Dataset Preview
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 3 new columns ({'CustomerID', 'Unnamed: 0', 'ProdTaken'})
This happened while the csv dataset builder was generating data using
hf://datasets/cbendale10/MLOps-Tourism-Prediction/tourism.csv (at revision f9381dfc457d5d621674638995548584cf26e156)
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 "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1831, in _prepare_split_single
writer.write_table(table)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/arrow_writer.py", line 644, in write_table
pa_table = table_cast(pa_table, self._schema)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2272, in table_cast
return cast_table_to_schema(table, schema)
File "/src/services/worker/.venv/lib/python3.9/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
{'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 1456, 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 1055, in convert_to_parquet
builder.download_and_prepare(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 894, in download_and_prepare
self._download_and_prepare(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 970, in _download_and_prepare
self._prepare_split(split_generator, **prepare_split_kwargs)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1702, in _prepare_split
for job_id, done, content in self._prepare_split_single(
File "/src/services/worker/.venv/lib/python3.9/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 3 new columns ({'CustomerID', 'Unnamed: 0', 'ProdTaken'})
This happened while the csv dataset builder was generating data using
hf://datasets/cbendale10/MLOps-Tourism-Prediction/tourism.csv (at revision f9381dfc457d5d621674638995548584cf26e156)
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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
30
|
Self Enquiry
| 3
| 18
|
Large Business
|
Female
| 2
| 3
|
Deluxe
| 3
|
Unmarried
| 1
| 0
| 2
| 1
| 0
|
Manager
| 21,577
|
28
|
Self Enquiry
| 1
| 13
|
Salaried
|
Male
| 3
| 5
|
Basic
| 3
|
Divorced
| 3
| 0
| 2
| 1
| 2
|
Executive
| 21,217
|
22
|
Self Enquiry
| 1
| 12
|
Small Business
|
Male
| 4
| 4
|
Basic
| 3
|
Unmarried
| 3
| 0
| 1
| 1
| 2
|
Executive
| 21,795
|
30
|
Company Invited
| 3
| 27
|
Large Business
|
Female
| 3
| 4
|
Basic
| 3
|
Divorced
| 3
| 0
| 3
| 0
| 2
|
Executive
| 20,835
|
27
|
Self Enquiry
| 3
| 30
|
Small Business
