
Married
| 5
| 0
| 5
| 1
| 2
|
Manager
| 21,334
|
0
| 33
|
Company Invited
| 3
| 23
|
Salaried
|
Male
| 2
| 3
|
Super Deluxe
| 3
|
Single
| 2
| 0
| 3
| 1
| 1
|
AVP
| 32,444
|
0
| 51
|
Company Invited
| 3
| 19
|
Small Business
|
Fe Male
| 4
| 4
|
Standard
| 3
|
Unmarried
| 6
| 0
| 5
| 1
| 3
|
Senior Manager
| 27,886
|
0
| 42
|
Self Enquiry
| 1
| 12
|
Salaried
|
Male
| 3
| 2
|
Deluxe
| 4
|
Unmarried
| 5
| 0
| 5
| 1
| 1
|
Manager
| 25,548
|
0
| 33
|
Self Enquiry
| 3
| 15
|
Large Business
|
Female
| 4
| 5
|
Deluxe
| 4
|
Divorced
| 3
| 1
| 2
| 1
| 1
|
Manager
| 23,906
|
0
| 30
|
Company Invited
| 1
| 17
|
Salaried
|
Female
| 4
| 4
|
Basic
| 4
|
Married
| 2
| 0
| 5
| 1
| 1
|
Executive
| 21,969
|
0
| 41
|
Self Enquiry
| 3
| 7
|
Small Business
|
Male
| 3
| 6
|
Deluxe
| 3
|
Divorced
| 4
| 1
| 3
| 1
| 1
|
Manager
| 26,135
|
0
| 38
|
Company Invited
| 1
| 12
|
Large Business
|
Male
| 3
| 2
|
Basic
| 3
|
Unmarried
| 2
| 0
| 5
| 1
| 1
|
Executive
| 22,178
|
0
| 28
|
Company Invited
| 3
| 9
|
Salaried
|
Male
| 3
| 6
|
Deluxe
| 3
|
Unmarried
| 5
| 0
| 4
| 1
| 2
|
Manager
| 23,749
|
0
| 27
|
Self Enquiry
| 1
| 24
|
Small Business
|
Male
| 4
| 6
|
Basic
| 3
|
Married
| 3
| 0
| 3
| 0
| 3
|
Executive
| 20,983
|
0
| 27
|
Self Enquiry
| 1
| 11
|
Salaried
|
Female
| 2
| 3
|
Basic
| 4
|
Single
| 2
| 1
| 3
| 0
| 1
|
Executive
| 17,478
|
0
| 24
|
Self Enquiry
| 1
| 11
|
Small Business
|
Male
| 3
| 2
|
Basic
| 5
|
Married
| 4
| 0
| 4
| 0
| 2
|
Executive
| 21,497
|
0
| 34
|
Company Invited
| 1
| 22
|
Salaried
|
Female
| 3
| 4
|
Basic
| 3
|
Single
| 2
| 0
| 5
| 1
| 2
|
Executive
| 17,553
|
1
| 37
|
Self Enquiry
| 3
| 17
|
Small Business
|
Male
| 3
| 5
|
Standard
| 5
|
Married
| 2
| 0
| 5
| 0
| 1
|
Senior Manager
| 25,772
|
0
| 34
|
Company Invited
| 1
| 7
|
Small Business
|
Male
| 3
| 4
|
Deluxe
| 5
|
Single
| 1
| 0
| 1
| 0
| 0
|
Manager
| 20,343
|
1
| 30
|
Company Invited
| 3
| 32
|
Small Business
|
Female
| 2
| 4
|
Deluxe
| 5
|
Unmarried
| 6
| 0
| 2
| 0
| 1
|
Manager
| 21,696
|
0
| 27
|
Self Enquiry
| 1
| 23
|
Large Business
|
Male
| 2
| 3
|
Basic
| 4
|
Married
| 1
| 1
| 4
| 0
| 0
|
Executive
| 18,058
|
0
| 36
|
Self Enquiry
| 1
| 9
|
Salaried
|
Male
| 3
| 5
|
Standard
| 4
|
Married
| 4
| 0
| 4
| 1
| 1
|
Senior Manager
| 28,952
|
0
| 40
|
Self Enquiry
| 1
| 30
|
Large Business
|
Male
| 3
| 3
|
Deluxe
| 3
|
Married
| 2
| 0
| 3
