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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 ({'9', '5', '17', '20', '7', '22', '4', '13', '6', '18', '16', '3', '8', '19', '21', '14', '1', '23', '0', '2', '11', '10', '12', '15'}) and 25 missing columns ({'Teenhome', 'NumWebVisitsMonth', 'NumCatalogPurchases', 'AcceptedCmp1', 'MntFruits', 'AcceptedCmp2', 'target', 'Income', 'MntMeatProducts', 'Education', 'NumStorePurchases', 'NumDealsPurchases', 'MntGoldProds', 'AcceptedCmp5', 'AcceptedCmp4', 'Age', 'AcceptedCmp3', 'Kidhome', 'MntWines', 'MntFishProducts', 'Recency', 'MntSweetProducts', 'Complain', 'NumWebPurchases', 'Marital_Status'}). This happened while the csv dataset builder was generating data using hf://datasets/synavate/medical_records_did/verida-differential-privacy/data/processed/PII_Customer_Personality_Analysis/data/2024_08_25_PII_Customer_Personality_Analysis_v0.1.csv (at revision ab59a830b1ada14892570e7b92c399557f9d5dcc) 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 2013, in _prepare_split_single writer.write_table(table) File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/arrow_writer.py", line 585, 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 2302, in table_cast return cast_table_to_schema(table, schema) File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2256, in cast_table_to_schema raise CastError( datasets.table.CastError: Couldn't cast Unnamed: 0: int64 0: double 1: double 2: double 3: double 4: double 5: double 6: double 7: double 8: double 9: double 10: double 11: double 12: double 13: double 14: double 15: double 16: double 17: double 18: double 19: double 20: double 21: double 22: double 23: double -- schema metadata -- pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 2879 to {'Unnamed: 0': Value(dtype='string', id=None), 'Education': Value(dtype='float64', id=None), 'Marital_Status': Value(dtype='float64', id=None), 'Income': Value(dtype='float64', id=None), 'Kidhome': Value(dtype='float64', id=None), 'Teenhome': Value(dtype='float64', id=None), 'Recency': Value(dtype='float64', id=None), 'MntWines': Value(dtype='float64', id=None), 'MntFruits': Value(dtype='float64', id=None), 'MntMeatProducts': Value(dtype='float64', id=None), 'MntFishProducts': Value(dtype='float64', id=None), 'MntSweetProducts': Value(dtype='float64', id=None), 'MntGoldProds': Value(dtype='float64', id=None), 'NumDealsPurchases': Value(dtype='float64', id=None), 'NumWebPurchases': Value(dtype='float64', id=None), 'NumCatalogPurchases': Value(dtype='float64', id=None), 'NumStorePurchases': Value(dtype='float64', id=None), 'NumWebVisitsMonth': Value(dtype='float64', id=None), 'AcceptedCmp3': Value(dtype='float64', id=None), 'AcceptedCmp4': Value(dtype='float64', id=None), 'AcceptedCmp5': Value(dtype='float64', id=None), 'AcceptedCmp1': Value(dtype='float64', id=None), 'AcceptedCmp2': Value(dtype='float64', id=None), 'Complain': Value(dtype='float64', id=None), 'target': Value(dtype='float64', id=None), 'Age': Value(dtype='float64', id=None)} 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 1529, 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 1154, in convert_to_parquet