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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 ({'ProductPitched', 'CustomerID', 'Unnamed: 0'}) and 1 missing columns ({'Age_Group'}).
This happened while the csv dataset builder was generating data using
hf://datasets/Mansoor747/MyToursim/tourism.csv (at revision b9ffcdeeb9c2b737d80deac800d24cd551553fb0), [/tmp/hf-datasets-cache/medium/datasets/52221377271344-config-parquet-and-info-Mansoor747-MyToursim-9bd49298/hub/datasets--Mansoor747--MyToursim/snapshots/b9ffcdeeb9c2b737d80deac800d24cd551553fb0/Xtest.csv (origin=hf://datasets/Mansoor747/MyToursim@b9ffcdeeb9c2b737d80deac800d24cd551553fb0/Xtest.csv), /tmp/hf-datasets-cache/medium/datasets/52221377271344-config-parquet-and-info-Mansoor747-MyToursim-9bd49298/hub/datasets--Mansoor747--MyToursim/snapshots/b9ffcdeeb9c2b737d80deac800d24cd551553fb0/Xtrain.csv (origin=hf://datasets/Mansoor747/MyToursim@b9ffcdeeb9c2b737d80deac800d24cd551553fb0/Xtrain.csv), /tmp/hf-datasets-cache/medium/datasets/52221377271344-config-parquet-and-info-Mansoor747-MyToursim-9bd49298/hub/datasets--Mansoor747--MyToursim/snapshots/b9ffcdeeb9c2b737d80deac800d24cd551553fb0/tourism.csv (origin=hf://datasets/Mansoor747/MyToursim@b9ffcdeeb9c2b737d80deac800d24cd551553fb0/tourism.csv), /tmp/hf-datasets-cache/medium/datasets/52221377271344-config-parquet-and-info-Mansoor747-MyToursim-9bd49298/hub/datasets--Mansoor747--MyToursim/snapshots/b9ffcdeeb9c2b737d80deac800d24cd551553fb0/ytest.csv (origin=hf://datasets/Mansoor747/MyToursim@b9ffcdeeb9c2b737d80deac800d24cd551553fb0/ytest.csv), /tmp/hf-datasets-cache/medium/datasets/52221377271344-config-parquet-and-info-Mansoor747-MyToursim-9bd49298/hub/datasets--Mansoor747--MyToursim/snapshots/b9ffcdeeb9c2b737d80deac800d24cd551553fb0/ytrain.csv (origin=hf://datasets/Mansoor747/MyToursim@b9ffcdeeb9c2b737d80deac800d24cd551553fb0/ytrain.csv)]
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 1887, in _prepare_split_single
writer.write_table(table)
File "/usr/local/lib/python3.12/site-packages/datasets/arrow_writer.py", line 674, 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
{'ProdTaken': Value('float64'), 'Age': Value('float64'), 'TypeofContact': Value('string'), 'CityTier': Value('float64'), 'DurationOfPitch': Value('float64'), 'Occupation': Value('string'), 'Gender': Value('string'), 'NumberOfPersonVisiting': Value('float64'), 'NumberOfFollowups': Value('float64'), 'PreferredPropertyStar': Value('float64'), 'MaritalStatus': Value('string'), 'NumberOfTrips': Value('float64'), 'Passport': Value('float64'), 'PitchSatisfactionScore': Value('float64'), 'OwnCar': Value('float64'), 'NumberOfChildrenVisiting': Value('float64'), 'Designation': Value('string'), 'MonthlyIncome': Value('float64'), 'Age_Group': Value('string')}
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 1347, 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 980, in convert_to_parquet
builder.download_and_prepare(
File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 884, in download_and_prepare
self._download_and_prepare(
File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 947, in _download_and_prepare
self._prepare_split(split_generator, **prepare_split_kwargs)
File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1736, 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 1889, 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 ({'ProductPitched', 'CustomerID', 'Unnamed: 0'}) and 1 missing columns ({'Age_Group'}).
