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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 9 new columns ({'Longitude', 'MedInc', 'Population', 'AveOccup', 'Latitude', 'AveRooms', 'HouseAge', 'MedHouseVal', 'AveBedrms'}) and 15 missing columns ({'education', 'age', 'capital-loss', 'race', 'capital-gain', 'income', 'occupation', 'fnlwgt', 'workclass', 'relationship', 'hours-per-week', 'native-country', 'sex', 'education-num', 'marital-status'}).
This happened while the csv dataset builder was generating data using
hf://datasets/ivopersus/LeakProTabular/regression/california_housing.csv (at revision 3f7efd23638118d4afcab18956323f9a0486dace), [/tmp/hf-datasets-cache/medium/datasets/30669423901681-config-parquet-and-info-ivopersus-LeakProTabular-be67b3b3/hub/datasets--ivopersus--LeakProTabular/snapshots/3f7efd23638118d4afcab18956323f9a0486dace/binary/adult/adult.csv (origin=hf://datasets/ivopersus/LeakProTabular@3f7efd23638118d4afcab18956323f9a0486dace/binary/adult/adult.csv), /tmp/hf-datasets-cache/medium/datasets/30669423901681-config-parquet-and-info-ivopersus-LeakProTabular-be67b3b3/hub/datasets--ivopersus--LeakProTabular/snapshots/3f7efd23638118d4afcab18956323f9a0486dace/regression/california_housing.csv (origin=hf://datasets/ivopersus/LeakProTabular@3f7efd23638118d4afcab18956323f9a0486dace/regression/california_housing.csv)]
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 1800, in _prepare_split_single
writer.write_table(table)
File "/usr/local/lib/python3.12/site-packages/datasets/arrow_writer.py", line 765, in write_table
self._write_table(pa_table, writer_batch_size=writer_batch_size)
File "/usr/local/lib/python3.12/site-packages/datasets/arrow_writer.py", line 773, in _write_table
pa_table = table_cast(pa_table, self._schema)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2321, in table_cast
return cast_table_to_schema(table, schema)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2249, in cast_table_to_schema
raise CastError(
datasets.table.CastError: Couldn't cast
MedInc: double
HouseAge: double
AveRooms: double
AveBedrms: double
Population: double
AveOccup: double
Latitude: double
Longitude: double
MedHouseVal: double
-- schema metadata --
pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 1326
to
{'age': Value('int64'), 'workclass': Value('string'), 'fnlwgt': Value('int64'), 'education': Value('string'), 'education-num': Value('int64'), 'marital-status': Value('string'), 'occupation': Value('string'), 'relationship': Value('string'), 'race': Value('string'), 'sex': Value('string'), 'capital-gain': Value('int64'), 'capital-loss': Value('int64'), 'hours-per-week': Value('int64'), 'native-country': Value('string'), 'income': Value('string')}
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 1348, 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 980, in convert_to_parquet
builder.download_and_prepare(
File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 882, in download_and_prepare
self._download_and_prepare(
File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 943, in _download_and_prepare
self._prepare_split(split_generator, **prepare_split_kwargs)
File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1646, 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 1802, 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 9 new columns ({'Longitude', 'MedInc', 'Population', 'AveOccup', 'Latitude', 'AveRooms', 'HouseAge', 'MedHouseVal', 'AveBedrms'}) and 15 missing columns ({'education', 'age', 'capital-loss', 'race', 'capital-gain', 'income', 'occupation', 'fnlwgt', 'workclass', 'relationship', 'hours-per-week', 'native-country', 'sex', 'education-num', 'marital-status'}).
