Datasets:

---

just-dna-seq

/

prs-percentiles

like 0

Follow

Just DNA seq 2

Error code:   StreamingRowsError
Exception:    CastError
Message:      Couldn't cast
pgs_id: large_string
superpopulation: large_string
mean: double
std: double
n: uint32
median: double
p5: double
p25: double
p75: double
p95: double
name: large_string
trait_reported: large_string
trait_efo: large_string
trait_efo_id: large_string
genome_build: large_string
n_variants: int64
pgp_id: large_string
pmid: int64
auroc_estimate: double
auroc_ci_lower: double
auroc_ci_upper: double
or_estimate: double
or_ci_lower: double
or_ci_upper: double
hr_estimate: double
hr_ci_lower: double
hr_ci_upper: double
cindex_estimate: double
cindex_ci_lower: double
cindex_ci_upper: double
ancestry_broad: large_string
n_individuals: int64
abs_risk_at_mean: double
abs_risk_method: large_string
abs_risk_prevalence: double
to
{'pgs_id': Value('large_string'), 'superpopulation': Value('large_string'), 'severity': Value('large_string'), 'issue': Value('large_string'), 'recommended_action': Value('large_string'), 'mean': Value('float64'), 'std': Value('float64'), 'n': Value('int64'), 'median': Value('float64'), 'p5': Value('float64'), 'p25': Value('float64'), 'p75': Value('float64'), 'p95': Value('float64')}
because column names don't match
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/utils.py", line 99, in get_rows_or_raise
                  return get_rows(
                         ^^^^^^^^^
                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 77, in get_rows
                  rows_plus_one = list(itertools.islice(ds, rows_max_number + 1))
                                  ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2690, in __iter__
                  for key, example in ex_iterable:
                                      ^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2227, in __iter__
                  for key, pa_table in self._iter_arrow():
                                       ^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2251, in _iter_arrow
                  for key, pa_table in self.ex_iterable._iter_arrow():
                                       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 494, in _iter_arrow
                  for key, pa_table in iterator:
                                       ^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 384, in _iter_arrow
                  for key, pa_table in self.generate_tables_fn(**gen_kwags):
                                       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/parquet/parquet.py", line 209, in _generate_tables
                  yield Key(file_idx, batch_idx), self._cast_table(pa_table)
                                                  ^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/parquet/parquet.py", line 147, in _cast_table
                  pa_table = table_cast(pa_table, self.info.features.arrow_schema)
                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2321, in table_cast
                  return cast_table_to_schema(table, schema)
                         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2249, in cast_table_to_schema
                  raise CastError(
              datasets.table.CastError: Couldn't cast
              pgs_id: large_string
              superpopulation: large_string
              mean: double
              std: double
              n: uint32
              median: double
              p5: double
              p25: double
              p75: double
              p95: double
              name: large_string
              trait_reported: large_string
              trait_efo: large_string
              trait_efo_id: large_string
              genome_build: large_string
              n_variants: int64
              pgp_id: large_string
              pmid: int64
              auroc_estimate: double
              auroc_ci_lower: double
              auroc_ci_upper: double
              or_estimate: double
              or_ci_lower: double
              or_ci_upper: double
              hr_estimate: double
              hr_ci_lower: double
              hr_ci_upper: double
              cindex_estimate: double
              cindex_ci_lower: double
              cindex_ci_upper: double
              ancestry_broad: large_string
              n_individuals: int64
              abs_risk_at_mean: double
              abs_risk_method: large_string
              abs_risk_prevalence: double
              to
              {'pgs_id': Value('large_string'), 'superpopulation': Value('large_string'), 'severity': Value('large_string'), 'issue': Value('large_string'), 'recommended_action': Value('large_string'), 'mean': Value('float64'), 'std': Value('float64'), 'n': Value('int64'), 'median': Value('float64'), 'p5': Value('float64'), 'p25': Value('float64'), 'p75': Value('float64'), 'p95': Value('float64')}
              because column names don't match