This happened while the csv dataset builder was generating data using
hf://datasets/Mansoor747/MyToursim/tourism.csv (at revision b9ffcdeeb9c2b737d80deac800d24cd551553fb0), [/tmp/hf-datasets-cache/medium/datasets/52221377271344-config-parquet-and-info-Mansoor747-MyToursim-9bd49298/hub/datasets--Mansoor747--MyToursim/snapshots/b9ffcdeeb9c2b737d80deac800d24cd551553fb0/Xtest.csv (origin=hf://datasets/Mansoor747/MyToursim@b9ffcdeeb9c2b737d80deac800d24cd551553fb0/Xtest.csv), /tmp/hf-datasets-cache/medium/datasets/52221377271344-config-parquet-and-info-Mansoor747-MyToursim-9bd49298/hub/datasets--Mansoor747--MyToursim/snapshots/b9ffcdeeb9c2b737d80deac800d24cd551553fb0/Xtrain.csv (origin=hf://datasets/Mansoor747/MyToursim@b9ffcdeeb9c2b737d80deac800d24cd551553fb0/Xtrain.csv), /tmp/hf-datasets-cache/medium/datasets/52221377271344-config-parquet-and-info-Mansoor747-MyToursim-9bd49298/hub/datasets--Mansoor747--MyToursim/snapshots/b9ffcdeeb9c2b737d80deac800d24cd551553fb0/tourism.csv (origin=hf://datasets/Mansoor747/MyToursim@b9ffcdeeb9c2b737d80deac800d24cd551553fb0/tourism.csv), /tmp/hf-datasets-cache/medium/datasets/52221377271344-config-parquet-and-info-Mansoor747-MyToursim-9bd49298/hub/datasets--Mansoor747--MyToursim/snapshots/b9ffcdeeb9c2b737d80deac800d24cd551553fb0/ytest.csv (origin=hf://datasets/Mansoor747/MyToursim@b9ffcdeeb9c2b737d80deac800d24cd551553fb0/ytest.csv), /tmp/hf-datasets-cache/medium/datasets/52221377271344-config-parquet-and-info-Mansoor747-MyToursim-9bd49298/hub/datasets--Mansoor747--MyToursim/snapshots/b9ffcdeeb9c2b737d80deac800d24cd551553fb0/ytrain.csv (origin=hf://datasets/Mansoor747/MyToursim@b9ffcdeeb9c2b737d80deac800d24cd551553fb0/ytrain.csv)]
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
float64 | Age
float64 | TypeofContact
string | CityTier
float64 | DurationOfPitch
float64 | Occupation
string | Gender
string | NumberOfPersonVisiting
float64 | NumberOfFollowups
float64 | PreferredPropertyStar
float64 | MaritalStatus
string | NumberOfTrips
float64 | Passport
float64 | PitchSatisfactionScore
float64 | OwnCar
float64 | NumberOfChildrenVisiting
float64 | Designation
string | MonthlyIncome
float64 | Age_Group
