Dataset Preview

Duplicate

Split (1)

train

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 8 new columns ({'CustomerID', 'ProdTaken', 'TypeofContact', 'MaritalStatus', 'Designation', 'CityTier', 'Occupation', 'ProductPitched'}) and 17 missing columns ({'ProductPitched_Super Deluxe', 'MaritalStatus_Unmarried', 'Occupation_Salaried', 'ProductPitched_Standard', 'Designation_VP', 'CityTier_3', 'MaritalStatus_Married', 'MaritalStatus_Single', 'ProductPitched_Deluxe', 'Occupation_Large Business', 'Designation_Executive', 'Designation_Senior Manager', 'TypeofContact_Self Enquiry', 'Occupation_Small Business', 'Designation_Manager', 'CityTier_2', 'ProductPitched_King'}).

This happened while the csv dataset builder was generating data using

hf://datasets/Divyap90/tourism_project_dataset/tourism.csv (at revision ea9f308876041ff8c737551786623fba7b794204)

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'), 'DurationOfPitch': Value('float64'), 'Gender': Value('int64'), 'NumberOfPersonVisiting': Value('float64'), 'NumberOfFollowups': Value('float64'), 'PreferredPropertyStar': Value('float64'), 'NumberOfTrips': Value('float64'), 'Passport': Value('int64'), 'PitchSatisfactionScore': Value('float64'), 'OwnCar': Value('int64'), 'NumberOfChildrenVisiting': Value('float64'), 'MonthlyIncome': Value('float64'), 'TypeofContact_Self Enquiry': Value('bool'), 'CityTier_2': Value('bool'), 'CityTier_3': Value('bool'), 'Occupation_Large Business': Value('bool'), 'Occupation_Salaried': Value('bool'), 'Occupation_Small Business': Value('bool'), 'MaritalStatus_Married': Value('bool'), 'MaritalStatus_Single': Value('bool'), 'MaritalStatus_Unmarried': Value('bool'), 'ProductPitched_Deluxe': Value('bool'), 'ProductPitched_King': Value('bool'), 'ProductPitched_Standard': Value('bool'), 'ProductPitched_Super Deluxe': Value('bool'), 'Designation_Executive': Value('bool'), 'Designation_Manager': Value('bool'), 'Designation_Senior Manager': Value('bool'), 'Designation_VP': Value('bool')}
              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 8 new columns ({'CustomerID', 'ProdTaken', 'TypeofContact', 'MaritalStatus', 'Designation', 'CityTier', 'Occupation', 'ProductPitched'}) and 17 missing columns ({'ProductPitched_Super Deluxe', 'MaritalStatus_Unmarried', 'Occupation_Salaried', 'ProductPitched_Standard', 'Designation_VP', 'CityTier_3', 'MaritalStatus_Married', 'MaritalStatus_Single', 'ProductPitched_Deluxe', 'Occupation_Large Business', 'Designation_Executive', 'Designation_Senior Manager', 'TypeofContact_Self Enquiry', 'Occupation_Small Business', 'Designation_Manager', 'CityTier_2', 'ProductPitched_King'}).
              
              This happened while the csv dataset builder was generating data using
              
              hf://datasets/Divyap90/tourism_project_dataset/tourism.csv (at revision ea9f308876041ff8c737551786623fba7b794204)
              