builder.download_and_prepare( File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1029, in download_and_prepare self._download_and_prepare( File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1124, 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 1884, 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 2015, 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 ({'9', '5', '17', '20', '7', '22', '4', '13', '6', '18', '16', '3', '8', '19', '21', '14', '1', '23', '0', '2', '11', '10', '12', '15'}) and 25 missing columns ({'Teenhome', 'NumWebVisitsMonth', 'NumCatalogPurchases', 'AcceptedCmp1', 'MntFruits', 'AcceptedCmp2', 'target', 'Income', 'MntMeatProducts', 'Education', 'NumStorePurchases', 'NumDealsPurchases', 'MntGoldProds', 'AcceptedCmp5', 'AcceptedCmp4', 'Age', 'AcceptedCmp3', 'Kidhome', 'MntWines', 'MntFishProducts', 'Recency', 'MntSweetProducts', 'Complain', 'NumWebPurchases', 'Marital_Status'}). This happened while the csv dataset builder was generating data using hf://datasets/synavate/medical_records_did/verida-differential-privacy/data/processed/PII_Customer_Personality_Analysis/data/2024_08_25_PII_Customer_Personality_Analysis_v0.1.csv (at revision ab59a830b1ada14892570e7b92c399557f9d5dcc) 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)
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Unnamed: 0
string | Education
float64 | Marital_Status
float64 | Income
float64 | Kidhome
float64 | Teenhome
float64 | Recency
float64 | MntWines
float64 | MntFruits
float64 | MntMeatProducts
float64 | MntFishProducts
float64 | MntSweetProducts
float64 | MntGoldProds
float64 | NumDealsPurchases
float64 | NumWebPurchases
float64 | NumCatalogPurchases
float64 | NumStorePurchases
float64 | NumWebVisitsMonth
float64 | AcceptedCmp3
float64 | AcceptedCmp4
float64 | AcceptedCmp5
float64 | AcceptedCmp1
float64 | AcceptedCmp2
float64 | Complain
float64 | target
float64 | Age
float64 |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Education | 1 | 0.006011 | 0.120692 | -0.04539 | 0.120128 | -0.011418 | 0.197886 | -0.082462 | 0.039961 | -0.114747 | -0.107279 | -0.097084 | 0.026208 | 0.082425 | 0.069049 | 0.067792 | -0.040822 | 0.005823 | 0.058885 | 0.032669 | -0.009741 | 0.021477 | -0.050863 | 0.090806 | 0.171065 |
Marital_Status | 0.006011 | 1 | 0.021353 | -0.021718 | -0.003243 | 0.011138 | 0.009229 | 0.000559 | 0.02781 | 0.034208 | 0.015651 | 0.000897 | -0.019294 | 0.000118 | 0.014931 | 0.002603 | -0.026658 | -0.026234 | 0.014274 | 0.010256 | -0.015569 | 0.018909 | -0.005394 | -0.012641 | 0.058229 |
Income | 0.120692 | 0.021353 | 1 | -0.428669 | 0.019133 | -0.00397 | 0.57865 | 0.430842 | 0.584633 | 0.438871 | 0.440744 | 0.325916 | -0.083101 | 0.387878 | 0.589162 | 0.529362 | -0.553088 | -0.016174 | 0.1844 | 0.335943 | 0.27682 | 0.087545 | -0.027225 | 0.133047 | 0.161791 |
Kidhome | -0.04539 | -0.021718 | -0.428669 | 1 | -0.039869 | 0.011492 | -0.497336 | -0.373396 | -0.439261 | -0.388884 | -0.378026 | -0.355029 | 0.216913 | -0.371977 | -0.504501 | -0.501349 | 0.447477 | 0.016066 | -0.162026 | -0.205305 | -0.174163 | -0.081868 | 0.040978 | -0.077909 | -0.233615 |