|
Female
| 3
| 5
|
Deluxe
| 3
|
Married
| 2
| 1
| 1
| 0
| 1
|
Manager
| 22,835
|
37
|
Company Invited
| 1
| 17
|
Salaried
|
Male
| 2
| 3
|
Standard
| 3
|
Married
| 2
| 1
| 3
| 0
| 1
|
Senior Manager
| 27,185
|
28
|
Company Invited
| 1
| 12
|
Salaried
|
Male
| 2
| 4
|
Basic
| 3
|
Married
| 2
| 1
| 4
| 1
| 1
|
Executive
| 17,703
|
38
|
Self Enquiry
| 3
| 7
|
Salaried
|
Male
| 3
| 5
|
Standard
| 3
|
Divorced
| 7
| 0
| 2
| 1
| 2
|
Senior Manager
| 29,287
|
27
|
Self Enquiry
| 1
| 11
|
Large Business
|
Male
| 2
| 4
|
Standard
| 3
|
Married
| 2
| 1
| 3
| 0
| 0
|
Senior Manager
| 27,808
|
36
|
Self Enquiry
| 1
| 30
|
Salaried
|
Male
| 3
| 5
|
Deluxe
| 3
|
Married
| 5
| 1
| 4
| 1
| 1
|
Manager
| 24,594
|
55
|
Self Enquiry
| 1
| 26
|
Small Business
|
Female
| 4
| 4
|
Deluxe
| 5
|
Married
| 2
| 1
| 3
| 0
| 1
|
Manager
| 24,163
|
21
|
Self Enquiry
| 1
| 18
|
Small Business
|
Female
| 4
| 5
|
Basic
| 5
|
Unmarried
| 3
| 1
| 3
| 1
| 3
|
Executive
| 21,278
|
29
|
Company Invited
| 3
| 7
|
Salaried
|
Male
| 3
| 5
|
Deluxe
| 3
|
Married
| 3
| 1
| 1
| 0
| 1
|
Manager
| 25,512
|
33
|
Company Invited
| 3
| 8
|
Small Business
|
Female
| 3
| 3
|
Deluxe
| 4
|
Single
| 1
| 0
| 1
| 0
| 0
|
Manager
| 20,147
|
29
|
Self Enquiry
| 1
| 14
|
Small Business
|
Male
| 3
| 4
|
Deluxe
| 3
|
Married
| 2
| 1
| 3
| 1
| 1
|
Manager
| 20,056
|
47
|
Company Invited
| 1
| 14
|
Small Business
|
Female
| 2
| 4
|
Deluxe
| 3
|
Married
| 4
| 0
| 5
| 1
| 1
|
Manager
| 23,936
|
25
|
Company Invited
| 1
| 14
|
Salaried
|
Female
| 3
| 4
|
Basic
| 3
|
Divorced
| 3
| 1
| 4
| 0
| 1
|
Executive
| 21,564
|
18
|
Company Invited
| 3
| 11
|
Small Business
|
Male
| 3
| 3
|
Basic
| 4
|
Single
| 2
| 1
| 4
| 1
| 2
|
Executive
| 16,878
|
31
|
Company Invited
| 3
| 26
|
Small Business
|
Female
| 2
| 3
|
Deluxe
| 3
|
Divorced
| 2
| 0
| 2
| 1
| 0
|
Manager
| 21,932
|
35
|
Self Enquiry
| 1
| 6
|
Salaried
|
Female
| 2
| 1
|
Basic
| 3
|
Single
| 4
| 0
| 3
| 1
| 1
|
Executive
| 17,506
|
31
|
Self Enquiry
| 3
| 11
|
Salaried
|
Female
| 3
| 3
|
Deluxe
| 3
|
Married
| 2
| 0
| 1
| 0
| 2
|
Manager
| 20,476
|
33
|
Company Invited
| 1
| 23
|
Salaried
|
Female
| 4
| 6
|
Basic
| 5
|
Unmarried
| 3
| 1
| 4
| 1
| 3
|
Executive
| 22,597
|
44
|
Company Invited
| 1
| 8
|
Small Business
|
Male
| 2
| 3
|
Standard
| 3
|
Unmarried
| 6
| 1
| 1
| 0
| 1
|
Senior Manager
| 25,209
|
48
|
Company Invited
| 1
| 23
|
Small Business
|
Male
