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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 66 new columns ({'charges', 'ca_metastatic', 'dzgroup_Coma', 'wblc', 'dzclass_COPD/CHF/Cirrhosis', 'dnr_no dnr', 'pafi', 'ph', 'dzgroup_Lung Cancer', 'dzgroup_Colon Cancer', 'sfdm2_<2 mo. follow-up', 'temp', 'glucose', 'income_under $11k', 'race_hispanic', 'income_$11-$25k', 'alb', 'dzgroup_MOSF w/Malig', 'dzclass_Cancer', 'ca_yes', 'dzgroup_CHF', 'sfdm2_adl>=4 (>=5 if sur)', 'urine', 'd.time', 'hday', 'dzclass_Coma', 'dzclass_ARF/MOSF', 'sod', 'crea', 'prg2m', 'adlsc', 'dnr_dnr before sadm', 'prg6m', 'bili', 'hospdead', 'surv2m', 'bun', 'meanbp', 'sps', 'sex', 'diabetes', 'dzgroup_ARF/MOSF w/Sepsis', 'hrt', 'income_$25-$50k', 'num.co', 'avtisst', 'dementia', 'age', 'aps', 'race_asian', 'sfdm2_Coma or Intub', 'race_black', 'resp', 'sfdm2_no(M2 and SIP pres)', 'sfdm2_SIP>=30', 'race_white', 'slos', 'income_>$50k', 'dzgroup_Cirrhosis', 'race_other', 'scoma', 'death', 'surv6m', 'edu', 'dnr_dnr after sadm', 'dzgroup_COPD'}) and 34 missing columns ({'readmitted', 'max_glu_serum>200', 'age>=70', 'num_lab_procedures', 'race_Caucasian', 'max_glu_serum', 'insulin_Up', 'Emergency_admission', 'num_procedures', 'A1Cresult', 'num_medications', 'change', 'A1Cresult>7', 'metformin_Steady', 'Urgent_admission', 'diabetesMed', 'number_inpatient', 'metformin_Up', 'Home', 'A1Cresult>8', 'number_outpatient', 'number_diagnoses', 'race_AfricanAmerican', 'race_Asian', 'time_in_hospital', 'Transferred', 'Elective_admission', 'number_emergency', 'insulin_Down', 'max_glu_serum>300', 'metformin_Down', 'gender', 'race_Hispanic', 'insulin_Steady'}).
This happened while the csv dataset builder was generating data using
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'hf://datasets/Srishti280992/sgshift-concept-shift-official-repro@0144042c4dc6bd2836446e4f05ba4c2fb796407c/outputs/complex_shift_b3_backup/fallback_b3/full_fig2/official_report/table2_official_by_rep.csv', 'hf://datasets/Srishti280992/sgshift-concept-shift-official-repro@0144042c4dc6bd2836446e4f05ba4c2fb796407c/outputs/complex_shift_b3_backup/fallback_b3/full_fig2/official_report/table2_official_summary.csv', 'hf://datasets/Srishti280992/sgshift-concept-shift-official-repro@0144042c4dc6bd2836446e4f05ba4c2fb796407c/outputs/complex_shift_b3_backup/fallback_b3/official_fallback_b3/by_rep_diabetes_official_fallback_b3.csv', 'hf://datasets/Srishti280992/sgshift-concept-shift-official-repro@0144042c4dc6bd2836446e4f05ba4c2fb796407c/outputs/complex_shift_b3_backup/fallback_b3/official_fallback_b3/by_rep_support2_official_fallback_b3.csv', 'hf://datasets/Srishti280992/sgshift-concept-shift-official-repro@0144042c4dc6bd2836446e4f05ba4c2fb796407c/outputs/complex_shift_b3_backup/fallback_b3/official_fallback_b3/raw_diabetes_official_fallback_b3.csv', 'hf://datasets/Srishti280992/sgshift-concept-shift-official-repro@0144042c4dc6bd2836446e4f05ba4c2fb796407c/outputs/complex_shift_b3_backup/fallback_b3/official_fallback_b3/raw_support2_official_fallback_b3.csv', 'hf://datasets/Srishti280992/sgshift-concept-shift-official-repro@0144042c4dc6bd2836446e4f05ba4c2fb796407c/outputs/complex_shift_b3_backup/fallback_b3/official_fallback_b3/summary_diabetes_official_fallback_b3.csv', 'hf://datasets/Srishti280992/sgshift-concept-shift-official-repro@0144042c4dc6bd2836446e4f05ba4c2fb796407c/outputs/complex_shift_b3_backup/fallback_b3/official_fallback_b3/summary_support2_official_fallback_b3.csv', 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'hf://datasets/Srishti280992/sgshift-concept-shift-official-repro@0144042c4dc6bd2836446e4f05ba4c2fb796407c/outputs/fig1_b6_split_fullmodels/complex_shift_b4_threads/official_complex/summary_complex_shift_by_scenario.csv', 'hf://datasets/Srishti280992/sgshift-concept-shift-official-repro@0144042c4dc6bd2836446e4f05ba4c2fb796407c/outputs/fig1_b6_split_fullmodels/complex_shift_b4_threads/official_complex/summary_complex_shift_overall.csv', 'hf://datasets/Srishti280992/sgshift-concept-shift-official-repro@0144042c4dc6bd2836446e4f05ba4c2fb796407c/outputs/fig1_b6_split_fullmodels/fallback_b3/full_fig2/official_fig2/real_world_sparse_elbows.csv', 'hf://datasets/Srishti280992/sgshift-concept-shift-official-repro@0144042c4dc6bd2836446e4f05ba4c2fb796407c/outputs/fig1_b6_split_fullmodels/fallback_b3/full_fig2/official_report/fig2_real_world_elbows.csv', 'hf://datasets/Srishti280992/sgshift-concept-shift-official-repro@0144042c4dc6bd2836446e4f05ba4c2fb796407c/outputs/fig1_b6_split_fullmodels/fallback_b3/full_fig2/official_report/table2_official_by_rep.csv', 