Datasets:

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PlMazet

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pretraining_datasets

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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 18 new columns ({'Grouped by Group.10', 'Grouped by Group.11', 'Unnamed: 1', 'Grouped by Group.2', 'Grouped by Group.3', 'Grouped by Group.1', 'Grouped by Group', 'Grouped by Group.7', 'Grouped by Group.9', 'Grouped by Group.13', 'Grouped by Group.5', 'Unnamed: 0', 'Grouped by Group.8', 'Grouped by Group.15', 'Grouped by Group.6', 'Grouped by Group.12', 'Grouped by Group.14', 'Grouped by Group.4'}) and 2 missing columns ({'marker', 'marker_class'}).

This happened while the csv dataset builder was generating data using

hf://datasets/PlMazet/pretraining_datasets/atlas_tableone.csv (at revision 5c4095750ad253243fc88d5b585819b929b51b78), ['hf://datasets/PlMazet/pretraining_datasets@5c4095750ad253243fc88d5b585819b929b51b78/atlas_marker_classes.csv', 'hf://datasets/PlMazet/pretraining_datasets@5c4095750ad253243fc88d5b585819b929b51b78/atlas_tableone.csv', 'hf://datasets/PlMazet/pretraining_datasets@5c4095750ad253243fc88d5b585819b929b51b78/panels/Bodenmiller_BCR_Panel1.csv', 'hf://datasets/PlMazet/pretraining_datasets@5c4095750ad253243fc88d5b585819b929b51b78/panels/SDY1389_CyTOF_Panel1.csv', 'hf://datasets/PlMazet/pretraining_datasets@5c4095750ad253243fc88d5b585819b929b51b78/panels/SDY1658_CyTOF_Panel1.csv', 'hf://datasets/PlMazet/pretraining_datasets@5c4095750ad253243fc88d5b585819b929b51b78/panels/SDY1733_CyTOF_Panel1.csv', 'hf://datasets/PlMazet/pretraining_datasets@5c4095750ad253243fc88d5b585819b929b51b78/panels/SDY1733_CyTOF_Panel2.csv', 'hf://datasets/PlMazet/pretraining_datasets@5c4095750ad253243fc88d5b585819b929b51b78/panels/SDY1998_Flow Cytometry_Panel1.csv', 'hf://datasets/PlMazet/pretraining_datasets@5c4095750ad253243fc88d5b585819b929b51b78/panels/SDY2583_Flow Cytometry_PanelCP10.csv', 'hf://datasets/PlMazet/pretraining_datasets@5c4095750ad253243fc88d5b585819b929b51b78/panels/SDY2583_Flow Cytometry_PanelCP16.csv', 'hf://datasets/PlMazet/pretraining_datasets@5c4095750ad253243fc88d5b585819b929b51b78/panels/SDY2583_Flow Cytometry_PanelCP22.csv', 'hf://datasets/PlMazet/pretraining_datasets@5c4095750ad253243fc88d5b585819b929b51b78/panels/SDY2583_Flow Cytometry_PanelCP23.csv', 'hf://datasets/PlMazet/pretraining_datasets@5c4095750ad253243fc88d5b585819b929b51b78/panels/SDY2583_Flow Cytometry_PanelCP24.csv', 'hf://datasets/PlMazet/pretraining_datasets@5c4095750ad253243fc88d5b585819b929b51b78/panels/SDY2583_Flow Cytometry_PanelCP7.csv', 'hf://datasets/PlMazet/pretraining_datasets@5c4095750ad253243fc88d5b585819b929b51b78/panels/SDY2583_Flow Cytometry_PanelCP8.csv', 'hf://datasets/PlMazet/pretraining_datasets@5c4095750ad253243fc88d5b585819b929b51b78/panels/SDY420_CyTOF_Panel1.csv', 'hf://datasets/PlMazet/pretraining_datasets@5c4095750ad253243fc88d5b585819b929b51b78/panels/SDY702_Flow Cytometry_Panel1.csv', 'hf://datasets/PlMazet/pretraining_datasets@5c4095750ad253243fc88d5b585819b929b51b78/panels/SDY702_Flow Cytometry_Panel2.csv', 'hf://datasets/PlMazet/pretraining_datasets@5c4095750ad253243fc88d5b585819b929b51b78/panels/SDY702_Flow Cytometry_Panel3.csv', 'hf://datasets/PlMazet/pretraining_datasets@5c4095750ad253243fc88d5b585819b929b51b78/panels/SDY702_Flow