string |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
0
| 44
|
Self Enquiry
| 1
| 8
|
Salaried
|
Female
| 3
| 1.5
| 3
|
Married
| 2
| 1
| 4
| 1
| 0
|
Senior Manager
| 22,879
|
Adult
|
0
| 35
|
Self Enquiry
| 3
| 20
|
Small Business
|
Male
| 3
| 4
| 3
|
Married
| 3
| 0
| 1
| 1
| 2
|
Senior Manager
| 27,306
|
Young Adult
|
0
| 47
|
Self Enquiry
| 3
| 7
|
Small Business
|
Female
| 4
| 4
| 5
|
Married
| 3
| 0
| 2
| 1
| 2
|
Senior Manager
| 29,131
|
Middle Aged
|
0
| 32
|
Self Enquiry
| 1
| 6
|
Salaried
|
Male
| 3
| 3
| 4
|
Married
| 2
| 0
| 3
| 1
| 0
|
Manager
| 21,220
|
Young Adult
|
0
| 59
|
Self Enquiry
| 1
| 9
|
Large Business
|
Male
| 3
| 4
| 3
|
Single
| 6
| 0
| 2
| 1
| 2
|
Executive
| 21,157
|
Middle Aged
|
0
| 44
|
Self Enquiry
| 3
| 11
|
Small Business
|
Male
| 2
| 3
| 4
|
Divorced
| 1
| 0
| 5
| 1
| 1
|
VP
| 32,126
|
Adult
|
0
| 32
|
Self Enquiry
| 1
| 35
|
Salaried
|
Female
| 2
| 4
| 4
|
Single
| 2
| 0
| 3
| 1
| 0
|
Executive
| 17,837
|
Young Adult
|
0
| 27
|
Self Enquiry
| 3
| 7
|
Salaried
|
Male
| 3
| 4
| 3
|
Married
| 3
| 0
| 5
| 0
| 2
|
Manager
| 23,974
|
Young Adult
|
0
| 38
|
Company Invited
| 3
| 8
|
Salaried
|
Male
| 2
| 4
| 3
|
Divorced
| 4
| 0
| 5
| 1
| 1
|
Manager
| 20,249
|
Adult
|
0
| 32
|
Self Enquiry
| 1
| 12
|
Large Business
|
Male
| 3
| 4
| 3
|
Married
| 2
| 1
| 4
| 1
| 1
|
Executive
| 23,499
|
Young Adult
|
0
| 40
|
Self Enquiry
| 1
| 30
|
Large Business
|
Male
| 3
| 3
| 3
|
Married
| 2
| 0
| 3
| 1
| 1
|
Manager
| 18,319
|
Adult
|
0
| 38
|
Self Enquiry
| 1
| 20
|
Small Business
|
Male
| 3
| 4
| 3
|
Married
| 3
| 0
| 1
| 0
| 1
|
Manager
| 22,963
|
Adult
|
0
| 35
|
Company Invited
| 3
| 6
|
Small Business
|
Fe Male
| 3
| 3
| 3
|
Unmarried
| 2
| 0
| 5
| 1
| 0
|
Senior Manager
| 23,789
|
Young Adult
|
0
| 35
|
Self Enquiry
| 1
| 8
|
Salaried
|
Female
| 3
| 3
| 5
|
Married
| 2
| 1
| 1
| 1
| 1
|
Executive
| 17,074
|
Young Adult
|
0
| 34
|
Self Enquiry
| 1
| 17
|
Small Business
|
Male
| 3
| 5.5
| 3
|
Married
| 2
| 0
| 5
| 0
| 1
|
Executive
| 22,086
|
Young Adult
|
0
| 33
|
Self Enquiry
| 1
| 36
|
Salaried
|
Female
| 3
| 5
| 4
|
Unmarried
| 3
| 0
| 3
| 1
| 1
|
Executive
| 21,515
|
Young Adult
|
0
| 51
|
Self Enquiry
| 1
| 15
|
Salaried
|
Male
| 3
| 3
