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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 |
End of preview.
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