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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 3 new columns ({'CustomerID', 'ProdTaken', 'Unnamed: 0'})
This happened while the csv dataset builder was generating data using
hf://datasets/subhradasgupta/gl-tourism-data/tourism.csv (at revision 99f779ad20ec3999a2f75b0db9c78704632c4b82)
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
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('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 3 new columns ({'CustomerID', 'ProdTaken', 'Unnamed: 0'})
This happened while the csv dataset builder was generating data using
hf://datasets/subhradasgupta/gl-tourism-data/tourism.csv (at revision 99f779ad20ec3999a2f75b0db9c78704632c4b82)
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 | 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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
33
|
Company Invited
| 3
| 15
|
Small Business
|
Female
| 3
| 4
|
Standard
| 3
|
Unmarried
| 3
| 0
| 4
| 1
| 2
|
Senior Manager
| 27,676
|
42
|
Company Invited
| 3
| 7
|
Small Business
|
Female
| 4
| 4
|
Deluxe
| 5
|
Married
| 2
| 0
| 3
| 0
| 2
|
Manager
| 22,781
|
59
|
Company Invited
| 2
| 8
|
Salaried
|
Female
| 2
| 4
|
King
| 3
|
Divorced
| 1
| 0
| 2
| 1
| 1
|
VP
| 33,844
|
26
|
Self Enquiry
| 3
| 11
|
Small Business
|
Male
| 3
| 5
|
Deluxe
| 5
|
Married
| 3
| 0
| 3
| 1
| 2
|
Manager
| 22,934
|
51
|
Company Invited
| 3
| 7
|
Salaried
|
Male
| 4
| 4
|
Deluxe
| 3
|
Married
| 2
| 0
| 3
| 1
| 2
|
Manager
| 25,406
|
47
|
Company Invited
| 3
| 15
|
Salaried
|
Male
| 2
| 5
|
Super Deluxe
| 3
|
Married
| 1
| 0
| 5
| 1
| 1
|
AVP
| 27,936
|
39
|
Company Invited
| 3
| 27
|
Salaried
|
Female
| 2
| 5
|
Deluxe
| 3
|
Married
| 7
| 0
| 5
| 0
| 0
|
Manager
| 20,736
|
31
|
Company Invited
| 1
| 26
|
Salaried
|
Male
| 3
| 3
|
Standard
| 3
|
Divorced
| 4
| 0
| 3
| 1
| 0
|
Senior Manager
| 24,824
|
58
|
Company Invited
| 1
| 6
|
Salaried
|
Male
| 2
| 5
|
Deluxe
| 3
|
Married
| 3
| 1
| 2
| 1
| 1
|
Manager
| 20,660
|
43
|
Self Enquiry
| 3
| 10
|
Small Business
|
Female
| 2
| 4
|
Standard
| 3
|
Unmarried
| 4
| 0
| 3
| 1
| 0
|
Senior Manager
| 25,231
|
49
|
Self Enquiry
| 1
| 7
|
Salaried
|
Male
| 4
| 5
|
Standard