| 3
|
Divorced
| 4
| 0
| 3
| 1
| 0
|
Executive
| 17,075
|
Middle Aged
|
0
| 29
|
Company Invited
| 3
| 30
|
Large Business
|
Male
| 2
| 1.5
| 5
|
Single
| 2
| 0
| 3
| 1
| 1
|
Executive
| 16,091
|
Young Adult
|
0
| 34
|
Company Invited
| 3
| 25
|
Small Business
|
Male
| 3
| 2
| 3
|
Single
| 1
| 1
| 2
| 1
| 2
|
Manager
| 20,304
|
Young Adult
|
0
| 38
|
Self Enquiry
| 1
| 14
|
Small Business
|
Male
| 2
| 4
| 3
|
Single
| 6
| 0
| 2
| 0
| 1
|
Senior Manager
| 32,126
|
Adult
|
0
| 46
|
Self Enquiry
| 1
| 6
|
Small Business
|
Male
| 3
| 3
| 5
|
Married
| 1
| 0
| 2
| 0
| 0
|
Senior Manager
| 24,396
|
Middle Aged
|
0
| 54
|
Self Enquiry
| 2
| 25
|
Small Business
|
Male
| 2
| 3
| 4
|
Divorced
| 3
| 0
| 3
| 1
| 0
|
Senior Manager
| 25,725
|
Middle Aged
|
0
| 56
|
Self Enquiry
| 1
| 15
|
Small Business
|
Male
| 2
| 3
| 3
|
Married
| 1
| 0
| 4
| 0
| 0
|
AVP
| 26,103
|
Middle Aged
|
0
| 30
|
Company Invited
| 1
| 10
|
Large Business
|
Male
| 2
| 3
| 3
|
Single
| 7
| 1
| 4
| 1
| 1
|
Executive
| 17,285
|
Young Adult
|
0
| 26
|
Self Enquiry
| 1
| 6
|
Small Business
|
Male
| 3
| 3
| 5
|
Single
| 1
| 0
| 5
| 1
| 2
|
Executive
| 17,867
|
Young Adult
|
0
| 33
|
Self Enquiry
| 1
| 13
|
Small Business
|
Male
| 2
| 3
| 3
|
Married
| 1
| 0
| 4
| 1
| 0
|
Senior Manager
| 26,691
|
Young Adult
|
0
| 24
|
Self Enquiry
| 1
| 23
|
Salaried
|
Male
| 3
| 4
| 4
|
Married
| 2
| 0
| 3
| 1
| 1
|
Executive
| 17,127
|
Youth
|
0
| 30
|
Self Enquiry
| 1
| 36
|
Salaried
|
Male
| 4
| 5.5
| 3
|
Married
| 2
| 0
| 5
| 1
| 3
|
Manager
| 25,062
|
Young Adult
|
0
| 33
|
Company Invited
| 3
| 8
|
Small Business
|
Female
| 3
| 3
| 4
|
Single
| 1
| 0
| 1
| 0
| 0
|
Manager
| 20,147
|
Young Adult
|
0
| 53
|
Company Invited
| 3
| 8
|
Small Business
|
Female
| 2
| 4
| 4
|
Married
| 3
| 0
| 1
| 1
| 0
|
Senior Manager
| 22,525
|
Middle Aged
|
0
| 29
|
Company Invited
| 3
| 14
|
Salaried
|
Male
| 3
| 4
| 5
|
Unmarried
| 2
| 0
| 3
| 1
| 2
|
Manager
| 23,576
|
Young Adult
|
0
| 39
|
Self Enquiry
| 1
| 15
|
Small Business
|
Male
| 2
| 3
| 5
|
Married
| 2
| 0
| 4
| 1
| 0
|
Manager
| 20,151
|
Adult
|
0
| 46
|
Self Enquiry
| 3
| 9
|
Salaried
|
Male
| 4
| 4
| 4
|
Married
| 2
| 0
| 5
| 1
| 3
|
Manager
| 23,483
|