'hf://datasets/Srishti280992/sgshift-concept-shift-official-repro@0144042c4dc6bd2836446e4f05ba4c2fb796407c/outputs/fig1_b6_split_fullmodels/fallback_b3/full_fig2/official_report/table2_official_summary.csv', 'hf://datasets/Srishti280992/sgshift-concept-shift-official-repro@0144042c4dc6bd2836446e4f05ba4c2fb796407c/outputs/fig1_b6_split_fullmodels/fallback_b3/official_fallback_b3/by_rep_diabetes_official_fallback_b3.csv', 'hf://datasets/Srishti280992/sgshift-concept-shift-official-repro@0144042c4dc6bd2836446e4f05ba4c2fb796407c/outputs/fig1_b6_split_fullmodels/fallback_b3/official_fallback_b3/by_rep_support2_official_fallback_b3.csv', 'hf://datasets/Srishti280992/sgshift-concept-shift-official-repro@0144042c4dc6bd2836446e4f05ba4c2fb796407c/outputs/fig1_b6_split_fullmodels/fallback_b3/official_fallback_b3/raw_diabetes_official_fallback_b3.csv', 'hf://datasets/Srishti280992/sgshift-concept-shift-official-repro@0144042c4dc6bd2836446e4f05ba4c2fb796407c/outputs/fig1_b6_split_fullmodels/fallback_b3/official_fallback_b3/raw_support2_official_fallback_b3.csv', 'hf://datasets/Srishti280992/sgshift-concept-shift-official-repro@0144042c4dc6bd2836446e4f05ba4c2fb796407c/outputs/fig1_b6_split_fullmodels/fallback_b3/official_fallback_b3/summary_diabetes_official_fallback_b3.csv', 'hf://datasets/Srishti280992/sgshift-concept-shift-official-repro@0144042c4dc6bd2836446e4f05ba4c2fb796407c/outputs/fig1_b6_split_fullmodels/fallback_b3/official_fallback_b3/summary_support2_official_fallback_b3.csv', 'hf://datasets/Srishti280992/sgshift-concept-shift-official-repro@0144042c4dc6bd2836446e4f05ba4c2fb796407c/outputs/fig1_b6_split_fullmodels/fig1_fast/fallback_b3/full_fig2/official_fig2/real_world_sparse_elbows.csv', 'hf://datasets/Srishti280992/sgshift-concept-shift-official-repro@0144042c4dc6bd2836446e4f05ba4c2fb796407c/outputs/fig1_b6_split_fullmodels/fig1_fast/fallback_b3/full_fig2/official_report/fig2_real_world_elbows.csv', 'hf://datasets/Srishti280992/sgshift-concept-shift-official-repro@0144042c4dc6bd2836446e4f05ba4c2fb796407c/outputs/fig1_b6_split_fullmodels/fig1_fast/fallback_b3/full_fig2/official_report/table2_official_by_rep.csv', 'hf://datasets/Srishti280992/sgshift-concept-shift-official-repro@0144042c4dc6bd2836446e4f05ba4c2fb796407c/outputs/fig1_b6_split_fullmodels/fig1_fast/fallback_b3/full_fig2/official_report/table2_official_summary.csv', 'hf://datasets/Srishti280992/sgshift-concept-shift-official-repro@0144042c4dc6bd2836446e4f05ba4c2fb796407c/outputs/fig1_b6_split_fullmodels/fig1_fast/fallback_b3/official_fallback_b3/by_rep_diabetes_official_fallback_b3.csv', 'hf://datasets/Srishti280992/sgshift-concept-shift-official-repro@0144042c4dc6bd2836446e4f05ba4c2fb796407c/outputs/fig1_b6_split_fullmodels/fig1_fast/fallback_b3/official_fallback_b3/by_rep_support2_official_fallback_b3.csv', 'hf://datasets/Srishti280992/sgshift-concept-shift-official-repro@0144042c4dc6bd2836446e4f05ba4c2fb796407c/outputs/fig1_b6_split_fullmodels/fig1_fast/fallback_b3/official_fallback_b3/raw_diabetes_official_fallback_b3.csv', 'hf://datasets/Srishti280992/sgshift-concept-shift-official-repro@0144042c4dc6bd2836446e4f05ba4c2fb796407c/outputs/fig1_b6_split_fullmodels/fig1_fast/fallback_b3/official_fallback_b3/raw_support2_official_fallback_b3.csv', 'hf://datasets/Srishti280992/sgshift-concept-shift-official-repro@0144042c4dc6bd2836446e4f05ba4c2fb796407c/outputs/fig1_b6_split_fullmodels/fig1_fast/fallback_b3/official_fallback_b3/summary_diabetes_official_fallback_b3.csv', 'hf://datasets/Srishti280992/sgshift-concept-shift-official-repro@0144042c4dc6bd2836446e4f05ba4c2fb796407c/outputs/fig1_b6_split_fullmodels/fig1_fast/fallback_b3/official_fallback_b3/summary_support2_official_fallback_b3.csv', 'hf://datasets/Srishti280992/sgshift-concept-shift-official-repro@0144042c4dc6bd2836446e4f05ba4c2fb796407c/outputs/fig1_b6_split_fullmodels/fig1_fast/full_fig2/official_fig2/real_world_sparse_elbows.csv', 'hf://datasets/Srishti280992/sgshift-concept-shift-official-repro@0144042c4dc6bd2836446e4f05ba4c2fb796407c/outputs/fig1_b6_split_fullmodels/fig1_fast/full_fig2/official_report/fig2_real_world_elbows.csv', 'hf://datasets/Srishti280992/sgshift-concept-shift-official-repro@0144042c4dc6bd2836446e4f05ba4c2fb796407c/outputs/fig1_b6_split_fullmodels/fig1_fast/full_fig2/official_report/table2_official_by_rep.csv', 'hf://datasets/Srishti280992/sgshift-concept-shift-official-repro@0144042c4dc6bd2836446e4f05ba4c2fb796407c/outputs/fig1_b6_split_fullmodels/fig1_fast/full_fig2/official_report/table2_official_summary.csv', 'hf://datasets/Srishti280992/sgshift-concept-shift-official-repro@0144042c4dc6bd2836446e4f05ba4c2fb796407c/outputs/fig1_b6_split_fullmodels/fig1_fast/official_fig1/by_rep_diabetes_sample_efficiency.csv', 