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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 18 missing columns ({'TypeofContact', 'DurationOfPitch', 'PitchSatisfactionScore', 'OwnCar', 'NumberOfPersonVisiting', 'NumberOfChildrenVisiting', 'Designation', 'NumberOfFollowups', 'Occupation', 'PreferredPropertyStar', 'Gender', 'Passport', 'Age', 'CityTier', 'MaritalStatus', 'NumberOfTrips', 'MonthlyIncome', 'ProductPitched'}).
This happened while the csv dataset builder was generating data using
hf://datasets/sam-vimes/tourism_data/prepped/y_train.csv (at revision 3f44b0725f39af9d98250d19090cd5499bcc8e11)
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('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 18 missing columns ({'TypeofContact', 'DurationOfPitch', 'PitchSatisfactionScore', 'OwnCar', 'NumberOfPersonVisiting', 'NumberOfChildrenVisiting', 'Designation', 'NumberOfFollowups', 'Occupation', 'PreferredPropertyStar', 'Gender', 'Passport', 'Age', 'CityTier', 'MaritalStatus', 'NumberOfTrips', 'MonthlyIncome', 'ProductPitched'}).
This happened while the csv dataset builder was generating data using
hf://datasets/sam-vimes/tourism_data/prepped/y_train.csv (at revision 3f44b0725f39af9d98250d19090cd5499bcc8e11)
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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
42
|
Self Enquiry
| 1
| 19
|
Large Business
|
Female
| 3
| 4
|
King
| 3
|
Divorced
| 3
| 0
| 4
| 1
| 1
|
VP
| 38,223
|
41
|
Company Invited
| 1
| 28
|
Salaried
|
Female
| 3
| 3
|
Deluxe
| 3
|
Married
| 4
| 1
| 5
| 0
| 0
|
Manager
| 20,467
|
28
|
Self Enquiry
| 1
| 15
|
Small Business
|
Female
| 4
| 4
|
Basic
| 3
|
Unmarried
| 3
| 0
| 4
| 1
| 3
|
Executive
| 22,123
|
26
|
Self Enquiry
| 3
| 35
|
Salaried
|
Male
| 3
| 5
|
Deluxe
| 3
|
Married
| 4
| 0
| 4
| 1
| 2
|
Manager
| 27,317
|
53
|
Self Enquiry
| 1
| 9
|
Salaried
|
Female
| 3
| 5
|
Basic
| 3
|
Unmarried
| 2
| 0
| 3
| 1
| 1
|
Executive
| 21,890
|
33
|
Self Enquiry
| 3
| 11
|
Small Business
|
Male
| 3
| 6
|
Standard
| 3
|
Married
| 3
| 0
| 1
| 1
| 1
|
Senior Manager
| 29,078
|
32
|
Self Enquiry
| 1
| 14
|
Small Business
|
Female
| 3
| 1
|
Deluxe
| 3
|
Divorced
| 6
| 0
| 3
| 1
| 2
|
Manager
| 20,175
|
51
|
Company Invited
| 3
| 19
|
Small Business
|
Female
| 4
| 4
|
Standard
| 3
|
Unmarried