| 3
|
Unmarried
| 2
| 1
| 5
| 0
| 3
|
Senior Manager
| 24,059
|
28
|
Company Invited
| 3
| 27
|
Salaried
|
Female
| 3
| 4
|
Deluxe
| 3
|
Single
| 3
| 0
| 2
| 1
| 2
|
Manager
| 28,659
|
30
|
Self Enquiry
| 3
| 10
|
Small Business
|
Female
| 3
| 4
|
Deluxe
| 4
|
Married
| 2
| 1
| 3
| 1
| 1
|
Manager
| 20,209
|
26
|
Company Invited
| 1
| 12
|
Salaried
|
Male
| 3
| 1
|
Basic
| 3
|
Married
| 1
| 0
| 4
| 1
| 1
|
Executive
| 17,544
|
37
|
Company Invited
| 1
| 17
|
Salaried
|
Male
| 2
| 3
|
Standard
| 3
|
Married
| 2
| 1
| 3
| 0
| 1
|
Senior Manager
| 27,185
|
38
|
Company Invited
| 2
| 6
|
Salaried
|
Male
| 2
| 3
|
Basic
| 4
|
Married
| 1
| 1
| 1
| 1
| 1
|
Executive
| 17,991
|
34
|
Company Invited
| 1
| 22
|
Salaried
|
Female
| 3
| 4
|
Basic
| 3
|
Single
| 2
| 0
| 5
| 1
| 1
|
Executive
| 17,553
|
47
|
Self Enquiry
| 1
| 8
|
Salaried
|
Female
| 2
| 3
|
Super Deluxe
| 3
|
Divorced
| 2
| 1
| 4
| 1
| 0
|
AVP
| 31,752
|
44
|
Company Invited
| 1
| 11
|
Salaried
|
Male
| 2
| 4
|
Basic
| 3
|
Single
| 4
| 0
| 1
| 0
| 1
|
Executive
| 18,162
|
39
|
Self Enquiry
| 1
| 13
|
Salaried
|
Female
| 3
| 5
|
Basic
| 3
|
Married
| 3
| 0
| 3
| 0
| 2
|
Executive
| 22,380
|
31
|
Self Enquiry
| 3
| 11
|
Salaried
|
Female
| 3
| 3
|
Deluxe
| 3
|
Married
| 2
| 0
| 1
| 0
| 2
|
Manager
| 20,476
|
31
|
Company Invited
| 3
| 26
|
Salaried
|
Male
| 3
| 1
|
Basic
| 3
|
Married
| 1
| 0
| 5
| 1
| 0
|
Executive
| 17,791
|
32
|
Self Enquiry
| 1
| 16
|
Salaried
|
Male
| 3
| 4
|
Standard
| 4
|
Married
| 3
| 0
| 3
| 1
| 2
|
Senior Manager
| 29,326
|
39
|
Company Invited
| 1
| 19
|
Salaried
|
Male
| 2
| 5
|
Deluxe
| 5
|
Married
| 4
| 0
| 5
| 1
| 1
|
Manager
| 24,966
|
45
|
Self Enquiry
| 1
| 6
|
Small Business
|
Female
| 3
| 3
|
Basic
| 3
|
Married
| 4
| 0
| 5
| 1
| 0
|
Executive
| 17,270
|
40
|
Self Enquiry
| 3
| 12
|
Large Business
|
Male
| 3
| 4
|
Deluxe
| 3
|
Divorced
| 5
| 0
| 2
| 0
| 2
|
Manager
| 20,764
|
40
|
Self Enquiry
| 1
| 26
|
Large Business
|
Male
| 3
| 3
|
Standard
| 3
|
Divorced
| 5
| 0
| 3
| 1
| 1
|
Senior Manager
| 25,322
|
38
|
Self Enquiry
| 3
| 7
|
Salaried
|
Male
| 3
| 5
|
Standard
| 3
|
Married
| 7
| 0
| 1
| 1
| 2
|
Senior Manager
| 29,287
|
39
|
Self Enquiry
| 1
| 12
|
Small Business
|
Male
| 3
| 3
|
Basic