Middle Aged
|
0
| 35
|
Self Enquiry
| 1
| 14
|
Salaried
|
Female
| 3
| 4
| 4
|
Single
| 2
| 0
| 3
| 1
| 1
|
Senior Manager
| 30,672
|
Young Adult
|
0
| 35
|
Company Invited
| 3
| 9
|
Small Business
|
Female
| 4
| 4
| 3
|
Married
| 7
| 0
| 5
| 0
| 1
|
Executive
| 20,909
|
Young Adult
|
0
| 33
|
Company Invited
| 1
| 7
|
Salaried
|
Female
| 4
| 5
| 4
|
Married
| 7
| 0
| 3
| 0
| 3
|
Executive
| 21,010
|
Young Adult
|
0
| 29
|
Company Invited
| 1
| 16
|
Salaried
|
Female
| 2
| 4
| 3
|
Unmarried
| 2
| 0
| 4
| 1
| 0
|
Executive
| 21,623
|
Young Adult
|
0
| 41
|
Company Invited
| 3
| 16
|
Salaried
|
Male
| 2
| 3
| 3
|
Single
| 1
| 0
| 1
| 0
| 1
|
Manager
| 21,230
|
Adult
|
0
| 43
|
Self Enquiry
| 1
| 36
|
Small Business
|
Male
| 3
| 5.5
| 3
|
Unmarried
| 6
| 0
| 3
| 1
| 1
|
Manager
| 22,950
|
Adult
|
0
| 35
|
Company Invited
| 3
| 13
|
Small Business
|
Female
| 3
| 5.5
| 3
|
Married
| 2
| 0
| 4
| 0
| 2
|
Executive
| 21,029
|
Young Adult
|
0
| 41
|
Self Enquiry
| 3
| 12
|
Salaried
|
Female
| 3
| 3
| 3
|
Single
| 4
| 1
| 1
| 0
| 0
|
Senior Manager
| 28,591
|
Adult
|
0
| 33
|
Self Enquiry
| 1
| 6
|
Salaried
|
Female
| 2
| 4
| 3
|
Unmarried
| 1
| 0
| 4
| 0
| 0
|
Manager
| 21,949
|
Young Adult
|
0
| 40
|
Company Invited
| 1
| 15
|
Small Business
|
Fe Male
| 2
| 3
| 3
|
Unmarried
| 1
| 0
| 4
| 0
| 0
|
Senior Manager
| 28,499
|
Adult
|
0
| 26
|
Company Invited
| 1
| 9
|
Large Business
|
Male
| 3
| 3
| 5
|
Single
| 1
| 0
| 3
| 0
| 1
|
Executive
| 18,102
|
Young Adult
|
0
| 41
|
Self Enquiry
| 1
| 25
|
Salaried
|
Male
| 2
| 3
| 5
|
Married
| 3
| 0
| 1
| 0
| 0
|
Manager
| 18,072
|
Adult
|
0
| 37
|
Company Invited
| 1
| 17
|
Salaried
|
Male
| 2
| 3
| 3
|
Married
| 2
| 1
| 3
| 0
| 1
|
Senior Manager
| 27,185
|
Adult
|
0
| 31
|
Self Enquiry
| 3
| 13
|
Salaried
|
Male
| 2
| 4
| 3
|
Married
| 4
| 0
| 4
| 1
| 1
|
Executive
| 17,329
|
Young Adult
|
0
| 45
|
Self Enquiry
| 3
| 8
|
Salaried
|
Male
| 3
| 5.5
| 4
|
Single
| 7
| 0
| 3
| 0
| 2
|
Manager
| 21,040
|
Adult
|
0
| 33
|
Company Invited
| 1
| 9
|
Salaried
|
Male
| 3
| 3
| 5
|
Single
| 2
| 1
| 5
| 1
| 2
|
Executive
| 18,348
|
Young Adult
|
0
| 33
|
Self Enquiry
| 1
| 9
|
Small Business
|
Female
| 4
| 4
| 4
|
Divorced
| 3
| 0
