The full dataset viewer is not available (click to read why). Only showing a preview of the rows.
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 2 new columns ({'dna_sequence', 'otu_id'}) and 2 missing columns ({'label', 'sid'}).
This happened while the csv dataset builder was generating data using
hf://datasets/hugging-science/AI4FA-Gadir/processed/dna_sequences/gadir_all_months/SRS4430061.csv (at revision 4ff68cf8756acf0022dde2fd1216bc3e4acd9028)
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 1831, in _prepare_split_single
writer.write_table(table)
File "/usr/local/lib/python3.12/site-packages/datasets/arrow_writer.py", line 714, in write_table
pa_table = table_cast(pa_table, self._schema)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2272, in table_cast
return cast_table_to_schema(table, schema)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2218, in cast_table_to_schema
raise CastError(
datasets.table.CastError: Couldn't cast
otu_id: string
dna_sequence: string
-- schema metadata --
pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 496
to
{'sid': Value('string'), 'label': 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 1339, 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 972, in convert_to_parquet
builder.download_and_prepare(
File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 894, in download_and_prepare
self._download_and_prepare(
File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 970, in _download_and_prepare
self._prepare_split(split_generator, **prepare_split_kwargs)
File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1702, 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 1833, 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 2 new columns ({'dna_sequence', 'otu_id'}) and 2 missing columns ({'label', 'sid'}).
This happened while the csv dataset builder was generating data using
hf://datasets/hugging-science/AI4FA-Gadir/processed/dna_sequences/gadir_all_months/SRS4430061.csv (at revision 4ff68cf8756acf0022dde2fd1216bc3e4acd9028)
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.
sid
string | label
int64 |
|---|---|
SRS4430387
| 1
|
SRS4430385
| 1
|
SRS4430357
| 0
|
SRS4430338
| 1
|
SRS4430304
| 0
|
SRS4430228
| 0
|
SRS4430192
| 1
|
SRS4430182
| 0
|
SRS4430163
| 0
|
SRS4430121
| 1
|
SRS4430110
| 1
|
SRS4430102
| 0
|
SRS4430080
| 0
|
SRS4430065
| 1
|
SRS4430384
| 1
|
SRS4430369
| 0
|
SRS4430354
| 0
|
SRS4430345
| 1
|
SRS4430340
| 0
|
SRS4430339
| 1
|
SRS4430337
| 0
|
SRS4430336
| 0
|
SRS4430335
| 1
|
SRS4430334
| 1
|
SRS4430323
| 1
|
SRS4430300
| 1
|
SRS4430291
| 0
|
SRS4430278
| 1
|
SRS4430276
| 1
|
SRS4430273
| 1
|
SRS4430268
| 1
|
SRS4430257
| 1
|
SRS4430223
| 1
|
SRS4430205
| 1
|
SRS4430189
| 1
|
SRS4430188
| 1
|
SRS4430179
| 1
|
SRS4430178
| 1
|
SRS4430173
| 0
|
SRS4430170
| 0
|
SRS4430115
| 0
|
SRS4430114
| 1
|
SRS4430112
| 0
|
SRS4430109
| 1
|
SRS4430083
| 0
|
SRS4430081
| 0
|
SRS4430071
| 1
|
SRS4430070
| 1
|
SRS4430068
| 1
|
SRS4430386
| 1
|
SRS4430406
| 1
|
SRS4430382
| 1
|
SRS4430377
| 1
|
SRS4430373
| 1
|
SRS4430367
| 0
|
SRS4430366
| 1
|
SRS4430364
| 1
|
SRS4430363
| 1
|
SRS4430360
| 1
|
SRS4430358
| 0
|
SRS4430353
| 1
|
SRS4430346
| 1
|
SRS4430343
| 1
|
SRS4430342
| 0
|
SRS4430341
| 0
|
SRS4430328
| 1
|
SRS4430324
| 1
|
SRS4430305
| 0
|
SRS4430302
| 1
|
SRS4430299
| 1
|
SRS4430293
| 0
|
SRS4430290
| 1
|
SRS4430289
| 1
|
SRS4430288
| 1
|
SRS4430284
| 1
|
SRS4430282
| 0
|
SRS4430275
| 0
|
SRS4430270
| 0
|
SRS4430255
| 1
|
SRS4430241
| 1
|
SRS4430230
| 0
|
SRS4430224
| 1
|
SRS4430218
| 1
|
SRS4430195
| 1
|
SRS4430185
| 1
|
SRS4430184
| 1
|
SRS4430180
| 1
|
SRS4430176
| 0
|
SRS4430177
| 0
|
SRS4430166
| 0
|
SRS4430130
| 1
|
SRS4430129
| 1
|
SRS4430127
| 1
|
SRS4430108
| 0
|
SRS4430107
| 1
|
SRS4430100
| 0
|
SRS4430079
| 0
|
SRS4430078
| 0
|
SRS4430076
| 1
|
SRS4430073
| 1
|
Food Allergy Microbiome Dataset (Experimental)
Dataset Summary
This is an experimental microbiome dataset designed for exploratory research in food allergy classification. The dataset contains multiple data modalities (DNA embeddings, microbiome embeddings, raw DNA sequences) collected longitudinally at several timepoints.