              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	DurationOfPitch float64	Gender int64	NumberOfPersonVisiting float64	NumberOfFollowups float64	PreferredPropertyStar float64	NumberOfTrips float64	Passport int64	PitchSatisfactionScore float64	OwnCar int64	NumberOfChildrenVisiting float64	MonthlyIncome float64	TypeofContact_Self Enquiry bool	CityTier_2 bool	CityTier_3 bool	Occupation_Large Business bool	Occupation_Salaried bool	Occupation_Small Business bool	MaritalStatus_Married bool	MaritalStatus_Single bool	MaritalStatus_Unmarried bool	ProductPitched_Deluxe bool	ProductPitched_King bool	ProductPitched_Standard bool	ProductPitched_Super Deluxe bool	Designation_Executive bool	Designation_Manager bool	Designation_Senior Manager bool	Designation_VP bool
2,273	-0.352304	-0.784172	2	-1.320898	0.256768	-0.727718	0.379672	0	-1.512074	0	-1.435165	-1.15388	false	false	false	false	true	false	true	false	false	false	false	false	false	true	false	false	false
73	-0.570326	-1.141437	2	0.070443	-0.736612	0.530247	-0.69787	0	-0.044614	0	-1.435165	-0.434628	true	false	false	false	true	false	false	false	false	true	false	false	false	false	true	false	false
167	-0.788347	-0.545995	1	-1.320898	-0.736612	-0.727718	-0.159099	0	0.689116	1	-0.262256	0.275303	true	false	true	false	true	false	false	false	false	false	false	true	false	false	false	true	false
4,725	0.192749	-0.784172	2	0.070443	0.256768	0.530247	-0.69787	0	0.689116	1	0.910652	0.632599	true	false	true	false	false	true	false	false	true	false	false	true	false	false	false	true	false
4,219	-0.025272	1.835773	1	0.070443	0.256768	0.530247	-0.69787	0	-0.044614	1	0.910652	0.260435	false	false	false	false	true	false	true	false	false	true	false	false	false	false	true	false	false
2,620	-0.352304	-0.784172	2	0.070443	0.256768	-0.727718	-0.69787	0	-0.044614	0	0.910652	-0.443949	true	false	false	false	true	false	false	true	false	false	false	false	false	true	false	false	false
3,015	-1.115379	-1.022348	1	1.461785	2.243527	-0.727718	0.918443	0	0.689116	1	2.083561	-0.030285	false	false	false	false	true	false	true	false	false	false	false	false	false	true	false	false	false
1,106	-0.788347	-1.141437	2	0.070443	0.256768	1.788212	-0.69787	0	0.689116	1	-0.262256	0.340771	true	false	true	false	true	false	true	false	false	true	false	false	false	false	true	false	false
4,541	1.718899	1.954861	1	0.070443	1.250147	-0.727718	0.918443	0	1.422846	0	0.910652	2.06955	false	false	false	false	false	true	true	false	false	false	false	false	true	false	false	false	false
3,334	1.936921	-1.022348	1	0.070443	0.256768	-0.727718	-0.69787	0	1.422846	1	0.910652	1.331878	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	true	false
93	0.955824	-1.141437	2	-1.320898	0.256768	1.788212	-0.159099	1	-0.778344	1	-0.262256	0.553595	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	true	false
4,519	0.192749	0.406712	2	-1.320898	1.250147	1.788212	0.379672	0	1.422846	1	-0.262256	0.396695	false	false	false	false	true	false	true	false	false	true	false	false	false	false	true	false	false
112	1.82791	1.954861	1	-2.712239	-1.729992	-0.727718	-0.159099	1	-0.044614	1	-1.435165	2.030492	false	true	false	false	true	false	false	true	false	false	false	false	true	false	false	false	false
1,287	0.519782	0.406712	2	0.070443	-2.723372	1.788212	1.457214	0	0.689116	1	-1.435165	-0.58598	true	false	false	false	false	true	true	false	false	true	false	false	false	false	true	false	false
