Dataset Viewer
The dataset viewer is not available for this split.
Cannot load the dataset split (in streaming mode) to extract the first rows.
Error code: StreamingRowsError
Exception: CastError
Message: Couldn't cast
decimalLatitude: double
decimalLongitude: double
year: int64
month: int64
eventDate: timestamp[s]
country: string
stateProvince: string
basisOfRecord: string
gbifID: string
Chloroperla tripunctata: struct<usageKey: int64, n_records: int64, status: string>
child 0, usageKey: int64
child 1, n_records: int64
child 2, status: string
Tamias sibiricus: struct<usageKey: int64, n_records: int64, status: string>
child 0, usageKey: int64
child 1, n_records: int64
child 2, status: string
Carpinus betulus: struct<usageKey: int64, n_records: int64, status: string>
child 0, usageKey: int64
child 1, n_records: int64
child 2, status: string
Populus nigra: struct<usageKey: int64, n_records: int64, status: string>
child 0, usageKey: int64
child 1, n_records: int64
child 2, status: string
Typhaeus typhoeus: struct<usageKey: int64, n_records: int64, status: string>
child 0, usageKey: int64
child 1, n_records: int64
child 2, status: string
Turdus merula: struct<usageKey: int64, n_records: int64, status: string>
child 0, usageKey: int64
child 1, n_records: int64
child 2, status: string
Vanessa cardui: struct<usageKey: int64, n_records: int64, status: string>
child 0, usageKey: int64
child 1, n_records: int64
child 2, status: string
Operophtera brumata: struct<usageKey: int64, n_records: int64, status: string>
child 0, usageKey: int64
child 1, n_records: int64
child 2, status: string
Procloeon bifidum: struct<usageKey: int64, n_records: int64, status:
...
ageKey: int64
child 1, n_records: int64
child 2, status: string
Canis lupus: struct<usageKey: int64, n_records: int64, status: string>
child 0, usageKey: int64
child 1, n_records: int64
child 2, status: string
Apodemus sylvaticus: struct<usageKey: int64, n_records: int64, status: string>
child 0, usageKey: int64
child 1, n_records: int64
child 2, status: string
Athous haemorrhoidalis: struct<usageKey: int64, n_records: int64, status: string>
child 0, usageKey: int64
child 1, n_records: int64
child 2, status: string
Anthophora plumipes: struct<usageKey: int64, n_records: int64, status: string>
child 0, usageKey: int64
child 1, n_records: int64
child 2, status: string
Ceratophyllum demersum: struct<usageKey: int64, n_records: int64, status: string>
child 0, usageKey: int64
child 1, n_records: int64
child 2, status: string
Vespertilio murinus: struct<usageKey: int64, n_records: int64, status: string>
child 0, usageKey: int64
child 1, n_records: int64
child 2, status: string
Cotesia glomerata: struct<usageKey: int64, n_records: int64, status: string>
child 0, usageKey: int64
child 1, n_records: int64
child 2, status: string
Agrotis segetum: struct<usageKey: int64, n_records: int64, status: string>
child 0, usageKey: int64
child 1, n_records: int64
child 2, status: string
Cenococcum geophilum: struct<usageKey: int64, n_records: int64, status: string>
child 0, usageKey: int64
child 1, n_records: int64
child 2, status: string
to
{'Parus major': {'usageKey': Value('int64'), 'n_records': Value('int64'), 'status': Value('string')}, 'Cyanistes caeruleus': {'usageKey': Value('int64'), 'n_records': Value('int64'), 'status': Value('string')}, 'Periparus ater': {'usageKey': Value('int64'), 'n_records': Value('int64'), 'status': Value('string')}, 'Lophophanes cristatus': {'usageKey': Value('int64'), 'n_records': Value('int64'), 'status': Value('string')}, 'Poecile palustris': {'usageKey': Value('int64'), 'n_records': Value('int64'), 'status': Value('string')}, 'Poecile montanus': {'usageKey': Value('int64'), 'n_records': Value('int64'), 'status': Value('string')}, 'Parus lugubris': {'usageKey': Value('int64'), 'n_records': Value('int64'), 'status': Value('string')}, 'Cyanistes cyanus': {'usageKey': Value('int64'), 'n_records': Value('int64'), 'status': Value('string')}, 'Phylloscopus collybita': {'usageKey': Value('int64'), 'n_records': Value('int64'), 'status': Value('string')}, 'Phylloscopus trochilus': {'usageKey': Value('int64'), 'n_records': Value('int64'), 'status': Value('string')}, 'Phylloscopus sibilatrix': {'usageKey': Value('int64'), 'n_records': Value('int64'), 'status': Value('string')}, 'Phylloscopus bonelli': {'usageKey': Value('int64'), 'n_records': Value('int64'), 'status': Value('string')}, 'Sylvia atricapilla': {'usageKey': Value('int64'), 'n_records': Value('int64'), 'status': Value('string')}, 'Sylvia borin': {'usageKey': Value('int64'), 'n_records': Value('int64'), 'status': Value('strin
...