| 5
|
Divorced
| 1
| 1
| 2
| 1
| 1
|
Executive
| 17,404
|
44
|
Self Enquiry
| 2
| 6
|
Small Business
|
Male
| 3
| 4
|
Standard
| 5
|
Married
| 1
| 0
| 4
| 1
| 0
|
Senior Manager
| 25,482
|
28
|
Company Invited
| 1
| 8
|
Small Business
|
Male
| 2
| 4
|
Basic
| 5
|
Single
| 1
| 0
| 4
| 0
| 0
|
Executive
| 17,561
|
52
|
Self Enquiry
| 1
| 18
|
Large Business
|
Female
| 3
| 5
|
Super Deluxe
| 4
|
Single
| 5
| 0
| 1
| 0
| 2
|
AVP
| 31,820
|
57
|
Self Enquiry
| 1
| 14
|
Salaried
|
Male
| 3
| 6
|
Standard
| 3
|
Unmarried
| 6
| 0
| 2
| 0
| 1
|
Senior Manager
| 25,938
|
52
|
Self Enquiry
| 3
| 11
|
Salaried
|
Male
| 3
| 3
|
Standard
| 4
|
Unmarried
| 1
| 1
| 4
| 1
| 1
|
Senior Manager
| 23,446
|
38
|
Self Enquiry
| 1
| 17
|
Salaried
|
Male
| 3
| 4
|
Deluxe
| 4
|
Unmarried
| 4
| 1
| 5
| 0
| 2
|
Manager
| 22,875
|
37
|
Self Enquiry
| 1
| 10
|
Salaried
|
Female
| 3
| 4
|
Basic
| 3
|
Married
| 7
| 0
| 2
| 1
| 1
|
Executive
| 21,513
|
33
|
Self Enquiry
| 1
| 15
|
Small Business
|
Male
| 2
| 3
|
Basic
| 3
|
Divorced
| 1
| 0
| 2
| 1
| 0
|
Executive
| 17,781
|
45
|
Self Enquiry
| 1
| 8
|
Salaried
|
Female
| 3
| 4
|
Basic
| 3
|
Single
| 2
| 0
| 3
| 1
| 0
|
Executive
| 17,274
|
32
|
Self Enquiry
| 1
| 19
|
Small Business
|
Female
| 4
| 4
|
Basic
| 3
|
Married
| 2
| 1
| 4
| 1
| 2
|
Executive
| 22,607
|
33
|
Self Enquiry
| 1
| 8
|
Salaried
|
Female
| 2
| 3
|
Basic
| 5
|
Divorced
| 1
| 0
| 3
| 1
| 0
|
Executive
| 17,707
|
30
|
Self Enquiry
| 1
| 14
|
Salaried
|
Female
| 3
| 1
|
Standard
| 5
|
Divorced
| 1
| 1
| 2
| 0
| 2
|
Senior Manager
| 26,416
|
33
|
Company Invited
| 1
| 14
|
Salaried
|
Male
| 4
| 3
|
Basic
| 4
|
Divorced
| 3
| 0
| 2
| 0
| 2
|
Executive
| 21,472
|
37
|
Company Invited
| 3
| 18
|
Large Business
|
Female
| 4
| 4
|
Standard
| 3
|
Married
| 2
| 0
| 5
| 0
| 3
|
Senior Manager
| 28,416
|
31
|
Self Enquiry
| 1
| 29
|
Salaried
|
Female
| 3
| 4
|
Basic
| 3
|
Married
| 6
| 1
| 1
| 0
| 1
|
Executive
| 20,810
|
58
|
Company Invited
| 1
| 6
|
Salaried
|
Male
| 2
| 5
|
Deluxe
| 3
|
Married
| 3
| 1
| 1
| 1
| 1
|
Manager
| 20,660
|
46
|
Self Enquiry
| 1
| 9
|
Salaried
|
Female
| 4
| 5
|
Basic
| 3
|
Single
| 3
| 0
| 3
| 1
| 1
|
Executive
| 20,952
|
44
|
Self Enquiry
| 1
| 14
|
Salaried
|
Female
| 3
| 4
|