Teenhome | 0.120128 | -0.003243 | 0.019133 | -0.039869 | 1 | 0.013838 | 0.003747 | -0.176558 | -0.261122 | -0.205242 | -0.163056 | -0.019887 | 0.386246 | 0.162077 | -0.112692 | 0.049737 | 0.13124 | -0.042522 | 0.038376 | -0.190791 | -0.144855 | -0.015521 | 0.003307 | -0.153901 | 0.350791 |
Recency | -0.011418 | 0.011138 | -0.00397 | 0.011492 | 0.013838 | 1 | 0.015721 | -0.005844 | 0.022518 | 0.000551 | 0.02511 | 0.017663 | 0.002115 | -0.005641 | 0.024081 | -0.000434 | -0.018564 | -0.032257 | 0.017566 | -0.000482 | -0.021061 | -0.0014 | 0.013637 | -0.199766 | 0.016295 |
MntWines | 0.197886 | 0.009229 | 0.57865 | -0.497336 | 0.003747 | 0.015721 | 1 | 0.387024 | 0.56886 | 0.397721 | 0.390326 | 0.392731 | 0.008886 | 0.553786 | 0.634753 | 0.640012 | -0.321978 | 0.061463 | 0.373143 | 0.47355 | 0.351417 | 0.206185 | -0.03947 | 0.246299 | 0.159451 |
MntFruits | -0.082462 | 0.000559 | 0.430842 | -0.373396 | -0.176558 | -0.005844 | 0.387024 | 1 | 0.547822 | 0.593431 | 0.571606 | 0.396487 | -0.134512 | 0.302039 | 0.486263 | 0.458491 | -0.418729 | 0.014424 | 0.006396 | 0.212871 | 0.191816 | -0.00998 | -0.005324 | 0.122443 | 0.017747 |
MntMeatProducts | 0.039961 | 0.02781 | 0.584633 | -0.439261 | -0.261122 | 0.022518 | 0.56886 | 0.547822 | 1 | 0.573574 | 0.535136 | 0.359446 | -0.121308 | 0.30709 | 0.734127 | 0.486006 | -0.539484 | 0.018438 | 0.091618 | 0.376867 | 0.313076 | 0.043521 | -0.023782 | 0.237746 | 0.033697 |
MntFishProducts | -0.114747 | 0.034208 | 0.438871 | -0.388884 | -0.205242 | 0.000551 | 0.397721 | 0.593431 | 0.573574 | 1 | 0.583867 | 0.427142 | -0.143241 | 0.299688 | 0.532757 | 0.457745 | -0.446423 | -0.000219 | 0.016105 | 0.196277 | 0.261608 | 0.002345 | -0.02122 | 0.108145 | 0.040425 |
MntSweetProducts | -0.107279 | 0.015651 | 0.440744 | -0.378026 | -0.163056 | 0.02511 | 0.390326 | 0.571606 | 0.535136 | 0.583867 | 1 | 0.35745 | -0.121432 | 0.333937 | 0.495136 | 0.455225 | -0.422371 | 0.00178 | 0.029313 | 0.25923 | 0.245102 | 0.010188 | -0.022641 | 0.11617 | 0.020204 |
MntGoldProds | -0.097084 | 0.000897 | 0.325916 | -0.355029 | -0.019887 | 0.017663 | 0.392731 | 0.396487 | 0.359446 | 0.427142 | 0.35745 | 1 | 0.051905 | 0.407066 | 0.442428 | 0.38918 | -0.247691 | 0.124958 | 0.024015 | 0.181397 | 0.170132 | 0.050734 | -0.031133 | 0.140332 | 0.064208 |
NumDealsPurchases | 0.026208 | -0.019294 | -0.083101 | 0.216913 | 0.386246 | 0.002115 | 0.008886 | -0.134512 | -0.121308 | -0.143241 | -0.121432 | 0.051905 | 1 | 0.24144 | -0.012118 | 0.066107 | 0.346048 | -0.023135 | 0.016077 | -0.184253 | -0.127374 | -0.037981 | 0.000497 | 0.003451 | 0.058668 |
NumWebPurchases | 0.082425 | 0.000118 | 0.387878 | -0.371977 | 0.162077 | -0.005641 | 0.553786 | 0.302039 | 0.30709 | 0.299688 | 0.333937 | 0.407066 | 0.24144 | 1 | 0.386868 | 0.51624 | -0.051226 | 0.042958 | 0.162932 | 0.141189 | 0.159292 | 0.034829 | -0.016642 | 0.151431 | 0.153051 |
NumCatalogPurchases | 0.069049 | 0.014931 | 0.589162 | -0.504501 | -0.112692 | 0.024081 | 0.634753 | 0.486263 | 0.734127 | 0.532757 | 0.495136 | 0.442428 | -0.012118 | 0.386868 | 1 | 0.51784 | -0.522004 | 0.104345 | 0.140182 | 0.322471 | 0.309026 | 0.099915 | -0.020839 | 0.219914 | 0.121764 |