Cytometry_Panel4.csv', 'hf://datasets/PlMazet/pretraining_datasets@5c4095750ad253243fc88d5b585819b929b51b78/panels/SDY702_Flow Cytometry_Panel5.csv', 'hf://datasets/PlMazet/pretraining_datasets@5c4095750ad253243fc88d5b585819b929b51b78/panels/SDY702_Flow Cytometry_Panel6.csv', 'hf://datasets/PlMazet/pretraining_datasets@5c4095750ad253243fc88d5b585819b929b51b78/panels/SDY702_Flow Cytometry_Panel7.csv', 'hf://datasets/PlMazet/pretraining_datasets@5c4095750ad253243fc88d5b585819b929b51b78/panels/SDY702_Flow Cytometry_Panel8.csv', 'hf://datasets/PlMazet/pretraining_datasets@5c4095750ad253243fc88d5b585819b929b51b78/panels/ccRCC_Immune_Atlas_CyTOF_TAM.csv', 'hf://datasets/PlMazet/pretraining_datasets@5c4095750ad253243fc88d5b585819b929b51b78/panels/ccRCC_Immune_Atlas_CyTOF_Tcells.csv', 'hf://datasets/PlMazet/pretraining_datasets@5c4095750ad253243fc88d5b585819b929b51b78/panels/gb83sywsjc_CyTOF_Panel1.csv', 'hf://datasets/PlMazet/pretraining_datasets@5c4095750ad253243fc88d5b585819b929b51b78/panels/jk8c3c3nmz_CyTOF_Lymphoid.csv', 'hf://datasets/PlMazet/pretraining_datasets@5c4095750ad253243fc88d5b585819b929b51b78/panels/jk8c3c3nmz_CyTOF_Myeloid.csv', 'hf://datasets/PlMazet/pretraining_datasets@5c4095750ad253243fc88d5b585819b929b51b78/panels/jk8c3c3nmz_Flow Cytometry_Panel1.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 1848, 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 2378, in table_cast
                  return cast_table_to_schema(table, schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2306, in cast_table_to_schema
                  raise CastError(
                  ...<3 lines>...
                  )
              datasets.table.CastError: Couldn't cast
              Unnamed: 0: string
              Unnamed: 1: string
              Grouped by Group: string
              Grouped by Group.1: string
              Grouped by Group.2: string
              Grouped by Group.3: string
              Grouped by Group.4: string
              Grouped by Group.5: string
              Grouped by Group.6: string
              Grouped by Group.7: string
              Grouped by Group.8: string
              Grouped by Group.9: string
              Grouped by Group.10: string
              Grouped by Group.11: string
              Grouped by Group.12: string
              Grouped by Group.13: string
              Grouped by Group.14: string
              Grouped by Group.15: string
              -- schema metadata --
              pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 2702
              to
              {'marker': Value('string'), 'marker_class': 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 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 1694, 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 1850, 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 18 new columns ({'Grouped by Group.10', 'Grouped by Group.11', 'Unnamed: 1', 'Grouped by Group.2', 'Grouped by Group.3', 'Grouped by Group.1', 'Grouped by Group', 'Grouped by Group.7', 'Grouped by Group.9', 'Grouped by Group.13', 'Grouped by Group.5', 'Unnamed: 0', 'Grouped by Group.8', 'Grouped by Group.15', 'Grouped by Group.6', 'Grouped by Group.12', 'Grouped by Group.14', 'Grouped by Group.4'}) and 2 missing columns ({'marker', 'marker_class'}).
              