This happened while the csv dataset builder was generating data using
hf://datasets/ivopersus/LeakProTabular/regression/california_housing.csv (at revision 3f7efd23638118d4afcab18956323f9a0486dace), [/tmp/hf-datasets-cache/medium/datasets/30669423901681-config-parquet-and-info-ivopersus-LeakProTabular-be67b3b3/hub/datasets--ivopersus--LeakProTabular/snapshots/3f7efd23638118d4afcab18956323f9a0486dace/binary/adult/adult.csv (origin=hf://datasets/ivopersus/LeakProTabular@3f7efd23638118d4afcab18956323f9a0486dace/binary/adult/adult.csv), /tmp/hf-datasets-cache/medium/datasets/30669423901681-config-parquet-and-info-ivopersus-LeakProTabular-be67b3b3/hub/datasets--ivopersus--LeakProTabular/snapshots/3f7efd23638118d4afcab18956323f9a0486dace/regression/california_housing.csv (origin=hf://datasets/ivopersus/LeakProTabular@3f7efd23638118d4afcab18956323f9a0486dace/regression/california_housing.csv)]
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 int64 | workclass string | fnlwgt int64 | education string | education-num int64 | marital-status string | occupation string | relationship string | race string | sex string | capital-gain int64 | capital-loss int64 | hours-per-week int64 | native-country string | income string |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
39 | State-gov | 77,516 | Bachelors | 13 | Never-married | Adm-clerical | Not-in-family | White | Male | 2,174 | 0 | 40 | United-States | <=50K |
50 | Self-emp-not-inc | 83,311 | Bachelors | 13 | Married-civ-spouse | Exec-managerial | Husband | White | Male | 0 | 0 | 13 | United-States | <=50K |
38 | Private | 215,646 | HS-grad | 9 | Divorced | Handlers-cleaners | Not-in-family | White | Male | 0 | 0 | 40 | United-States | <=50K |
53 | Private | 234,721 | 11th | 7 | Married-civ-spouse | Handlers-cleaners | Husband | Black | Male | 0 | 0 | 40 | United-States | <=50K |
28 | Private | 338,409 | Bachelors | 13 | Married-civ-spouse | Prof-specialty | Wife | Black | Female | 0 | 0 | 40 | Cuba | <=50K |
37 | Private | 284,582 | Masters | 14 | Married-civ-spouse | Exec-managerial | Wife | White | Female | 0 | 0 | 40 | United-States | <=50K |
49 | Private | 160,187 | 9th | 5 | Married-spouse-absent | Other-service | Not-in-family | Black | Female | 0 | 0 | 16 | Jamaica | <=50K |
52 | Self-emp-not-inc | 209,642 | HS-grad | 9 | Married-civ-spouse | Exec-managerial | Husband | White | Male | 0 | 0 | 45 | United-States | >50K |
31 | Private | 45,781 | Masters | 14 | Never-married | Prof-specialty | Not-in-family | White | Female | 14,084 | 0 | 50 | United-States | >50K |
42 | Private | 159,449 | Bachelors | 13 | Married-civ-spouse | Exec-managerial | Husband | White | Male | 5,178 | 0 | 40 | United-States | >50K |
37 | Private | 280,464 | Some-college | 10 | Married-civ-spouse | Exec-managerial | Husband | Black | Male | 0 | 0 | 80 | United-States | >50K |
30 | State-gov | 141,297 | Bachelors | 13 | Married-civ-spouse | Prof-specialty | Husband | Asian-Pac-Islander | Male | 0 | 0 | 40 | India | >50K |
23 | Private | 122,272 | Bachelors | 13 | Never-married | Adm-clerical | Own-child | White | Female | 0 | 0 | 30 | United-States | <=50K |
32 | Private | 205,019 | Assoc-acdm | 12 | Never-married | Sales | Not-in-family | Black | Male | 0 | 0 | 50 | United-States | <=50K |
40 | Private | 121,772 | Assoc-voc | 11 | Married-civ-spouse | Craft-repair | Husband | Asian-Pac-Islander | Male | 0 | 0 | 40 | ? | >50K |
34 | Private | 245,487 | 7th-8th | 4 | Married-civ-spouse | Transport-moving | Husband | Amer-Indian-Eskimo | Male | 0 | 0 | 45 | Mexico | <=50K |
25 | Self-emp-not-inc | 176,756 | HS-grad | 9 | Never-married | Farming-fishing | Own-child | White | Male | 0 | 0 | 35 | United-States | <=50K |
32 | Private | 186,824 | HS-grad | 9 | Never-married | Machine-op-inspct | Unmarried | White | Male | 0 | 0 | 40 | United-States | <=50K |