| 6
| 0
| 5
| 1
| 3
|
Senior Manager
| 27,886
|
29
|
Company Invited
| 1
| 20
|
Salaried
|
Female
| 2
| 3
|
Standard
| 3
|
Unmarried
| 1
| 1
| 5
| 1
| 0
|
Senior Manager
| 22,553
|
38
|
Self Enquiry
| 1
| 16
|
Small Business
|
Female
| 3
| 3
|
Deluxe
| 3
|
Married
| 4
| 0
| 3
| 0
| 1
|
Manager
| 24,824
|
46
|
Company Invited
| 1
| 14
|
Salaried
|
Male
| 4
| 3
|
Deluxe
| 3
|
Divorced
| 6
| 0
| 2
| 0
| 3
|
Manager
| 25,112
|
28
|
Self Enquiry
| 1
| 15
|
Small Business
|
Female
| 3
| 2
|
Basic
| 3
|
Married
| 2
| 0
| 4
| 0
| 1
|
Executive
| 22,195
|
28
|
Self Enquiry
| 1
| 13
|
Salaried
|
Male
| 3
| 5
|
Basic
| 3
|
Married
| 3
| 0
| 1
| 1
| 2
|
Executive
| 21,217
|
35
|
Self Enquiry
| 1
| 29
|
Small Business
|
Male
| 3
| 5
|
Basic
| 3
|
Married
| 1
| 0
| 1
| 1
| 0
|
Executive
| 17,705
|
35
|
Self Enquiry
| 3
| 9
|
Salaried
|
Male
| 3
| 4
|
Deluxe
| 3
|
Unmarried
| 3
| 0
| 5
| 0
| 1
|
Manager
| 24,952
|
32
|
Self Enquiry
| 3
| 6
|
Small Business
|
Male
| 3
| 4
|
Basic
| 4
|
Married
| 1
| 0
| 1
| 0
| 2
|
Executive
| 17,269
|
41
|
Self Enquiry
| 1
| 15
|
Salaried
|
Male
| 3
| 3
|
Basic
| 5
|
Married
| 2
| 0
| 5
| 1
| 1
|
Executive
| 17,289
|
36
|
Self Enquiry
| 1
| 14
|
Salaried
|
Male
| 4
| 5
|
Basic
| 3
|
Married
| 3
| 0
| 3
| 1
| 1
|
Executive
| 21,368
|
21
|
Self Enquiry
| 1
| 11
|
Large Business
|
Male
| 3
| 4
|
Basic
| 5
|
Unmarried
| 3
| 0
| 3
| 1
| 1
|
Executive
| 21,651
|
33
|
Self Enquiry
| 1
| 12
|
Salaried
|
Male
| 4
| 3
|
Basic
| 4
|
Married
| 2
| 1
| 2
| 1
| 1
|
Executive
| 21,976
|
27
|
Self Enquiry
| 1
| 7
|
Small Business
|
Male
| 3
| 5
|
Basic
| 5
|
Married
| 3
| 0
| 3
| 1
| 2
|
Executive
| 22,633
|
33
|
Company Invited
| 1
| 36
|
Small Business
|
Female
| 4
| 4
|
Basic
| 3
|
Unmarried
| 2
| 0
| 3
| 1
| 3
|
Executive
| 22,703
|
29
|
Self Enquiry
| 3
| 12
|
Small Business
|
Male
| 4
| 4
|
Deluxe
| 3
|
Unmarried
| 3
| 0
| 3
| 0
| 2
|
Manager
| 23,586
|
58
|
Self Enquiry
| 1
| 8
|
Large Business
|
Male
| 2
| 3
|
Basic
| 3
|
Single
| 5
| 0
| 2
| 1
| 1
|
Executive
| 17,479
|
47
|
Self Enquiry
| 3
| 17
|
Small Business
|
Female
| 4
| 5
|
Standard
| 3
|
Divorced
| 4
| 1
| 2
| 1
| 2
|
Senior Manager
| 27,749
|
34
|
Self Enquiry
| 1
| 26
|
Large Business
|
Female
| 2
| 1
|
Basic
| 3
|
Divorced
| 1
| 0
| 1
| 1
| 0
|
Executive
| 17,585
|
44
|
Self Enquiry
| 1
| 34