| 4
| 2
|
Deluxe
| 3
|
Married
| 3
| 1
| 2
| 0
| 1
|
Manager
| 23,745
|
43
|
Company Invited
| 1
| 15
|
Small Business
|
Male
| 3
| 3
|
Deluxe
| 3
|
Married
| 4
| 1
| 3
| 1
| 0
|
Manager
| 20,679
|
36
|
Self Enquiry
| 1
| 7
|
Salaried
|
Female
| 3
| 2
|
Basic
| 3
|
Single
| 5
| 0
| 3
| 0
| 1
|
Executive
| 21,184
|
44
|
Self Enquiry
| 1
| 34
|
Large Business
|
Male
| 3
| 2
|
Basic
| 4
|
Married
| 7
| 0
| 5
| 1
| 2
|
Executive
| 23,554
|
39
|
Company Invited
| 1
| 9
|
Small Business
|
Female
| 3
| 5
|
Basic
| 4
|
Single
| 3
| 0
| 1
| 1
| 1
|
Executive
| 21,118
|
34
|
Company Invited
| 1
| 22
|
Salaried
|
Female
| 3
| 4
|
Basic
| 3
|
Single
| 2
| 0
| 5
| 1
| 1
|
Executive
| 17,553
|
33
|
Self Enquiry
| 3
| 14
|
Salaried
|
Male
| 4
| 5
|
Deluxe
| 3
|
Divorced
| 3
| 0
| 3
| 1
| 3
|
Manager
| 24,162
|
41
|
Self Enquiry
| 3
| 17
|
Small Business
|
Male
| 4
| 5
|
Standard
| 4
|
Married
| 4
| 0
| 4
| 0
| 1
|
Senior Manager
| 28,383
|
34
|
Self Enquiry
| 3
| 14
|
Salaried
|
Female
| 3
| 3
|
Deluxe
| 5
|
Divorced
| 6
| 0
| 2
| 1
| 0
|
Manager
| 21,500
|
27
|
Self Enquiry
| 1
| 23
|
Small Business
|
Male
| 3
| 4
|
Basic
| 4
|
Married
| 4
| 1
| 2
| 1
| 2
|
Executive
| 21,051
|
51
|
Self Enquiry
| 1
| 15
|
Salaried
|
Male
| 3
| 3
|
Basic
| 3
|
Divorced
| 4
| 0
| 3
| 1
| 0
|
Executive
| 17,075
|
46
|
Self Enquiry
| 1
| 16
|
Salaried
|
Male
| 3
| 4
|
Deluxe
| 4
|
Married
| 2
| 0
| 4
| 1
| 1
|
Manager
| 21,026
|
29
|
Self Enquiry
| 1
| 15
|
Salaried
|
Female
| 3
| 5
|
Basic
| 4
|
Single
| 3
| 0
| 4
| 0
| 2
|
Executive
| 20,832
|
38
|
Self Enquiry
| 3
| 9
|
Small Business
|
Male
| 4
| 4
|
Deluxe
| 3
|
Married
| 6
| 1
| 3
| 0
| 3
|
Manager
| 28,280
|
46
|
Company Invited
| 3
| 33
|
Salaried
|
Female
| 4
| 4
|
Deluxe
| 5
|
Married
| 4
| 0
| 1
| 0
| 3
|
Manager
| 22,964
|
59
|
Company Invited
| 1
| 9
|
Salaried
|
Male
| 3
| 5
|
Basic
| 3
|
Married
| 2
| 1
| 2
| 0
| 1
|
Executive
| 21,058
|
44
|
Self Enquiry
| 1
| 13
|
Small Business
|
Female
| 4
| 5
|
Deluxe
| 3
|
Unmarried
| 3
| 1
| 4
| 1
| 2
|
Manager
| 22,759
|
37
|
Self Enquiry
| 2
| 20
|
Salaried
|
Male
| 3
| 5
|
Basic
| 5
|
Married
| 6
| 1
| 5
| 1
| 2
|
Executive
| 23,317
|
45
|
Company Invited
| 1
| 31
|
Salaried
|
Male
| 3
| 4
|
Basic
| 3
|
Married
| 5
| 1
| 5
| 0
| 2
|
Executive
| 21,839
|
40
|
Self Enquiry
| 1
| 30
|
Large Business
|
Male
| 3
| 3
|
Deluxe
| 3
|
Married
| 2
| 0
| 3
| 1
| 1
|
Manager
| 18,319
|
28
