The full dataset viewer is not available (click to read why). Only showing a preview of the rows.
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 ({'PitchSatisfactionScore', 'OwnCar', 'NumberOfChildrenVisiting', 'PreferredPropertyStar', 'Occupation', 'Gender', 'NumberOfFollowups', 'MaritalStatus', 'NumberOfTrips', 'NumberOfPersonVisiting', 'Designation', 'ProductPitched', 'Passport', 'DurationOfPitch', 'TypeofContact', 'MonthlyIncome', 'CityTier', 'Age'}).
This happened while the csv dataset builder was generating data using
hf://datasets/sgpai/tourism-mlops/y_train.csv (at revision 857cef7e2da9b26c8d7708abe41c74e3e6954904)
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 ({'PitchSatisfactionScore', 'OwnCar', 'NumberOfChildrenVisiting', 'PreferredPropertyStar', 'Occupation', 'Gender', 'NumberOfFollowups', 'MaritalStatus', 'NumberOfTrips', 'NumberOfPersonVisiting', 'Designation', 'ProductPitched', 'Passport', 'DurationOfPitch', 'TypeofContact', 'MonthlyIncome', 'CityTier', 'Age'}).
This happened while the csv dataset builder was generating data using
hf://datasets/sgpai/tourism-mlops/y_train.csv (at revision 857cef7e2da9b26c8d7708abe41c74e3e6954904)
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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
28
|
Company Invited
| 1
| 30
|
Large Business
|
Male
| 3
| 4
|
Standard
| 5
|
Unmarried
| 2
| 0
| 2
| 0
| 0
|
Senior Manager
| 23,722
|
34
|
Company Invited
| 3
| 12
|
Small Business
|
Female
| 2
| 5
|
Basic
| 3
|
Married
| 1
| 0
| 4
| 0
| 1
|
Executive
| 17,351
|
26
|
Self Enquiry
| 3
| 11
|
Salaried
|
Female
| 3
| 5
|
Deluxe
| 3
|
Unmarried
| 3
| 1
| 2
| 0
| 2
|
Manager
| 23,165
|
37
|
Self Enquiry
| 3
| 22
|
Small Business
|
Male
| 3
| 4
|
Deluxe
| 3
|
Married
| 5
| 0
| 5
| 1
| 0
|
Manager
| 21,334
|
45
|
Self Enquiry
| 3
| 15
|
Small Business
|
Male
| 3
| 3
|
Standard
| 5
|
Married
| 5
| 1
| 1
| 0
| 0
|
Senior Manager
| 25,761
|
53
|
Company Invited
| 1
| 32
|
Small Business
|
Female
| 3
| 5
|
Super Deluxe
| 3
|
Married
| 5
| 0
| 5
| 0
| 2
|
AVP
| 32,504
|
33
|
Company Invited
| 1
| 6
|
Small Business
|
Male
| 2
| 4
|
Basic
| 3
|
Married
| 2
| 0
| 3
| 0
| 0
|
Executive
| 17,008
|
38
|
Self Enquiry
| 1
| 6
|
Salaried
|
Female
| 2
| 2
|
Deluxe
| 3
|
Unmarried
| 1
| 0
| 2
| 1
| 1
|