|
Large Business
|
Male
| 3
| 2
|
Basic
| 4
|
Married
| 7
| 0
| 5
| 1
| 2
|
Executive
| 23,554
|
38
|
Self Enquiry
| 1
| 17
|
Small Business
|
Female
| 4
| 4
|
Basic
| 4
|
Married
| 3
| 0
| 1
| 1
| 1
|
Executive
| 22,614
|
24
|
Self Enquiry
| 1
| 24
|
Salaried
|
Male
| 2
| 3
|
Basic
| 3
|
Divorced
| 1
| 0
| 4
| 1
| 0
|
Executive
| 17,774
|
30
|
Self Enquiry
| 1
| 26
|
Salaried
|
Male
| 2
| 3
|
Deluxe
| 5
|
Married
| 1
| 0
| 4
| 0
| 1
|
Manager
| 24,957
|
45
|
Self Enquiry
| 1
| 16
|
Salaried
|
Male
| 4
| 4
|
Basic
| 5
|
Divorced
| 3
| 1
| 3
| 1
| 1
|
Executive
| 21,237
|
34
|
Company Invited
| 1
| 7
|
Small Business
|
Male
| 3
| 4
|
Deluxe
| 5
|
Single
| 1
| 0
| 1
| 0
| 0
|
Manager
| 20,343
|
39
|
Company Invited
| 1
| 36
|
Salaried
|
Female
| 3
| 4
|
Deluxe
| 3
|
Single
| 3
| 0
| 3
| 1
| 1
|
Manager
| 21,084
|
33
|
Self Enquiry
| 1
| 16
|
Small Business
|
Female
| 3
| 4
|
Basic
| 5
|
Unmarried
| 2
| 0
| 4
| 1
| 2
|
Executive
| 22,878
|
28
|
Self Enquiry
| 1
| 24
|
Large Business
|
Male
| 3
| 4
|
Basic
| 4
|
Married
| 2
| 1
| 4
| 0
| 1
|
Executive
| 21,736
|
43
|
Company Invited
| 1
| 26
|
Small Business
|
Male
| 3
| 2
|
Basic
| 3
|
Married
| 8
| 1
| 3
| 0
| 1
|
Executive
| 21,437
|
42
|
Company Invited
| 1
| 32
|
Small Business
|
Female
| 2
| 3
|
Standard
| 5
|
Divorced
| 4
| 1
| 3
| 0
| 1
|
Senior Manager
| 28,191
|
53
|
Self Enquiry
| 3
| 6
|
Small Business
|
Female
| 2
| 3
|
Deluxe
| 5
|
Unmarried
| 1
| 0
| 2
| 1
| 1
|
Manager
| 23,381
|
37
|
Self Enquiry
| 2
| 15
|
Salaried
|
Male
| 4
| 5
|
Basic
| 5
|
Married
| 2
| 0
| 1
| 0
| 2
|
Executive
| 21,020
|
31
|
Self Enquiry
| 1
| 29
|
Small Business
|
Male
| 3
| 4
|
Deluxe
| 3
|
Divorced
| 1
| 0
| 3
| 1
| 1
|
Manager
| 20,582
|
37
|
Company Invited
| 1
| 17
|
Salaried
|
Male
| 2
| 3
|
Standard
| 3
|
Married
| 2
| 1
| 3
| 1
| 1
|
Senior Manager
| 27,185
|
31
|
Self Enquiry
| 2
| 16
|
Salaried
|
Male
| 3
| 4
|
Deluxe
| 3
|
Married
| 2
| 1
| 3
| 1
| 2
|
Manager
| 25,025
|
27
|
Self Enquiry
| 1
| 11
|
Large Business
|
Male
| 2
| 4
|
Standard
| 3
|
Married
| 2
| 1
| 3
| 0
| 0
|
Senior Manager
| 27,808
|
40
|
Company Invited
| 3
| 11
|
Salaried
|
Male
| 2
| 4
|
Standard
| 5
|
Divorced
| 6
| 1
| 5
| 0
| 1
|
Senior Manager
| 25,475
|
38
|
Self Enquiry
| 1
| 23
|
Salaried
|
Female
| 3
| 4
|
Standard
| 3
|
Married
| 1
| 0
