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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 2 new columns ({'ProdTaken', 'CustomerID'})
This happened while the csv dataset builder was generating data using
hf://datasets/kalrap/M10_AIML_MLOps_Tourism_Project/tourism.csv (at revision 40e2c3f41c4ae11c43e34e9164870dc258086f3f)
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
{'Unnamed: 0': Value('int64'), 'Age': Value('float64'), 'TypeofContact': Value('int64'), '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 2 new columns ({'ProdTaken', 'CustomerID'})
This happened while the csv dataset builder was generating data using
hf://datasets/kalrap/M10_AIML_MLOps_Tourism_Project/tourism.csv (at revision 40e2c3f41c4ae11c43e34e9164870dc258086f3f)
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.
Unnamed: 0
int64 | Age
float64 | TypeofContact
int64 | 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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
1,214
| 44
| 1
| 1
| 8
|
Salaried
|
Female
| 3
| 1
|
Standard
| 3
|
Married
| 2
| 1
| 4
| 1
| 0
|
Senior Manager
| 22,879
|
3,829
| 35
| 1
| 3
| 20
|
Small Business
|
Male
| 3
| 4
|
Standard
| 3
|
Married
| 3
| 0
| 1
| 1
| 2
|
Senior Manager
| 27,306
|
2,622
| 47
| 1
| 3
| 7
|
Small Business
|
Female
| 4
| 4
|
Standard
| 5
|
Married
| 3
| 0
| 2
| 1
| 2
|
Senior Manager
| 29,131
|
1,543
| 32
| 1
| 1
| 6
|
Salaried
|
Male
| 3
| 3
|
Deluxe
| 4
|
Married
| 2
| 0
| 3
| 1
| 0
|
Manager
| 21,220
|
3,144
| 59
| 1
| 1
| 9
|
Large Business
|
Male
| 3
| 4
|
Basic
| 3
|
Single
| 6
| 0
| 2
| 1
| 2
|
Executive
| 21,157
|
907
| 44
| 1
| 3
| 11
|
Small Business
|
Male
| 2
| 3
|
King
| 4
|
Divorced
| 1
| 0
| 5
| 1
| 1
|
VP
| 33,213
|
1,426
| 32
| 1
| 1
| 35
|
Salaried
|
Female
| 2
| 4
|
Basic
| 4
|
Single
| 2
| 0
| 3
| 1
| 0
|
Executive
| 17,837
|
4,269
| 27
| 1
| 3
| 7
|
Salaried
|
Male
| 3
| 4
|
Deluxe
| 3
|
Married
| 3
| 0
| 5
| 0
| 2
|
Manager
| 23,974
|
261
| 38
| 0
| 3
| 8
|
Salaried
|
Male
| 2
| 4
|
Deluxe
| 3
|
Divorced
| 4
| 0
| 5
| 1
| 1
|
Manager
| 20,249
|
4,223
| 32
| 1
| 1
| 12
|
Large Business
|
Male
| 3
| 4
|
Basic
| 3
|
Married
| 2
| 1
| 4
| 1
| 1
|
Executive