3,583	-0.461315	-0.426906	1	0.070443	-1.729992	-0.727718	0.918443	0	1.422846	1	0.910652	-0.263747	true	false	false	false	true	false	true	false	false	false	false	false	false	true	false	false	false
1,551	-0.243294	-1.141437	2	-2.712239	0.256768	-0.727718	-0.69787	0	0.689116	1	-1.435165	-1.180511	true	false	false	false	false	true	false	true	false	false	false	false	false	true	false	false	false
1,284	0.192749	0.049447	2	0.070443	-0.736612	-0.727718	-1.236642	0	-0.044614	1	-1.435165	1.172982	true	false	false	false	false	true	false	false	true	false	false	true	false	false	false	true	false
3,232	-0.897358	0.168535	1	0.070443	0.256768	-0.727718	0.918443	0	0.689116	1	0.910652	-0.186518	true	false	false	false	true	false	false	false	true	true	false	false	false	false	true	false	false
2,887	-1.551422	-0.545995	2	0.070443	1.250147	-0.727718	1.995985	0	1.422846	1	-0.262256	-0.134588	false	false	false	true	false	false	false	false	true	false	false	false	false	true	false	false	false
294	-0.025272	-0.069641	2	-1.320898	-0.736612	-0.727718	-0.69787	1	-0.778344	0	-1.435165	-1.298796	false	false	false	false	false	true	false	false	false	false	false	false	false	true	false	false	false
4,606	-0.461315	-0.665083	1	1.461785	0.256768	1.788212	-0.159099	0	-1.512074	1	-0.262256	0.493676	true	false	false	false	false	true	true	false	false	true	false	false	false	false	true	false	false
4,015	-0.461315	-1.022348	2	1.461785	0.256768	1.788212	-0.159099	0	-1.512074	0	0.910652	-0.342752	true	false	false	false	true	false	false	false	true	false	false	false	false	true	false	false	false
4,115	1.391867	1.121242	2	1.461785	0.256768	-0.727718	-0.159099	1	-1.512074	0	-0.262256	0.511207	false	false	false	false	true	false	true	false	false	true	false	false	false	false	true	false	false
2,067	0.519782	-1.141437	1	-1.320898	0.256768	-0.727718	-1.236642	1	-0.044614	0	-1.435165	-0.469692	true	false	false	false	true	false	true	false	false	true	false	false	false	false	true	false	false
4,801	0.628792	2.07395	1	0.070443	0.256768	1.788212	0.918443	1	-0.044614	0	-0.262256	1.928629	false	false	false	false	false	true	true	false	false	false	false	true	false	false	false	true	false
1,383	-0.134283	-0.069641	2	0.070443	-2.723372	0.530247	-0.69787	0	1.422846	1	-1.435165	-1.191385	false	false	false	false	true	false	true	false	false	false	false	false	false	true	false	false	false
1,350	-1.115379	-0.90326	1	-1.320898	-2.723372	-0.727718	-1.236642	0	-1.512074	0	-0.262256	-0.37249	true	false	true	false	false	true	false	false	true	true	false	false	false	false	true	false	false
4,288	-0.897358	0.049447	2	1.461785	0.256768	-0.727718	-0.159099	0	-0.044614	1	0.910652	0.167005	true	false	true	false	true	false	false	false	true	true	false	false	false	false	true	false	false
2,690	-0.352304	-0.426906	1	1.461785	1.250147	-0.727718	-0.159099	0	-0.778344	0	2.083561	-0.352739	true	false	false	false	true	false	false	false	false	false	false	false	false	true	false	false	false
3,576	0.410771	0.644889	1	0.070443	0.256768	1.788212	-0.159099	0	-0.044614	0	0.910652	0.030744	true	false	true	false	true	false	true	false	false	true	false	false	false	false	true	false	false
4,866	-0.570326	0.525801	2	1.461785	1.250147	1.788212	1.995985	1	-1.512074	1	-0.262256	-0.48789	true	false	true	false	false	true	true	false	false	true	false	false	false	false	true	false	false