| 4
| 0
| 1
|
Executive
| 21,048
|
Young Adult
|
0
| 33
|
Self Enquiry
| 1
| 14
|
Salaried
|
Male
| 3
| 3
| 3
|
Unmarried
| 3
| 1
| 3
| 0
| 2
|
Manager
| 21,388
|
Young Adult
|
0
| 30
|
Self Enquiry
| 3
| 18
|
Large Business
|
Female
| 2
| 3
| 3
|
Unmarried
| 1
| 0
| 2
| 1
| 0
|
Manager
| 21,577
|
Young Adult
|
0
| 42
|
Company Invited
| 1
| 25
|
Small Business
|
Male
| 2
| 2
| 3
|
Married
| 7
| 1
| 3
| 1
| 1
|
Executive
| 17,759
|
Adult
|
0
| 46
|
Self Enquiry
| 1
| 8
|
Salaried
|
Male
| 2
| 3
| 3
|
Married
| 7
| 0
| 5
| 1
| 0
|
AVP
| 32,126
|
Middle Aged
|
0
| 51
|
Self Enquiry
| 1
| 16
|
Salaried
|
Male
| 4
| 4
| 3
|
Married
| 6
| 0
| 5
| 1
| 3
|
Executive
| 21,058
|
Middle Aged
|
0
| 30
|
Self Enquiry
| 1
| 8
|
Salaried
|
Female
| 2
| 5
| 3
|
Single
| 3
| 0
| 1
| 1
| 0
|
Manager
| 21,091
|
Young Adult
|
0
| 37
|
Company Invited
| 1
| 25
|
Salaried
|
Male
| 3
| 3
| 3
|
Divorced
| 6
| 0
| 5
| 0
| 1
|
Executive
| 22,366
|
Adult
|
0
| 28
|
Company Invited
| 2
| 6
|
Salaried
|
Male
| 2
| 3
| 3
|
Married
| 2
| 0
| 4
| 0
| 1
|
Executive
| 17,706
|
Young Adult
|
0
| 42
|
Self Enquiry
| 1
| 12
|
Small Business
|
Male
| 2
| 3
| 5
|
Married
| 1
| 0
| 3
| 1
| 0
|
Senior Manager
| 28,348
|
Adult
|
0
| 44
|
Self Enquiry
| 1
| 10
|
Small Business
|
Male
| 2
| 3
| 4
|
Single
| 1
| 0
| 2
| 1
| 0
|
Manager
| 20,933
|
Adult
|
0
| 39
|
Company Invited
| 1
| 9
|
Small Business
|
Female
| 3
| 5
| 4
|
Single
| 3
| 0
| 1
| 1
| 1
|
Executive
| 21,118
|
Adult
|
0
| 42
|
Self Enquiry
| 1
| 23
|
Salaried
|
Female
| 2
| 2
| 5
|
Unmarried
| 4
| 1
| 2
| 0
| 0
|
Manager
| 21,545
|
Adult
|
0
| 39
|
Company Invited
| 1
| 28
|
Small Business
|
Fe Male
| 2
| 3
| 5
|
Unmarried
| 2
| 1
| 5
| 1
| 1
|
Senior Manager
| 25,880
|
Adult
|
0
| 28
|
Company Invited
| 1
| 6
|
Salaried
|
Female
| 2
| 5
| 3
|
Divorced
| 1
| 0
| 3
| 1
| 0
|
Manager
| 21,674
|
Young Adult
|
0
| 43
|
Self Enquiry
| 1
| 20
|
Salaried
|
Male
| 3
| 3
| 5
|
Married
| 7
| 0
| 5
| 1
| 1
|
AVP
| 32,126
|
Adult
|
0
| 45
|
Self Enquiry
| 1
| 22
|
Small Business
|
Female
| 4
| 4
| 3
|
Divorced
| 3
| 0
| 3
| 0
| 2
|
Senior Manager
| 26,656
|
Adult
|
0
| 53
|
Self Enquiry
| 1
| 13
|
Large Business
|
Male
| 4
| 4
| 5
|
Married