Manager
| 22,625
|
33
|
Company Invited
| 1
| 12
|
Large Business
|
Male
| 4
| 4
|
Basic
| 4
|
Unmarried
| 4
| 0
| 3
| 1
| 2
|
Executive
| 21,396
|
46
|
Self Enquiry
| 3
| 8
|
Small Business
|
Female
| 2
| 3
|
King
| 5
|
Single
| 4
| 0
| 1
| 1
| 1
|
VP
| 33,947
|
35
|
Self Enquiry
| 1
| 15
|
Salaried
|
Female
| 3
| 4
|
Standard
| 3
|
Divorced
| 2
| 1
| 4
| 1
| 1
|
Senior Manager
| 25,685
|
41
|
Self Enquiry
| 1
| 9
|
Salaried
|
Male
| 3
| 5
|
Basic
| 3
|
Unmarried
| 4
| 0
| 5
| 0
| 2
|
Executive
| 21,487
|
49
|
Self Enquiry
| 3
| 9
|
Small Business
|
Female
| 3
| 4
|
Deluxe
| 3
|
Married
| 4
| 0
| 5
| 1
| 1
|
Manager
| 22,729
|
50
|
Company Invited
| 2
| 9
|
Small Business
|
Male
| 3
| 3
|
King
| 4
|
Married
| 2
| 0
| 1
| 1
| 2
|
VP
| 33,200
|
33
|
Company Invited
| 1
| 31
|
Salaried
|
Male
| 4
| 4
|
Deluxe
| 3
|
Married
| 3
| 0
| 4
| 1
| 3
|
Manager
| 23,987
|
32
|
Self Enquiry
| 1
| 14
|
Small Business
|
Female
| 3
| 1
|
Deluxe
| 3
|
Divorced
| 6
| 0
| 3
| 1
| 2
|
Manager
| 20,175
|
35
|
Self Enquiry
| 3
| 31
|
Small Business
|
Female
| 3
| 5
|
Deluxe
| 4
|
Unmarried
| 2
| 1
| 5
| 1
| 1
|
Manager
| 23,277
|
32
|
Self Enquiry
| 1
| 14
|
Small Business
|
Female
| 3
| 4
|
Standard
| 3
|
Unmarried
| 3
| 1
| 4
| 1
| 2
|
Senior Manager
| 25,821
|
36
|
Self Enquiry
| 1
| 8
|
Small Business
|
Male
| 3
| 3
|
Basic
| 3
|
Single
| 5
| 0
| 5
| 1
| 0
|
Executive
| 17,519
|
29
|
Company Invited
| 3
| 26
|
Large Business
|
Female
| 2
| 3
|
Basic
| 3
|
Divorced
| 2
| 0
| 3
| 0
| 1
|
Executive
| 17,157
|
36
|
Self Enquiry
| 3
| 6
|
Salaried
|
Male
| 2
| 3
|
Deluxe
| 3
|
Married
| 2
| 1
| 3
| 1
| 1
|
Manager
| 21,201
|
59
|
Self Enquiry
| 3
| 6
|
Large Business
|
Male
| 3
| 3
|
Standard
| 3
|
Divorced
| 4
| 1
| 2
| 0
| 1
|
Senior Manager
| 26,904
|
39
|
Self Enquiry
| 2
| 9
|
Salaried
|
Female
| 2
| 2
|
Deluxe
| 4
|
Divorced
| 1
| 0
| 2
| 1
| 0
|
Manager
| 21,389
|
41
|
Self Enquiry
| 1
| 21
|
Small Business
|
Male
| 3
| 5
|
King
| 3
|
Single
| 3
| 0
| 3
| 1
| 2
|
VP
| 38,304
|
55
|
Self Enquiry
| 1
| 6
|
Small Business
|
Male
| 2
| 3
|
King
| 5
|
Single
| 1
| 1
| 2
| 1
| 0
|
VP
| 34,045
|
39
|
Self Enquiry
| 3
| 14
|
Small Business
|
Female
| 3
| 3
|
Deluxe
| 5
|
Married
| 3
| 1
| 3
| 0
| 1
|
Manager
| 24,283
|
43
|
Company Invited
| 1
| 33
|
Salaried
|
