Datasets:

NoraResearchLab
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cmibs-critical-metals-black-shales

Error code:   StreamingRowsError
Exception:    CastError
Message:      Couldn't cast
row_uid: large_string
analyte: large_string
value: double
source_file: large_string
-- schema metadata --
pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 729
to
{'row_uid': Value('string'), 'analyte': Value('string'), 'value': Value('float64')}
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 483, 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 2840, in __iter__
                  for key, example in ex_iterable:
                                      ^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2373, in __iter__
                  for key, pa_table in self._iter_arrow():
                                       ~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2398, 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 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
              row_uid: large_string
              analyte: large_string
              value: double
              source_file: large_string
              -- schema metadata --
              pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 729
              to
              {'row_uid': Value('string'), 'analyte': Value('string'), 'value': Value('float64')}
              because column names don't match

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CMIBS — Global Geochemical Database for Critical Metals in Black Shales

451,472 samples, 4,177,965 measurements, global coverage (seven continents), 1961-2014. Modernized from the USGS ScienceBase data release into two linked GeoParquet tables for AI, API, and GIS use.

geoparquet/samples.parquet — one row per sample: identifying/metadata columns, latitude, longitude, point geometry (EPSG:4326)
geoparquet/measurements.parquet — long format: one row per (sample, analyte), join back to samples on row_uid
metadata.json — provenance, citation, counts, standardization notes, known caveats

Why two tables instead of one wide table

The legacy database mixes 130+ analytical methods across historical and new compilations with inconsistent per-method columns. Splitting sample metadata from analyte measurements (long format) avoids hundreds of mostly-empty columns and is the standard structure for programmatic geochemistry access.

Caveats

Analyte vs. identifying/metadata columns were split per source table using keyword heuristics on column names (see ID_COLUMN_HINTS in the build notebook), not a hand-verified data dictionary — cross-check analyte column meanings against USGS documentation files bundled in the raw download before treating this as authoritative for a specific element.

Source & Citation

Granitto, Matthew, Giles, S.A., and Kelley, K.D., 2017, Global Geochemical Database for Critical Metals in Black Shales: U.S. Geological Survey data release, https://doi.org/10.5066/F71G0K7X

License

CC0 1.0 Universal

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