Datasets:

---

petrrysavy

/

krebs

like 0

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 499 new columns ({'0.0255741127348643.1', '0.02502606882168926', '0.023291925465838508.11', '0.02830188679245283.8', '0.028346456692913385.24', '0.011922503725782414', '0.012462612163509471', '0.022233712512926575.1', '0.028346456692913385.3', '0.023291925465838508', '0.006631927996210327', '0.02776322682032478.3', '0.02338877338877339.1', '0.008177008177008177', '0.01580826109127996', '0.013527054108216433', '0.025587467362924284.1', '0.026687598116169546', '0.02556077203964528.8', '0.02830188679245283.5', '0.028361344537815126.1', '0.012967581047381545.1', '0.014765784114052953.3', '0.0076886112445939455.1', '0.026687598116169546.11', '0.02284527518172378.5', '0.013567839195979899', '0.013164556962025316', '0.015282730514518594.1', '0.02502606882168926.1', '0.02338877338877339', '0.02556077203964528.6', '0.027225130890052355.1', '0.013131313131313131.3', '0.01245019920318725.1', '0.018442622950819672.1', '0.024479166666666666.1', '0.01309823677581864.2', '0.006134969325153374', '0.0057361376673040155', '0.005717008099094807', '0.014758269720101781.5', '0.026687598116169546.14', '0.025587467362924284', '0.011904761904761904', '0.01580826109127996.6', '0.014758269720101781.2', '0.012632642748863061.2', '0.011175898931000973.1', '0.028346456692913385', '0.02284527518172378', '0.014227642276422764.1', '0.026673640167364017', '0.023291925465838508.7', '0.018480492813141684.3', '0.02779234399580493.3', '0.008173076923076924.3', '0.008173076923076924', '0.005248091603053435.1', '0.0200617283950617
...
.012645422357106728', '0.006086142322097378', '0.013171225937183385', '0.028346456692913385.11', '0.011280039234919078', '0.011690209449585971', '0.02556077203964528.7', '0.01354062186559679.1', '0.005671077504725898', '0.013131313131313131.1', '0.026687598116169546.26', '0.024479166666666666', '0.0056657223796034', '0.013171225937183385.1', '0.022233712512926575.6', '0.024479166666666666.5', '0.02007205352547607', '0.0091478093403948', '0.02830188679245283.4', '0.010174418604651164', '0.013171225937183385.4', '0.01580020387359837', '0.02556077203964528.9', '0.02830188679245283.15', '0.01355421686746988', '0.026659696811291166.8', '0.018480492813141684.2', '0.012444001991040319.3', '0.009775171065493646', '0.013157894736842105', '0.006708193579300431.1', '0.014227642276422764', '0.027806925498426022', '0.023291925465838508.4', '0.013691683569979716.2', '0.018480492813141684', '0.02830188679245283.22', '0.0051401869158878505', '0.005245588936576061', '0.028346456692913385.6', '0.026687598116169546.21', '0.025587467362924284.5', '0.028361344537815126.4', '0.010832102412604629', '0.017957927142124165.1', '0.006704980842911878.1', '0.028346456692913385.18', '0.024479166666666666.2', '0.028346456692913385.8', '0.02830188679245283.3', '0.02779234399580493.4', '0.012632642748863061', '0.02830188679245283.17', '0.028346456692913385.21', '0.008687258687258687', '0.026687598116169546.9', '0.011892963330029732.1', '0.022857142857142857', '0.013124684502776375', '0.022857142857142857.2'}) and 