'usageKey': Value('int64'), 'n_records': Value('int64'), 'status': Value('string')}, 'Inonotus hispidus': {'usageKey': Value('int64'), 'n_records': Value('int64'), 'status': Value('string')}, 'Pleurotus ostreatus': {'usageKey': Value('int64'), 'n_records': Value('int64'), 'status': Value('string')}, 'Armillaria mellea': {'usageKey': Value('int64'), 'n_records': Value('int64'), 'status': Value('string')}, 'Hericium erinaceus': {'usageKey': Value('int64'), 'n_records': Value('int64'), 'status': Value('string')}, 'Meripilus giganteus': {'usageKey': Value('int64'), 'n_records': Value('int64'), 'status': Value('string')}, 'Grifola frondosa': {'usageKey': Value('int64'), 'n_records': Value('int64'), 'status': Value('string')}, 'Polyporus squamosus': {'usageKey': Value('int64'), 'n_records': Value('int64'), 'status': Value('string')}, 'Fistulina hepatica': {'usageKey': Value('int64'), 'n_records': Value('int64'), 'status': Value('string')}, 'Piptoporus betulinus': {'usageKey': Value('int64'), 'n_records': Value('int64'), 'status': Value('string')}, 'Bjerkandera adusta': {'usageKey': Value('int64'), 'n_records': Value('int64'), 'status': Value('string')}, 'Schizophyllum commune': {'usageKey': Value('int64'), 'n_records': Value('int64'), 'status': Value('string')}, 'Auricularia auricula-judae': {'usageKey': Value('int64'), 'n_records': Value('int64'), 'status': Value('string')}, 'Xylaria polymorpha': {'usageKey': Value('int64'), 'n_records': Value('int64'), 'status': Value('string')}}
because column names don't match
Traceback: Traceback (most recent call last):
File "/src/services/worker/src/worker/utils.py", line 147, in get_rows_or_raise
return get_rows(
dataset=dataset,
...<4 lines>...
column_names=column_names,
)
File "/src/libs/libcommon/src/libcommon/utils.py", line 272, in decorator
return func(*args, **kwargs)
File "/src/services/worker/src/worker/utils.py", line 127, in get_rows
rows_plus_one = list(itertools.islice(safe_iter(ds, dataset=dataset), rows_max_number + 1))
File "/src/services/worker/src/worker/utils.py", line 478, in safe_iter
yield from ds.decode(False) if ds.features else ds
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2818, in __iter__
for key, example in ex_iterable:
^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2355, in __iter__
for key, pa_table in self._iter_arrow():
~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2380, in _iter_arrow
for key, pa_table in self.ex_iterable._iter_arrow():
~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 536, in _iter_arrow
for key, pa_table in iterator:
^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 419, in _iter_arrow
for key, pa_table in self.generate_tables_fn(**gen_kwags):
~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 343, in _generate_tables
self._cast_table(pa_table, json_field_paths=json_field_paths),
~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 132, in _cast_table
pa_table = table_cast(pa_table, self.info.features.arrow_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
decimalLatitude: double
decimalLongitude: double
year: int64
month: int64
eventDate: timestamp[s]
country: string
stateProvince: string
basisOfRecord: string
gbifID: string
Chloroperla tripunctata: struct<usageKey: int64, n_records: int64, status: string>
child 0, usageKey: int64
child 1, n_records: int64
child 2, status: string
Tamias sibiricus: struct<usageKey: int64, n_records: int64, status: string>
child 0, usageKey: int64
child 1, n_records: int64
child 2, status: string
Carpinus betulus: struct<usageKey: int64, n_records: int64, status: string>
child 0, usageKey: int64
child 1, n_records: int64
child 2, status: string
Populus nigra: struct<usageKey: int64, n_records: int64, status: string>
child 0, usageKey: int64
child 1, n_records: int64
child 2, status: string
Typhaeus typhoeus: struct<usageKey: int64, n_records: int64, status: string>
child 0, usageKey: int64
child 1, n_records: int64
child 2, status: string
Turdus merula: struct<usageKey: int64, n_records: int64, status: string>
child 0, usageKey: int64
child 1, n_records: int64
child 2, status: string
Vanessa cardui: struct<usageKey: int64, n_records: int64, status: string>
child 0, usageKey: int64
child 1, n_records: int64
child 2, status: string
Operophtera brumata: struct<usageKey: int64, n_records: int64, status: string>
child 0, usageKey: int64
child 1, n_records: int64
child 2, status: string
Procloeon bifidum: struct<usageKey: int64, n_records: int64, status:
...
