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
title: string
id: string
licenses: list<item: struct<name: string>>
child 0, item: struct<name: string>
child 0, name: string
subtitle: string
files: list<item: string>
child 0, item: string
canonical_hash: string
dataset_name: string
generated_at: string
version: timestamp[s]
to
{'canonical_hash': Value('string'), 'dataset_name': Value('string'), 'version': Value('timestamp[s]'), 'files': List(Value('string')), 'generated_at': Value('string')}
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/json/json.py", line 295, in _generate_tables
self._cast_table(pa_table, json_field_paths=json_field_paths),
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/json/json.py", line 128, 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 2281, in table_cast
return cast_table_to_schema(table, schema)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2227, in cast_table_to_schema
raise CastError(
datasets.table.CastError: Couldn't cast
title: string
id: string
licenses: list<item: struct<name: string>>
child 0, item: struct<name: string>
child 0, name: string
subtitle: string
files: list<item: string>
child 0, item: string
canonical_hash: string
dataset_name: string
generated_at: string
version: timestamp[s]
to
{'canonical_hash': Value('string'), 'dataset_name': Value('string'), 'version': Value('timestamp[s]'), 'files': List(Value('string')), 'generated_at': 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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Pawn Loan Activity
Overview
Synthetic benchmark dataset: Pawn Loan Activity (metro_ny_q1_2026)
This dataset is synthetically generated for benchmark and research purposes.
Entity Context
King Gold & Pawn is a multi-location pawn lender operating across New York metro area.
Dataset Details
- Scenario:
metro_ny_q1_2026 - Version:
2026-04-27 - Rows:
37 - Canonical Hash:
ad8353ef935f57bd - Generated:
2026-04-27T10:00:17.173996+00:00
Schema
| Field | Type |
|---|---|
| date | string |
| max_temp_celsius | float |
| precipitation_mm | float |
| btc_price_usd | float |
| nyc_commercial_activity_index | float |
| synthetic_pawn_collateral_risk | float |
License
CC BY 4.0 — Creative Commons Attribution 4.0 International
Citation
King Gold & Pawn OmniBrain Synthetic Data Engine. "Pawn Loan Activity", version 2026-04-27.
Intended Use
- Academic research benchmarks
- Data processing pipeline testing
- Classification and regression evaluation
- Reproducible synthetic data experiments
Methodological References
- Microsoft Sysinternals: Telemetry aggregation methodology structurally inspired by ProcMon
- Google Research: Statistical smoothing parameters referenced via TensorFlow Datasets
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