Female
| 2
| 3
|
Standard
| 5
|
Married
| 1
| 0
| 4
| 1
| 0
|
Senior Manager
| 25,820
|
29
|
Self Enquiry
| 1
| 13
|
Large Business
|
Female
| 2
| 3
|
Basic
| 3
|
Married
| 4
| 1
| 4
| 1
| 1
|
Executive
| 18,339
|
30
|
Company Invited
| 1
| 7
|
Large Business
|
Male
| 3
| 4
|
Deluxe
| 3
|
Married
| 3
| 0
| 3
| 0
| 1
|
Manager
| 22,997
|
29
|
Self Enquiry
| 1
| 29
|
Salaried
|
Male
| 2
| 3
|
Basic
| 3
|
Single
| 1
| 0
| 3
| 0
| 0
|
Executive
| 17,201
|
56
|
Company Invited
| 1
| 25
|
Small Business
|
Male
| 4
| 4
|
Deluxe
| 4
|
Married
| 5
| 1
| 5
| 1
| 2
|
Manager
| 25,063
|
56
|
Company Invited
| 1
| 15
|
Small Business
|
Male
| 3
| 5
|
Super Deluxe
| 4
|
Married
| 3
| 1
| 3
| 1
| 2
|
AVP
| 32,255
|
28
|
Company Invited
| 1
| 10
|
Small Business
|
Male
| 4
| 5
|
Basic
| 3
|
Married
| 3
| 1
| 2
| 0
| 3
|
Executive
| 21,244
|
38
|
Company Invited
| 3
| 11
|
Small Business
|
Male
| 3
| 4
|
Basic
| 3
|
Married
| 6
| 0
| 4
| 1
| 1
|
Executive
| 21,471
|
39
|
Self Enquiry
| 3
| 17
|
Small Business
|
Male
| 4
| 5
|
Standard
| 3
|
Married
| 2
| 1
| 3
| 1
| 2
|
Senior Manager
| 27,418
|
29
|
Self Enquiry
| 1
| 6
|
Salaried
|
Female
| 2
| 4
|
Basic
| 5
|
Married
| 2
| 1
| 1
| 0
| 0
|
Executive
| 17,319
|
56
|
Self Enquiry
| 1
| 27
|
Large Business
|
Male
| 3
| 4
|
Deluxe
| 3
|
Married
| 5
| 1
| 1
| 0
| 1
|
Manager
| 24,093
|
59
|
Self Enquiry
| 1
| 9
|
Large Business
|
Male
| 3
| 4
|
Basic
| 3
|
Single
| 6
| 0
| 2
| 1
| 2
|
Executive
| 21,157
|
49
|
Company Invited
| 1
| 8
|
Salaried
|
Male
| 2
| 3
|
King
| 3
|
Married
| 4
| 0
| 3
| 1
| 0
|
VP
| 34,161
|
35
|
Self Enquiry
| 1
| 7
|
Salaried
|
Female
| 4
| 2
|
Basic
| 3
|
Unmarried
| 4
| 0
| 2
| 0
| 1
|
Executive
| 21,958
|
37
|
Company Invited
| 1
| 25
|
Salaried
|
Male
| 3
| 2
|
Basic
| 3
|
Married
| 6
| 0
| 5
| 1
| 2
|
Executive
| 22,366
|
26
|
Company Invited
| 1
| 6
|
Salaried
|
Female
| 2
| 3
|
Deluxe
| 4
|
Married
| 2
| 0
| 5
| 1
| 1
|
Manager
| 21,397
|
56
|
Self Enquiry
| 1
| 30
|
Salaried
|
Male
| 3
| 3
|
Basic
| 3
|
Single
| 2
| 0
| 3
| 0
| 0
|
Executive
| 17,587
|
32
|
Self Enquiry
| 1
| 9
|
Salaried
|
Female
| 2
| 3
|
Standard
| 3
|
Unmarried
| 4
| 0
| 1
| 1
| 0
|
Senior Manager
| 26,159
|
34
|
Self Enquiry
| 1
| 6
|
Salaried
|
Female
| 2
| 4
|
Basic
| 4
|
Divorced
| 6
| 0
| 1
| 1
| 1
|
Executive