1,947	1.391867	-0.784172	2	0.070443	-0.736612	0.530247	-0.69787	0	-1.512074	1	0.910652	2.224009	false	true	false	false	false	true	true	false	false	false	true	false	false	false	false	false	true
1,940	-1.442412	1.716684	2	-1.320898	-0.736612	-0.727718	-1.236642	0	0.689116	1	-0.262256	-1.282374	false	false	true	false	false	true	true	false	false	false	false	false	false	true	false	false	false
4,511	0.628792	-1.022348	1	0.070443	1.250147	-0.727718	-0.69787	1	-0.044614	0	-0.262256	0.346541	true	false	false	false	true	false	true	false	false	true	false	false	false	false	true	false	false
1,148	0.192749	0.049447	2	0.070443	-0.736612	1.788212	-0.159099	0	1.422846	1	0.910652	-0.621709	true	false	false	false	false	true	true	false	false	true	false	false	false	false	true	false	false
1,740	1.936921	-1.141437	2	-1.320898	-0.736612	1.788212	-1.236642	1	-1.512074	1	-0.262256	2.411534	true	false	false	false	false	true	false	true	false	false	true	false	false	false	false	false	true
4,849	-0.461315	-0.665083	0	0.070443	0.256768	-0.727718	-0.159099	0	0.689116	1	-0.262256	0.379163	false	false	false	false	true	false	false	false	true	false	false	false	false	true	false	false	false
3,699	-0.352304	0.883066	0	1.461785	0.256768	1.788212	0.379672	1	1.422846	0	-0.262256	0.901792	true	false	true	false	true	false	false	false	true	false	false	true	false	false	false	true	false
4,027	-1.333401	1.121242	2	0.070443	0.256768	-0.727718	-0.69787	0	0.689116	0	-0.262256	-0.383142	true	false	false	false	true	false	true	false	false	false	false	false	false	true	false	false	false
1,613	-0.788347	1.002154	1	0.070443	-0.736612	-0.727718	-0.69787	0	-1.512074	1	0.910652	-1.230888	true	false	false	false	true	false	false	true	false	false	false	false	false	true	false	false	false
4,206	-0.570326	-0.426906	1	0.070443	0.256768	0.530247	-0.159099	0	-0.044614	0	-0.262256	-0.379813	false	false	true	false	false	true	true	false	false	false	false	false	false	true	false	false	false
2,757	-0.352304	-0.426906	1	1.461785	0.256768	0.530247	2.534756	0	-0.044614	1	2.083561	1.637244	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	true	false
2,191	1.391867	1.716684	2	0.070443	-0.736612	-0.727718	0.379672	1	0.689116	1	0.910652	1.28594	true	false	false	false	true	false	true	false	false	false	false	false	true	false	false	false	false
673	-0.461315	-1.141437	2	0.070443	0.256768	1.788212	0.379672	1	0.689116	0	-1.435165	-1.193826	true	false	false	false	true	false	false	true	false	false	false	false	false	true	false	false	false
3,264	-0.134283	0.287624	2	0.070443	0.256768	-0.727718	-0.159099	0	1.422846	0	-0.262256	0.103757	false	false	true	false	false	true	true	false	false	true	false	false	false	false	true	false	false
2,645	1.391867	1.121242	2	1.461785	0.256768	-0.727718	-0.159099	1	-0.778344	0	0.910652	0.511207	false	false	false	false	true	false	true	false	false	true	false	false	false	false	true	false	false
3,648	1.282857	-0.18873	1	1.461785	0.256768	-0.727718	0.379672	1	0.689116	1	0.910652	-0.409551	false	false	true	false	false	true	true	false	false	false	false	false	false	true	false	false	false
3,412	-0.025272	-0.18873	1	0.070443	-1.729992	1.788212	0.379672	0	-1.512074	1	-0.262256	0.030744	false	false	true	false	false	true	false	false	false	true	false	false	false	false	true	false	false
143	-0.788347	1.002154	1	0.070443	-0.736612	-0.727718	-0.69787	0	-0.778344	1	-1.435165	-1.230888	true	false	false	false	true	false	false	true	false	false	false	false	false	true	false	false	false