              This happened while the csv dataset builder was generating data using
              
              hf://datasets/PlMazet/pretraining_datasets/atlas_tableone.csv (at revision 5c4095750ad253243fc88d5b585819b929b51b78), ['hf://datasets/PlMazet/pretraining_datasets@5c4095750ad253243fc88d5b585819b929b51b78/atlas_marker_classes.csv', 'hf://datasets/PlMazet/pretraining_datasets@5c4095750ad253243fc88d5b585819b929b51b78/atlas_tableone.csv', 'hf://datasets/PlMazet/pretraining_datasets@5c4095750ad253243fc88d5b585819b929b51b78/panels/Bodenmiller_BCR_Panel1.csv', 'hf://datasets/PlMazet/pretraining_datasets@5c4095750ad253243fc88d5b585819b929b51b78/panels/SDY1389_CyTOF_Panel1.csv', 'hf://datasets/PlMazet/pretraining_datasets@5c4095750ad253243fc88d5b585819b929b51b78/panels/SDY1658_CyTOF_Panel1.csv', 'hf://datasets/PlMazet/pretraining_datasets@5c4095750ad253243fc88d5b585819b929b51b78/panels/SDY1733_CyTOF_Panel1.csv', 'hf://datasets/PlMazet/pretraining_datasets@5c4095750ad253243fc88d5b585819b929b51b78/panels/SDY1733_CyTOF_Panel2.csv', 'hf://datasets/PlMazet/pretraining_datasets@5c4095750ad253243fc88d5b585819b929b51b78/panels/SDY1998_Flow Cytometry_Panel1.csv', 'hf://datasets/PlMazet/pretraining_datasets@5c4095750ad253243fc88d5b585819b929b51b78/panels/SDY2583_Flow Cytometry_PanelCP10.csv', 'hf://datasets/PlMazet/pretraining_datasets@5c4095750ad253243fc88d5b585819b929b51b78/panels/SDY2583_Flow Cytometry_PanelCP16.csv', 'hf://datasets/PlMazet/pretraining_datasets@5c4095750ad253243fc88d5b585819b929b51b78/panels/SDY2583_Flow Cytometry_PanelCP22.csv', 'hf://datasets/PlMazet/pretraining_datasets@5c4095750ad253243fc88d5b585819b929b51b78/panels/SDY2583_Flow Cytometry_PanelCP23.csv', 'hf://datasets/PlMazet/pretraining_datasets@5c4095750ad253243fc88d5b585819b929b51b78/panels/SDY2583_Flow Cytometry_PanelCP24.csv', 'hf://datasets/PlMazet/pretraining_datasets@5c4095750ad253243fc88d5b585819b929b51b78/panels/SDY2583_Flow Cytometry_PanelCP7.csv', 'hf://datasets/PlMazet/pretraining_datasets@5c4095750ad253243fc88d5b585819b929b51b78/panels/SDY2583_Flow Cytometry_PanelCP8.csv', 'hf://datasets/PlMazet/pretraining_datasets@5c4095750ad253243fc88d5b585819b929b51b78/panels/SDY420_CyTOF_Panel1.csv', 'hf://datasets/PlMazet/pretraining_datasets@5c4095750ad253243fc88d5b585819b929b51b78/panels/SDY702_Flow Cytometry_Panel1.csv', 'hf://datasets/PlMazet/pretraining_datasets@5c4095750ad253243fc88d5b585819b929b51b78/panels/SDY702_Flow Cytometry_Panel2.csv', 'hf://datasets/PlMazet/pretraining_datasets@5c4095750ad253243fc88d5b585819b929b51b78/panels/SDY702_Flow Cytometry_Panel3.csv', 'hf://datasets/PlMazet/pretraining_datasets@5c4095750ad253243fc88d5b585819b929b51b78/panels/SDY702_Flow Cytometry_Panel4.csv', 'hf://datasets/PlMazet/pretraining_datasets@5c4095750ad253243fc88d5b585819b929b51b78/panels/SDY702_Flow Cytometry_Panel5.csv', 'hf://datasets/PlMazet/pretraining_datasets@5c4095750ad253243fc88d5b585819b929b51b78/panels/SDY702_Flow Cytometry_Panel6.csv', 'hf://datasets/PlMazet/pretraining_datasets@5c4095750ad253243fc88d5b585819b929b51b78/panels/SDY702_Flow Cytometry_Panel7.csv', 'hf://datasets/PlMazet/pretraining_datasets@5c4095750ad253243fc88d5b585819b929b51b78/panels/SDY702_Flow Cytometry_Panel8.csv', 'hf://datasets/PlMazet/pretraining_datasets@5c4095750ad253243fc88d5b585819b929b51b78/panels/ccRCC_Immune_Atlas_CyTOF_TAM.csv', 'hf://datasets/PlMazet/pretraining_datasets@5c4095750ad253243fc88d5b585819b929b51b78/panels/ccRCC_Immune_Atlas_CyTOF_Tcells.csv', 'hf://datasets/PlMazet/pretraining_datasets@5c4095750ad253243fc88d5b585819b929b51b78/panels/gb83sywsjc_CyTOF_Panel1.csv', 'hf://datasets/PlMazet/pretraining_datasets@5c4095750ad253243fc88d5b585819b929b51b78/panels/jk8c3c3nmz_CyTOF_Lymphoid.csv', 'hf://datasets/PlMazet/pretraining_datasets@5c4095750ad253243fc88d5b585819b929b51b78/panels/jk8c3c3nmz_CyTOF_Myeloid.csv', 'hf://datasets/PlMazet/pretraining_datasets@5c4095750ad253243fc88d5b585819b929b51b78/panels/jk8c3c3nmz_Flow Cytometry_Panel1.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)