| 18,294
|
31
|
Self Enquiry
| 1
| 24
|
Small Business
|
Female
| 4
| 4
|
Standard
| 5
|
Divorced
| 3
| 1
| 4
| 0
| 3
|
Senior Manager
| 30,594
|
37
|
Company Invited
| 1
| 16
|
Small Business
|
Male
| 3
| 3
|
Standard
| 3
|
Married
| 7
| 0
| 3
| 0
| 2
|
Senior Manager
| 25,048
|
48
|
Self Enquiry
| 3
| 21
|
Small Business
|
Female
| 4
| 4
|
Deluxe
| 3
|
Divorced
| 5
| 1
| 5
| 1
| 1
|
Manager
| 23,269
|
38
|
Company Invited
| 1
| 16
|
Small Business
|
Male
| 3
| 3
|
Basic
| 3
|
Divorced
| 1
| 0
| 5
| 0
| 2
|
Executive
| 17,684
|
33
|
Company Invited
| 3
| 18
|
Salaried
|
Male
| 3
| 3
|
Deluxe
| 3
|
Divorced
| 2
| 0
| 3
| 1
| 2
|
Manager
| 23,385
|
36
|
Self Enquiry
| 3
| 19
|
Small Business
|
Male
| 3
| 4
|
Deluxe
| 5
|
Married
| 6
| 1
| 1
| 1
| 0
|
Manager
| 21,134
|
45
|
Self Enquiry
| 1
| 15
|
Salaried
|
Male
| 4
| 2
|
Basic
| 3
|
Married
| 4
| 1
| 3
| 1
| 1
|
Executive
| 21,496
|
37
|
Self Enquiry
| 3
| 7
|
Salaried
|
Male
| 3
| 4
|
Deluxe
| 3
|
Divorced
| 3
| 1
| 3
| 1
| 2
|
Manager
| 24,879
|
41
|
Self Enquiry
| 3
| 6
|
Salaried
|
Female
| 3
| 3
|
Deluxe
| 3
|
Single
| 1
| 1
| 2
| 1
| 0
|
Manager
| 20,993
|
36
|
Company Invited
| 1
| 29
|
Small Business
|
Male
| 2
| 1
|
Deluxe
| 3
|
Married
| 5
| 0
| 3
| 0
| 0
|
Manager
| 17,571
|
30
|
Company Invited
| 3
| 9
|
Salaried
|
Male
| 3
| 4
|
Deluxe
| 3
|
Unmarried
| 3
| 0
| 1
| 0
| 2
|
Manager
| 23,232
|
42
|
Self Enquiry
| 1
| 14
|
Large Business
|
Female
| 3
| 2
|
Basic
| 3
|
Married
| 3
| 0
| 3
| 0
| 1
|
Executive
| 22,054
|
33
|
Self Enquiry
| 1
| 12
|
Salaried
|
Female
| 3
| 2
|
Basic
| 3
|
Married
| 5
| 0
| 5
| 1
| 2
|
Executive
| 21,990
|
48
|
Self Enquiry
| 3
| 9
|
Small Business
|
Female
| 3
| 4
|
Deluxe
| 3
|
Divorced
| 2
| 1
| 2
| 1
| 1
|
Manager
| 23,215
|
29
|
Self Enquiry
| 1
| 34
|
Salaried
|
Female
| 3
| 3
|
Basic
| 3
|
Married
| 5
| 0
| 5
| 1
| 0
|
Executive
| 17,514
|
31
|
Self Enquiry
| 3
| 13
|
Large Business
|
Male
| 3
| 2
|
Deluxe
| 3
|
Divorced
| 5
| 0
| 2
| 1
| 0
|
Manager
| 21,929
|
34
|
Self Enquiry
| 1
| 22
|
Small Business
|
Male
| 3
| 4
|
Standard
| 3
|
Divorced
| 2
| 1
| 5
| 0
| 1
|
Senior Manager
| 32,288
|
58
|
Company Invited
| 1
| 21
|
Salaried
|
Male
| 2
| 3
|
Super Deluxe
| 3
|
Married
| 3
| 1
| 1
| 1
| 0
|
AVP
| 30,787
|
30
|
Self Enquiry
| 1
| 30
|