|
Self Enquiry
| 3
| 11
|
Small Business
|
Male
| 2
| 3
|
Deluxe
| 5
|
Unmarried
| 1
| 0
| 1
| 1
| 0
|
Manager
| 23,463
|
36
|
Self Enquiry
| 1
| 29
|
Salaried
|
Male
| 3
| 6
|
Basic
| 3
|
Unmarried
| 2
| 0
| 4
| 1
| 2
|
Executive
| 22,908
|
55
|
Self Enquiry
| 1
| 14
|
Small Business
|
Female
| 2
| 3
|
Super Deluxe
| 3
|
Married
| 3
| 1
| 3
| 1
| 1
|
AVP
| 29,756
|
43
|
Company Invited
| 1
| 27
|
Small Business
|
Male
| 3
| 3
|
Basic
| 3
|
Divorced
| 1
| 0
| 4
| 0
| 2
|
Executive
| 17,258
|
43
|
Self Enquiry
| 3
| 15
|
Small Business
|
Male
| 3
| 4
|
Deluxe
| 4
|
Married
| 2
| 0
| 3
| 1
| 1
|
Manager
| 25,503
|
38
|
Company Invited
| 3
| 8
|
Salaried
|
Male
| 2
| 4
|
Deluxe
| 3
|
Divorced
| 4
| 0
| 5
| 1
| 1
|
Manager
| 20,249
|
37
|
Self Enquiry
| 1
| 15
|
Large Business
|
Female
| 3
| 4
|
Standard
| 3
|
Married
| 3
| 0
| 4
| 1
| 2
|
Senior Manager
| 28,774
|
35
|
Self Enquiry
| 1
| 7
|
Salaried
|
Male
| 3
| 5
|
Basic
| 3
|
Divorced
| 3
| 1
| 2
| 0
| 1
|
Executive
| 22,300
|
39
|
Company Invited
| 2
| 9
|
Salaried
|
Male
| 4
| 4
|
Basic
| 4
|
Married
| 7
| 0
| 3
| 1
| 3
|
Executive
| 21,270
|
21
|
Company Invited
| 3
| 6
|
Large Business
|
Female
| 3
| 4
|
Basic
| 4
|
Single
| 2
| 1
| 5
| 1
| 2
|
Executive
| 17,174
|
30
|
Self Enquiry
| 3
| 15
|
Small Business
|
Male
| 2
| 3
|
Basic
| 3
|
Single
| 2
| 0
| 5
| 0
| 0
|
Executive
| 16,081
|
23
|
Self Enquiry
| 1
| 26
|
Small Business
|
Male
| 4
| 4
|
Basic
| 3
|
Married
| 3
| 0
| 1
| 1
| 1
|
Executive
| 21,001
|
25
|
Self Enquiry
| 1
| 25
|
Salaried
|
Male
| 3
| 4
|
Basic
| 3
|
Divorced
| 2
| 0
| 4
| 1
| 1
|
Executive
| 21,452
|
39
|
Self Enquiry
| 1
| 16
|
Small Business
|
Male
| 3
| 3
|
Deluxe
| 5
|
Married
| 3
| 0
| 5
| 1
| 2
|
Manager
| 20,377
|
40
|
Self Enquiry
| 1
| 10
|
Small Business
|
Female
| 2
| 3
|
King
| 3
|
Divorced
| 2
| 0
| 5
| 0
| 1
|
VP
| 34,033
|
41
|
Self Enquiry
| 3
| 6
|
Small Business
|
Male
| 2
| 1
|
Standard
| 5
|
Married
| 2
| 0
| 3
| 1
| 1
|
Senior Manager
| 23,392
|
24
|
Self Enquiry
| 1
| 11
|
Small Business
|
Female
| 3
| 4
|
Basic
| 4
|
Unmarried
| 3
| 0
| 3
| 1
| 2
|
Executive
| 21,973
|
53
|
Self Enquiry
| 1
| 15
|
Small Business
|
Male
| 3
| 5
|
Deluxe
| 4
|
Married
| 4
| 0
| 1
| 1
| 1
|
Manager
| 23,619
|
37
|
Self Enquiry
| 3
| 10
|
Salaried
|
Male
| 3
| 5
|
Standard
| 3
|
Married
| 3
| 1
| 1
| 1
| 1
|
Senior Manager
| 29,003
|
31
|
Company Invited
| 1
| 11
|
