Recording 4 venues
KXLOWAKalshiFinancialsOne-time20 open on Nov 1

Lowe's Annual KPI historical data

 

Lowe's Annual KPI price history on Kalshi: 20 markets, every order book change and trade, as daily Parquet files.

Example market: Will Lowe's Companies Inc. report Above 760 million retail customer transactions in fiscal 2026?

72.8 thousand rows20 markets646 KB6 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
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", "2026-10-27", "2026-10-27", series="KXLOWA")

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