| 23,499
|
243
| 40
| 1
| 1
| 30
|
Large Business
|
Male
| 3
| 3
|
Deluxe
| 3
|
Married
| 2
| 0
| 3
| 1
| 1
|
Manager
| 18,319
|
3,533
| 38
| 1
| 1
| 20
|
Small Business
|
Male
| 3
| 4
|
Deluxe
| 3
|
Married
| 3
| 0
| 1
| 0
| 1
|
Manager
| 22,963
|
228
| 35
| 0
| 3
| 6
|
Small Business
|
Fe Male
| 3
| 3
|
Standard
| 3
|
Unmarried
| 2
| 0
| 5
| 1
| 0
|
Senior Manager
| 23,789
|
1,110
| 35
| 1
| 1
| 8
|
Salaried
|
Female
| 3
| 3
|
Basic
| 5
|
Married
| 2
| 1
| 1
| 1
| 1
|
Executive
| 17,074
|
4,350
| 34
| 1
| 1
| 17
|
Small Business
|
Male
| 3
| 6
|
Basic
| 3
|
Married
| 2
| 0
| 5
| 0
| 1
|
Executive
| 22,086
|
3,870
| 33
| 1
| 1
| 36
|
Salaried
|
Female
| 3
| 5
|
Basic
| 4
|
Unmarried
| 3
| 0
| 3
| 1
| 1
|
Executive
| 21,515
|
87
| 51
| 1
| 1
| 15
|
Salaried
|
Male
| 3
| 3
|
Basic
| 3
|
Divorced
| 4
| 0
| 3
| 1
| 0
|
Executive
| 17,075
|
1,365
| 29
| 0
| 3
| 30
|
Large Business
|
Male
| 2
| 1
|
Basic
| 5
|
Single
| 2
| 0
| 3
| 1
| 1
|
Executive
| 16,091
|
378
| 34
| 0
| 3
| 25
|
Small Business
|
Male
| 3
| 2
|
Deluxe
| 3
|
Single
| 1
| 1
| 2
| 1
| 2
|
Manager
| 20,304
|
2,522
| 38
| 1
| 1
| 14
|
Small Business
|
Male
| 2
| 4
|
Standard
| 3
|
Single
| 6
| 0
| 2
| 0
| 1
|
Senior Manager
| 32,342
|
209
| 46
| 1
| 1
| 6
|
Small Business
|
Male
| 3
| 3
|
Standard
| 5
|
Married
| 1
| 0
| 2
| 0
| 0
|
Senior Manager
| 24,396
|
510
| 54
| 1
| 2
| 25
|
Small Business
|
Male
| 2
| 3
|
Standard
| 4
|
Divorced
| 3
| 0
| 3
| 1
| 0
|
Senior Manager
| 25,725
|
2,022
| 56
| 1
| 1
| 15
|
Small Business
|
Male
| 2
| 3
|
Super Deluxe
| 3
|
Married
| 1
| 0
| 4
| 0
| 0
|
AVP
| 26,103
|
385
| 30
| 0
| 1
| 10
|
Large Business
|
Male
| 2
| 3
|
Basic
| 3
|
Single
| 19
| 1
| 4
| 1
| 1
|
Executive
| 17,285
|
1,386
| 26
| 1
| 1
| 6
|
Small Business
|
Male
| 3
| 3
|
Basic
| 5
|
Single
| 1
| 0
| 5
| 1
| 2
|
Executive
| 17,867
|
2,060
| 33
| 1
| 1
| 13
|
Small Business
|
Male
| 2
| 3
|
Standard
| 3
|
Married
| 1
| 0
| 4
| 1
| 0
|
Senior Manager
| 26,691
|
1,946
| 24
| 1
| 1
| 23
|
Salaried
|
Male
| 3
| 4
|
Basic
| 4
|
Married
| 2
| 0
| 3
| 1
| 1
|
Executive
| 17,127
|
3,768
| 30
| 1
| 1
| 36
|
Salaried
|
Male
| 4
| 6
|
Deluxe
| 3
|
Married
| 2
| 0
| 5
| 1
