Datasets:

PXIN
/

fracture-crypto-l2-enriched-v2

Error code:   StreamingRowsError
Exception:    CastError
Message:      Couldn't cast
ask_conc_10: double
ask_conc_5: double
ask_sz_l1: double
ask_sz_l10: double
ask_sz_l5: double
bar_duration_ms: int64
best_ask: double
best_bid: double
bid_conc_10: double
bid_conc_5: double
bid_sz_l1: double
bid_sz_l10: double
bid_sz_l5: double
body_pct: double
close: double
close_time: int64
ctx_timestamp: int64
cvd: double
cvd_delta: double
depth_ratio_l1_l10: double
depth_ratio_l5_l20: double
funding: double
high: double
imb_l1: double
imb_l10: double
imb_l5: double
impact_ask_px: double
impact_bid_px: double
l2_timestamp: int64
liquidity_01pct_usdt: double
liquidity_02pct_usdt: double
low: double
mark_px: double
micro_price: double
micro_price_delta_bps: double
mid: double
open: double
open_interest: double
open_time: int64
oracle_px: double
pair: large_string
premium: double
price_impact: double
range_pct: double
return: double
spread_bps: double
spread_depth_l10: double
tick_count: int64
token_volume: double
trade_intensity: int64
volume_usdt: double
vwap_ask_10: double
vwap_ask_5: double
vwap_bid_10: double
vwap_bid_5: double
vwap_dev_10_bps: double
vwap_dev_5_bps: double
vwap_mid_10: double
vwap_mid_5: double
to
{'close_time': Value('timestamp[us]'), 'pair': 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/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
              ask_conc_10: double
              ask_conc_5: double
              ask_sz_l1: double
              ask_sz_l10: double
              ask_sz_l5: double
              bar_duration_ms: int64
              best_ask: double
              best_bid: double
              bid_conc_10: double
              bid_conc_5: double
              bid_sz_l1: double
              bid_sz_l10: double
              bid_sz_l5: double
              body_pct: double
              close: double
              close_time: int64
              ctx_timestamp: int64
              cvd: double
              cvd_delta: double
              depth_ratio_l1_l10: double
              depth_ratio_l5_l20: double
              funding: double
              high: double
              imb_l1: double
              imb_l10: double
              imb_l5: double
              impact_ask_px: double
              impact_bid_px: double
              l2_timestamp: int64
              liquidity_01pct_usdt: double
              liquidity_02pct_usdt: double
              low: double
              mark_px: double
              micro_price: double
              micro_price_delta_bps: double
              mid: double
              open: double
              open_interest: double
              open_time: int64
              oracle_px: double
              pair: large_string
              premium: double
              price_impact: double
              range_pct: double
              return: double
              spread_bps: double
              spread_depth_l10: double
              tick_count: int64
              token_volume: double
              trade_intensity: int64
              volume_usdt: double
              vwap_ask_10: double
              vwap_ask_5: double
              vwap_bid_10: double
              vwap_bid_5: double
              vwap_dev_10_bps: double
              vwap_dev_5_bps: double
              vwap_mid_10: double
              vwap_mid_5: double
              to
              {'close_time': Value('timestamp[us]'), 'pair': Value('string')}
              because column names don't match

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Fracture Crypto L2-Enriched Dollar Bars v2

Updated: May 2026
Coverage: Sept 2025 - April 30, 2026
Pairs: BTCUSDT, ETHUSDT, SOLUSDT, BNBUSDT, HYPEUSDT, TRXUSDT

What's New in v2

Extended date range: Now includes data through April 30, 2026 (previously March 2026)
8 new columns: funding, mark_px, open_interest, oracle_px, premium, price_impact, trade_intensity, ctx_timestamp
Total columns: 59 (up from 51)
Total rows: ~10.8M enriched dollar bars

Columns

Core OHLCV

open_time, close_time, open, high, low, close, volume_usdt, token_volume

Bar Metadata

bar_duration_ms, tick_count, return, range_pct, body_pct, ctx_timestamp

L1 Order Book

best_bid, best_ask, bid_sz_l1, ask_sz_l1, imb_l1, spread_bps

L5/L10 Order Book

bid_sz_l5, ask_sz_l5, bid_sz_l10, ask_sz_l10, imb_l5, imb_l10, spread_depth_l10
depth_ratio_l1_l10, depth_ratio_l5_l20

Microstructure

micro_price, micro_price_delta_bps, cvd, cvd_delta
bid_conc_5, bid_conc_10, ask_conc_5, ask_conc_10
vwap_bid_5, vwap_ask_5, vwap_bid_10, vwap_ask_10, vwap_mid_5, vwap_mid_10
vwap_dev_5_bps, vwap_dev_10_bps, liquidity_01pct_usdt, liquidity_02pct_usdt

Hyperliquid-specific (NEW)

funding, mark_px, open_interest, oracle_px, premium, price_impact, trade_intensity

Derived

impact_bid_px, impact_ask_px

Usage

import polars as pl
df = pl.read_parquet("hf://datasets/PXIN/fracture-crypto-l2-enriched-v2/BTCUSDT_enriched.parquet")

License

MIT

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