Warning: This dataset is experimental. Its structure is frozen for ongoing research, and it is not ready for benchmarking.
Dataset Structure
The dataset is organized by data type and timepoint:
βββ metadata
β βββ gadir_all_months.csv
β βββ gadir_preprocessed_0-6_months.csv
β βββ gadir_preprocessed_12-18_months.csv
β βββ gadir_preprocessed_18-24_months.csv
β βββ gadir_preprocessed_24-30_months.csv
β βββ gadir_preprocessed_30+_months.csv
β βββ gadir_preprocessed_6-12_months.csv
βββ processed
β βββ dna_embeddings
β β βββ gadir_all_months
β β β βββ dna_embeddings.h5
β β βββ gadir_preprocessed_0-6_months
β β β βββ dna_embeddings.h5
β β βββ gadir_preprocessed_12-18_months
β β β βββ dna_embeddings.h5
β β βββ gadir_preprocessed_18-24_months
β β β βββ dna_embeddings.h5
β β βββ gadir_preprocessed_24-30_months
β β β βββ dna_embeddings.h5
β β βββ gadir_preprocessed_30+_months
β β β βββ dna_embeddings.h5
β β βββ gadir_preprocessed_6-12_months
β β βββ dna_embeddings.h5
β βββ dna_sequences
β β βββ gadir_all_months
β β β βββ SRS4430061.csv
...
β β βββ gadir_preprocessed_0-6_months
β β β βββ SRS4430065.csv
...
β β βββ gadir_preprocessed_12-18_months
β β β βββ SRS4430062.csv
...
β β βββ gadir_preprocessed_18-24_months
β β β βββ SRS4430061.csv
...
β β βββ gadir_preprocessed_24-30_months
β β β βββ SRS4430075.csv
...
β β βββ gadir_preprocessed_30+_months
β β β βββ SRS4430067.csv
...
β β βββ gadir_preprocessed_6-12_months
β β βββ SRS4430068.csv
...
β βββ microbiome_embeddings
β βββ gadir_all_months
β β βββ microbiome_embeddings.h5
β βββ gadir_preprocessed_0-6_months
β β βββ microbiome_embeddings.h5
β βββ gadir_preprocessed_12-18_months
β β βββ microbiome_embeddings.h5
β βββ gadir_preprocessed_18-24_months
β β βββ microbiome_embeddings.h5
β βββ gadir_preprocessed_24-30_months
β β βββ microbiome_embeddings.h5
β βββ gadir_preprocessed_30+_months
β β βββ microbiome_embeddings.h5
β βββ gadir_preprocessed_6-12_months
β βββ microbiome_embeddings.h5
βββ README.md
- DNA embeddings:
.h5files with embedding vectors derived from DNA sequences. - Microbiome embeddings:
.h5files containing microbiome feature vectors. - DNA sequences: raw
.csvfiles representing sequences or processed features.
Each timepoint contains multiple samples per subject.
File names (e.g., ERS4519281.csv) serve as sample IDs. Subject IDs and mappings are implicit; users must manage them carefully.
Intended Use
- Task: Exploratory classification of food allergies.
- Users are expected to define their own train/test splits.
- Critical: Do not split samples randomly; multiple samples per subject exist. Splits should be done at the subject level to avoid data leakage.
Data Notes
- Longitudinal: Samples are collected at multiple months (1, 2, 3).
- Multi-modal: Embeddings and sequences are provided separately; users may combine them as needed.
- No labels are embedded per file. Labels must be handled separately or mapped from your internal records.
- This dataset is research-focused, not benchmark-ready.
License
This experimental dataset is currently released under Apache License 2.0
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