499 missing columns ({'0.018628912071535022', '0.020239880059970013.4', '0.010130246020260492.3', '0.01168736303871439.2', '0.010144927536231883.12', '0.021148036253776436.13', '0.019461077844311378.5', '0.015625', '0.018670649738610903.15', '0.020454545454545454.10', '0.01868460388639761.2', '0.011627906976744186.2', '0.020239880059970013.8', '0.02042360060514372.50', '0.02180451127819549', '0.00931899641577061', '0.011670313639679067', '0.020239880059970013', '0.0131852879944483', '0.019461077844311378.4', '0.010144927536231883.9', '0.018670649738610903.16', '0.01944652206432311.17', '0.01003584229390681', '0.01868460388639761.3', '0.02042360060514372.2', '0.020239880059970013.3', '0.017857142857142856.1', '0.01065340909090909.2', '0.01944652206432311.6', '0.013960323291697281', '0.019461077844311378.13', '0.017830609212481426.12', '0.015475313190862197.4', '0.02042360060514372.3', '0.02042360060514372.10', '0.02042360060514372.36', '0.02042360060514372.13', '0.009312320916905445.2', '0.010806916426512969', '0.021148036253776436.20', '0.019461077844311378.9', '0.020454545454545454.8', '0.010660980810234541.2', '0.018615040953090096', '0.02042360060514372.18', '0.02042360060514372.48', '0.020255063765941484.4', '0.02042360060514372.9', '0.01704966641957005.6', '0.009312320916905445.1', '0.014522821576763486', '0.015475313190862197.10', '0.01944652206432311.20', '0.02042360060514372.19', '0.01944652206432311.13', '0.017857142857142856.4', '0.013215859030837005.1', '0.017830609212481426.3', '0.020
...
7714.2', '0.017830609212481426.20', '0.02262443438914027.2', '0.015475313190862197.1', '0.010877447425670777', '0.010706638115631691.1', '0.018670649738610903.14', '0.01167883211678832.3', '0.02042360060514372.8', '0.016260162601626018', '0.017011834319526627.3', '0.019667170953101363.3', '0.02042360060514372.12', '0.010137581462708182.2', '0.020454545454545454.12', '0.01079913606911447', '0.02042360060514372.15', '0.010706638115631691', '0.011871508379888268', '0.021148036253776436.24', '0.01090909090909091', '0.013939838591342627.1', '0.011188811188811189', '0.013186813186813187.1', '0.018670649738610903.12', '0.020454545454545454.2', '0.01968205904617714.1', '0.02260738507912585.2', '0.018628912071535022.7', '0.01944652206432311.12', '0.0111731843575419', '0.021021021021021023', '0.011180992313067784', '0.018628912071535022.1', '0.017830609212481426.19', '0.011661807580174927.2', '0.015475313190862197', '0.016236162361623615', '0.017830609212481426.8', '0.010699001426533523.1', '0.02042360060514372.23', '0.019667170953101363.12', '0.010668563300142247', '0.017817371937639197.3', '0.018656716417910446.1', '0.02180451127819549.23', '0.02260738507912585.3', '0.013980868285504048', '0.015475313190862197.2', '0.01592797783933518', '0.021148036253776436.10', '0.02042360060514372.35', '0.011963406052076003', '0.01704966641957005.1', '0.01314878892733564', '0.017011834319526627.5', '0.018628912071535022.3', '0.01132342533616419', '0.010144927536231883.6', '0.02180451127819549.17'}).

