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Cannot load the dataset split (in streaming mode) to extract the first rows.
Error code: StreamingRowsError
Exception: TypeError
Message: Couldn't cast array of type
list<item: struct<id: string, name: string, glyph: string, pitch: string, items: list<item: struct<glyph: string, name: string, mult100: int64, weight: int64, rarity: string>>>>
to
{'rules': Value('string'), 'table': List({'17': Value('float64'), '18': Value('float64'), '19': Value('float64'), '20': Value('float64'), '21': Value('float64'), 'upcard': Value('string'), 'bust': Value('float64')})}
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/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 2378, in table_cast
return cast_table_to_schema(table, schema)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2312, in cast_table_to_schema
cast_array_to_feature(
~~~~~~~~~~~~~~~~~~~~~^
table[name] if name in table_column_names else pa.array([None] * len(table), type=schema.field(name).type),
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
feature,
^^^^^^^^
)
^
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 1861, in wrapper
return pa.chunked_array([func(chunk, *args, **kwargs) for chunk in array.chunks])
~~~~^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2158, in cast_array_to_feature
raise TypeError(f"Couldn't cast array of type\n{_short_str(array.type)}\nto\n{_short_str(feature)}")
TypeError: Couldn't cast array of type
list<item: struct<id: string, name: string, glyph: string, pitch: string, items: list<item: struct<glyph: string, name: string, mult100: int64, weight: int64, rarity: string>>>>
to
{'rules': Value('string'), 'table': List({'17': Value('float64'), '18': Value('float64'), '19': Value('float64'), '20': Value('float64'), '21': Value('float64'), 'upcard': Value('string'), 'bust': Value('float64')})}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.
Betkyo odds data
Machine-readable tables behind the Betkyo Journal, exported from the casino game engine source rather than typed by hand. Each JSON file carries its provenance (source names the engine module, article the derivation, generated the export date) and a data object; the CSV next to it is the same table flattened. index.json lists them all.
| File | What it is | Derivation |
|---|---|---|
keno-paytables |
All forty keno payout tables (level × picks × hits), total-return multipliers | What a keno risk level actually changes |
plinko-multipliers |
Plinko bucket multipliers for every risk level and row count | Plinko, priced |
roulette-bets |
Bet kinds, pockets covered, multiplier, expected return; wheel order and red pockets | A roulette bet is a string |
blackjack-dealer-outcomes |
Dealer final-total distribution by upcard, infinite shoe, dealer stands on all 17s | Dealer bust odds by upcard |
koban-ladder |
Koban Flip cumulative multiplier after n straight calls, floored to cents | Designing Koban Flip |
fukubukuro-bags |
Item weights (millionths) and payout multiples for both lucky bags | Designing Fukubukuro |
import pandas as pd
keno = pd.read_csv("hf://datasets/betkyo/odds-data/keno-paytables.csv")
Canonical, current copies: betkyo.com/data. Archived, citable version: doi:10.5281/zenodo.22725012. Repository mirror and the derivation scripts that turn these tables into the return figures quoted in the articles: github.com/betkyo-open-labs. Method: How the Journal verifies a number.
Licence: CC BY 4.0. Attribute as "Betkyo Journal, betkyo.com/data". Corrections: dev@betkyo.com.
These tables describe games of chance with a house edge; nothing here is betting advice. 18+.
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