| 5
| 1
| 4
| 1
| 2
|
Manager
| 24,255
|
Middle Aged
|
0
| 42
|
Self Enquiry
| 1
| 16
|
Salaried
|
Male
| 4
| 4
| 5
|
Married
| 4
| 0
| 1
| 0
| 1
|
Executive
| 20,916
|
Adult
|
0
| 36
|
Self Enquiry
| 1
| 33
|
Small Business
|
Male
| 3
| 3
| 3
|
Divorced
| 7
| 0
| 3
| 1
| 0
|
Manager
| 20,237
|
Adult
|
0
| 22
|
Self Enquiry
| 1
| 7
|
Large Business
|
Female
| 4
| 5
| 4
|
Single
| 3
| 1
| 5
| 0
| 3
|
Executive
| 20,748
|
Youth
|
0
| 37
|
Self Enquiry
| 1
| 12
|
Salaried
|
Male
| 4
| 4
| 4
|
Unmarried
| 2
| 0
| 2
| 0
| 3
|
Manager
| 24,592
|
Adult
|
0
| 30
|
Company Invited
| 3
| 20
|
Large Business
|
Fe Male
| 3
| 4
| 4
|
Unmarried
| 7
| 0
| 3
| 0
| 2
|
Manager
| 24,443
|
Young Adult
|
0
| 36
|
Company Invited
| 1
| 18
|
Small Business
|
Male
| 4
| 5
| 5
|
Married
| 4
| 1
| 5
| 1
| 3
|
Senior Manager
| 28,562
|
Adult
|
0
| 40
|
Self Enquiry
| 1
| 10
|
Small Business
|
Female
| 2
| 3
| 3
|
Divorced
| 2
| 0
| 5
| 0
| 1
|
VP
| 32,126
|
Adult
|
0
| 51
|
Company Invited
| 1
| 14
|
Salaried
|
Male
| 2
| 5
| 3
|
Unmarried
| 3
| 0
| 2
| 0
| 1
|
Senior Manager
| 25,650
|
Middle Aged
|
0
| 39
|
Self Enquiry
| 3
| 7
|
Salaried
|
Male
| 3
| 5
| 5
|
Unmarried
| 6
| 0
| 3
| 0
| 2
|
Executive
| 21,536
|
Adult
|
0
| 43
|
Self Enquiry
| 1
| 18
|
Salaried
|
Male
| 2
| 4
| 4
|
Married
| 2
| 0
| 3
| 0
| 1
|
AVP
| 29,336
|
Adult
|
0
| 35
|
Self Enquiry
| 1
| 10
|
Salaried
|
Male
| 3
| 3
| 3
|
Married
| 2
| 0
| 4
| 0
| 0
|
Executive
| 16,951
|
Young Adult
|
0
| 40
|
Company Invited
| 1
| 9
|
Large Business
|
Female
| 4
| 4
| 3
|
Single
| 2
| 0
| 2
| 1
| 2
|
Senior Manager
| 29,616
|
Adult
|
0
| 27
|
Self Enquiry
| 3
| 17
|
Small Business
|
Male
| 3
| 4
| 3
|
Unmarried
| 3
| 0
| 1
| 0
| 1
|
Manager
| 23,362
|
Young Adult
|
0
| 26
|
Company Invited
| 1
| 8
|
Salaried
|
Male
| 2
| 3
| 5
|
Divorced
| 7
| 1
| 5
| 1
| 0
|
Executive
| 17,042
|
Young Adult
|
0
| 43
|
Company Invited
| 3
| 32
|
Salaried
|
Male
| 3
| 3
| 3
|
Divorced
| 2
| 1
| 2
| 0
| 0
|
AVP
| 31,959
|
Adult
|
0
| 32
|
Self Enquiry
| 1
| 18
|
Small Business
|
Male
| 4
| 4
| 5
|
Divorced
| 3
| 1
| 2
| 0
| 3
|
Manager
| 25,511
|
Young Adult
|
0
| 35
|
Self Enquiry
| 1
| 12
|
Small Business
|
Female
| 3
| 5
| 5
|
Single
