Example: BTC Liquidation Heatmap

Visualizing Liquidation Events

We built an open-source Jupyter notebook that visualizes BTC liquidation events on Hyperliquid using historical data from 0xArchive.

Fetches liquidation data via the oxarchive Python SDK

Deduplicates trade records and maps long vs short positions

Generates 6 visualizations:

Price vs time liquidation heatmap - density map of liquidation activity

Scatter plot with BTC price overlay - longs in red, shorts in green

Hourly liquidation volume distribution - when do liquidations cluster?

Size distribution with percentile stats - how large are typical liquidations?

Cascade detection - finds P99 liquidation bursts in 5-min windows

Long vs short imbalance over time with price subplot

13,399 unique liquidations - shorts hit 2x harder (64.9%) than longs (35.1%), $143M total notional.

pip install -r requirements.txt
cp .env.example .env
jupyter notebook liquidation_heatmap.ipynb

Works with a free API key from 0xarchive.io/dashboard (BTC, 30-day lookback).

We're planning more examples - funding rate arb, OI divergence, market microstructure.