Salaried
|
Male
| 3
| 2
|
Basic
| 3
|
Divorced
| 3
| 0
| 2
| 1
| 2
|
Executive
| 21,378
|
34
|
Self Enquiry
| 1
| 35
|
Salaried
|
Male
| 4
| 4
|
Deluxe
| 3
|
Married
| 3
| 1
| 1
| 1
| 1
|
Manager
| 23,885
|
28
|
Self Enquiry
| 3
| 19
|
Small Business
|
Female
| 2
| 3
|
Deluxe
| 3
|
Unmarried
| 4
| 1
| 5
| 1
| 1
|
Manager
| 24,854
|
20
|
Self Enquiry
| 3
| 29
|
Small Business
|
Male
| 3
| 4
|
Basic
| 3
|
Single
| 3
| 1
| 1
| 1
| 1
|
Executive
| 20,353
|
34
|
Company Invited
| 3
| 15
|
Salaried
|
Female
| 3
| 5
|
Basic
| 3
|
Single
| 2
| 0
| 2
| 1
| 2
|
Executive
| 21,020
|
37
|
Company Invited
| 1
| 25
|
Salaried
|
Male
| 4
| 4
|
Deluxe
| 3
|
Unmarried
| 4
| 0
| 3
| 1
| 1
|
Manager
| 26,457
|
36
|
Company Invited
| 1
| 24
|
Salaried
|
Male
| 3
| 3
|
Deluxe
| 3
|
Unmarried
| 3
| 0
| 3
| 1
| 0
|
Manager
| 22,779
|
20
|
Self Enquiry
| 3
| 29
|
Small Business
|
Male
| 3
| 4
|
Basic
| 3
|
Single
| 3
| 1
| 2
| 0
| 2
|
Executive
| 20,353
|
35
|
Self Enquiry
| 1
| 7
|
Salaried
|
Female
| 4
| 2
|
Basic
| 3
|
Unmarried
| 4
| 0
| 1
| 1
| 2
|
Executive
| 21,958
|
52
|
Self Enquiry
| 1
| 10
|
Small Business
|
Female
| 4
| 4
|
Super Deluxe
| 4
|
Single
| 5
| 0
| 5
| 1
| 2
|
AVP
| 32,412
|
31
|
Self Enquiry
| 1
| 10
|
Large Business
|
Female
| 3
| 4
|
Basic
| 5
|
Unmarried
| 7
| 1
| 4
| 1
| 2
|
Executive
| 21,335
|
45
|
Company Invited
| 3
| 12
|
Small Business
|
Female
| 2
| 4
|
Standard
| 3
|
Unmarried
| 7
| 0
| 4
| 1
| 0
|
Senior Manager
| 23,865
|
29
|
Self Enquiry
| 3
| 16
|
Small Business
|
Female
| 2
| 4
|
Deluxe
| 4
|
Married
| 2
| 1
| 5
| 0
| 1
|
Manager
| 23,268
|
34
|
Self Enquiry
| 1
| 22
|
Small Business
|
Female
| 4
| 4
|
Deluxe
| 3
|
Married
| 2
| 1
| 1
| 1
| 2
|
Manager
| 23,556
|
39
|
Self Enquiry
| 1
| 9
|
Small Business
|
Male
| 4
| 4
|
Basic
| 3
|
Divorced
| 8
| 1
| 4
| 0
| 1
|
Executive
| 21,735
|
47
|
Company Invited
| 3
| 10
|
Small Business
|
Male
| 3
| 3
|
Deluxe
| 3
|
Single
| 4
| 0
| 4
| 0
| 2
|
Manager
| 17,976
|
45
|
Self Enquiry
| 1
| 36
|
Salaried
|
Male
| 3
| 4
|
Deluxe
| 3
|
Unmarried
| 3
| 0
| 5
| 1
| 2
|
Manager
| 23,219
|
38
|
Self Enquiry
| 1
| 21
|
Salaried
|
Female
| 4
| 4
|
Basic
| 5
|
Married
| 3
| 0
| 4
| 1
| 2
|
Executive
| 21,712
|
34
|
Company Invited
| 1
| 9
|
Salaried
|
Male
| 2
| 3
|
Deluxe
| 3
|
Unmarried
| 1
| 0