| 1
| 1
| 2
|
Senior Manager
| 23,823
|
29
|
Self Enquiry
| 1
| 34
|
Salaried
|
Female
| 3
| 3
|
Basic
| 3
|
Married
| 5
| 0
| 5
| 1
| 0
|
Executive
| 17,514
|
56
|
Company Invited
| 1
| 6
|
Salaried
|
Male
| 2
| 3
|
Deluxe
| 3
|
Married
| 2
| 0
| 3
| 0
| 0
|
Manager
| 21,306
|
25
|
Self Enquiry
| 3
| 19
|
Small Business
|
Male
| 2
| 3
|
Basic
| 3
|
Married
| 2
| 0
| 3
| 1
| 1
|
Executive
| 17,096
|
32
|
Company Invited
| 3
| 9
|
Salaried
|
Female
| 3
| 4
|
Standard
| 3
|
Married
| 3
| 1
| 1
| 1
| 1
|
Senior Manager
| 28,530
|
43
|
Self Enquiry
| 3
| 19
|
Small Business
|
Male
| 4
| 4
|
Deluxe
| 3
|
Married
| 5
| 1
| 1
| 0
| 1
|
Manager
| 23,765
|
33
|
Self Enquiry
| 1
| 7
|
Salaried
|
Male
| 4
| 5
|
Basic
| 3
|
Unmarried
| 2
| 1
| 5
| 1
| 1
|
Executive
| 22,408
|
39
|
Self Enquiry
| 2
| 7
|
Salaried
|
Male
| 3
| 2
|
Basic
| 3
|
Divorced
| 3
| 0
| 4
| 1
| 1
|
Executive
| 21,522
|
28
|
Self Enquiry
| 1
| 22
|
Small Business
|
Male
| 3
| 2
|
Deluxe
| 5
|
Single
| 1
| 0
| 5
| 0
| 2
|
Manager
| 20,661
|
37
|
Company Invited
| 1
| 25
|
Small Business
|
Female
| 4
| 4
|
Basic
| 3
|
Single
| 3
| 0
| 3
| 0
| 2
|
Executive
| 20,831
|
29
|
Self Enquiry
| 1
| 21
|
Salaried
|
Female
| 3
| 5
|
Basic
| 3
|
Divorced
| 1
| 1
| 5
| 1
| 0
|
Executive
| 17,168
|
32
|
Self Enquiry
| 1
| 14
|
Small Business
|
Female
| 3
| 4
|
Standard
| 3
|
Unmarried
| 3
| 1
| 4
| 1
| 2
|
Senior Manager
| 25,821
|
35
|
Self Enquiry
| 1
| 9
|
Small Business
|
Male
| 4
| 2
|
Basic
| 3
|
Married
| 2
| 1
| 1
| 0
| 2
|
Executive
| 21,610
|
30
|
Self Enquiry
| 1
| 8
|
Salaried
|
Female
| 4
| 4
|
Basic
| 3
|
Married
| 3
| 0
| 1
| 1
| 3
|
Executive
| 22,438
|
27
|
Self Enquiry
| 1
| 15
|
Small Business
|
Female
| 4
| 3
|
Basic
| 4
|
Single
| 2
| 0
| 3
| 0
| 1
|
Executive
| 17,279
|
43
|
Self Enquiry
| 3
| 22
|
Small Business
|
Female
| 3
| 3
|
Super Deluxe
| 3
|
Married
| 6
| 1
| 3
| 0
| 0
|
AVP
| 31,064
|
32
|
Self Enquiry
| 1
| 19
|
Small Business
|
Female
| 4
| 4
|
Basic
| 3
|
Divorced
| 2
| 1
| 4
| 1
| 3
|
Executive
| 22,607
|
31
|
Self Enquiry
| 1
| 8
|
Small Business
|
Male
| 4
| 4
|
Basic
| 4
|
Married
| 2
| 1
| 4
| 1
| 3
|
Executive
| 22,257
|
25
|
Company Invited
| 1
| 9
|
Large Business
|
Female
| 3
| 4
|
Basic
| 3
|
Unmarried
| 3
| 1
| 3
| 1
| 2
|
Executive
| 22,438
|
22
|
Self Enquiry
| 1
| 10
|