Standard
| 5
|
Divorced
| 2
| 0
| 5
| 1
| 1
|
Senior Manager
| 28,663
|
42
|
Self Enquiry
| 2
| 16
|
Salaried
|
Female
| 2
| 3
|
Super Deluxe
| 5
|
Divorced
| 1
| 0
| 3
| 0
| 1
|
AVP
| 31,799
|
43
|
Company Invited
| 1
| 13
|
Small Business
|
Male
| 2
| 1
|
Basic
| 3
|
Married
| 5
| 0
| 4
| 1
| 0
|
Executive
| 17,089
|
38
|
Company Invited
| 1
| 18
|
Salaried
|
Male
| 3
| 4
|
Standard
| 3
|
Married
| 3
| 1
| 3
| 1
| 2
|
Senior Manager
| 30,863
|
28
|
Self Enquiry
| 1
| 11
|
Salaried
|
Male
| 4
| 4
|
Basic
| 3
|
Married
| 3
| 0
| 4
| 1
| 2
|
Executive
| 21,195
|
37
|
Self Enquiry
| 3
| 23
|
Small Business
|
Female
| 4
| 5
|
Deluxe
| 5
|
Divorced
| 6
| 0
| 5
| 1
| 1
|
Manager
| 24,325
|
34
|
Company Invited
| 1
| 36
|
Small Business
|
Female
| 3
| 5
|
Deluxe
| 3
|
Unmarried
| 3
| 0
| 5
| 1
| 1
|
Manager
| 23,186
|
35
|
Self Enquiry
| 1
| 17
|
Small Business
|
Male
| 3
| 4
|
Deluxe
| 5
|
Unmarried
| 3
| 0
| 4
| 0
| 1
|
Manager
| 24,803
|
52
|
Self Enquiry
| 1
| 6
|
Salaried
|
Male
| 3
| 3
|
Super Deluxe
| 3
|
Married
| 3
| 0
| 1
| 1
| 2
|
AVP
| 32,099
|
35
|
Self Enquiry
| 1
| 14
|
Salaried
|
Female
| 3
| 4
|
Standard
| 4
|
Single
| 2
| 0
| 5
| 0
| 1
|
Senior Manager
| 30,672
|
57
|
Self Enquiry
| 1
| 30
|
Salaried
|
Male
| 2
| 2
|
Standard
| 3
|
Married
| 4
| 1
| 4
| 1
| 1
|
Senior Manager
| 24,439
|
37
|
Self Enquiry
| 3
| 10
|
Small Business
|
Female
| 4
| 5
|
Standard
| 3
|
Married
| 2
| 0
| 3
| 1
| 1
|
Senior Manager
| 26,322
|
46
|
Self Enquiry
| 1
| 14
|
Salaried
|
Male
| 3
| 4
|
Standard
| 5
|
Married
| 4
| 0
| 3
| 1
| 2
|
Senior Manager
| 28,402
|
36
|
Self Enquiry
| 1
| 12
|
Salaried
|
Male
| 2
| 3
|
Basic
| 3
|
Divorced
| 1
| 0
| 5
| 1
| 1
|
Executive
| 18,210
|
50
|
Self Enquiry
| 1
| 30
|
Salaried
|
Male
| 3
| 3
|
Super Deluxe
| 3
|
Married
| 4
| 1
| 4
| 1
| 2
|
AVP
| 28,973
|
34
|
Self Enquiry
| 3
| 15
|
Salaried
|
Female
| 3
| 3
|
Deluxe
| 3
|
Divorced
| 2
| 0
| 2
| 1
| 2
|
Manager
| 20,714
|
52
|
Self Enquiry
| 3
| 34
|
Salaried
|
Male
| 3
| 4
|
Deluxe
| 3
|
Single
| 3
| 1
| 5
| 1
| 2
|
Manager
| 32,704
|
32
|
Self Enquiry
| 3
| 9
|
Salaried
|
Male
| 4
| 4
|
Deluxe
| 3
|
Unmarried
| 6
| 1
| 5
| 1
| 2
|
Manager
| 25,260
|
34
|
Company Invited
| 3
| 14
|
Salaried
|
Female
| 2
| 4