3,867	-1.551422	-1.022348	2	1.461785	0.256768	-0.727718	-0.69787	0	-0.044614	0	2.083561	-0.249766	true	false	false	false	true	false	false	false	true	false	false	false	false	true	false	false	false
1,651	-0.352304	2.07395	1	0.070443	-0.736612	0.530247	-0.159099	0	-0.044614	0	-1.435165	-1.302125	true	false	false	false	false	true	false	true	false	false	false	false	false	true	false	false	false
4,005	1.609889	1.478508	2	1.461785	0.256768	-0.727718	-0.69787	1	1.422846	0	2.083561	0.208726	true	false	true	false	false	true	false	false	true	true	false	false	false	false	true	false	false
3,192	-1.115379	2.431215	2	1.461785	2.243527	1.788212	-0.69787	0	-0.044614	0	-0.262256	0.103979	false	false	true	false	false	true	false	false	true	true	false	false	false	false	true	false	false
706	0.30176	1.716684	0	0.070443	-2.723372	0.530247	0.918443	1	-0.044614	1	0.910652	1.113062	false	false	true	false	true	false	false	false	true	false	false	false	true	false	false	false	false
891	0.737803	-0.90326	1	0.070443	-2.723372	-0.727718	-0.69787	0	0.689116	1	-1.435165	-1.368702	true	false	false	false	true	false	false	false	false	false	false	false	false	true	false	false	false
4,676	-1.115379	-0.784172	2	0.070443	0.256768	1.788212	2.534756	1	1.422846	0	-0.262256	-0.54559	false	false	false	false	true	false	true	false	false	false	false	false	false	true	false	false	false
3,308	0.519782	-0.426906	2	1.461785	1.250147	1.788212	2.534756	0	-0.044614	1	-0.262256	-0.531165	false	false	false	false	true	false	true	false	false	false	false	false	false	true	false	false	false
2,939	-1.006369	-0.784172	2	0.070443	0.256768	1.788212	-0.69787	0	1.422846	0	0.910652	-0.323889	true	false	true	false	false	true	true	false	false	false	false	false	false	true	false	false	false
4,588	2.372964	-0.426906	1	0.070443	1.250147	0.530247	0.379672	1	1.422846	1	0.910652	1.342975	true	false	false	true	false	false	true	false	false	false	false	true	false	false	false	true	false
3,430	0.30176	1.478508	2	0.070443	1.250147	-0.727718	0.918443	1	-1.512074	0	0.910652	0.359412	true	false	true	false	true	false	false	false	false	true	false	false	false	false	true	false	false
3,767	-0.897358	-1.022348	2	0.070443	0.256768	-0.727718	-0.159099	0	0.689116	0	0.910652	-0.398233	false	true	false	false	true	false	true	false	false	false	false	false	false	true	false	false	false
3,004	-0.243294	-0.069641	1	0.070443	0.256768	1.788212	0.918443	0	1.422846	1	-0.262256	0.137711	true	false	false	false	true	false	true	false	false	true	false	false	false	false	true	false	false
1,039	-0.352304	-0.069641	1	-1.320898	-0.736612	-0.727718	-0.69787	0	-1.512074	1	-1.435165	-1.206476	true	true	false	true	false	false	false	false	false	false	false	false	false	true	false	false	false
1,018	-0.134283	-0.665083	2	-1.320898	0.256768	-0.727718	-0.69787	0	1.422846	1	-0.262256	-0.525617	true	false	false	false	true	false	false	true	false	true	false	false	false	false	true	false	false
147	0.410771	0.049447	2	0.070443	0.256768	1.788212	0.918443	0	-0.778344	1	-1.435165	1.997869	false	false	false	false	true	false	true	false	false	false	false	false	true	false	false	false	false
1,563	0.955824	-1.141437	2	-1.320898	0.256768	1.788212	-0.159099	1	-1.512074	1	-0.262256	0.553595	false	false	false	false	false	true	true	false	false	false	false	true	false	false	false	true	false