Small Business
|
Male
| 4
| 5
|
Basic
| 3
|
Unmarried
| 3
| 0
| 5
| 1
| 3
|
Executive
| 21,908
|
30
|
Self Enquiry
| 3
| 17
|
Salaried
|
Male
| 3
| 4
|
Basic
| 3
|
Unmarried
| 3
| 0
| 4
| 0
| 1
|
Executive
| 21,320
|
37
|
Company Invited
| 1
| 16
|
Salaried
|
Male
| 4
| 2
|
Basic
| 4
|
Married
| 3
| 0
| 5
| 1
| 1
|
Executive
| 21,488
|
43
|
Company Invited
| 1
| 9
|
Salaried
|
Male
| 3
| 4
|
Standard
| 3
|
Married
| 4
| 1
| 3
| 1
| 1
|
Senior Manager
| 28,802
|
28
|
Self Enquiry
| 1
| 25
|
Small Business
|
Male
| 3
| 4
|
Basic
| 5
|
Divorced
| 2
| 0
| 3
| 1
| 2
|
Executive
| 18,196
|
26
|
Self Enquiry
| 1
| 27
|
Small Business
|
Male
| 2
| 3
|
Basic
| 3
|
Married
| 2
| 0
| 5
| 1
| 1
|
Executive
| 17,377
|
19
|
Company Invited
| 1
| 15
|
Small Business
|
Male
| 4
| 4
|
Basic
| 3
|
Single
| 3
| 0
| 5
| 0
| 1
|
Executive
| 20,582
|
36
|
Self Enquiry
| 1
| 15
|
Salaried
|
Male
| 3
| 2
|
Basic
| 3
|
Married
| 3
| 0
| 5
| 1
| 2
|
Executive
| 20,947
|
49
|
Company Invited
| 1
| 24
|
Salaried
|
Male
| 3
| 3
|
Deluxe
| 3
|
Married
| 2
| 1
| 1
| 0
| 0
|
Manager
| 21,804
|
48
|
Self Enquiry
| 1
| 8
|
Large Business
|
Male
| 3
| 1
|
Basic
| 4
|
Single
| 6
| 0
| 2
| 0
| 2
|
Executive
| 17,559
|
50
|
Self Enquiry
| 1
| 32
|
Salaried
|
Female
| 3
| 4
|
Basic
| 5
|
Married
| 3
| 0
| 3
| 0
| 1
|
Executive
| 21,889
|
43
|
Company Invited
| 1
| 13
|
Small Business
|
Male
| 2
| 2
|
Basic
| 3
|
Married
| 5
| 0
| 4
| 0
| 1
|
Executive
| 17,089
|
34
|
Company Invited
| 3
| 29
|
Small Business
|
Male
| 4
| 4
|
Deluxe
| 4
|
Divorced
| 2
| 0
| 2
| 0
| 2
|
Manager
| 24,824
|
28
|
Company Invited
| 1
| 30
|
Large Business
|
Male
| 3
| 4
|
Standard
| 5
|
Unmarried
| 2
| 0
| 1
| 1
| 1
|
Senior Manager
| 23,722
|
39
|
Self Enquiry
| 3
| 21
|
Salaried
|
Male
| 4
| 4
|
Deluxe
| 4
|
Married
| 2
| 0
| 5
| 1
| 3
|
Manager
| 28,602
|
33
|
Self Enquiry
| 1
| 6
|
Small Business
|
Female
| 3
| 1
|
Super Deluxe
| 3
|
Married
| 5
| 0
| 1
| 1
| 0
|
AVP
| 31,184
|
29
|
Self Enquiry
| 3
| 8
|
Small Business
|
Male
| 3
| 4
|
Deluxe
| 4
|
Married
| 3
| 0
| 4
| 1
| 0
|
Manager
| 21,644
|
33
|
Self Enquiry
| 1
| 6
|
Salaried
|
Female
| 2
| 4
|
Deluxe
| 3
|
Unmarried
| 1
| 0
| 4
| 0
| 0
|
Manager
| 21,949
|
29
|
Company Invited
| 1
| 13
|
Salaried
|
Male
| 3
| 5
|
Basic
| 3
|
Married
| 3
| 1
| 4
| 1
| 1
|
Executive
| 21,381
