Hugging Face's logo

Datasets:
meganariley
/
us-national-parks-biodiversity

Tasks:
Other
Modalities:
Tabular
Text
Formats:
parquet
Languages:
English
Size:
1M - 10M
Tags:
biodiversity
national-parks
wildlife
flora
fauna
iNaturalist
Libraries:
Datasets
pandas
Polars
License:
Dataset card Data Studio Files
xet
 Community
1
Dataset Viewer
Auto-converted to Parquet Duplicate
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
park_name: large_string
park_full_name: large_string
park_place_id: int64
park_state: large_string
park_biome: large_string
taxon_id: int64
taxon_name: large_string
common_name: large_string
kingdom: large_string
iconic_taxon: large_string
taxon_rank: large_string
year: int64
month: int64
obs_count: int64
obs_count_baseline: int64
trend_direction: large_string
first_observed_year: double
peak_month_current: int64
peak_month_baseline: int64
peak_month_shift_days: int64
confidence: large_string
photo_url: large_string
inat_url: large_string
last_updated: large_string
-- schema metadata --
pandas: '{"index_columns": [], "column_indexes": [], "columns": [{"name":' + 2973
to
{'park_name': Value('large_string'), 'park_full_name': Value('large_string'), 'park_place_id': Value('int64'), 'park_state': Value('large_string'), 'park_biome': Value('large_string'), 'taxon_id': Value('int64'), 'taxon_name': Value('large_string'), 'common_name': Value('large_string'), 'kingdom': Value('large_string'), 'iconic_taxon': Value('large_string'), 'taxon_rank': Value('large_string'), 'obs_count_total': Value('int64'), 'peak_months': Value('large_string'), 'peak_seasons': Value('large_string'), 'monthly_counts': Value('large_string'), 'confidence': Value('large_string'), 'photo_url': Value('large_string'), 'wikipedia_url': Value('large_string'), 'inat_url': Value('large_string'), 'collected_at': Value('large_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/parquet/parquet.py", line 220, in _generate_tables
                  yield Key(file_idx, batch_idx), self._cast_table(pa_table)
                                                  ~~~~~~~~~~~~~~~~^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/parquet/parquet.py", line 156, 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
              park_name: large_string
              park_full_name: large_string
              park_place_id: int64
              park_state: large_string
              park_biome: large_string
              taxon_id: int64
              taxon_name: large_string
              common_name: large_string
              kingdom: large_string
              iconic_taxon: large_string
              taxon_rank: large_string
              year: int64
              month: int64
              obs_count: int64
              obs_count_baseline: int64
              trend_direction: large_string
              first_observed_year: double
              peak_month_current: int64
              peak_month_baseline: int64
              peak_month_shift_days: int64
              confidence: large_string
              photo_url: large_string
              inat_url: large_string
              last_updated: large_string
              -- schema metadata --
              pandas: '{"index_columns": [], "column_indexes": [], "columns": [{"name":' + 2973
              to
              {'park_name': Value('large_string'), 'park_full_name': Value('large_string'), 'park_place_id': Value('int64'), 'park_state': Value('large_string'), 'park_biome': Value('large_string'), 'taxon_id': Value('int64'), 'taxon_name': Value('large_string'), 'common_name': Value('large_string'), 'kingdom': Value('large_string'), 'iconic_taxon': Value('large_string'), 'taxon_rank': Value('large_string'), 'obs_count_total': Value('int64'), 'peak_months': Value('large_string'), 'peak_seasons': Value('large_string'), 'monthly_counts': Value('large_string'), 'confidence': Value('large_string'), 'photo_url': Value('large_string'), 'wikipedia_url': Value('large_string'), 'inat_url': Value('large_string'), 'collected_at': Value('large_string')}
              because column names don't match

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.

🌿 US National Park Biodiversity Atlas

Community-verified species observations from iNaturalist, structured by national park, kingdom, and season. Built as the data backbone for the park-wildlife-atlas Space.

V1 Parks (5 parks)

Park State Biome
Denali AK Subarctic tundra / boreal forest
Big Bend TX Chihuahuan desert / riparian
Death Valley CA/NV Mojave/Great Basin desert
Olympic WA Temperate rainforest / alpine
Yosemite CA Sierra Nevada montane / subalpine

Schema

Column Type Description
park_name string Short park name
park_full_name string Official NPS name
park_place_id int iNaturalist place ID
park_state string State abbreviation(s)
park_biome string Biome / ecosystem description
taxon_id int iNaturalist taxon ID
taxon_name string Scientific name
common_name string Common name (if available)
kingdom string bird / mammal / plant / fungi / reptile / amphibian / fish / insect / arachnid
iconic_taxon string iNaturalist iconic taxon (e.g. Aves, Plantae)
taxon_rank string species / genus / family / etc.
obs_count_total int Total research-grade observations in park
peak_months JSON list Top 3 months by observation count (1–12)
peak_seasons JSON list Derived seasons: winter / spring / summer / fall
monthly_counts JSON dict Full {"1": N, "2": N, … "12": N} distribution
confidence string high (≥100 obs) / medium (≥20) / low (<20)
photo_url string iNaturalist default photo (medium)
wikipedia_url string Wikipedia link if available
inat_url string iNaturalist taxon page
collected_at string ISO timestamp of collection

Versioning

  • v1 — 5 parks (Denali, Big Bend, Death Valley, Olympic, Yosemite), kingdoms: bird/mammal/reptile/amphibian/fish/insect/arachnid/plant/fungi
  • v2 — 20 parks (planned), ML trait tags, vision-verified confidence scores
  • v3 — All 63 NPS units, fine-grained habitat zones within parks, encounter probability model

Source

All observation data sourced from iNaturalist under CC-BY-NC licensing. Only research quality grade observations are included (community-verified).

Citation 

@dataset{riley2026npbio,
  author    = {Megan Riley},
  title     = {US National Park Biodiversity Atlas},
  year      = {2026},
  publisher = {Hugging Face},
  url       = {https://huggingface.co/datasets/meganariley/us-national-parks-biodiversity}
}
Downloads last month
127
Number of rows:
2,323,944
Total file size:
10.7 MB

Space using meganariley/us-national-parks-biodiversity 1