Large Business
|
Male
| 3
| 4
|
Basic
| 3
|
Single
| 20
| 1
| 4
| 1
| 2
|
Executive
| 20,963
|
50
|
Self Enquiry
| 1
| 8
|
Small Business
|
Male
| 3
| 3
|
King
| 3
|
Married
| 3
| 1
| 1
| 1
| 2
|
VP
| 34,237
|
26
|
Self Enquiry
| 1
| 31
|
Salaried
|
Male
| 2
| 5
|
Basic
| 3
|
Single
| 2
| 0
| 1
| 0
| 0
|
Executive
| 17,293
|
51
|
Company Invited
| 1
| 27
|
Small Business
|
Male
| 3
| 4
|
Super Deluxe
| 3
|
Married
| 4
| 1
| 4
| 1
| 2
|
AVP
| 29,923
|
34
|
Self Enquiry
| 3
| 8
|
Salaried
|
Male
| 2
| 3
|
Deluxe
| 3
|
Single
| 2
| 0
| 5
| 0
| 0
|
Manager
| 21,274
|
41
|
Self Enquiry
| 3
| 7
|
Small Business
|
Male
| 3
| 6
|
Deluxe
| 3
|
Divorced
| 4
| 1
| 3
| 1
| 1
|
Manager
| 26,135
|
32
|
Self Enquiry
| 1
| 18
|
Small Business
|
Male
| 4
| 4
|
Deluxe
| 5
|
Married
| 3
| 1
| 1
| 1
| 2
|
Manager
| 25,511
|
43
|
Self Enquiry
| 1
| 13
|
Salaried
|
Female
| 2
| 3
|
Standard
| 5
|
Divorced
| 1
| 0
| 5
| 1
| 0
|
Senior Manager
| 24,985
|
54
|
Self Enquiry
| 3
| 7
|
Small Business
|
Female
| 3
| 4
|
Deluxe
| 5
|
Unmarried
| 2
| 0
| 1
| 1
| 2
|
Manager
| 27,059
|
32
|
Self Enquiry
| 1
| 11
|
Salaried
|
Male
| 3
| 2
|
Basic
| 4
|
Married
| 1
| 1
| 2
| 1
| 0
|
Executive
| 18,298
|
25
|
Self Enquiry
| 3
| 7
|
Large Business
|
Female
| 4
| 4
|
Basic
| 4
|
Unmarried
| 3
| 1
| 4
| 0
| 1
|
Executive
| 21,880
|
37
|
Self Enquiry
| 1
| 13
|
Salaried
|
Male
| 3
| 4
|
Basic
| 3
|
Divorced
| 2
| 0
| 5
| 1
| 2
|
Executive
| 21,888
|
61
|
Self Enquiry
| 3
| 23
|
Small Business
|
Male
| 3
| 4
|
Deluxe
| 5
|
Unmarried
| 2
| 0
| 4
| 1
| 1
|
Manager
| 24,083
|
36
|
Self Enquiry
| 1
| 33
|
Small Business
|
Male
| 3
| 3
|
Deluxe
| 3
|
Divorced
| 7
| 0
| 3
| 1
| 0
|
Manager
| 20,237
|
26
|
Self Enquiry
| 1
| 13
|
Small Business
|
Female
| 2
| 4
|
Standard
| 5
|
Married
| 1
| 1
| 4
| 1
| 1
|
Senior Manager
| 17,875
|
55
|
Company Invited
| 1
| 8
|
Salaried
|
Male
| 3
| 3
|
Standard
| 4
|
Married
| 4
| 0
| 1
| 0
| 1
|
Senior Manager
| 25,976
|
42
|
Company Invited
| 3
| 32
|
Small Business
|
Female
| 3
| 3
|
Super Deluxe
| 4
|
Married
| 6
| 0
| 3
| 1
| 1
|
AVP
| 28,525
|
27
|
Self Enquiry
| 3
| 8
|
Small Business
|
Female
| 2
| 1
|
Deluxe
| 3
|
Unmarried
| 1
| 0
| 1
| 0
| 1
|
Manager
| 21,500
|
46
|
Self Enquiry
| 1
| 6
|
Small Business
|
Male
| 3
| 3
|
Standard
| 5
|
Married
| 1
| 0
| 2
| 0
| 0
|
Senior Manager
| 24,396
|
39
|
Self Enquiry
| 1
| 17
|
Small Business
|
Female
| 4
| 4
|