|
40
|
Company Invited
| 1
| 22
|
Small Business
|
Male
| 2
| 4
|
Deluxe
| 3
|
Single
| 7
| 0
| 5
| 1
| 1
|
Manager
| 20,094
|
50
|
Self Enquiry
| 1
| 15
|
Salaried
|
Female
| 3
| 4
|
Standard
| 4
|
Divorced
| 6
| 0
| 4
| 0
| 1
|
Senior Manager
| 26,081
|
31
|
Company Invited
| 3
| 26
|
Small Business
|
Female
| 2
| 3
|
Deluxe
| 3
|
Divorced
| 2
| 0
| 2
| 1
| 0
|
Manager
| 21,932
|
21
|
Company Invited
| 1
| 13
|
Salaried
|
Female
| 4
| 5
|
Basic
| 3
|
Unmarried
| 3
| 1
| 1
| 0
| 1
|
Executive
| 21,604
|
40
|
Self Enquiry
| 1
| 7
|
Small Business
|
Female
| 4
| 4
|
Basic
| 3
|
Married
| 2
| 0
| 3
| 0
| 2
|
Executive
| 20,910
|
57
|
Self Enquiry
| 3
| 35
|
Small Business
|
Male
| 2
| 4
|
Super Deluxe
| 3
|
Married
| 4
| 0
| 3
| 1
| 0
|
AVP
| 29,118
|
44
|
Self Enquiry
| 1
| 16
|
Salaried
|
Male
| 3
| 3
|
Basic
| 3
|
Single
| 2
| 1
| 3
| 1
| 0
|
Executive
| 17,936
|
25
|
Self Enquiry
| 3
| 17
|
Small Business
|
Female
| 4
| 4
|
Deluxe
| 3
|
Married
| 3
| 1
| 2
| 0
| 3
|
Manager
| 22,938
|
37
|
Self Enquiry
| 3
| 9
|
Salaried
|
Male
| 2
| 3
|
Standard
| 3
|
Unmarried
| 3
| 0
| 3
| 0
| 0
|
Senior Manager
| 22,428
|
38
|
Company Invited
| 1
| 12
|
Large Business
|
Male
| 3
| 2
|
Basic
| 3
|
Unmarried
| 2
| 0
| 5
| 1
| 1
|
Executive
| 22,178
|
42
|
Self Enquiry
| 1
| 10
|
Large Business
|
Male
| 2
| 3
|
King
| 3
|
Married
| 2
| 0
| 1
| 0
| 0
|
VP
| 34,232
|
43
|
Company Invited
| 1
| 33
|
Small Business
|
Female
| 3
| 4
|
Standard
| 5
|
Divorced
| 5
| 1
| 3
| 0
| 2
|
Senior Manager
| 31,869
|
41
|
Self Enquiry
| 1
| 7
|
Salaried
|
Female
| 3
| 4
|
Deluxe
| 3
|
Married
| 6
| 0
| 3
| 0
| 2
|
Manager
| 25,191
|
21
|
Self Enquiry
| 1
| 6
|
Salaried
|
Male
| 3
| 5
|
Basic
| 3
|
Unmarried
| 3
| 0
| 3
| 0
| 1
|
Executive
| 21,711
|
51
|
Self Enquiry
| 1
| 31
|
Salaried
|
Male
| 4
| 4
|
Super Deluxe
| 3
|
Married
| 5
| 1
| 4
| 1
| 3
|
AVP
| 32,651
|
31
|
Company Invited
| 3
| 33
|
Small Business
|
Female
| 3
| 5
|
Deluxe
| 5
|
Unmarried
| 7
| 0
| 2
| 0
| 2
|
Manager
| 25,374
|
27
|
Self Enquiry
| 1
| 13
|
Salaried
|
Female
| 3
| 5
|
Basic
| 4
|
Married
| 3
| 0
| 3
| 1
| 2
|
Executive
| 21,046
|
52
|
Company Invited
| 3
| 9
|
Small Business
|
Male
| 3
| 4
|
Standard
| 4
|
Divorced
| 4
| 0
| 4
| 0
| 1
|
Senior Manager
| 29,274
|
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