'hf://datasets/Srishti280992/sgshift-concept-shift-official-repro@0144042c4dc6bd2836446e4f05ba4c2fb796407c/outputs/fig1_b6_split_fullmodels/fig1_fast/official_fig1/raw_diabetes_sample_efficiency.csv', 'hf://datasets/Srishti280992/sgshift-concept-shift-official-repro@0144042c4dc6bd2836446e4f05ba4c2fb796407c/outputs/fig1_b6_split_fullmodels/fig1_fast/official_fig1/summary_diabetes_sample_efficiency.csv', 'hf://datasets/Srishti280992/sgshift-concept-shift-official-repro@0144042c4dc6bd2836446e4f05ba4c2fb796407c/outputs/fig1_b6_split_fullmodels/fig1_fast/official_report/fig1_sample_efficiency_summary.csv', 'hf://datasets/Srishti280992/sgshift-concept-shift-official-repro@0144042c4dc6bd2836446e4f05ba4c2fb796407c/outputs/fig1_b6_split_fullmodels/fig1_fast/official_report/table2_official_by_rep.csv', 'hf://datasets/Srishti280992/sgshift-concept-shift-official-repro@0144042c4dc6bd2836446e4f05ba4c2fb796407c/outputs/fig1_b6_split_fullmodels/fig1_fast/official_report/table2_official_summary.csv', 'hf://datasets/Srishti280992/sgshift-concept-shift-official-repro@0144042c4dc6bd2836446e4f05ba4c2fb796407c/outputs/fig1_b6_split_fullmodels/full_fig2/official_fig2/real_world_sparse_elbows.csv', 'hf://datasets/Srishti280992/sgshift-concept-shift-official-repro@0144042c4dc6bd2836446e4f05ba4c2fb796407c/outputs/fig1_b6_split_fullmodels/full_fig2/official_report/fig2_real_world_elbows.csv', 'hf://datasets/Srishti280992/sgshift-concept-shift-official-repro@0144042c4dc6bd2836446e4f05ba4c2fb796407c/outputs/fig1_b6_split_fullmodels/full_fig2/official_report/table2_official_by_rep.csv', 'hf://datasets/Srishti280992/sgshift-concept-shift-official-repro@0144042c4dc6bd2836446e4f05ba4c2fb796407c/outputs/fig1_b6_split_fullmodels/full_fig2/official_report/table2_official_summary.csv', 'hf://datasets/Srishti280992/sgshift-concept-shift-official-repro@0144042c4dc6bd2836446e4f05ba4c2fb796407c/outputs/fig1_b6_split_fullmodels/official_fig1_n100/by_rep_diabetes_sample_efficiency.csv', 'hf://datasets/Srishti280992/sgshift-concept-shift-official-repro@0144042c4dc6bd2836446e4f05ba4c2fb796407c/outputs/fig1_b6_split_fullmodels/official_fig1_n100/by_rep_diabetes_sample_efficiency_n100.csv', 'hf://datasets/Srishti280992/sgshift-concept-shift-official-repro@0144042c4dc6bd2836446e4f05ba4c2fb796407c/outputs/fig1_b6_split_fullmodels/official_fig1_n100/raw_diabetes_sample_efficiency.csv', 'hf://datasets/Srishti280992/sgshift-concept-shift-official-repro@0144042c4dc6bd2836446e4f05ba4c2fb796407c/outputs/fig1_b6_split_fullmodels/official_fig1_n100/raw_diabetes_sample_efficiency_n100.csv', 'hf://datasets/Srishti280992/sgshift-concept-shift-official-repro@0144042c4dc6bd2836446e4f05ba4c2fb796407c/outputs/fig1_b6_split_fullmodels/official_fig1_n100/summary_diabetes_sample_efficiency.csv', 'hf://datasets/Srishti280992/sgshift-concept-shift-official-repro@0144042c4dc6bd2836446e4f05ba4c2fb796407c/outputs/fig1_b6_split_fullmodels/official_fig1_n100/summary_diabetes_sample_efficiency_n100.csv', 'hf://datasets/Srishti280992/sgshift-concept-shift-official-repro@0144042c4dc6bd2836446e4f05ba4c2fb796407c/outputs/fig1_b6_split_fullmodels/official_fig1_n200/by_rep_diabetes_sample_efficiency.csv', 'hf://datasets/Srishti280992/sgshift-concept-shift-official-repro@0144042c4dc6bd2836446e4f05ba4c2fb796407c/outputs/fig1_b6_split_fullmodels/official_fig1_n200/by_rep_diabetes_sample_efficiency_n200.csv', 'hf://datasets/Srishti280992/sgshift-concept-shift-official-repro@0144042c4dc6bd2836446e4f05ba4c2fb796407c/outputs/fig1_b6_split_fullmodels/official_fig1_n200/raw_diabetes_sample_efficiency.csv', 'hf://datasets/Srishti280992/sgshift-concept-shift-official-repro@0144042c4dc6bd2836446e4f05ba4c2fb796407c/outputs/fig1_b6_split_fullmodels/official_fig1_n200/raw_diabetes_sample_efficiency_n200.csv', 'hf://datasets/Srishti280992/sgshift-concept-shift-official-repro@0144042c4dc6bd2836446e4f05ba4c2fb796407c/outputs/fig1_b6_split_fullmodels/official_fig1_n200/summary_diabetes_sample_efficiency.csv', 'hf://datasets/Srishti280992/sgshift-concept-shift-official-repro@0144042c4dc6bd2836446e4f05ba4c2fb796407c/outputs/fig1_b6_split_fullmodels/official_fig1_n200/summary_diabetes_sample_efficiency_n200.csv', 'hf://datasets/Srishti280992/sgshift-concept-shift-official-repro@0144042c4dc6bd2836446e4f05ba4c2fb796407c/outputs/fig1_fast/fallback_b3/full_fig2/official_fig2/real_world_sparse_elbows.csv', 'hf://datasets/Srishti280992/sgshift-concept-shift-official-repro@0144042c4dc6bd2836446e4f05ba4c2fb796407c/outputs/fig1_fast/fallback_b3/full_fig2/official_report/fig2_real_world_elbows.csv', 