| 4
| 0
| 2
| 0
| 1
|
Senior Manager
| 30,309
|
Young Adult
|
0
| 34
|
Self Enquiry
| 1
| 11
|
Small Business
|
Female
| 3
| 5
| 4
|
Married
| 7
| 0
| 4
| 0
| 2
|
Executive
| 21,300
|
Young Adult
|
0
| 31
|
Self Enquiry
| 1
| 14
|
Salaried
|
Female
| 2
| 4
| 4
|
Single
| 2
| 0
| 4
| 0
| 1
|
Executive
| 16,261
|
Young Adult
|
0
| 35
|
Self Enquiry
| 3
| 16
|
Salaried
|
Female
| 4
| 4
| 3
|
Married
| 3
| 0
| 1
| 0
| 1
|
Manager
| 24,392
|
Young Adult
|
0
| 42
|
Company Invited
| 3
| 16
|
Salaried
|
Male
| 3
| 5.5
| 3
|
Married
| 2
| 0
| 5
| 1
| 2
|
AVP
| 24,829
|
Adult
|
0
| 34
|
Self Enquiry
| 1
| 14
|
Salaried
|
Female
| 2
| 3
| 5
|
Married
| 4
| 0
| 5
| 1
| 1
|
Manager
| 20,121
|
Young Adult
|
0
| 34
|
Self Enquiry
| 1
| 9
|
Salaried
|
Female
| 3
| 4
| 5
|
Divorced
| 2
| 0
| 3
| 1
| 1
|
Executive
| 21,385
|
Young Adult
|
0
| 34
|
Self Enquiry
| 1
| 13
|
Salaried
|
Fe Male
| 2
| 3
| 4
|
Unmarried
| 1
| 0
| 3
| 1
| 0
|
Senior Manager
| 26,994
|
Young Adult
|
0
| 39
|
Self Enquiry
| 1
| 36
|
Large Business
|
Male
| 3
| 4
| 3
|
Divorced
| 5
| 0
| 2
| 0
| 2
|
Manager
| 24,939
|
Adult
|
0
| 29
|
Self Enquiry
| 1
| 12
|
Large Business
|
Male
| 3
| 4
| 3
|
Unmarried
| 3
| 1
| 1
| 0
| 1
|
Executive
| 22,119
|
Young Adult
|
0
| 35
|
Company Invited
| 1
| 8
|
Small Business
|
Male
| 2
| 3
| 3
|
Married
| 3
| 0
| 3
| 0
| 1
|
Manager
| 20,762
|
Young Adult
|
0
| 26
|
Self Enquiry
| 3
| 10
|
Small Business
|
Male
| 2
| 4
| 3
|
Single
| 2
| 1
| 2
| 1
| 1
|
Manager
| 20,828
|
Young Adult
|
0
| 37
|
Self Enquiry
| 1
| 10
|
Salaried
|
Female
| 3
| 4
| 3
|
Married
| 7
| 0
| 2
| 1
| 1
|
Executive
| 21,513
|
Adult
|
0
| 35
|
Company Invited
| 1
| 16
|
Salaried
|
Male
| 4
| 4
| 5
|
Married
| 6
| 0
| 3
| 0
| 2
|
Manager
| 24,024
|
Young Adult
|
0
| 40
|
Company Invited
| 1
| 9
|
Salaried
|
Male
| 3
| 4
| 3
|
Married
| 2
| 0
| 3
| 1
| 1
|
AVP
| 30,847
|
Adult
|
0
| 33
|
Self Enquiry
| 3
| 11
|
Small Business
|
Female
| 2
| 3
| 3
|
Single
| 2
| 1
| 2
| 1
| 0
|
Executive
| 17,851
|
Young Adult
|
0
| 38
|
Self Enquiry
| 3
| 15
|
Small Business
|
Male
| 3
| 4
| 4
|
Divorced
| 1
| 0
| 4
| 0
| 0
|
Executive
| 17,899
|
Adult
|
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