| 1
| 1
|
Manager
| 18,319
|
0
| 38
|
Self Enquiry
| 1
| 7
|
Large Business
|
Fe Male
| 3
| 4
|
Standard
| 3
|
Unmarried
| 6
| 0
| 5
| 1
| 2
|
Senior Manager
| 26,169
|
1
| 33
|
Self Enquiry
| 3
| 9
|
Small Business
|
Male
| 3
| 5
|
Deluxe
| 4
|
Single
| 2
| 1
| 1
| 1
| 1
|
Manager
| 28,585
|
0
| 30
|
Self Enquiry
| 1
| 16
|
Salaried
|
Male
| 2
| 5
|
Basic
| 3
|
Unmarried
| 2
| 0
| 1
| 1
| 1
|
Executive
| 22,661
|
0
| 52
|
Self Enquiry
| 1
| 6
|
Salaried
|
Male
| 3
| 3
|
Super Deluxe
| 3
|
Married
| 3
| 0
| 1
| 1
| 2
|
AVP
| 32,099
|
1
| 33
|
Self Enquiry
| 3
| 7
|
Salaried
|
Male
| 3
| 6
|
Deluxe
| 4
|
Unmarried
| 8
| 0
| 3
| 0
| 2
|
Manager
| 25,413
|
1
| 20
|
Company Invited
| 1
| 17
|
Small Business
|
Female
| 4
| 5
|
Basic
| 4
|
Single
| 3
| 1
| 5
| 0
| 3
|
Executive
| 20,537
|
0
| 38
|
Company Invited
| 1
| 29
|
Salaried
|
Male
| 2
| 4
|
Standard
| 3
|
Unmarried
| 1
| 0
| 3
| 0
| 0
|
Senior Manager
| 24,526
|
0
| 31
|
Self Enquiry
| 1
| 17
|
Salaried
|
Male
| 2
| 3
|
Basic
| 3
|
Married
| 4
| 1
| 3
| 0
| 0
|
Executive
| 17,356
|
1
| 52
|
Self Enquiry
| 1
| 11
|
Salaried
|
Male
| 3
| 4
|
Basic
| 3
|
Divorced
| 2
| 1
| 2
| 1
| 2
|
Executive
| 21,139
|
0
| 39
|
Self Enquiry
| 1
| 10
|
Large Business
|
Female
| 3
| 4
|
Deluxe
| 3
|
Unmarried
| 5
| 1
| 5
| 1
| 1
|
Manager
| 22,995
|
0
| 40
|
Self Enquiry
| 3
| 11
|
Salaried
|
Female
| 3
| 5
|
Deluxe
| 3
|
Married
| 6
| 0
| 5
| 1
| 2
|
Manager
| 24,580
|
0
| 26
|
Self Enquiry
| 1
| 26
|
Small Business
|
Male
| 4
| 4
|
Basic
| 3
|
Divorced
| 5
| 0
| 5
| 1
| 3
|
Executive
| 22,347
|
1
| 47
|
Company Invited
| 3
| 15
|
Salaried
|
Male
| 2
| 5
|
Super Deluxe
| 3
|
Married
| 1
| 0
| 5
| 1
| 1
|
AVP
| 27,936
|
0
| 28
|
Self Enquiry
| 3
| 16
|
Small Business
|
Male
| 3
| 3
|
Basic
| 4
|
Married
| 2
| 0
| 5
| 0
| 2
|
Executive
| 16,052
|
1
| 19
|
Company Invited
| 1
| 15
|
Small Business
|
Male
| 4
| 4
|
Basic
| 3
|
Single
| 3
| 0
| 5
| 0
| 1
|
Executive
| 20,582
|
0
| 52
|
Self Enquiry
| 3
| 9
|
Small Business
|
Male
| 2
| 4
|
Super Deluxe
| 5
|
Married
| 2
| 0
| 5
| 1
| 0
|
AVP
| 31,856
|
1
| 20
|
Company Invited
| 3
| 7
|
Large Business
|
Female
| 4
| 6
|
Basic
| 5
|
Single
| 2
| 0
| 3
| 1
| 2
|
Executive
| 21,003
|
0
| 43
|
Self Enquiry
| 3
| 15
|
Small Business
|
Male
| 3
| 4
|
Deluxe
| 4
|
Divorced
| 2
| 0
| 3
| 0
| 2
|
Manager
| 25,503
|
0
| 30
|