NumStorePurchases | 0.067792 | 0.002603 | 0.529362 | -0.501349 | 0.049737 | -0.000434 | 0.640012 | 0.458491 | 0.486006 | 0.457745 | 0.455225 | 0.38918 | 0.066107 | 0.51624 | 0.51784 | 1 | -0.432398 | -0.068913 | 0.17802 | 0.212954 | 0.178743 | 0.085271 | -0.016941 | 0.036241 | 0.127891 |
NumWebVisitsMonth | -0.040822 | -0.026658 | -0.553088 | 0.447477 | 0.13124 | -0.018564 | -0.321978 | -0.418729 | -0.539484 | -0.446423 | -0.422371 | -0.247691 | 0.346048 | -0.051226 | -0.522004 | -0.432398 | 1 | 0.061307 | -0.028666 | -0.277883 | -0.194773 | -0.007362 | 0.019785 | -0.002209 | -0.123904 |
AcceptedCmp3 | 0.005823 | -0.026234 | -0.016174 | 0.016066 | -0.042522 | -0.032257 | 0.061463 | 0.014424 | 0.018438 | -0.000219 | 0.00178 | 0.124958 | -0.023135 | 0.042958 | 0.104345 | -0.068913 | 0.061307 | 1 | -0.079659 | 0.080248 | 0.095683 | 0.071702 | 0.008124 | 0.254005 | -0.061784 |
AcceptedCmp4 | 0.058885 | 0.014274 | 0.1844 | -0.162026 | 0.038376 | 0.017566 | 0.373143 | 0.006396 | 0.091618 | 0.016105 | 0.029313 | 0.024015 | 0.016077 | 0.162932 | 0.140182 | 0.17802 | -0.028666 | -0.079659 | 1 | 0.311314 | 0.242782 | 0.29505 | -0.027652 | 0.180205 | 0.066109 |
AcceptedCmp5 | 0.032669 | 0.010256 | 0.335943 | -0.205305 | -0.190791 | -0.000482 | 0.47355 | 0.212871 | 0.376867 | 0.196277 | 0.25923 | 0.181397 | -0.184253 | 0.141189 | 0.322471 | 0.212954 | -0.277883 | 0.080248 | 0.311314 | 1 | 0.407878 | 0.222121 | -0.009576 | 0.323374 | -0.010575 |
AcceptedCmp1 | -0.009741 | -0.015569 | 0.27682 | -0.174163 | -0.144855 | -0.021061 | 0.351417 | 0.191816 | 0.313076 | 0.261608 | 0.245102 | 0.170132 | -0.127374 | 0.159292 | 0.309026 | 0.178743 | -0.194773 | 0.095683 | 0.242782 | 0.407878 | 1 | 0.176637 | -0.025594 | 0.297345 | 0.009611 |
AcceptedCmp2 | 0.021477 | 0.018909 | 0.087545 | -0.081868 | -0.015521 | -0.0014 | 0.206185 | -0.00998 | 0.043521 | 0.002345 | 0.010188 | 0.050734 | -0.037981 | 0.034829 | 0.099915 | 0.085271 | -0.007362 | 0.071702 | 0.29505 | 0.222121 | 0.176637 | 1 | -0.011459 | 0.169294 | 0.006717 |
Complain | -0.050863 | -0.005394 | -0.027225 | 0.040978 | 0.003307 | 0.013637 | -0.03947 | -0.005324 | -0.023782 | -0.02122 | -0.022641 | -0.031133 | 0.000497 | -0.016642 | -0.020839 | -0.016941 | 0.019785 | 0.008124 | -0.027652 | -0.009576 | -0.025594 | -0.011459 | 1 | -0.002029 | 0.030407 |
target | 0.090806 | -0.012641 | 0.133047 | -0.077909 | -0.153901 | -0.199766 | 0.246299 | 0.122443 | 0.237746 | 0.108145 | 0.11617 | 0.140332 | 0.003451 | 0.151431 | 0.219914 | 0.036241 | -0.002209 | 0.254005 | 0.180205 | 0.323374 | 0.297345 | 0.169294 | -0.002029 | 1 | -0.023692 |
Age | 0.171065 | 0.058229 | 0.161791 | -0.233615 | 0.350791 | 0.016295 | 0.159451 | 0.017747 | 0.033697 | 0.040425 | 0.020204 | 0.064208 | 0.058668 | 0.153051 | 0.121764 | 0.127891 | -0.123904 | -0.061784 | 0.066109 | -0.010575 | 0.009611 | 0.006717 | 0.030407 | -0.023692 | 1 |
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70 | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null |
71 | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null |
72 | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null |
73 | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null |
74 | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null | null |
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