This happened while the csv dataset builder was generating data using

hf://datasets/petrrysavy/krebs/krebs3/threes1.tsv (at revision 229ef67a0e37072643d1ccc215629cefa560b0b0)

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 1870, in _prepare_split_single
                  writer.write_table(table)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/arrow_writer.py", line 622, 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 2292, in table_cast
                  return cast_table_to_schema(table, schema)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2240, in cast_table_to_schema
                  raise CastError(
              datasets.table.CastError: Couldn't cast
              FUMARATE: string
              0.0: double
              0.0.1: double
              0.0.2: double
              0.0.3: double
              0.0.4: double
              0.0.5: double
              4.601932811780948E-4: double
              0.001388888888888889: double
              0.0037209302325581397: double
              0.004195804195804196: double
              0.0051401869158878505: double
              0.005615348619560131: double
              0.006086142322097378: double
              0.005620608899297424: double
              0.005625879043600563: double
              0.006100422336931018: double
              0.0061118946873530795: double
              0.005647058823529412: double
              0.005655042412818096: double
              0.006134969325153374: double
              0.0056657223796034: double
              0.005671077504725898: double
              0.005668398677373642: double
              0.0056657223796034.1: double
              0.005198487712665407: double
              0.005676442762535478: double
              0.006625650733554188: double
              0.006635071090047393: double
              0.006631927996210327: double
              0.006638217164532954: double
              0.006635071090047393.1: double
              0.006644518272425249: double
              0.006172839506172839: double
              0.005717008099094807: double
              0.005235602094240838: double
              0.005240590757503573: double
              0.005245588936576061: double
              0.005248091603053435: double
              0.005248091603053435.1: double
              0.005733397037744864: double
              0.0057306590257879654: double
              0.005733397037744864.1: double
              0.0057361376673040155: double
              0.006226053639846743: double
              0.006704980842911878: double
              0.006704980842911878.1: double
              0.006708193579300431: double
              0.006711409395973154: double
              0.006708193579300431.1: double
              0.00671462829736211: double
              0.00672107537205953: double
              0.007684918347742555: double
              0.0076886112445939455: double
              0.0076886112445939455.1: d
              ...
              0.02779234399580493.1: double
              0.02779234399580493.2: double
              0.02779234399580493.3: double
              0.027806925498426022: double
              0.02779234399580493.4: double
              0.027806925498426022.1: double
              0.028346456692913385: double
              0.028346456692913385.1: double
              0.028346456692913385.2: double
              0.028346456692913385.3: double
              0.028346456692913385.4: double
              0.028346456692913385.5: double
              0.028346456692913385.6: double
              0.028346456692913385.7: double
              0.028346456692913385.8: double
              0.028346456692913385.9: double
              0.028346456692913385.10: double
              0.028346456692913385.11: double
              0.028346456692913385.12: double
              0.028346456692913385.13: double
              0.028346456692913385.14: double
              0.028346456692913385.15: double
              0.028346456692913385.16: double
              0.028346456692913385.17: double
              0.028346456692913385.18: double
              0.028346456692913385.19: double
              0.028346456692913385.20: double
              0.028346456692913385.21: double
              0.028346456692913385.22: double
              0.028346456692913385.23: double
              0.028346456692913385.24: double
              0.028361344537815126: double
              0.028361344537815126.1: double
              0.028361344537815126.2: double
              0.028361344537815126.3: double
              0.028361344537815126.4: double
              0.028361344537815126.5: double
              0.028361344537815126.6: double
              0.028901734104046242: double
              0.028901734104046242.1: double
              0.028901734104046242.2: double
              0.028901734104046242.3: double
              0.028901734104046242.4: double
              0.028901734104046242.5: double
              0.029442691903259727: double
              -- schema metadata --
              pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 71786
              to
              {'FUMARATE': Value(dtype='string', id=None), '0.017361111111111112': Value(dtype='float64', id=None), '0.015625': Value(dtype='float64', id=None), '0.01592797783933518': Value(dtype='float64', id=None), '0.015785861358956762': Value(dtype='float64', id=None), '0.01443298969072165': Value(dtype='float64', id=None), '0.015862068965517243': Value(dtype='float64', id=None), '0.014522821576763486': Value(dtype='float64', id=None), '0.013167013167013167': Value(dtype='float64', id=None), '0.013167013167013167.1': Value(dtype='float64', id=None), '0.013176144244105409': Value(dtype='float64', id=None), '0.01314878892733564': Value(dtype='float64', id=None), '0.013167013167013167.2': Value(dtype='float64', id=None), '0.013167013167013167.3': Value(dtype='float64', id=None), '0.01313969571230982': Value(dtype='float64', id=None), '0.013167013167013167.4': Value(dtype='float64', id=None), '0.013167013167013167.5': Value(dtype='float64', id=None), '0.013176144244105409.1': Value(dtype='float64', id=None), '0.013167013167013167.6': Value(dtype='float64', id=None), '0.0131852879944483': Value(dtype='float64', id=None), '0.0131852879944483.1': Value(dtype='float64', id=None), '0.013194444444444444': Value(dtype='float64', id=None), '0.0131852879944483.2': Value(dtype='float64', id=None), '0.01321279554937413': Value(dtype='float64', id=None), '0.013927576601671309': Value(dtype='float64', id=None), '0.013927576601671309.1': Value(dtype='float64', id=None), '0.013927576601671309.2': Value(d
              ...
              dtype='float64', id=None), '0.019667170953101363.4': Value(dtype='float64', id=None), '0.019667170953101363.5': Value(dtype='float64', id=None), '0.019667170953101363.6': Value(dtype='float64', id=None), '0.019667170953101363.7': Value(dtype='float64', id=None), '0.019667170953101363.8': Value(dtype='float64', id=None), '0.019667170953101363.9': Value(dtype='float64', id=None), '0.019667170953101363.10': Value(dtype='float64', id=None), '0.019667170953101363.11': Value(dtype='float64', id=None), '0.01968205904617714': Value(dtype='float64', id=None), '0.019667170953101363.12': Value(dtype='float64', id=None), '0.01968205904617714.1': Value(dtype='float64', id=None), '0.01968205904617714.2': Value(dtype='float64', id=None), '0.020454545454545454': Value(dtype='float64', id=None), '0.020454545454545454.1': Value(dtype='float64', id=None), '0.020454545454545454.2': Value(dtype='float64', id=None), '0.020454545454545454.3': Value(dtype='float64', id=None), '0.020454545454545454.4': Value(dtype='float64', id=None), '0.020454545454545454.5': Value(dtype='float64', id=None), '0.020454545454545454.6': Value(dtype='float64', id=None), '0.020454545454545454.7': Value(dtype='float64', id=None), '0.020454545454545454.8': Value(dtype='float64', id=None), '0.020454545454545454.9': Value(dtype='float64', id=None), '0.020454545454545454.10': Value(dtype='float64', id=None), '0.020454545454545454.11': Value(dtype='float64', id=None), '0.020454545454545454.12': 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 1417, 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 1049, in convert_to_parquet
                  builder.download_and_prepare(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 924, in download_and_prepare
                  self._download_and_prepare(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1000, 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 1741, 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 1872, 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 499 new columns ({'0.0255741127348643.1', '0.02502606882168926', '0.023291925465838508.11', '0.02830188679245283.8', '0.028346456692913385.24', '0.011922503725782414', '0.012462612163509471', '0.022233712512926575.1', '0.028346456692913385.3', '0.023291925465838508', '0.006631927996210327', '0.02776322682032478.3', '0.02338877338877339.1', '0.008177008177008177', '0.01580826109127996', '0.013527054108216433', '0.025587467362924284.1', '0.026687598116169546', '0.02556077203964528.8', '0.02830188679245283.5', '0.028361344537815126.1', '0.012967581047381545.1', '0.014765784114052953.3', '0.0076886112445939455.1', '0.026687598116169546.11', '0.02284527518172378.5', '0.013567839195979899', '0.013164556962025316', '0.015282730514518594.1', '0.02502606882168926.1', '0.02338877338877339', '0.02556077203964528.6', '0.027225130890052355.1', '0.013131313131313131.3', '0.01245019920318725.1', '0.018442622950819672.1', '0.024479166666666666.1', '0.01309823677581864.2', '0.006134969325153374', '0.0057361376673040155', '0.005717008099094807', '0.014758269720101781.5', '0.026687598116169546.14', '0.025587467362924284', '0.011904761904761904', '0.01580826109127996.6', '0.014758269720101781.2', '0.012632642748863061.2', '0.011175898931000973.1', '0.028346456692913385', '0.02284527518172378', '0.014227642276422764.1', '0.026673640167364017', '0.023291925465838508.7', '0.018480492813141684.3', '0.02779234399580493.3', '0.008173076923076924.3', '0.008173076923076924', '0.005248091603053435.1', '0.0200617283950617