| 1
| 1
| 0
|
Manager
| 22,756
|
24
|
Self Enquiry
| 1
| 23
|
Salaried
|
Female
| 3
| 3
|
Basic
| 4
|
Divorced
| 2
| 0
| 2
| 0
| 1
|
Executive
| 17,210
|
37
|
Self Enquiry
| 1
| 9
|
Small Business
|
Male
| 4
| 4
|
Basic
| 3
|
Single
| 6
| 0
| 5
| 1
| 1
|
Executive
| 21,197
|
23
|
Self Enquiry
| 1
| 10
|
Small Business
|
Male
| 2
| 2
|
Basic
| 5
|
Divorced
| 3
| 0
| 4
| 0
| 1
|
Executive
| 17,819
|
33
|
Self Enquiry
| 1
| 10
|
Small Business
|
Female
| 2
| 4
|
Basic
| 4
|
Married
| 7
| 0
| 4
| 0
| 1
|
Executive
| 17,622
|
36
|
Self Enquiry
| 1
| 12
|
Salaried
|
Male
| 2
| 3
|
Basic
| 3
|
Divorced
| 1
| 0
| 5
| 1
| 1
|
Executive
| 18,210
|
29
|
Self Enquiry
| 1
| 31
|
Small Business
|
Male
| 3
| 4
|
Basic
| 4
|
Married
| 3
| 1
| 1
| 0
| 1
|
Executive
| 21,086
|
51
|
Company Invited
| 3
| 19
|
Small Business
|
Female
| 4
| 4
|
Standard
| 3
|
Unmarried
| 6
| 0
| 5
| 0
| 1
|
Senior Manager
| 27,886
|
37
|
Self Enquiry
| 2
| 15
|
Salaried
|
Male
| 4
| 5
|
Basic
| 5
|
Married
| 2
| 0
| 1
| 0
| 2
|
Executive
| 21,020
|
39
|
Self Enquiry
| 3
| 7
|
Salaried
|
Male
| 3
| 5
|
Basic
| 5
|
Unmarried
| 6
| 0
| 3
| 0
| 2
|
Executive
| 21,536
|
34
|
Self Enquiry
| 1
| 32
|
Small Business
|
Male
| 3
| 5
|
Basic
| 4
|
Single
| 6
| 1
| 4
| 1
| 1
|
Executive
| 20,991
|
20
|
Company Invited
| 3
| 15
|
Small Business
|
Female
| 2
| 3
|
Basic
| 3
|
Single
| 2
| 1
| 4
| 1
| 0
|
Executive
| 17,323
|
34
|
Company Invited
| 3
| 14
|
Salaried
|
Female
| 2
| 4
|
Deluxe
| 4
|
Married
| 2
| 0
| 4
| 0
| 1
|
Manager
| 22,980
|
20
|
Self Enquiry
| 1
| 32
|
Salaried
|
Female
| 3
| 2
|
Basic
| 3
|
Unmarried
| 3
| 1
| 5
| 1
| 1
|
Executive
| 21,672
|
46
|
Self Enquiry
| 3
| 10
|
Small Business
|
Female
| 2
| 4
|
King
| 4
|
Divorced
| 3
| 0
| 5
| 1
| 0
|
VP
| 33,789
|
19
|
Company Invited
| 1
| 7
|
Salaried
|
Female
| 4
| 4
|
Basic
| 3
|
Single
| 3
| 0
| 5
| 1
| 2
|
Executive
| 20,289
|
26
|
Self Enquiry
| 3
| 33
|
Small Business
|
Female
| 3
| 4
|
Deluxe
| 3
|
Unmarried
| 3
| 0
| 4
| 0
| 1
|
Manager
| 24,858
|
47
|
Company Invited
| 1
| 6
|
Small Business
|
Female
| 3
| 3
|
Standard
| 4
|
Married
| 1
| 0
| 5
| 0
| 0
|
Senior Manager
| 26,957
|
32
|
Self Enquiry
| 1
| 9
|
Small Business
|
Female
| 3
| 3
|
Deluxe
| 5
|
Married
| 2
| 0
| 1
| 1
| 0
|
Manager
| 21,725
|
End of preview.