|
Deluxe
| 4
|
Divorced
| 2
| 0
| 4
| 1
| 1
|
Manager
| 22,980
|
41
|
Self Enquiry
| 3
| 7
|
Small Business
|
Male
| 3
| 6
|
Deluxe
| 3
|
Divorced
| 4
| 1
| 3
| 1
| 1
|
Manager
| 26,135
|
42
|
Self Enquiry
| 1
| 6
|
Salaried
|
Female
| 3
| 3
|
Basic
| 5
|
Married
| 4
| 0
| 3
| 1
| 1
|
Executive
| 17,576
|
28
|
Self Enquiry
| 1
| 15
|
Small Business
|
Female
| 3
| 3
|
Basic
| 3
|
Married
| 6
| 0
| 3
| 1
| 1
|
Executive
| 17,377
|
48
|
Company Invited
| 1
| 6
|
Small Business
|
Male
| 2
| 1
|
Super Deluxe
| 3
|
Single
| 3
| 0
| 1
| 0
| 0
|
AVP
| 31,885
|
53
|
Self Enquiry
| 3
| 6
|
Small Business
|
Female
| 2
| 3
|
Deluxe
| 5
|
Unmarried
| 1
| 0
| 2
| 1
| 1
|
Manager
| 23,381
|
34
|
Company Invited
| 1
| 10
|
Salaried
|
Female
| 3
| 4
|
Basic
| 3
|
Married
| 3
| 1
| 1
| 1
| 2
|
Executive
| 21,587
|
32
|
Self Enquiry
| 1
| 11
|
Salaried
|
Female
| 3
| 4
|
Deluxe
| 4
|
Married
| 4
| 0
| 3
| 1
| 0
|
Manager
| 20,878
|
32
|
Self Enquiry
| 3
| 13
|
Salaried
|
Male
| 3
| 4
|
Deluxe
| 3
|
Married
| 2
| 0
| 3
| 1
| 0
|
Manager
| 20,484
|
29
|
Self Enquiry
| 1
| 16
|
Small Business
|
Female
| 4
| 4
|
Basic
| 3
|
Married
| 7
| 0
| 3
| 1
| 2
|
Executive
| 21,055
|
36
|
Self Enquiry
| 3
| 23
|
Small Business
|
Male
| 4
| 4
|
Standard
| 4
|
Married
| 2
| 0
| 1
| 1
| 2
|
Senior Manager
| 26,698
|
33
|
Self Enquiry
| 1
| 8
|
Small Business
|
Male
| 3
| 3
|
Basic
| 3
|
Single
| 5
| 0
| 3
| 1
| 2
|
Executive
| 17,496
|
39
|
Self Enquiry
| 1
| 16
|
Small Business
|
Male
| 3
| 3
|
Super Deluxe
| 5
|
Married
| 2
| 1
| 3
| 1
| 2
|
AVP
| 32,068
|
35
|
Self Enquiry
| 1
| 13
|
Small Business
|
Male
| 3
| 4
|
Basic
| 5
|
Unmarried
| 4
| 0
| 4
| 0
| 1
|
Executive
| 21,638
|
51
|
Company Invited
| 1
| 14
|
Salaried
|
Male
| 2
| 5
|
Standard
| 3
|
Unmarried
| 3
| 0
| 2
| 0
| 1
|
Senior Manager
| 25,650
|
46
|
Self Enquiry
| 3
| 16
|
Small Business
|
Female
| 3
| 4
|
Standard
| 3
|
Married
| 3
| 1
| 1
| 0
| 0
|
Senior Manager
| 24,071
|
30
|
Self Enquiry
| 2
| 6
|
Salaried
|
Male
| 2
| 3
|
Basic
| 3
|
Married
| 1
| 0
| 1
| 0
| 1
|
Executive
| 17,064
|
52
|
Self Enquiry
| 1
| 13
|
Salaried
|
Male
| 2
| 3
|
Standard
| 4
|
Unmarried
| 1
| 0
| 3
| 1
| 1
|
Senior Manager
| 25,445
|
31
|
Self Enquiry
| 3
| 12
|
Small Business