Self Enquiry
| 1
| 8
|
Salaried
|
Female
| 4
| 4
|
Basic
| 3
|
Married
| 3
| 0
| 1
| 1
| 3
|
Executive
| 22,438
|
1
| 51
|
Company Invited
| 3
| 7
|
Salaried
|
Male
| 4
| 4
|
Deluxe
| 3
|
Married
| 2
| 0
| 3
| 1
| 2
|
Manager
| 25,406
|
0
| 41
|
Company Invited
| 1
| 16
|
Salaried
|
Male
| 4
| 5
|
Deluxe
| 3
|
Married
| 2
| 0
| 5
| 0
| 2
|
Manager
| 23,554
|
0
| 33
|
Company Invited
| 3
| 15
|
Small Business
|
Fe Male
| 3
| 4
|
Standard
| 3
|
Unmarried
| 3
| 0
| 4
| 1
| 2
|
Senior Manager
| 27,676
|
0
| 22
|
Company Invited
| 3
| 16
|
Small Business
|
Male
| 3
| 4
|
Basic
| 3
|
Unmarried
| 3
| 0
| 4
| 0
| 1
|
Executive
| 21,288
|
0
| 40
|
Self Enquiry
| 1
| 16
|
Salaried
|
Female
| 2
| 1
|
Basic
| 3
|
Married
| 4
| 1
| 3
| 0
| 1
|
Executive
| 17,213
|
0
| 53
|
Self Enquiry
| 3
| 6
|
Small Business
|
Female
| 2
| 3
|
Deluxe
| 5
|
Unmarried
| 1
| 0
| 1
| 1
| 1
|
Manager
| 23,381
|
1
| 29
|
Company Invited
| 1
| 9
|
Small Business
|
Male
| 3
| 5
|
Basic
| 5
|
Single
| 2
| 0
| 4
| 0
| 1
|
Executive
| 21,239
|
0
| 44
|
Company Invited
| 1
| 16
|
Small Business
|
Male
| 4
| 4
|
Deluxe
| 3
|
Married
| 5
| 1
| 3
| 1
| 3
|
Manager
| 24,357
|
0
| 23
|
Self Enquiry
| 1
| 13
|
Small Business
|
Male
| 4
| 4
|
Basic
| 3
|
Divorced
| 2
| 0
| 2
| 1
| 1
|
Executive
| 21,451
|
0
| 43
|
Self Enquiry
| 1
| 36
|
Small Business
|
Male
| 3
| 6
|
Deluxe
| 3
|
Unmarried
| 6
| 0
| 3
| 1
| 1
|
Manager
| 22,950
|
0
| 33
|
Company Invited
| 3
| 23
|
Salaried
|
Male
| 2
| 3
|
Super Deluxe
| 3
|
Single
| 2
| 0
| 3
| 1
| 0
|
AVP
| 32,444
|
0
| 37
|
Company Invited
| 3
| 7
|
Small Business
|
Fe Male
| 3
| 4
|
Deluxe
| 3
|
Unmarried
| 6
| 0
| 1
| 1
| 2
|
Manager
| 25,331
|
0
| 37
|
Self Enquiry
| 1
| 16
|
Salaried
|
Female
| 2
| 1
|
Standard
| 3
|
Married
| 2
| 1
| 1
| 0
| 1
|
Senior Manager
| 28,744
|
1
| 40
|
Self Enquiry
| 3
| 10
|
Small Business
|
Female
| 3
| 4
|
Deluxe
| 3
|
Married
| 6
| 1
| 4
| 1
| 2
|
Manager
| 23,916
|
0
| 36
|
Self Enquiry
| 1
| 7
|
Salaried
|
Female
| 3
| 2
|
Basic
| 3
|
Single
| 5
| 0
| 3
| 1
| 2
|
Executive
| 21,184
|
0
| 50
|
Self Enquiry
| 1
| 23
|
Small Business
|
Female
| 4
| 4
|
Basic
| 5
|
Married
| 6
| 1
| 1
| 1
| 2
|
Executive
| 21,265
|
1
| 21
|
Company Invited
| 3
| 6
|
Large Business
|
Female
| 3
| 4
|
Basic
| 4
|
Single
| 2
| 1
| 5
| 1
| 2
|
Executive
| 17,174
|
1
| 28
|
Self Enquiry
| 3
| 9
