Datasets:

---

lwaekfjlk

/

prediction-market-news

like 0

Error code:   DatasetGenerationCastError
Exception:    DatasetGenerationCastError
Message:      An error occurred while generating the dataset

All the data files must have the same columns, but at some point there are 40 new columns ({'kalshi_raw', 'event_ticker', 'floor_strike', 'tag_ids', 'settlement_value', 'outcome', 'description', 'close_time', 'no_bid', 'daily_time_series', 'title', 'cap_strike', 'no_ask', 'yes_bid', 'market_ticker', 'start_ts', 'volumn', 'end_ts', 'tags', 'time_series', 'result', 'series_ticker', 'settlement_source', 'category', 'rules', 'status', 'split_type', 'volume', 'split_cutoff_ts', 'open_time', 'last_price', 'daily_breakpoints', 'open_interest', 'yes_ask', 'snapshot_history', 'resolution_source', 'strike_type', 'expiration_time', 'liquidity', 'subtitle'}) and 10 missing columns ({'before', 'news', 'window_history', 'z_score', 'attributions', 'window_start', 'change', 'window_end', 'after', 'sample_type'}).

This happened while the json dataset builder was generating data using

hf://datasets/lwaekfjlk/prediction-market-news/kalshi/kalshi_data_processed_with_news_test_2025-11-01_zscore_top200.jsonl (at revision 700a108b8103f03cea392b90b31e8d075c8f208b)

Please either edit the data files to have matching columns, or separate them into different configurations (see docs at https://hf.co/docs/hub/datasets-manual-configuration#multiple-configurations)
Traceback:    Traceback (most recent call last):
                File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1831, in _prepare_split_single
                  writer.write_table(table)
                File "/usr/local/lib/python3.12/site-packages/datasets/arrow_writer.py", line 714, in write_table
                  pa_table = table_cast(pa_table, self._schema)
                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2272, in table_cast
                  return cast_table_to_schema(table, schema)
                         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2218, in cast_table_to_schema
                  raise CastError(
              datasets.table.CastError: Couldn't cast
              event_id: string
              market_id: string
              question: string
              resolution_source: null
              volumn: null
              outcome: string
              description: string
              start_ts: double
              end_ts: double
              tags: null
              tag_ids: null
              categories: list<item: string>
                child 0, item: string
              daily_time_series: list<item: struct<t: int64, p: double>>
                child 0, item: struct<t: int64, p: double>
                    child 0, t: int64
                    child 1, p: double
              time_series: list<item: struct<t: int64, p: double>>
                child 0, item: struct<t: int64, p: double>
                    child 0, t: int64
                    child 1, p: double
              daily_breakpoints: list<item: struct<before: struct<t: double, p: double>, after: struct<t: double, p: double>, change: (... 245 chars omitted)
                child 0, item: struct<before: struct<t: double, p: double>, after: struct<t: double, p: double>, change: double, z_ (... 233 chars omitted)
                    child 0, before: struct<t: double, p: double>
                        child 0, t: double
                        child 1, p: double
                    child 1, after: struct<t: double, p: double>
                        child 0, t: double
                        child 1, p: double
                    child 2, change: double
                    child 3, z_score: double
                    child 4, window_start: double
                    child 5, window_end: double
                    child 6, window_history: list<item: struct<t: double, p: double>>
                        child 0, item: struct<t: double, p: double>
                            child 0, t: double
                            child 1, p: double
                    child 7, news: list<item: struct<title: string, description: string, url: string, published_at: timestamp[s], sourc (... 11 chars omitted)
                        child 0, item: struct<title: string, description: string, url: string, published_at: timestamp[s], source: string>
                            child 0, title: string
                            child 1, description: string
                            child 2, url: string
                            child 3, published_at: timestamp[s]
                            child 4, source: string
              event_ticker: string
              market_ticker: string
              title: string
              subtitle: string
              category: null
              series_ticker: null
              strike_type: null
              floor_strike: null
              cap_strike: null
              open_time: null
              close_time: null
              expiration_time: null
              settlement_value: null
              result: null
              status: null
              volume: null
              open_interest: null
              liquidity: null
              yes_bid: null
              yes_ask: null
              no_bid: null
              no_ask: null
              last_price: null
              settlement_source: null
              snapshot_history: null
              rules: null
              kalshi_raw: null
              split_cutoff_ts: double
              split_type: string
              to
              {'market_id': Value('string'), 'event_id': Value('string'), 'question': Value('string'), 'categories': List(Value('string')), 'sample_type': Value('string'), 'before': {'t': Value('float64'), 'p': Value('float64')}, 'after': {'t': Value('float64'), 'p': Value('float64')}, 'change': Value('float64'), 'z_score': Value('float64'), 'window_start': Value('float64'), 'window_end': Value('float64'), 'window_history': List({'t': Value('float64'), 'p': Value('float64')}), 'news': List({'title': Value('string'), 'description': Value('string'), 'url': Value('string'), 'published_at': Value('timestamp[s]'), 'source': Value('string')}), 'attributions': List({'news_idx': Value('int64'), 'score': Value('float64')})}
              because column names don't match
              
              During handling of the above exception, another exception occurred:
              
              Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1339, in compute_config_parquet_and_info_response
                  parquet_operations = convert_to_parquet(builder)
                                       ^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 972, in convert_to_parquet
                  builder.download_and_prepare(
                File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 894, in download_and_prepare
                  self._download_and_prepare(
                File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 970, in _download_and_prepare
                  self._prepare_split(split_generator, **prepare_split_kwargs)
                File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1702, in _prepare_split
                  for job_id, done, content in self._prepare_split_single(
                                               ^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1833, in _prepare_split_single
                  raise DatasetGenerationCastError.from_cast_error(
              datasets.exceptions.DatasetGenerationCastError: An error occurred while generating the dataset
              
              All the data files must have the same columns, but at some point there are 40 new columns ({'kalshi_raw', 'event_ticker', 'floor_strike', 'tag_ids', 'settlement_value', 'outcome', 'description', 'close_time', 'no_bid', 'daily_time_series', 'title', 'cap_strike', 'no_ask', 'yes_bid', 'market_ticker', 'start_ts', 'volumn', 'end_ts', 'tags', 'time_series', 'result', 'series_ticker', 'settlement_source', 'category', 'rules', 'status', 'split_type', 'volume', 'split_cutoff_ts', 'open_time', 'last_price', 'daily_breakpoints', 'open_interest', 'yes_ask', 'snapshot_history', 'resolution_source', 'strike_type', 'expiration_time', 'liquidity', 'subtitle'}) and 10 missing columns ({'before', 'news', 'window_history', 'z_score', 'attributions', 'window_start', 'change', 'window_end', 'after', 'sample_type'}).
              
              This happened while the json dataset builder was generating data using
              
              hf://datasets/lwaekfjlk/prediction-market-news/kalshi/kalshi_data_processed_with_news_test_2025-11-01_zscore_top200.jsonl (at revision 700a108b8103f03cea392b90b31e8d075c8f208b)
              
              Please either edit the data files to have matching columns, or separate them into different configurations (see docs at https://hf.co/docs/hub/datasets-manual-configuration#multiple-configurations)