'hf://datasets/Srishti280992/sgshift-concept-shift-official-repro@0144042c4dc6bd2836446e4f05ba4c2fb796407c/outputs/fig1_fast/fallback_b3/full_fig2/official_report/table2_official_by_rep.csv', 'hf://datasets/Srishti280992/sgshift-concept-shift-official-repro@0144042c4dc6bd2836446e4f05ba4c2fb796407c/outputs/fig1_fast/fallback_b3/full_fig2/official_report/table2_official_summary.csv', 'hf://datasets/Srishti280992/sgshift-concept-shift-official-repro@0144042c4dc6bd2836446e4f05ba4c2fb796407c/outputs/fig1_fast/fallback_b3/official_fallback_b3/by_rep_diabetes_official_fallback_b3.csv', 'hf://datasets/Srishti280992/sgshift-concept-shift-official-repro@0144042c4dc6bd2836446e4f05ba4c2fb796407c/outputs/fig1_fast/fallback_b3/official_fallback_b3/by_rep_support2_official_fallback_b3.csv', 'hf://datasets/Srishti280992/sgshift-concept-shift-official-repro@0144042c4dc6bd2836446e4f05ba4c2fb796407c/outputs/fig1_fast/fallback_b3/official_fallback_b3/raw_diabetes_official_fallback_b3.csv', 'hf://datasets/Srishti280992/sgshift-concept-shift-official-repro@0144042c4dc6bd2836446e4f05ba4c2fb796407c/outputs/fig1_fast/fallback_b3/official_fallback_b3/raw_support2_official_fallback_b3.csv', 'hf://datasets/Srishti280992/sgshift-concept-shift-official-repro@0144042c4dc6bd2836446e4f05ba4c2fb796407c/outputs/fig1_fast/fallback_b3/official_fallback_b3/summary_diabetes_official_fallback_b3.csv', 'hf://datasets/Srishti280992/sgshift-concept-shift-official-repro@0144042c4dc6bd2836446e4f05ba4c2fb796407c/outputs/fig1_fast/fallback_b3/official_fallback_b3/summary_support2_official_fallback_b3.csv', 'hf://datasets/Srishti280992/sgshift-concept-shift-official-repro@0144042c4dc6bd2836446e4f05ba4c2fb796407c/outputs/fig1_fast/full_fig2/official_fig2/real_world_sparse_elbows.csv', 'hf://datasets/Srishti280992/sgshift-concept-shift-official-repro@0144042c4dc6bd2836446e4f05ba4c2fb796407c/outputs/fig1_fast/full_fig2/official_report/fig2_real_world_elbows.csv', 'hf://datasets/Srishti280992/sgshift-concept-shift-official-repro@0144042c4dc6bd2836446e4f05ba4c2fb796407c/outputs/fig1_fast/full_fig2/official_report/table2_official_by_rep.csv', 'hf://datasets/Srishti280992/sgshift-concept-shift-official-repro@0144042c4dc6bd2836446e4f05ba4c2fb796407c/outputs/fig1_fast/full_fig2/official_report/table2_official_summary.csv', 'hf://datasets/Srishti280992/sgshift-concept-shift-official-repro@0144042c4dc6bd2836446e4f05ba4c2fb796407c/outputs/fig1_fast/official_fig1/by_rep_diabetes_sample_efficiency.csv', 'hf://datasets/Srishti280992/sgshift-concept-shift-official-repro@0144042c4dc6bd2836446e4f05ba4c2fb796407c/outputs/fig1_fast/official_fig1/raw_diabetes_sample_efficiency.csv', 'hf://datasets/Srishti280992/sgshift-concept-shift-official-repro@0144042c4dc6bd2836446e4f05ba4c2fb796407c/outputs/fig1_fast/official_fig1/summary_diabetes_sample_efficiency.csv', 'hf://datasets/Srishti280992/sgshift-concept-shift-official-repro@0144042c4dc6bd2836446e4f05ba4c2fb796407c/outputs/fig1_fast/official_report/fig1_sample_efficiency_summary.csv', 'hf://datasets/Srishti280992/sgshift-concept-shift-official-repro@0144042c4dc6bd2836446e4f05ba4c2fb796407c/outputs/fig1_fast/official_report/table2_official_by_rep.csv', 'hf://datasets/Srishti280992/sgshift-concept-shift-official-repro@0144042c4dc6bd2836446e4f05ba4c2fb796407c/outputs/fig1_fast/official_report/table2_official_summary.csv', 'hf://datasets/Srishti280992/sgshift-concept-shift-official-repro@0144042c4dc6bd2836446e4f05ba4c2fb796407c/outputs/full_fig2/official_fig2/real_world_sparse_elbows.csv', 'hf://datasets/Srishti280992/sgshift-concept-shift-official-repro@0144042c4dc6bd2836446e4f05ba4c2fb796407c/outputs/full_fig2/official_report/fig2_real_world_elbows.csv', 'hf://datasets/Srishti280992/sgshift-concept-shift-official-repro@0144042c4dc6bd2836446e4f05ba4c2fb796407c/outputs/full_fig2/official_report/table2_official_by_rep.csv', 'hf://datasets/Srishti280992/sgshift-concept-shift-official-repro@0144042c4dc6bd2836446e4f05ba4c2fb796407c/outputs/full_fig2/official_report/table2_official_summary.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/python3.14/site-packages/datasets/builder.py", line 1837, in _prepare_split_single
writer.write_table(table)
~~~~~~~~~~~~~~~~~~^^^^^^^
File "/usr/local/lib/python3.14/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/python3.14/site-packages/datasets/arrow_writer.py", line 773, in _write_table
pa_table = table_cast(pa_table, self._schema)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2369, in table_cast
return cast_table_to_schema(table, schema)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2297, in cast_table_to_schema
raise CastError(
...<3 lines>...