2,904	-1.115379	2.431215	2	0.070443	0.256768	-0.727718	1.995985	0	1.422846	1	-0.262256	-0.043156	true	false	true	false	false	true	true	false	false	true	false	false	false	false	true	false	false
4,732	-0.570326	1.359419	2	1.461785	-1.729992	-0.727718	-0.69787	0	1.422846	1	-0.262256	-0.379369	false	false	true	false	true	false	true	false	false	false	false	false	false	true	false	false	false
3,961	0.083739	1.240331	2	1.461785	0.256768	0.530247	1.457214	0	0.689116	0	0.910652	-0.328105	true	false	false	false	true	false	true	false	false	false	false	false	false	true	false	false	false
4,035	-0.352304	1.597596	2	1.461785	0.256768	0.530247	-0.69787	0	-1.512074	0	-0.262256	0.365182	false	false	true	false	false	true	true	false	false	true	false	false	false	false	true	false	false
962	1.500878	-0.545995	2	-1.320898	-0.736612	0.530247	-0.69787	1	-0.044614	1	-0.262256	1.297702	true	true	false	false	true	false	true	false	false	false	false	false	true	false	false	false	false
553	0.30176	-0.90326	1	-1.320898	0.256768	-0.727718	-1.236642	1	-0.044614	1	-0.262256	-1.295245	true	false	false	false	false	true	false	true	false	false	false	false	false	true	false	false	false
1,845	1.282857	-0.307818	2	-1.320898	0.256768	-0.727718	-1.236642	0	-1.512074	1	-1.435165	0.618396	true	false	false	false	true	false	false	false	true	false	false	true	false	false	false	true	false
3,765	1.173846	0.049447	1	1.461785	0.256768	-0.727718	1.457214	0	-0.044614	1	-0.262256	-0.531608	true	false	false	false	true	false	false	true	false	false	false	false	false	true	false	false	false
1,724	-0.897358	1.240331	2	-1.320898	-0.736612	-0.727718	-0.159099	0	-1.512074	1	-1.435165	-0.276841	true	false	true	false	false	true	true	false	false	true	false	false	false	false	true	false	false
4,384	-1.333401	1.835773	2	0.070443	0.256768	-0.727718	-0.69787	0	0.689116	1	0.910652	-0.466141	false	false	true	false	false	true	true	false	false	false	false	false	false	true	false	false	false
2,340	-0.243294	0.883066	2	0.070443	-0.736612	1.788212	0.379672	1	-0.044614	0	0.910652	0.174772	true	false	true	false	true	false	true	false	false	true	false	false	false	false	true	false	false
4,257	-0.788347	0.168535	1	0.070443	1.250147	0.530247	-0.159099	1	1.422846	1	-0.262256	0.836103	true	false	true	false	false	true	true	false	false	true	false	false	false	false	true	false	false
1,662	-0.243294	1.597596	2	-1.320898	0.256768	-0.727718	0.379672	1	0.689116	1	-1.435165	-0.502093	true	false	false	false	true	false	true	false	false	true	false	false	false	false	true	false	false
1,847	-0.134283	-0.90326	1	0.070443	-0.736612	-0.727718	0.918443	0	1.422846	1	-1.435165	-1.250639	true	false	false	false	true	false	true	false	false	false	false	false	false	true	false	false	false
1,126	1.391867	-1.260525	2	-1.320898	-0.736612	-0.727718	0.918443	1	1.422846	0	-0.262256	2.475003	true	false	true	false	false	true	true	false	false	false	true	false	false	false	false	false	true
4,689	0.737803	1.954861	2	1.461785	1.250147	-0.727718	1.995985	0	0.689116	1	0.910652	1.397568	true	false	true	false	false	true	true	false	false	false	false	true	false	false	false	true	false
811	0.083739	-0.90326	2	-1.320898	-0.736612	0.530247	-1.236642	0	0.689116	1	-1.435165	-0.183633	true	false	true	false	false	true	false	false	true	false	false	true	false	false	false	true	false
