Recording 4 venues
KXSTATELEGHIKalshiElectionsOne-time126 open on Nov 3

Hawaii Legislature race winner? odds & historical data

 

Hawaii Legislature race winner? price history on Kalshi: 126 markets, every order book change and trade, as daily Parquet files.

Example market: Will the Democratic Party win the 2028 Hawaii Senate District 16 election?

10.3 thousand rows126 markets91.7 KB7 datasets, full order book includedUpdated daily

Datasets

One file per dataset per UTC day. Data dictionary · Hourly coverage

DatasetWhat it holdsPlanSample
Order book (L2, incremental)
book_l2
Every price level and every change to the YES and NO bid books. Snapshot rows set a level; delta rows add to it.
9 columns
  • ts_recvtimestamp[ns, UTC]
  • ts_venuetimestamp[ns, UTC]
  • tickerstring
  • seriesstring
  • seqint64
  • is_snapshotbool
  • sidestring
  • pricefloat64
  • sizefloat64
Full bookSampleParquet·CSV
Order book snapshots (top 10, 1 second)
book_snap_1s
The top ten YES bid and ask levels at the end of every second in which the book changed.
43 columns
  • tstimestamp[ns, UTC]
  • tickerstring
  • seriesstring
  • bid_px_0float64
  • bid_px_1float64
  • bid_px_2float64
  • bid_px_3float64
  • bid_px_4float64
  • bid_px_5float64
  • bid_px_6float64
  • bid_px_7float64
  • bid_px_8float64
  • bid_px_9float64
  • bid_sz_0float64
  • bid_sz_1float64
  • bid_sz_2float64
  • bid_sz_3float64
  • bid_sz_4float64
  • bid_sz_5float64
  • bid_sz_6float64
  • bid_sz_7float64
  • bid_sz_8float64
  • bid_sz_9float64
  • ask_px_0float64
  • ask_px_1float64
  • ask_px_2float64
  • ask_px_3float64
  • ask_px_4float64
  • ask_px_5float64
  • ask_px_6float64
  • ask_px_7float64
  • ask_px_8float64
  • ask_px_9float64
  • ask_sz_0float64
  • ask_sz_1float64
  • ask_sz_2float64
  • ask_sz_3float64
  • ask_sz_4float64
  • ask_sz_5float64
  • ask_sz_6float64
  • ask_sz_7float64
  • ask_sz_8float64
  • ask_sz_9float64
ResearchSampleParquet·CSV
Top of book (every change)
bbo
Best YES bid and ask with sizes, one row each time any of the four values changes.
8 columns
  • ts_recvtimestamp[ns, UTC]
  • ts_venuetimestamp[ns, UTC]
  • tickerstring
  • seriesstring
  • yes_bidfloat64
  • yes_bid_sizefloat64
  • yes_askfloat64
  • yes_ask_sizefloat64
ResearchSampleParquet·CSV
Top of book (1-minute bars)
bbo_1m
Minute bars of the YES mid with closing bid and ask, plus trade count and volume.
12 columns
  • minutetimestamp[ns, UTC]
  • tickerstring
  • seriesstring
  • mid_openfloat64
  • mid_highfloat64
  • mid_lowfloat64
  • mid_closefloat64
  • yes_bid_closefloat64
  • yes_ask_closefloat64
  • book_updatesint64
  • trade_countint64
  • trade_volumefloat64
ResearchSampleParquet·CSV
Trades
trades
Every recorded fill with YES price, size, and taker side.
8 columns
  • ts_recvtimestamp[ns, UTC]
  • ts_venuetimestamp[ns, UTC]
  • tickerstring
  • seriesstring
  • trade_idstring
  • yes_pricefloat64
  • sizefloat64
  • taker_sidestring
ResearchSampleParquet·CSV
Markets (point-in-time universe)
markets
One row per market open at any time during the day: terms, strikes, times, tick size, rules, fees, and outcome.
22 columns
  • tickerstring
  • event_tickerstring
  • seriesstring
  • titlestring
  • yes_sub_titlestring
  • categorystring
  • market_typestring
  • statusstring
  • resultstring
  • open_tstimestamp[ns, UTC]
  • close_tstimestamp[ns, UTC]
  • expected_expiration_tstimestamp[ns, UTC]
  • floor_strikefloat64
  • cap_strikefloat64
  • strike_typestring
  • tick_structurestring
  • price_rangesstring
  • can_close_earlybool
  • fee_typestring
  • fee_multiplierfloat64
  • rules_primarystring
  • rules_secondarystring
ExplorerSampleParquet·CSV
Settlements
settlements
Every market that settled during the day: result, settlement value, the underlying value it settled on, and when.
15 columns
  • tickerstring
  • event_tickerstring
  • seriesstring
  • categorystring
  • resultstring
  • settlement_valuefloat64
  • expiration_valuestring
  • close_tstimestamp[ns, UTC]
  • settlement_tstimestamp[ns, UTC]
  • ts_recvtimestamp[ns, UTC]
  • floor_strikefloat64
  • cap_strikefloat64
  • strike_typestring
  • coin_price_startfloat64
  • coin_price_endfloat64
ExplorerSampleParquet·CSV
# pip install "kalshieye[pandas]"
from kalshieye import Client

kx = Client()  # reads KALSHIEYE_API_KEY
df = kx.load("bbo_1m", "2026-11-01", "2026-11-01", series="KXSTATELEGHI")

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