38 | Private | 28,887 | 11th | 7 | Married-civ-spouse | Sales | Husband | White | Male | 0 | 0 | 50 | United-States | <=50K |
43 | Self-emp-not-inc | 292,175 | Masters | 14 | Divorced | Exec-managerial | Unmarried | White | Female | 0 | 0 | 45 | United-States | >50K |
40 | Private | 193,524 | Doctorate | 16 | Married-civ-spouse | Prof-specialty | Husband | White | Male | 0 | 0 | 60 | United-States | >50K |
54 | Private | 302,146 | HS-grad | 9 | Separated | Other-service | Unmarried | Black | Female | 0 | 0 | 20 | United-States | <=50K |
35 | Federal-gov | 76,845 | 9th | 5 | Married-civ-spouse | Farming-fishing | Husband | Black | Male | 0 | 0 | 40 | United-States | <=50K |
43 | Private | 117,037 | 11th | 7 | Married-civ-spouse | Transport-moving | Husband | White | Male | 0 | 2,042 | 40 | United-States | <=50K |
59 | Private | 109,015 | HS-grad | 9 | Divorced | Tech-support | Unmarried | White | Female | 0 | 0 | 40 | United-States | <=50K |
56 | Local-gov | 216,851 | Bachelors | 13 | Married-civ-spouse | Tech-support | Husband | White | Male | 0 | 0 | 40 | United-States | >50K |
19 | Private | 168,294 | HS-grad | 9 | Never-married | Craft-repair | Own-child | White | Male | 0 | 0 | 40 | United-States | <=50K |
54 | ? | 180,211 | Some-college | 10 | Married-civ-spouse | ? | Husband | Asian-Pac-Islander | Male | 0 | 0 | 60 | South | >50K |
39 | Private | 367,260 | HS-grad | 9 | Divorced | Exec-managerial | Not-in-family | White | Male | 0 | 0 | 80 | United-States | <=50K |
49 | Private | 193,366 | HS-grad | 9 | Married-civ-spouse | Craft-repair | Husband | White | Male | 0 | 0 | 40 | United-States | <=50K |
23 | Local-gov | 190,709 | Assoc-acdm | 12 | Never-married | Protective-serv | Not-in-family | White | Male | 0 | 0 | 52 | United-States | <=50K |
20 | Private | 266,015 | Some-college | 10 | Never-married | Sales | Own-child | Black | Male | 0 | 0 | 44 | United-States | <=50K |
45 | Private | 386,940 | Bachelors | 13 | Divorced | Exec-managerial | Own-child | White | Male | 0 | 1,408 | 40 | United-States | <=50K |
30 | Federal-gov | 59,951 | Some-college | 10 | Married-civ-spouse | Adm-clerical | Own-child | White | Male | 0 | 0 | 40 | United-States | <=50K |
22 | State-gov | 311,512 | Some-college | 10 | Married-civ-spouse | Other-service | Husband | Black | Male | 0 | 0 | 15 | United-States | <=50K |
48 | Private | 242,406 | 11th | 7 | Never-married | Machine-op-inspct | Unmarried | White | Male | 0 | 0 | 40 | Puerto-Rico | <=50K |
21 | Private | 197,200 | Some-college | 10 | Never-married | Machine-op-inspct | Own-child | White | Male | 0 | 0 | 40 | United-States | <=50K |
19 | Private | 544,091 | HS-grad | 9 | Married-AF-spouse | Adm-clerical | Wife | White | Female | 0 | 0 | 25 | United-States | <=50K |
31 | Private | 84,154 | Some-college | 10 | Married-civ-spouse | Sales | Husband | White | Male | 0 | 0 | 38 | ? | >50K |
48 | Self-emp-not-inc | 265,477 | Assoc-acdm | 12 | Married-civ-spouse | Prof-specialty | Husband | White | Male | 0 | 0 | 40 | United-States | <=50K |
31 | Private | 507,875 | 9th | 5 | Married-civ-spouse | Machine-op-inspct | Husband | White | Male | 0 | 0 | 43 | United-States | <=50K |
53 | Self-emp-not-inc | 88,506 | Bachelors | 13 | Married-civ-spouse | Prof-specialty | Husband | White | Male | 0 | 0 | 40 | United-States | <=50K |
24 | Private | 172,987 | Bachelors | 13 | Married-civ-spouse | Tech-support | Husband | White | Male | 0 | 0 | 50 | United-States | <=50K |
49 | Private | 94,638 | HS-grad | 9 | Separated | Adm-clerical | Unmarried | White | Female | 0 | 0 | 40 | United-States | <=50K |
25 | Private | 289,980 | HS-grad | 9 | Never-married | Handlers-cleaners | Not-in-family | White | Male | 0 | 0 | 35 | United-States | <=50K |