| 3
|
Manager
| 25,062
|
1,253
| 33
| 0
| 3
| 8
|
Small Business
|
Female
| 3
| 3
|
Deluxe
| 4
|
Single
| 1
| 0
| 1
| 0
| 0
|
Manager
| 20,147
|
2,230
| 53
| 0
| 3
| 8
|
Small Business
|
Female
| 2
| 4
|
Standard
| 4
|
Married
| 3
| 0
| 1
| 1
| 0
|
Senior Manager
| 22,525
|
3,514
| 29
| 0
| 3
| 14
|
Salaried
|
Male
| 3
| 4
|
Deluxe
| 5
|
Unmarried
| 2
| 0
| 3
| 1
| 2
|
Manager
| 23,576
|
1,372
| 39
| 1
| 1
| 15
|
Small Business
|
Male
| 2
| 3
|
Deluxe
| 5
|
Married
| 2
| 0
| 4
| 1
| 0
|
Manager
| 20,151
|
4,366
| 46
| 1
| 3
| 9
|
Salaried
|
Male
| 4
| 4
|
Deluxe
| 4
|
Married
| 2
| 0
| 5
| 1
| 3
|
Manager
| 23,483
|
2,466
| 35
| 1
| 1
| 14
|
Salaried
|
Female
| 3
| 4
|
Standard
| 4
|
Single
| 2
| 0
| 3
| 1
| 1
|
Senior Manager
| 30,672
|
4,073
| 35
| 0
| 3
| 9
|
Small Business
|
Female
| 4
| 4
|
Basic
| 3
|
Married
| 8
| 0
| 5
| 0
| 1
|
Executive
| 20,909
|
4,596
| 33
| 0
| 1
| 7
|
Salaried
|
Female
| 4
| 5
|
Basic
| 4
|
Married
| 8
| 0
| 3
| 0
| 3
|
Executive
| 21,010
|
2,373
| 29
| 0
| 1
| 16
|
Salaried
|
Female
| 2
| 4
|
Basic
| 3
|
Unmarried
| 2
| 0
| 4
| 1
| 0
|
Executive
| 21,623
|
1,916
| 41
| 0
| 3
| 16
|
Salaried
|
Male
| 2
| 3
|
Deluxe
| 3
|
Single
| 1
| 0
| 1
| 0
| 1
|
Manager
| 21,230
|
3,268
| 43
| 1
| 1
| 36
|
Small Business
|
Male
| 3
| 6
|
Deluxe
| 3
|
Unmarried
| 6
| 0
| 3
| 1
| 1
|
Manager
| 22,950
|
4,329
| 35
| 0
| 3
| 13
|
Small Business
|
Female
| 3
| 6
|
Basic
| 3
|
Married
| 2
| 0
| 4
| 0
| 2
|
Executive
| 21,029
|
1,685
| 41
| 1
| 3
| 12
|
Salaried
|
Female
| 3
| 3
|
Standard
| 3
|
Single
| 4
| 1
| 1
| 0
| 0
|
Senior Manager
| 28,591
|
694
| 33
| 1
| 1
| 6
|
Salaried
|
Female
| 2
| 4
|
Deluxe
| 3
|
Unmarried
| 1
| 0
| 4
| 0
| 0
|
Manager
| 21,949
|
837
| 40
| 0
| 1
| 15
|
Small Business
|
Fe Male
| 2
| 3
|
Standard
| 3
|
Unmarried
| 1
| 0
| 4
| 0
| 0
|
Senior Manager
| 28,499
|
1,852
| 26
| 0
| 1
| 9
|
Large Business
|
Male
| 3
| 3
|
Basic
| 5
|
Single
| 1
| 0
| 3
| 0
| 1
|
Executive
| 18,102
|
1,712
| 41
| 1
| 1
| 25
|
Salaried
|
Male
| 2
| 3
|
Deluxe
| 5
|
Married
| 3
| 0
| 1
| 0
| 0
|
Manager
| 18,072
|
222
| 37
| 0
| 1
| 17
|
Salaried
|
Male
| 2
| 3
|
Standard
| 3
|
Married
| 2
| 1
| 3
| 0
| 1
|