3,624	-0.025272	-0.18873	2	1.461785	0.256768	0.530247	0.379672	0	-1.512074	0	2.083561	-0.552025	true	false	false	false	true	false	false	true	false	false	false	false	false	true	false	false	false
2,754	-0.570326	-0.784172	2	1.461785	1.250147	1.788212	0.918443	0	-0.044614	0	0.910652	0.42377	true	true	false	false	true	false	false	false	false	true	false	false	false	false	true	false	false
2,890	0.519782	0.168535	2	0.070443	0.256768	-0.727718	-0.69787	0	-0.778344	0	0.910652	0.383824	false	false	true	false	true	false	false	false	true	true	false	false	false	false	true	false	false
523	1.391867	2.193038	2	0.070443	-1.729992	-0.727718	-0.69787	1	-0.778344	1	0.910652	-1.100175	true	false	false	false	false	true	false	false	false	false	false	false	false	true	false	false	false
4,393	-1.333401	-0.18873	1	0.070443	0.256768	-0.727718	-0.159099	1	0.689116	0	-0.262256	-0.358287	false	false	false	false	true	false	true	false	false	false	false	false	false	true	false	false	false
853	-1.987465	-0.069641	2	-1.320898	-0.736612	1.788212	-0.69787	0	-0.044614	0	-1.435165	-1.248641	true	false	false	false	true	false	false	true	false	false	false	false	false	true	false	false	false
4,598	0.410771	0.168535	2	1.461785	1.250147	0.530247	0.379672	0	0.689116	0	-0.262256	1.155006	true	false	true	false	false	true	true	false	false	false	false	true	false	false	false	true	false
2,909	1.064835	1.121242	1	0.070443	0.256768	-0.727718	1.995985	0	-0.044614	1	-0.262256	1.337427	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	true	false
3,123	-0.570326	1.359419	1	0.070443	0.256768	-0.727718	-0.159099	0	-0.778344	1	-0.262256	0.539614	false	false	true	false	false	true	false	false	false	true	false	false	false	false	true	false	false
750	0.737803	2.193038	1	-1.320898	-2.723372	-0.727718	0.379672	1	-0.778344	1	-0.262256	1.141025	true	false	true	false	false	true	false	false	false	false	false	false	true	false	false	false	false
2,983	1.500878	-0.069641	2	0.070443	0.256768	0.530247	-0.69787	0	-0.778344	1	-0.262256	-0.138805	true	false	true	false	false	true	false	false	false	false	false	false	false	true	false	false	false
2,325	-0.025272	-1.022348	1	-1.320898	0.256768	-0.727718	-0.69787	0	-1.512074	0	-1.435165	-0.37826	true	false	false	false	true	false	true	false	false	true	false	false	false	false	true	false	false
3,552	-0.134283	-1.022348	2	1.461785	1.250147	1.788212	-0.159099	0	-1.512074	0	2.083561	-0.455045	true	false	false	false	false	true	false	true	false	false	false	false	false	true	false	false	false
2,780	-0.788347	-0.069641	2	1.461785	2.243527	1.788212	-0.159099	1	-0.044614	1	0.910652	-0.528502	true	false	false	false	true	false	false	false	false	false	false	false	false	true	false	false	false
4,586	0.628792	0.644889	0	1.461785	1.250147	-0.727718	-0.69787	0	-0.044614	1	-0.262256	0.386931	true	false	true	false	false	true	false	false	true	true	false	false	false	false	true	false	false
4,234	-1.006369	-0.784172	2	1.461785	0.256768	-0.727718	-0.159099	1	0.689116	0	0.910652	-0.004985	true	false	true	false	true	false	false	false	true	true	false	false	false	false	true	false	false
4,176	-0.461315	-0.784172	2	0.070443	1.250147	1.788212	1.457214	0	0.689116	0	0.910652	-0.515852	true	false	false	true	false	false	false	true	false	true	false	false	false	false	true	false	false

End of preview.

No dataset card yet

Downloads last month: 143

Datasets:

Divyap90
/

tourism_project_dataset

Space using Divyap90/tourism_project_dataset 1