57 | Federal-gov | 337,895 | Bachelors | 13 | Married-civ-spouse | Prof-specialty | Husband | Black | Male | 0 | 0 | 40 | United-States | >50K |
53 | Private | 144,361 | HS-grad | 9 | Married-civ-spouse | Machine-op-inspct | Husband | White | Male | 0 | 0 | 38 | United-States | <=50K |
44 | Private | 128,354 | Masters | 14 | Divorced | Exec-managerial | Unmarried | White | Female | 0 | 0 | 40 | United-States | <=50K |
41 | State-gov | 101,603 | Assoc-voc | 11 | Married-civ-spouse | Craft-repair | Husband | White | Male | 0 | 0 | 40 | United-States | <=50K |
29 | Private | 271,466 | Assoc-voc | 11 | Never-married | Prof-specialty | Not-in-family | White | Male | 0 | 0 | 43 | United-States | <=50K |
25 | Private | 32,275 | Some-college | 10 | Married-civ-spouse | Exec-managerial | Wife | Other | Female | 0 | 0 | 40 | United-States | <=50K |
18 | Private | 226,956 | HS-grad | 9 | Never-married | Other-service | Own-child | White | Female | 0 | 0 | 30 | ? | <=50K |
47 | Private | 51,835 | Prof-school | 15 | Married-civ-spouse | Prof-specialty | Wife | White | Female | 0 | 1,902 | 60 | Honduras | >50K |
50 | Federal-gov | 251,585 | Bachelors | 13 | Divorced | Exec-managerial | Not-in-family | White | Male | 0 | 0 | 55 | United-States | >50K |
47 | Self-emp-inc | 109,832 | HS-grad | 9 | Divorced | Exec-managerial | Not-in-family | White | Male | 0 | 0 | 60 | United-States | <=50K |
43 | Private | 237,993 | Some-college | 10 | Married-civ-spouse | Tech-support | Husband | White | Male | 0 | 0 | 40 | United-States | >50K |
46 | Private | 216,666 | 5th-6th | 3 | Married-civ-spouse | Machine-op-inspct | Husband | White | Male | 0 | 0 | 40 | Mexico | <=50K |
35 | Private | 56,352 | Assoc-voc | 11 | Married-civ-spouse | Other-service | Husband | White | Male | 0 | 0 | 40 | Puerto-Rico | <=50K |
41 | Private | 147,372 | HS-grad | 9 | Married-civ-spouse | Adm-clerical | Husband | White | Male | 0 | 0 | 48 | United-States | <=50K |
30 | Private | 188,146 | HS-grad | 9 | Married-civ-spouse | Machine-op-inspct | Husband | White | Male | 5,013 | 0 | 40 | United-States | <=50K |
30 | Private | 59,496 | Bachelors | 13 | Married-civ-spouse | Sales | Husband | White | Male | 2,407 | 0 | 40 | United-States | <=50K |
32 | ? | 293,936 | 7th-8th | 4 | Married-spouse-absent | ? | Not-in-family | White | Male | 0 | 0 | 40 | ? | <=50K |
48 | Private | 149,640 | HS-grad | 9 | Married-civ-spouse | Transport-moving | Husband | White | Male | 0 | 0 | 40 | United-States | <=50K |
42 | Private | 116,632 | Doctorate | 16 | Married-civ-spouse | Prof-specialty | Husband | White | Male | 0 | 0 | 45 | United-States | >50K |
29 | Private | 105,598 | Some-college | 10 | Divorced | Tech-support | Not-in-family | White | Male | 0 | 0 | 58 | United-States | <=50K |
36 | Private | 155,537 | HS-grad | 9 | Married-civ-spouse | Craft-repair | Husband | White | Male | 0 | 0 | 40 | United-States | <=50K |
28 | Private | 183,175 | Some-college | 10 | Divorced | Adm-clerical | Not-in-family | White | Female | 0 | 0 | 40 | United-States | <=50K |
53 | Private | 169,846 | HS-grad | 9 | Married-civ-spouse | Adm-clerical | Wife | White | Female | 0 | 0 | 40 | United-States | >50K |
49 | Self-emp-inc | 191,681 | Some-college | 10 | Married-civ-spouse | Exec-managerial | Husband | White | Male | 0 | 0 | 50 | United-States | >50K |
25 | ? | 200,681 | Some-college | 10 | Never-married | ? | Own-child | White | Male | 0 | 0 | 40 | United-States | <=50K |
19 | Private | 101,509 | Some-college | 10 | Never-married | Prof-specialty | Own-child | White | Male | 0 | 0 | 32 | United-States | <=50K |
31 | Private | 309,974 | Bachelors | 13 | Separated | Sales | Own-child | Black | Female | 0 | 0 | 40 | United-States | <=50K |
29 | Self-emp-not-inc | 162,298 | Bachelors | 13 | Married-civ-spouse | Sales | Husband | White | Male | 0 | 0 | 70 | United-States | >50K |