Senior Manager
| 27,185
|
2,145
| 31
| 1
| 3
| 13
|
Salaried
|
Male
| 2
| 4
|
Basic
| 3
|
Married
| 4
| 0
| 4
| 1
| 1
|
Executive
| 17,329
|
4,867
| 45
| 1
| 3
| 8
|
Salaried
|
Male
| 3
| 6
|
Deluxe
| 4
|
Single
| 8
| 0
| 3
| 0
| 2
|
Manager
| 21,040
|
514
| 33
| 0
| 1
| 9
|
Salaried
|
Male
| 3
| 3
|
Basic
| 5
|
Single
| 2
| 1
| 5
| 1
| 2
|
Executive
| 18,348
|
2,795
| 33
| 1
| 1
| 9
|
Small Business
|
Female
| 4
| 4
|
Basic
| 4
|
Divorced
| 3
| 0
| 4
| 0
| 1
|
Executive
| 21,048
|
1,074
| 33
| 1
| 1
| 14
|
Salaried
|
Male
| 3
| 3
|
Deluxe
| 3
|
Unmarried
| 3
| 1
| 3
| 0
| 2
|
Manager
| 21,388
|
402
| 30
| 1
| 3
| 18
|
Large Business
|
Female
| 2
| 3
|
Deluxe
| 3
|
Unmarried
| 1
| 0
| 2
| 1
| 0
|
Manager
| 21,577
|
547
| 42
| 0
| 1
| 25
|
Small Business
|
Male
| 2
| 2
|
Basic
| 3
|
Married
| 7
| 1
| 3
| 1
| 1
|
Executive
| 17,759
|
1,899
| 46
| 1
| 1
| 8
|
Salaried
|
Male
| 2
| 3
|
Super Deluxe
| 3
|
Married
| 7
| 0
| 5
| 1
| 0
|
AVP
| 32,861
|
4,656
| 51
| 1
| 1
| 16
|
Salaried
|
Male
| 4
| 4
|
Basic
| 3
|
Married
| 6
| 0
| 5
| 1
| 3
|
Executive
| 21,058
|
1,880
| 30
| 1
| 1
| 8
|
Salaried
|
Female
| 2
| 5
|
Deluxe
| 3
|
Single
| 3
| 0
| 1
| 1
| 0
|
Manager
| 21,091
|
2,742
| 37
| 0
| 1
| 25
|
Salaried
|
Male
| 3
| 3
|
Basic
| 3
|
Divorced
| 6
| 0
| 5
| 0
| 1
|
Executive
| 22,366
|
1,323
| 28
| 0
| 2
| 6
|
Salaried
|
Male
| 2
| 3
|
Basic
| 3
|
Married
| 2
| 0
| 4
| 0
| 1
|
Executive
| 17,706
|
1,357
| 42
| 1
| 1
| 12
|
Small Business
|
Male
| 2
| 3
|
Standard
| 5
|
Married
| 1
| 0
| 3
| 1
| 0
|
Senior Manager
| 28,348
|
617
| 44
| 1
| 1
| 10
|
Small Business
|
Male
| 2
| 3
|
Deluxe
| 4
|
Single
| 1
| 0
| 2
| 1
| 0
|
Manager
| 20,933
|
3,637
| 39
| 0
| 1
| 9
|
Small Business
|
Female
| 3
| 5
|
Basic
| 4
|
Single
| 3
| 0
| 1
| 1
| 1
|
Executive
| 21,118
|
253
| 42
| 1
| 1
| 23
|
Salaried
|
Female
| 2
| 2
|
Deluxe
| 5
|
Unmarried
| 4
| 1
| 2
| 0
| 0
|
Manager
| 21,545
|
2,223
| 39
| 0
| 1
| 28
|
Small Business
|
Fe Male
| 2
| 3
|
Standard
| 5
|
Unmarried
| 2
| 1
| 5
| 1
| 1
|
Senior Manager
| 25,880
|
944
| 28
| 0
| 1
| 6
|
Salaried
|
Female
| 2
| 5
|
Deluxe
| 3
|
Divorced
| 1
| 0
| 3
| 1
| 0
|
Manager
| 21,674
|
2,079
| 43
| 1
| 1