|
Male
| 3
| 2
|
Deluxe
| 3
|
Married
| 5
| 0
| 5
| 1
| 2
|
Manager
| 20,460
|
29
|
Self Enquiry
| 1
| 21
|
Salaried
|
Female
| 3
| 5
|
Basic
| 3
|
Divorced
| 1
| 1
| 5
| 1
| 0
|
Executive
| 17,168
|
55
|
Self Enquiry
| 1
| 8
|
Salaried
|
Female
| 3
| 3
|
Super Deluxe
| 3
|
Single
| 3
| 1
| 5
| 0
| 1
|
AVP
| 31,659
|
55
|
Self Enquiry
| 1
| 24
|
Large Business
|
Female
| 3
| 4
|
Standard
| 3
|
Married
| 2
| 0
| 5
| 0
| 1
|
Senior Manager
| 29,417
|
55
|
Company Invited
| 1
| 8
|
Small Business
|
Male
| 2
| 4
|
Super Deluxe
| 5
|
Single
| 1
| 0
| 3
| 1
| 1
|
AVP
| 31,756
|
21
|
Self Enquiry
| 1
| 21
|
Salaried
|
Male
| 3
| 3
|
Basic
| 3
|
Single
| 2
| 0
| 3
| 1
| 1
|
Executive
| 16,232
|
37
|
Company Invited
| 1
| 25
|
Salaried
|
Male
| 4
| 4
|
Deluxe
| 3
|
Unmarried
| 4
| 0
| 3
| 0
| 2
|
Manager
| 26,457
|
43
|
Self Enquiry
| 1
| 8
|
Small Business
|
Female
| 3
| 1
|
Basic
| 3
|
Married
| 2
| 0
| 1
| 1
| 2
|
Executive
| 17,645
|
30
|
Self Enquiry
| 1
| 28
|
Salaried
|
Female
| 3
| 2
|
Standard
| 5
|
Married
| 3
| 0
| 5
| 1
| 2
|
Senior Manager
| 28,658
|
37
|
Self Enquiry
| 1
| 9
|
Small Business
|
Male
| 4
| 4
|
Basic
| 3
|
Single
| 6
| 0
| 5
| 1
| 2
|
Executive
| 21,197
|
40
|
Company Invited
| 1
| 6
|
Salaried
|
Male
| 3
| 4
|
Super Deluxe
| 4
|
Married
| 2
| 0
| 1
| 1
| 1
|
AVP
| 28,503
|
29
|
Self Enquiry
| 1
| 15
|
Salaried
|
Female
| 4
| 4
|
Basic
| 3
|
Unmarried
| 3
| 0
| 4
| 1
| 2
|
Executive
| 21,988
|
27
|
Self Enquiry
| 1
| 23
|
Salaried
|
Female
| 2
| 3
|
Basic
| 3
|
Single
| 2
| 1
| 5
| 1
| 0
|
Executive
| 17,394
|
36
|
Company Invited
| 1
| 15
|
Salaried
|
Female
| 3
| 4
|
Deluxe
| 3
|
Married
| 3
| 0
| 5
| 1
| 2
|
Manager
| 22,826
|
46
|
Company Invited
| 1
| 11
|
Salaried
|
Male
| 3
| 4
|
Deluxe
| 4
|
Divorced
| 3
| 0
| 4
| 1
| 2
|
Manager
| 23,125
|
30
|
Self Enquiry
| 1
| 35
|
Small Business
|
Female
| 4
| 5
|
Basic
| 5
|
Unmarried
| 3
| 0
| 1
| 0
| 2
|
Executive
| 22,463
|
29
|
Self Enquiry
| 3
| 6
|
Small Business
|
Female
| 2
| 4
|
Basic
| 3
|
Married
| 7
| 1
| 2
| 0
| 1
|
Executive
| 17,800
|
29
|
Self Enquiry
| 1
| 6
|
Salaried
|
Female
| 2
| 4
|
Basic
| 5
|
Married
| 2
| 1
| 1
| 0
| 0
|
Executive
| 17,319
|
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