Deluxe
| 3
|
Married
| 5
| 0
| 3
| 0
| 2
|
Manager
| 28,502
|
39
|
Self Enquiry
| 1
| 17
|
Small Business
|
Female
| 3
| 6
|
Standard
| 3
|
Married
| 5
| 0
| 1
| 1
| 2
|
Senior Manager
| 31,884
|
38
|
Self Enquiry
| 2
| 13
|
Salaried
|
Male
| 4
| 4
|
Basic
| 5
|
Married
| 6
| 1
| 2
| 1
| 1
|
Executive
| 20,751
|
35
|
Self Enquiry
| 1
| 7
|
Salaried
|
Male
| 3
| 4
|
Deluxe
| 3
|
Married
| 2
| 0
| 4
| 1
| 1
|
Manager
| 24,162
|
39
|
Self Enquiry
| 1
| 7
|
Salaried
|
Female
| 3
| 2
|
Deluxe
| 3
|
Unmarried
| 2
| 0
| 1
| 0
| 1
|
Manager
| 26,303
|
27
|
Self Enquiry
| 3
| 30
|
Small Business
|
Female
| 3
| 5
|
Deluxe
| 3
|
Divorced
| 2
| 1
| 2
| 1
| 1
|
Manager
| 22,835
|
39
|
Company Invited
| 1
| 28
|
Small Business
|
Female
| 2
| 3
|
Standard
| 5
|
Unmarried
| 2
| 1
| 5
| 1
| 0
|
Senior Manager
| 25,880
|
23
|
Self Enquiry
| 1
| 12
|
Salaried
|
Male
| 3
| 1
|
Basic
| 5
|
Married
| 2
| 1
| 3
| 0
| 0
|
Executive
| 16,601
|
31
|
Company Invited
| 3
| 29
|
Salaried
|
Female
| 4
| 4
|
Standard
| 5
|
Married
| 2
| 0
| 1
| 1
| 2
|
Senior Manager
| 27,090
|
31
|
Self Enquiry
| 1
| 29
|
Salaried
|
Female
| 3
| 4
|
Basic
| 3
|
Divorced
| 6
| 1
| 2
| 0
| 2
|
Executive
| 20,810
|
35
|
Self Enquiry
| 3
| 16
|
Small Business
|
Male
| 2
| 4
|
Standard
| 5
|
Married
| 1
| 0
| 5
| 1
| 1
|
Senior Manager
| 25,306
|
31
|
Company Invited
| 1
| 6
|
Salaried
|
Female
| 3
| 1
|
Standard
| 4
|
Unmarried
| 2
| 0
| 3
| 1
| 2
|
Senior Manager
| 22,446
|
38
|
Self Enquiry
| 1
| 16
|
Small Business
|
Female
| 2
| 5
|
Standard
| 3
|
Married
| 4
| 0
| 1
| 1
| 1
|
Senior Manager
| 28,206
|
30
|
Company Invited
| 1
| 10
|
Large Business
|
Male
| 2
| 3
|
Basic
| 3
|
Single
| 19
| 1
| 4
| 1
| 1
|
Executive
| 17,285
|
34
|
Self Enquiry
| 3
| 32
|
Small Business
|
Male
| 3
| 5
|
Standard
| 4
|
Unmarried
| 4
| 1
| 5
| 1
| 1
|
Senior Manager
| 27,058
|
54
|
Self Enquiry
| 3
| 13
|
Small Business
|
Male
| 3
| 4
|
Deluxe
| 3
|
Married
| 4
| 1
| 5
| 0
| 2
|
Manager
| 20,984
|
23
|
Self Enquiry
| 3
| 13
|
Salaried
|
Male
| 2
| 3
|
Basic
| 3
|
Married
| 2
| 1
| 1
| 1
| 0
|
Executive
| 17,275
|
24
|
Self Enquiry
| 1
| 17
|
Large Business
|
Male
| 3
| 2
|
Basic
| 3
|
Married
| 4
| 0
| 1
| 1
| 1
|
Executive
| 20,751
|
46
|
Self Enquiry
| 3
| 27
|
Salaried
|
Female
| 3
| 4
|
Deluxe
| 3
|
Unmarried
| 2
| 0
| 1
| 1
| 1
|
Manager
| 23,528
|
End of preview.
No dataset card yet
- Downloads last month
- 14