| 20
|
Salaried
|
Male
| 3
| 3
|
Super Deluxe
| 5
|
Married
| 7
| 0
| 5
| 1
| 1
|
AVP
| 32,159
|
3,372
| 45
| 1
| 1
| 22
|
Small Business
|
Female
| 4
| 4
|
Standard
| 3
|
Divorced
| 3
| 0
| 3
| 0
| 2
|
Senior Manager
| 26,656
|
4,382
| 53
| 1
| 1
| 13
|
Large Business
|
Male
| 4
| 4
|
Deluxe
| 5
|
Married
| 5
| 1
| 4
| 1
| 2
|
Manager
| 24,255
|
4,062
| 42
| 1
| 1
| 16
|
Salaried
|
Male
| 4
| 4
|
Basic
| 5
|
Married
| 4
| 0
| 1
| 0
| 1
|
Executive
| 20,916
|
9
| 36
| 1
| 1
| 33
|
Small Business
|
Male
| 3
| 3
|
Deluxe
| 3
|
Divorced
| 7
| 0
| 3
| 1
| 0
|
Manager
| 20,237
|
3,259
| 22
| 1
| 1
| 7
|
Large Business
|
Female
| 4
| 5
|
Basic
| 4
|
Single
| 3
| 1
| 5
| 0
| 3
|
Executive
| 20,748
|
2,664
| 37
| 1
| 1
| 12
|
Salaried
|
Male
| 4
| 4
|
Deluxe
| 4
|
Unmarried
| 2
| 0
| 2
| 0
| 3
|
Manager
| 24,592
|
3,501
| 30
| 0
| 3
| 20
|
Large Business
|
Fe Male
| 3
| 4
|
Deluxe
| 4
|
Unmarried
| 7
| 0
| 3
| 0
| 2
|
Manager
| 24,443
|
3,967
| 36
| 0
| 1
| 18
|
Small Business
|
Male
| 4
| 5
|
Standard
| 5
|
Married
| 4
| 1
| 5
| 1
| 3
|
Senior Manager
| 28,562
|
186
| 40
| 1
| 1
| 10
|
Small Business
|
Female
| 2
| 3
|
King
| 3
|
Divorced
| 2
| 0
| 5
| 0
| 1
|
VP
| 34,033
|
136
| 51
| 0
| 1
| 14
|
Salaried
|
Male
| 2
| 5
|
Standard
| 3
|
Unmarried
| 3
| 0
| 2
| 0
| 1
|
Senior Manager
| 25,650
|
3,835
| 39
| 1
| 3
| 7
|
Salaried
|
Male
| 3
| 5
|
Basic
| 5
|
Unmarried
| 6
| 0
| 3
| 0
| 2
|
Executive
| 21,536
|
390
| 43
| 1
| 1
| 18
|
Salaried
|
Male
| 2
| 4
|
Super Deluxe
| 4
|
Married
| 2
| 0
| 3
| 0
| 1
|
AVP
| 29,336
|
40
| 35
| 1
| 1
| 10
|
Salaried
|
Male
| 3
| 3
|
Basic
| 3
|
Married
| 2
| 0
| 4
| 0
| 0
|
Executive
| 16,951
|
2,695
| 40
| 0
| 1
| 9
|
Large Business
|
Female
| 4
| 4
|
Standard
| 3
|
Single
| 2
| 0
| 2
| 1
| 2
|
Senior Manager
| 29,616
|
3,753
| 27
| 1
| 3
| 17
|
Small Business
|
Male
| 3
| 4
|
Deluxe
| 3
|
Unmarried
| 3
| 0
| 1
| 0
| 1
|
Manager
| 23,362
|
762
| 26
| 0
| 1
| 8
|
Salaried
|
Male
| 2
| 3
|
Basic
| 5
|
Divorced
| 7
| 1
| 5
| 1
| 0
|
Executive
| 17,042
|
119
| 43
| 0
| 3
| 32
|
Salaried
|
Male
| 3
| 3
|
Super Deluxe
| 3
|
Divorced
| 2
| 1
| 2
| 0
| 0
|
AVP
| 31,959
|
3,339
| 32
| 1
| 1
| 18
|
Small Business