ageKey: int64
child 1, n_records: int64
child 2, status: string
Canis lupus: struct<usageKey: int64, n_records: int64, status: string>
child 0, usageKey: int64
child 1, n_records: int64
child 2, status: string
Apodemus sylvaticus: struct<usageKey: int64, n_records: int64, status: string>
child 0, usageKey: int64
child 1, n_records: int64
child 2, status: string
Athous haemorrhoidalis: struct<usageKey: int64, n_records: int64, status: string>
child 0, usageKey: int64
child 1, n_records: int64
child 2, status: string
Anthophora plumipes: struct<usageKey: int64, n_records: int64, status: string>
child 0, usageKey: int64
child 1, n_records: int64
child 2, status: string
Ceratophyllum demersum: struct<usageKey: int64, n_records: int64, status: string>
child 0, usageKey: int64
child 1, n_records: int64
child 2, status: string
Vespertilio murinus: struct<usageKey: int64, n_records: int64, status: string>
child 0, usageKey: int64
child 1, n_records: int64
child 2, status: string
Cotesia glomerata: struct<usageKey: int64, n_records: int64, status: string>
child 0, usageKey: int64
child 1, n_records: int64
child 2, status: string
Agrotis segetum: struct<usageKey: int64, n_records: int64, status: string>
child 0, usageKey: int64
child 1, n_records: int64
child 2, status: string
Cenococcum geophilum: struct<usageKey: int64, n_records: int64, status: string>
child 0, usageKey: int64
child 1, n_records: int64
child 2, status: string
to
{'Parus major': {'usageKey': Value('int64'), 'n_records': Value('int64'), 'status': Value('string')}, 'Cyanistes caeruleus': {'usageKey': Value('int64'), 'n_records': Value('int64'), 'status': Value('string')}, 'Periparus ater': {'usageKey': Value('int64'), 'n_records': Value('int64'), 'status': Value('string')}, 'Lophophanes cristatus': {'usageKey': Value('int64'), 'n_records': Value('int64'), 'status': Value('string')}, 'Poecile palustris': {'usageKey': Value('int64'), 'n_records': Value('int64'), 'status': Value('string')}, 'Poecile montanus': {'usageKey': Value('int64'), 'n_records': Value('int64'), 'status': Value('string')}, 'Parus lugubris': {'usageKey': Value('int64'), 'n_records': Value('int64'), 'status': Value('string')}, 'Cyanistes cyanus': {'usageKey': Value('int64'), 'n_records': Value('int64'), 'status': Value('string')}, 'Phylloscopus collybita': {'usageKey': Value('int64'), 'n_records': Value('int64'), 'status': Value('string')}, 'Phylloscopus trochilus': {'usageKey': Value('int64'), 'n_records': Value('int64'), 'status': Value('string')}, 'Phylloscopus sibilatrix': {'usageKey': Value('int64'), 'n_records': Value('int64'), 'status': Value('string')}, 'Phylloscopus bonelli': {'usageKey': Value('int64'), 'n_records': Value('int64'), 'status': Value('string')}, 'Sylvia atricapilla': {'usageKey': Value('int64'), 'n_records': Value('int64'), 'status': Value('string')}, 'Sylvia borin': {'usageKey': Value('int64'), 'n_records': Value('int64'), 'status': Value('strin
...
'usageKey': Value('int64'), 'n_records': Value('int64'), 'status': Value('string')}, 'Inonotus hispidus': {'usageKey': Value('int64'), 'n_records': Value('int64'), 'status': Value('string')}, 'Pleurotus ostreatus': {'usageKey': Value('int64'), 'n_records': Value('int64'), 'status': Value('string')}, 'Armillaria mellea': {'usageKey': Value('int64'), 'n_records': Value('int64'), 'status': Value('string')}, 'Hericium erinaceus': {'usageKey': Value('int64'), 'n_records': Value('int64'), 'status': Value('string')}, 'Meripilus giganteus': {'usageKey': Value('int64'), 'n_records': Value('int64'), 'status': Value('string')}, 'Grifola frondosa': {'usageKey': Value('int64'), 'n_records': Value('int64'), 'status': Value('string')}, 'Polyporus squamosus': {'usageKey': Value('int64'), 'n_records': Value('int64'), 'status': Value('string')}, 'Fistulina hepatica': {'usageKey': Value('int64'), 'n_records': Value('int64'), 'status': Value('string')}, 'Piptoporus betulinus': {'usageKey': Value('int64'), 'n_records': Value('int64'), 'status': Value('string')}, 'Bjerkandera adusta': {'usageKey': Value('int64'), 'n_records': Value('int64'), 'status': Value('string')}, 'Schizophyllum commune': {'usageKey': Value('int64'), 'n_records': Value('int64'), 'status': Value('string')}, 'Auricularia auricula-judae': {'usageKey': Value('int64'), 'n_records': Value('int64'), 'status': Value('string')}, 'Xylaria polymorpha': {'usageKey': Value('int64'), 'n_records': Value('int64'), 'status': Value('string')}}
because column names don't matchNeed help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
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