)
datasets.table.CastError: Couldn't cast
age: double
death: int64
sex: int64
hospdead: int64
slos: int64
d.time: int64
num.co: int64
edu: double
scoma: double
charges: double
avtisst: double
sps: double
aps: double
surv2m: double
surv6m: double
hday: int64
diabetes: int64
dementia: int64
prg2m: double
prg6m: double
meanbp: double
wblc: double
hrt: double
resp: double
temp: double
pafi: double
alb: double
bili: double
crea: double
sod: double
ph: double
glucose: double
bun: double
urine: double
adlsc: double
dzgroup_ARF/MOSF w/Sepsis: int64
dzgroup_CHF: int64
dzgroup_COPD: int64
dzgroup_Cirrhosis: int64
dzgroup_Colon Cancer: int64
dzgroup_Coma: int64
dzgroup_Lung Cancer: int64
dzgroup_MOSF w/Malig: int64
dzclass_ARF/MOSF: int64
dzclass_COPD/CHF/Cirrhosis: int64
dzclass_Cancer: int64
dzclass_Coma: int64
income_$11-$25k: int64
income_$25-$50k: int64
income_>$50k: int64
income_under $11k: int64
race_asian: int64
race_black: int64
race_hispanic: int64
race_other: int64
race_white: int64
dnr_dnr after sadm: int64
dnr_dnr before sadm: int64
dnr_no dnr: int64
sfdm2_<2 mo. follow-up: int64
sfdm2_Coma or Intub: int64
sfdm2_SIP>=30: int64
sfdm2_adl>=4 (>=5 if sur): int64
sfdm2_no(M2 and SIP pres): int64
ca_metastatic: int64
ca_yes: int64
-- schema metadata --
pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 8090
to
{'gender': Value('int64'), 'time_in_hospital': Value('int64'), 'num_lab_procedures': Value('int64'), 'num_procedures': Value('int64'), 'num_medications': Value('int64'), 'number_outpatient': Value('int64'), 'number_emergency': Value('int64'), 'number_inpatient': Value('int64'), 'number_diagnoses': Value('int64'), 'max_glu_serum': Value('int64'), 'A1Cresult': Value('int64'), 'change': Value('int64'), 'diabetesMed': Value('int64'), 'race_Caucasian': Value('int64'), 'race_AfricanAmerican': Value('int64'), 'race_Hispanic': Value('int64'), 'race_Asian': Value('int64'), 'age>=70': Value('int64'), 'max_glu_serum>200': Value('int64'), 'max_glu_serum>300': Value('int64'), 'A1Cresult>7': Value('int64'), 'A1Cresult>8': Value('int64'), 'metformin_Up': Value('int64'), 'metformin_Down': Value('int64'), 'metformin_Steady': Value('int64'), 'insulin_Up': Value('int64'), 'insulin_Down': Value('int64'), 'insulin_Steady': Value('int64'), 'Transferred': Value('int64'), 'Home': Value('int64'), 'Emergency_admission': Value('int64'), 'Elective_admission': Value('int64'), 'Urgent_admission': Value('int64'), 'readmitted': Value('int64')}
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 1369, in compute_config_parquet_and_info_response
parquet_operations, partial, estimated_dataset_info = stream_convert_to_parquet(
~~~~~~~~~~~~~~~~~~~~~~~~~^
builder, max_dataset_size_bytes=max_dataset_size_bytes
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
)
^
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 948, in stream_convert_to_parquet
builder._prepare_split(split_generator=splits_generators[split], file_format="parquet")
~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1683, in _prepare_split
for job_id, done, content in self._prepare_split_single(
~~~~~~~~~~~~~~~~~~~~~~~~~~^
gen_kwargs=gen_kwargs, job_id=job_id, **_prepare_split_args
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
):
^
File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1839, in _prepare_split_single
raise DatasetGenerationCastError.from_cast_error(
...<4 lines>...