|
Male
| 4
| 4
|
Deluxe
| 5
|
Divorced
| 3
| 1
| 2
| 0
| 3
|
Manager
| 25,511
|
2,560
| 35
| 1
| 1
| 12
|
Small Business
|
Female
| 3
| 5
|
Standard
| 5
|
Single
| 4
| 0
| 2
| 0
| 1
|
Senior Manager
| 30,309
|
4,135
| 34
| 1
| 1
| 11
|
Small Business
|
Female
| 3
| 5
|
Basic
| 4
|
Married
| 8
| 0
| 4
| 0
| 2
|
Executive
| 21,300
|
1,016
| 31
| 1
| 1
| 14
|
Salaried
|
Female
| 2
| 4
|
Basic
| 4
|
Single
| 2
| 0
| 4
| 0
| 1
|
Executive
| 16,261
|
4,748
| 35
| 1
| 3
| 16
|
Salaried
|
Female
| 4
| 4
|
Deluxe
| 3
|
Married
| 3
| 0
| 1
| 0
| 1
|
Manager
| 24,392
|
4,865
| 42
| 0
| 3
| 16
|
Salaried
|
Male
| 3
| 6
|
Super Deluxe
| 3
|
Married
| 2
| 0
| 5
| 1
| 2
|
AVP
| 24,829
|
2,030
| 34
| 1
| 1
| 14
|
Salaried
|
Female
| 2
| 3
|
Deluxe
| 5
|
Married
| 4
| 0
| 5
| 1
| 1
|
Manager
| 20,121
|
2,680
| 34
| 1
| 1
| 9
|
Salaried
|
Female
| 3
| 4
|
Basic
| 5
|
Divorced
| 2
| 0
| 3
| 1
| 1
|
Executive
| 21,385
|
22
| 34
| 1
| 1
| 13
|
Salaried
|
Fe Male
| 2
| 3
|
Standard
| 4
|
Unmarried
| 1
| 0
| 3
| 1
| 0
|
Senior Manager
| 26,994
|
2,643
| 39
| 1
| 1
| 36
|
Large Business
|
Male
| 3
| 4
|
Deluxe
| 3
|
Divorced
| 5
| 0
| 2
| 0
| 2
|
Manager
| 24,939
|
3,965
| 29
| 1
| 1
| 12
|
Large Business
|
Male
| 3
| 4
|
Basic
| 3
|
Unmarried
| 3
| 1
| 1
| 0
| 1
|
Executive
| 22,119
|
1,288
| 35
| 0
| 1
| 8
|
Small Business
|
Male
| 2
| 3
|
Deluxe
| 3
|
Married
| 3
| 0
| 3
| 0
| 1
|
Manager
| 20,762
|
293
| 26
| 1
| 3
| 10
|
Small Business
|
Male
| 2
| 4
|
Deluxe
| 3
|
Single
| 2
| 1
| 2
| 1
| 1
|
Manager
| 20,828
|
2,562
| 37
| 1
| 1
| 10
|
Salaried
|
Female
| 3
| 4
|
Basic
| 3
|
Married
| 7
| 0
| 2
| 1
| 1
|
Executive
| 21,513
|
3,734
| 35
| 0
| 1
| 16
|
Salaried
|
Male
| 4
| 4
|
Deluxe
| 5
|
Married
| 6
| 0
| 3
| 0
| 2
|
Manager
| 24,024
|
4,727
| 40
| 0
| 1
| 9
|
Salaried
|
Male
| 3
| 4
|
Super Deluxe
| 3
|
Married
| 2
| 0
| 3
| 1
| 1
|
AVP
| 30,847
|
363
| 33
| 1
| 3
| 11
|
Small Business
|
Female
| 2
| 3
|
Basic
| 3
|
Single
| 2
| 1
| 2
| 1
| 0
|
Executive
| 17,851
|
642
| 38
| 1
| 3
| 15
|
Small Business
|
Male
| 3
| 4
|
Basic
| 4
|
Divorced
| 1
| 0
| 4
| 0
| 0
|
Executive
| 17,899
|
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