|
Small Business
|
Female
| 4
| 6
|
King
| 4
|
Single
| 4
| 1
| 5
| 1
| 2
|
VP
| 21,195
|
0
| 52
|
Self Enquiry
| 1
| 15
|
Salaried
|
Male
| 3
| 5
|
Standard
| 4
|
Divorced
| 7
| 0
| 3
| 1
| 2
|
Senior Manager
| 31,168
|
1
| 40
|
Self Enquiry
| 1
| 14
|
Small Business
|
Male
| 3
| 4
|
Basic
| 3
|
Unmarried
| 2
| 1
| 4
| 1
| 2
|
Executive
| 24,094
|
0
| 29
|
Self Enquiry
| 1
| 12
|
Small Business
|
Female
| 2
| 3
|
Basic
| 3
|
Married
| 2
| 0
| 3
| 0
| 1
|
Executive
| 18,131
|
0
| 35
|
Company Invited
| 1
| 17
|
Small Business
|
Male
| 3
| 4
|
Standard
| 5
|
Divorced
| 3
| 1
| 5
| 1
| 1
|
Senior Manager
| 24,884
|
0
| 38
|
Self Enquiry
| 3
| 13
|
Small Business
|
Male
| 4
| 4
|
Deluxe
| 3
|
Married
| 6
| 0
| 3
| 1
| 1
|
Manager
| 25,180
|
0
| 51
|
Company Invited
| 1
| 6
|
Small Business
|
Female
| 1
| 4
|
Standard
| 5
|
Unmarried
| 4
| 0
| 2
| 1
| 0
|
Senior Manager
| 22,484
|
0
| 22
|
Company Invited
| 3
| 16
|
Small Business
|
Male
| 3
| 4
|
Basic
| 3
|
Unmarried
| 3
| 0
| 4
| 1
| 1
|
Executive
| 21,288
|
0
| 36
|
Self Enquiry
| 2
| 19
|
Salaried
|
Male
| 2
| 3
|
Basic
| 4
|
Married
| 5
| 0
| 3
| 1
| 1
|
Executive
| 17,143
|
0
| 31
|
Self Enquiry
| 1
| 17
|
Small Business
|
Male
| 3
| 3
|
Deluxe
| 5
|
Married
| 2
| 1
| 1
| 1
| 1
|
Manager
| 21,833
|
0
| 28
|
Self Enquiry
| 3
| 16
|
Small Business
|
Male
| 3
| 4
|
Deluxe
| 3
|
Unmarried
| 3
| 0
| 1
| 0
| 2
|
Manager
| 22,783
|
0
| 50
|
Self Enquiry
| 1
| 7
|
Large Business
|
Female
| 3
| 5
|
Super Deluxe
| 3
|
Single
| 2
| 1
| 3
| 0
| 1
|
AVP
| 32,642
|
0
| 28
|
Self Enquiry
| 1
| 13
|
Salaried
|
Male
| 3
| 5
|
Basic
| 3
|
Married
| 3
| 0
| 1
| 1
| 2
|
Executive
| 21,217
|
0
| 40
|
Self Enquiry
| 1
| 14
|
Salaried
|
Female
| 3
| 3
|
Deluxe
| 5
|
Married
| 3
| 1
| 1
| 0
| 0
|
Manager
| 21,516
|
0
| 29
|
Self Enquiry
| 1
| 21
|
Salaried
|
Male
| 2
| 3
|
Basic
| 3
|
Single
| 2
| 0
| 3
| 0
| 0
|
Executive
| 17,340
|
0
| 40
|
Self Enquiry
| 1
| 17
|
Small Business
|
Male
| 4
| 4
|
Standard
| 3
|
Single
| 2
| 0
| 3
| 1
| 1
|
Senior Manager
| 32,142
|
0
| 29
|
Company Invited
| 1
| 7
|
Small Business
|
Male
| 3
| 4
|
Basic
| 3
|
Single
| 2
| 1
| 4
| 0
| 1
|
Executive
| 20,832
|
0
| 31
|
Self Enquiry
| 1
| 8
|
Small Business
|
Male
| 4
| 4
|
Basic
| 4
|
Married
| 2
| 1
| 4
| 1
| 3
|
Executive
| 22,257
|
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