              ...
              .012645422357106728', '0.006086142322097378', '0.013171225937183385', '0.028346456692913385.11', '0.011280039234919078', '0.011690209449585971', '0.02556077203964528.7', '0.01354062186559679.1', '0.005671077504725898', '0.013131313131313131.1', '0.026687598116169546.26', '0.024479166666666666', '0.0056657223796034', '0.013171225937183385.1', '0.022233712512926575.6', '0.024479166666666666.5', '0.02007205352547607', '0.0091478093403948', '0.02830188679245283.4', '0.010174418604651164', '0.013171225937183385.4', '0.01580020387359837', '0.02556077203964528.9', '0.02830188679245283.15', '0.01355421686746988', '0.026659696811291166.8', '0.018480492813141684.2', '0.012444001991040319.3', '0.009775171065493646', '0.013157894736842105', '0.006708193579300431.1', '0.014227642276422764', '0.027806925498426022', '0.023291925465838508.4', '0.013691683569979716.2', '0.018480492813141684', '0.02830188679245283.22', '0.0051401869158878505', '0.005245588936576061', '0.028346456692913385.6', '0.026687598116169546.21', '0.025587467362924284.5', '0.028361344537815126.4', '0.010832102412604629', '0.017957927142124165.1', '0.006704980842911878.1', '0.028346456692913385.18', '0.024479166666666666.2', '0.028346456692913385.8', '0.02830188679245283.3', '0.02779234399580493.4', '0.012632642748863061', '0.02830188679245283.17', '0.028346456692913385.21', '0.008687258687258687', '0.026687598116169546.9', '0.011892963330029732.1', '0.022857142857142857', '0.013124684502776375', '0.022857142857142857.2'}) and 499 missing columns ({'0.018628912071535022', '0.020239880059970013.4', '0.010130246020260492.3', '0.01168736303871439.2', '0.010144927536231883.12', '0.021148036253776436.13', '0.019461077844311378.5', '0.015625', '0.018670649738610903.15', '0.020454545454545454.10', '0.01868460388639761.2', '0.011627906976744186.2', '0.020239880059970013.8', '0.02042360060514372.50', '0.02180451127819549', '0.00931899641577061', '0.011670313639679067', '0.020239880059970013', '0.0131852879944483', '0.019461077844311378.4', '0.010144927536231883.9', '0.018670649738610903.16', '0.01944652206432311.17', '0.01003584229390681', '0.01868460388639761.3', '0.02042360060514372.2', '0.020239880059970013.3', '0.017857142857142856.1', '0.01065340909090909.2', '0.01944652206432311.6', '0.013960323291697281', '0.019461077844311378.13', '0.017830609212481426.12', '0.015475313190862197.4', '0.02042360060514372.3', '0.02042360060514372.10', '0.02042360060514372.36', '0.02042360060514372.13', '0.009312320916905445.2', '0.010806916426512969', '0.021148036253776436.20', '0.019461077844311378.9', '0.020454545454545454.8', '0.010660980810234541.2', '0.018615040953090096', '0.02042360060514372.18', '0.02042360060514372.48', '0.020255063765941484.4', '0.02042360060514372.9', '0.01704966641957005.6', '0.009312320916905445.1', '0.014522821576763486', '0.015475313190862197.10', '0.01944652206432311.20', '0.02042360060514372.19', '0.01944652206432311.13', '0.017857142857142856.4', '0.013215859030837005.1', '0.017830609212481426.3', '0.020
              ...
              7714.2', '0.017830609212481426.20', '0.02262443438914027.2', '0.015475313190862197.1', '0.010877447425670777', '0.010706638115631691.1', '0.018670649738610903.14', '0.01167883211678832.3', '0.02042360060514372.8', '0.016260162601626018', '0.017011834319526627.3', '0.019667170953101363.3', '0.02042360060514372.12', '0.010137581462708182.2', '0.020454545454545454.12', '0.01079913606911447', '0.02042360060514372.15', '0.010706638115631691', '0.011871508379888268', '0.021148036253776436.24', '0.01090909090909091', '0.013939838591342627.1', '0.011188811188811189', '0.013186813186813187.1', '0.018670649738610903.12', '0.020454545454545454.2', '0.01968205904617714.1', '0.02260738507912585.2', '0.018628912071535022.7', '0.01944652206432311.12', '0.0111731843575419', '0.021021021021021023', '0.011180992313067784', '0.018628912071535022.1', '0.017830609212481426.19', '0.011661807580174927.2', '0.015475313190862197', '0.016236162361623615', '0.017830609212481426.8', '0.010699001426533523.1', '0.02042360060514372.23', '0.019667170953101363.12', '0.010668563300142247', '0.017817371937639197.3', '0.018656716417910446.1', '0.02180451127819549.23', '0.02260738507912585.3', '0.013980868285504048', '0.015475313190862197.2', '0.01592797783933518', '0.021148036253776436.10', '0.02042360060514372.35', '0.011963406052076003', '0.01704966641957005.1', '0.01314878892733564', '0.017011834319526627.5', '0.018628912071535022.3', '0.01132342533616419', '0.010144927536231883.6', '0.02180451127819549.17'}).
              
              This happened while the csv dataset builder was generating data using
              
              hf://datasets/petrrysavy/krebs/krebs3/threes1.tsv (at revision 229ef67a0e37072643d1ccc215629cefa560b0b0)
              
              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)