23 | Private | 211,678 | Some-college | 10 | Never-married | Machine-op-inspct | Not-in-family | White | Male | 0 | 0 | 40 | United-States | <=50K |
79 | Private | 124,744 | Some-college | 10 | Married-civ-spouse | Prof-specialty | Other-relative | White | Male | 0 | 0 | 20 | United-States | <=50K |
27 | Private | 213,921 | HS-grad | 9 | Never-married | Other-service | Own-child | White | Male | 0 | 0 | 40 | Mexico | <=50K |
40 | Private | 32,214 | Assoc-acdm | 12 | Married-civ-spouse | Adm-clerical | Husband | White | Male | 0 | 0 | 40 | United-States | <=50K |
67 | ? | 212,759 | 10th | 6 | Married-civ-spouse | ? | Husband | White | Male | 0 | 0 | 2 | United-States | <=50K |
18 | Private | 309,634 | 11th | 7 | Never-married | Other-service | Own-child | White | Female | 0 | 0 | 22 | United-States | <=50K |
31 | Local-gov | 125,927 | 7th-8th | 4 | Married-civ-spouse | Farming-fishing | Husband | White | Male | 0 | 0 | 40 | United-States | <=50K |
18 | Private | 446,839 | HS-grad | 9 | Never-married | Sales | Not-in-family | White | Male | 0 | 0 | 30 | United-States | <=50K |
52 | Private | 276,515 | Bachelors | 13 | Married-civ-spouse | Other-service | Husband | White | Male | 0 | 0 | 40 | Cuba | <=50K |
46 | Private | 51,618 | HS-grad | 9 | Married-civ-spouse | Other-service | Wife | White | Female | 0 | 0 | 40 | United-States | <=50K |
59 | Private | 159,937 | HS-grad | 9 | Married-civ-spouse | Sales | Husband | White | Male | 0 | 0 | 48 | United-States | <=50K |
44 | Private | 343,591 | HS-grad | 9 | Divorced | Craft-repair | Not-in-family | White | Female | 14,344 | 0 | 40 | United-States | >50K |
53 | Private | 346,253 | HS-grad | 9 | Divorced | Sales | Own-child | White | Female | 0 | 0 | 35 | United-States | <=50K |
49 | Local-gov | 268,234 | HS-grad | 9 | Married-civ-spouse | Protective-serv | Husband | White | Male | 0 | 0 | 40 | United-States | >50K |
33 | Private | 202,051 | Masters | 14 | Married-civ-spouse | Prof-specialty | Husband | White | Male | 0 | 0 | 50 | United-States | <=50K |
30 | Private | 54,334 | 9th | 5 | Never-married | Sales | Not-in-family | White | Male | 0 | 0 | 40 | United-States | <=50K |
43 | Federal-gov | 410,867 | Doctorate | 16 | Never-married | Prof-specialty | Not-in-family | White | Female | 0 | 0 | 50 | United-States | >50K |
57 | Private | 249,977 | Assoc-voc | 11 | Married-civ-spouse | Prof-specialty | Husband | White | Male | 0 | 0 | 40 | United-States | <=50K |
37 | Private | 286,730 | Some-college | 10 | Divorced | Craft-repair | Unmarried | White | Female | 0 | 0 | 40 | United-States | <=50K |
28 | Private | 212,563 | Some-college | 10 | Divorced | Machine-op-inspct | Unmarried | Black | Female | 0 | 0 | 25 | United-States | <=50K |
30 | Private | 117,747 | HS-grad | 9 | Married-civ-spouse | Sales | Wife | Asian-Pac-Islander | Female | 0 | 1,573 | 35 | ? | <=50K |
34 | Local-gov | 226,296 | Bachelors | 13 | Married-civ-spouse | Protective-serv | Husband | White | Male | 0 | 0 | 40 | United-States | >50K |
29 | Local-gov | 115,585 | Some-college | 10 | Never-married | Handlers-cleaners | Not-in-family | White | Male | 0 | 0 | 50 | United-States | <=50K |
48 | Self-emp-not-inc | 191,277 | Doctorate | 16 | Married-civ-spouse | Prof-specialty | Husband | White | Male | 0 | 1,902 | 60 | United-States | >50K |
37 | Private | 202,683 | Some-college | 10 | Married-civ-spouse | Sales | Husband | White | Male | 0 | 0 | 48 | United-States | >50K |
48 | Private | 171,095 | Assoc-acdm | 12 | Divorced | Exec-managerial | Unmarried | White | Female | 0 | 0 | 40 | England | <=50K |
32 | Federal-gov | 249,409 | HS-grad | 9 | Never-married | Other-service | Own-child | Black | Male | 0 | 0 | 40 | United-States | <=50K |
End of preview.