)
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 66 new columns ({'charges', 'ca_metastatic', 'dzgroup_Coma', 'wblc', 'dzclass_COPD/CHF/Cirrhosis', 'dnr_no dnr', 'pafi', 'ph', 'dzgroup_Lung Cancer', 'dzgroup_Colon Cancer', 'sfdm2_<2 mo. follow-up', 'temp', 'glucose', 'income_under $11k', 'race_hispanic', 'income_$11-$25k', 'alb', 'dzgroup_MOSF w/Malig', 'dzclass_Cancer', 'ca_yes', 'dzgroup_CHF', 'sfdm2_adl>=4 (>=5 if sur)', 'urine', 'd.time', 'hday', 'dzclass_Coma', 'dzclass_ARF/MOSF', 'sod', 'crea', 'prg2m', 'adlsc', 'dnr_dnr before sadm', 'prg6m', 'bili', 'hospdead', 'surv2m', 'bun', 'meanbp', 'sps', 'sex', 'diabetes', 'dzgroup_ARF/MOSF w/Sepsis', 'hrt', 'income_$25-$50k', 'num.co', 'avtisst', 'dementia', 'age', 'aps', 'race_asian', 'sfdm2_Coma or Intub', 'race_black', 'resp', 'sfdm2_no(M2 and SIP pres)', 'sfdm2_SIP>=30', 'race_white', 'slos', 'income_>$50k', 'dzgroup_Cirrhosis', 'race_other', 'scoma', 'death', 'surv6m', 'edu', 'dnr_dnr after sadm', 'dzgroup_COPD'}) and 34 missing columns ({'readmitted', 'max_glu_serum>200', 'age>=70', 'num_lab_procedures', 'race_Caucasian', 'max_glu_serum', 'insulin_Up', 'Emergency_admission', 'num_procedures', 'A1Cresult', 'num_medications', 'change', 'A1Cresult>7', 'metformin_Steady', 'Urgent_admission', 'diabetesMed', 'number_inpatient', 'metformin_Up', 'Home', 'A1Cresult>8', 'number_outpatient', 'number_diagnoses', 'race_AfricanAmerican', 'race_Asian', 'time_in_hospital', 'Transferred', 'Elective_admission', 'number_emergency', 'insulin_Down', 'max_glu_serum>300', 'metformin_Down', 'gender', 'race_Hispanic', 'insulin_Steady'}).
This happened while the csv dataset builder was generating data using
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'hf://datasets/Srishti280992/sgshift-concept-shift-official-repro@0144042c4dc6bd2836446e4f05ba4c2fb796407c/outputs/complex_shift_b3_backup/fallback_b3/full_fig2/official_report/table2_official_by_rep.csv', 'hf://datasets/Srishti280992/sgshift-concept-shift-official-repro@0144042c4dc6bd2836446e4f05ba4c2fb796407c/outputs/complex_shift_b3_backup/fallback_b3/full_fig2/official_report/table2_official_summary.csv', 'hf://datasets/Srishti280992/sgshift-concept-shift-official-repro@0144042c4dc6bd2836446e4f05ba4c2fb796407c/outputs/complex_shift_b3_backup/fallback_b3/official_fallback_b3/by_rep_diabetes_official_fallback_b3.csv', 'hf://datasets/Srishti280992/sgshift-concept-shift-official-repro@0144042c4dc6bd2836446e4f05ba4c2fb796407c/outputs/complex_shift_b3_backup/fallback_b3/official_fallback_b3/by_rep_support2_official_fallback_b3.csv', 'hf://datasets/Srishti280992/sgshift-concept-shift-official-repro@0144042c4dc6bd2836446e4f05ba4c2fb796407c/outputs/complex_shift_b3_backup/fallback_b3/official_fallback_b3/raw_diabetes_official_fallback_b3.csv', 'hf://datasets/Srishti280992/sgshift-concept-shift-official-repro@0144042c4dc6bd2836446e4f05ba4c2fb796407c/outputs/complex_shift_b3_backup/fallback_b3/official_fallback_b3/raw_support2_official_fallback_b3.csv', 'hf://datasets/Srishti280992/sgshift-concept-shift-official-repro@0144042c4dc6bd2836446e4f05ba4c2fb796407c/outputs/complex_shift_b3_backup/fallback_b3/official_fallback_b3/summary_diabetes_official_fallback_b3.csv', 'hf://datasets/Srishti280992/sgshift-concept-shift-official-repro@0144042c4dc6bd2836446e4f05ba4c2fb796407c/outputs/complex_shift_b3_backup/fallback_b3/official_fallback_b3/summary_support2_official_fallback_b3.csv', 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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.
gender int64 | time_in_hospital int64 | num_lab_procedures int64 | num_procedures int64 | num_medications int64 | number_outpatient int64 | number_emergency int64 | number_inpatient int64 | number_diagnoses int64 | max_glu_serum int64 | A1Cresult int64 | change int64 | diabetesMed int64 | race_Caucasian int64 | race_AfricanAmerican int64 | race_Hispanic int64 | race_Asian int64 | age>=70 int64 | max_glu_serum>200 int64 | max_glu_serum>300 int64 | A1Cresult>7 int64 | A1Cresult>8 int64 | metformin_Up int64 | metformin_Down int64 | metformin_Steady int64 | insulin_Up int64 | insulin_Down int64 | insulin_Steady int64 | Transferred int64 | Home int64 | Emergency_admission int64 | Elective_admission int64 | Urgent_admission int64 | readmitted int64 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
0 | 2 | 11 | 5 | 13 | 2 | 0 | 1 | 6 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 0 |
1 | 2 | 44 | 1 | 16 | 0 | 0 | 0 | 7 | 0 | 0 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 0 |
1 | 1 | 51 | 0 | 8 | 0 | 0 | 0 | 5 | 0 | 0 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 1 | 0 | 0 | 0 |
1 | 5 | 73 | 0 | 12 | 0 | 0 | 0 | 8 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 1 |
0 | 9 | 47 | 2 | 17 | 0 | 0 | 0 | 9 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 1 | 0 | 0 | 1 |
0 | 7 | 60 | 0 | 15 | 0 | 1 | 0 | 8 | 0 | 0 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 1 |
1 | 10 | 55 | 1 | 31 | 0 | 0 | 0 | 8 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 1 | 0 | 0 | 0 |
1 | 12 | 75 | 5 | 13 | 0 | 0 | 0 | 9 | 0 | 0 | 1 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 0 |
1 | 4 | 45 | 4 | 17 | 0 | 0 | 0 | 8 | 0 | 0 | 1 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 1 | 0 | 0 | 1 |
0 | 3 | 29 | 0 | 11 | 0 | 0 | 0 | 3 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 0 |
1 | 5 | 35 | 5 | 23 | 0 | 0 | 0 | 9 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 1 | 0 | 0 | 1 |
1 | 6 | 64 | 3 | 18 | 0 | 0 | 0 | 7 | 0 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 0 |
0 | 5 | 52 | 0 | 14 | 0 | 0 | 0 | 8 | 0 | 0 | 1 | 1 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 1 |
0 | 6 | 87 | 0 | 18 | 0 | 0 | 0 | 9 | 0 | 0 | 1 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 1 | 0 | 0 | 0 |
1 | 1 | 53 | 0 | 10 | 0 | 0 | 0 | 8 | 0 | 0 | 1 | 1 | 0 | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 1 |
0 | 6 | 27 | 0 | 16 | 0 | 0 | 0 | 8 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 1 | 0 | 0 | 1 |
0 | 2 | 41 | 0 | 11 | 0 | 0 | 0 | 6 | 0 | 0 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 1 | 1 | 0 | 0 | 1 |
0 | 4 | 33 | 0 | 12 | 0 | 0 | 0 | 3 | 0 | 0 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 1 | 0 | 1 | 1 | 0 | 0 | 1 |
1 | 7 | 47 | 2 | 22 | 0 | 0 | 0 | 8 | 0 | 0 | 1 | 1 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 1 | 0 | 0 | 0 |
0 | 1 | 28 | 0 | 15 | 0 | 0 | 0 | 4 | 0 | 0 | 1 | 1 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 1 |
1 | 3 | 59 | 0 | 11 | 0 | 0 | 0 | 6 | 0 | 0 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 1 | 0 | 1 | 1 | 0 | 0 | 1 |
0 | 8 | 55 | 2 | 17 | 0 | 0 | 0 | 9 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 1 | 0 | 0 | 1 |
0 | 1 | 53 | 0 | 11 | 1 | 0 | 0 | 9 | 0 | 0 | 1 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 1 | 1 | 0 | 0 | 1 |
0 | 4 | 48 | 2 | 15 | 0 | 1 | 0 | 9 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 1 | 0 | 0 | 1 |
1 | 4 | 45 | 0 | 16 | 0 | 0 | 0 | 8 | 0 | 0 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 1 |
0 | 3 | 64 | 0 | 15 | 0 | 0 | 1 | 9 | 0 | 0 | 1 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 1 |
1 | 4 | 57 | 0 | 17 | 0 | 0 | 0 | 9 | 0 | 0 | 1 | 1 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 1 | 0 | 0 | 0 |
0 | 7 | 75 | 2 | 22 | 0 | 0 | 0 | 7 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 1 |
1 | 12 | 83 | 2 | 32 | 0 | 0 | 0 | 9 | 0 | 0 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 1 |
0 | 5 | 34 | 0 | 17 | 0 | 0 | 1 | 7 | 0 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 1 |
0 | 4 | 51 | 0 | 9 | 0 | 0 | 0 | 4 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 1 |
1 | 1 | 58 | 1 | 12 | 0 | 0 | 0 | 6 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 1 |
1 | 3 | 52 | 0 | 13 | 0 | 0 | 2 | 9 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 0 |
1 | 1 | 59 | 0 | 10 | 0 | 0 | 0 | 7 | 0 | 0 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 1 | 1 | 0 | 0 | 0 |
1 | 3 | 39 | 0 | 13 | 0 | 0 | 0 | 7 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 1 |
0 | 5 | 36 | 0 | 14 | 0 | 0 | 0 | 5 | 0 | 0 | 1 | 1 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 1 | 0 | 0 | 1 |
0 | 6 | 65 | 3 | 18 | 0 | 0 | 0 | 9 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 1 | 0 | 0 | 1 |
0 | 5 | 64 | 0 | 21 | 0 | 0 | 1 | 8 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 1 | 0 | 0 | 1 |
1 | 3 | 55 | 4 | 23 | 0 | 0 | 1 | 9 | 0 | 0 | 1 | 1 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 1 | 1 | 0 | 0 | 0 |
1 | 1 | 59 | 0 | 12 | 0 | 0 | 0 | 7 | 0 | 1 | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 1 | 0 | 0 | 0 |
0 | 3 | 31 | 2 | 11 | 0 | 0 | 0 | 9 | 0 | 0 | 1 | 1 | 0 | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 1 | 1 | 0 | 0 | 0 |
1 | 2 | 34 | 0 | 9 | 0 | 0 | 0 | 7 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 1 |
0 | 3 | 34 | 0 | 11 | 0 | 0 | 0 | 8 | 0 | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 1 |
1 | 5 | 72 | 5 | 22 | 0 | 0 | 0 | 9 | 0 | 0 | 1 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 1 | 1 | 0 | 0 | 1 |
1 | 14 | 78 | 1 | 19 | 0 | 0 | 0 | 8 | 0 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 1 |
0 | 2 | 48 | 0 | 11 | 0 | 0 | 0 | 5 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 1 | 0 | 0 | 0 |
1 | 4 | 65 | 2 | 19 | 0 | 0 | 0 | 7 | 0 | 1 | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 1 | 0 | 0 | 1 |
0 | 1 | 56 | 0 | 4 | 1 | 0 | 1 | 3 | 0 | 0 | 1 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 1 | 0 | 0 | 1 | 1 |
0 | 7 | 55 | 1 | 16 | 0 | 0 | 1 | 7 | 0 | 0 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 1 |
1 | 1 | 37 | 0 | 13 | 0 | 0 | 0 | 6 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 1 | 0 | 0 | 1 |
0 | 2 | 18 | 0 | 15 | 5 | 1 | 0 | 3 | 0 | 0 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 1 | 1 | 0 | 0 | 1 |
0 | 11 | 44 | 0 | 19 | 0 | 1 | 6 | 8 | 0 | 0 | 1 | 1 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 1 |
1 | 4 | 52 | 0 | 9 | 0 | 0 | 0 | 4 | 0 | 0 | 1 | 1 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 1 |
0 | 4 | 51 | 0 | 18 | 0 | 0 | 0 | 7 | 0 | 0 | 1 | 1 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 0 |
1 | 1 | 58 | 0 | 8 | 0 | 0 | 1 | 5 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 1 |
0 | 1 | 48 | 1 | 14 | 2 | 1 | 0 | 7 | 0 | 0 | 1 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 1 | 1 | 0 | 0 | 1 |
0 | 3 | 63 | 1 | 16 | 0 | 0 | 0 | 6 | 0 | 0 | 1 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 0 |
1 | 2 | 48 | 0 | 8 | 0 | 0 | 0 | 7 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 1 | 0 | 0 | 1 |
1 | 3 | 90 | 0 | 15 | 7 | 0 | 3 | 9 | 0 | 0 | 1 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 1 |
0 | 2 | 44 | 0 | 16 | 0 | 0 | 1 | 8 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 0 |
0 | 4 | 77 | 4 | 29 | 0 | 0 | 0 | 9 | 0 | 0 | 1 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 1 | 1 | 0 | 0 | 1 |
0 | 6 | 60 | 1 | 25 | 0 | 0 | 1 | 6 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 1 | 0 | 0 | 1 |
1 | 1 | 45 | 0 | 4 | 0 | 0 | 0 | 6 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 1 | 0 |
0 | 8 | 77 | 4 | 40 | 0 | 0 | 0 | 9 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 1 |
0 | 4 | 46 | 0 | 23 | 0 | 0 | 0 | 9 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 1 | 0 | 0 | 1 |
0 | 2 | 33 | 4 | 8 | 0 | 0 | 0 | 9 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 1 | 0 | 0 | 0 |
0 | 2 | 41 | 0 | 5 | 0 | 0 | 0 | 8 | 0 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 1 | 0 | 1 | 1 | 0 | 0 | 1 |
1 | 12 | 60 | 0 | 21 | 0 | 0 | 0 | 8 | 0 | 1 | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 1 | 0 | 0 | 0 |
1 | 3 | 56 | 6 | 18 | 0 | 0 | 0 | 9 | 0 | 0 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 1 | 1 | 0 | 0 | 0 |
1 | 3 | 80 | 1 | 12 | 0 | 0 | 0 | 9 | 0 | 0 | 1 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 1 | 0 | 0 | 0 |
0 | 2 | 36 | 1 | 9 | 0 | 0 | 5 | 7 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 1 | 0 | 0 | 0 |
0 | 6 | 53 | 0 | 15 | 0 | 0 | 0 | 8 | 0 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 1 | 0 | 0 | 1 |
1 | 2 | 55 | 0 | 12 | 0 | 0 | 0 | 8 | 0 | 0 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 1 |
1 | 4 | 50 | 0 | 8 | 0 | 0 | 0 | 8 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 1 |
0 | 3 | 63 | 1 | 18 | 0 | 0 | 2 | 6 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 1 | 0 | 0 | 1 |
0 | 1 | 37 | 0 | 10 | 0 | 0 | 0 | 9 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 1 | 0 | 0 | 0 |
0 | 10 | 59 | 1 | 12 | 0 | 0 | 0 | 9 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 0 |
1 | 12 | 69 | 0 | 19 | 0 | 0 | 0 | 6 | 0 | 0 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 0 |
0 | 4 | 60 | 1 | 13 | 0 | 0 | 0 | 5 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 1 |
1 | 3 | 38 | 0 | 6 | 0 | 0 | 0 | 6 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 1 |
0 | 7 | 37 | 1 | 29 | 0 | 0 | 2 | 8 | 0 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 1 | 1 | 0 | 0 | 1 |
1 | 8 | 46 | 3 | 20 | 0 | 0 | 0 | 8 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 0 |
0 | 6 | 73 | 0 | 17 | 0 | 0 | 0 | 4 | 0 | 0 | 1 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 1 |
0 | 4 | 87 | 0 | 12 | 1 | 0 | 1 | 9 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 1 |
0 | 7 | 50 | 0 | 9 | 0 | 0 | 0 | 9 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 1 | 0 | 0 | 0 |
1 | 6 | 42 | 1 | 10 | 0 | 0 | 0 | 8 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 1 |
0 | 4 | 84 | 1 | 15 | 0 | 0 | 0 | 9 | 0 | 0 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 1 |
0 | 1 | 49 | 3 | 5 | 0 | 0 | 0 | 3 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 1 | 0 | 0 | 0 |
1 | 2 | 50 | 1 | 6 | 0 | 0 | 0 | 9 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 1 | 0 | 0 | 1 |
0 | 2 | 52 | 0 | 10 | 0 | 0 | 5 | 9 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 1 | 0 | 0 | 0 |
0 | 3 | 41 | 3 | 11 | 0 | 0 | 0 | 8 | 0 | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 1 |
1 | 5 | 60 | 0 | 10 | 0 | 0 | 0 | 7 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 1 | 0 | 0 | 1 |
0 | 3 | 64 | 0 | 9 | 0 | 0 | 0 | 6 | 0 | 0 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 0 |
0 | 6 | 48 | 4 | 16 | 0 | 1 | 0 | 9 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 1 |
0 | 5 | 45 | 2 | 16 | 0 | 0 | 0 | 6 | 0 | 0 | 1 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 1 |
0 | 5 | 43 | 3 | 26 | 0 | 0 | 4 | 8 | 0 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 1 | 1 | 0 | 0 | 1 |
1 | 1 | 58 | 0 | 8 | 0 | 0 | 0 | 7 | 0 | 0 | 1 | 1 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 1 | 0 |
1 | 2 | 53 | 0 | 14 | 0 | 0 | 0 | 8 | 0 | 0 | 1 | 1 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 1 | 0 | 1 | 1 | 0 | 0 | 1 |
0 | 2 | 62 | 0 | 14 | 0 | 1 | 3 | 9 | 0 | 0 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 1 | 0 | 0 | 1 |
0 | 6 | 54 | 0 | 17 | 0 | 0 | 2 | 8 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 1 |
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