---
license: cc-by-4.0
task_categories:
- time-series-forecasting
- reinforcement-learning
tags:
- finance
- crypto
- algorithmic-trading
- orderbook
- level-2
- market-microstructure
- quant
- hyperliquid
- btc
- bitcoin
size_categories:
- n<1K
---

# 📊 Hyperliquid Bitcoin (BTC) Level 2 Orderbook Depth - Free Sample

> **🚀 GET THE FULL DATASET:** > You are currently viewing a **7-day free sample**. 
> Stop wasting weeks on data engineering. Get the complete, institutional-grade dataset featuring **12+ months of continuous history across 24 crypto assets (~2.3 Million rows)** directly at 👉 **[ImbalanceLabs.com](https://imbalancelabs.com/)**

---

## 🛑 Stop Trading on "Liquidity Illusions"

Standard OHLCV candles hide the true market intent, spread, spoofing walls, and slippage. When training Deep Learning (LSTM, Transformers) or Reinforcement Learning (RL) trading agents, standard candles often lead to overfitting and account liquidations in live environments because the models cannot evaluate the real cost of execution.

This dataset provides **Cleaned, Normalized, and Time-Aligned Level 2 Orderbook Depth Data**. It extracts the raw microstructural edge from the **Hyperliquid DEX** (the leading L1 Perpetual Decentralized Exchange) and transforms it into noise-free, 5-minute bars.

## ⚡ Why This Data is Different?

* **No Clock Drift:** Time-aligned 5-minute bars, eliminating the asynchrony and timestamp issues of raw WebSocket feeds.
* **Deep Liquidity Profiling:** 10-level depth (bids/asks) featuring cumulative passive volumes and basis-point distance from the mid-price.
* **Ready for AI/ML:** 47 pre-computed columns per row. Feed directly into Pandas, RL environments, LSTM networks, or XGBoost.
* **True Market Intent:** Escaping CEX noise and spoofing. DEX orderbooks reflect genuine liquidity and institutional positioning.

## 🗂️ Data Schema (47 Columns)

This sample contains data for the **BTC-USDT** perpetual futures contract. Each row represents one 5-minute aggregated orderbook snapshot.

| Column Category | Columns | Description |
| :--- | :--- | :--- |
| **Time & Asset** | `timestamp_utc`, `instrument_symbol` | ISO 8601 UTC time and trading pair |
| **Standard OHLCV** | `open_price`, `high_price`, `low_price`, `close_price`, `interval_traded_volume` | Mid-price tracking and taker flow volume |
| **Depth - Volume** | `bid_volume_level_1..10`, `ask_volume_level_1..10` | Cumulative passive bid/ask volume across 10 levels |
| **Depth - Distance**| `bid_distance_level_1..10`, `ask_distance_level_1..10` | Distance from the mid-price in basis points (bps) |

## 🚀 Accelerate Your Research

Building L2 depth pipelines from raw decentralized exchange feeds requires custom parsers, strict timestamp alignment, and massive compute — before you even start your research.

Skip the heavy data engineering. Download the ready-to-use CSV datasets and jump straight to training models, backtesting TWAP/VWAP strategies, and extracting alpha.

👉 **[Download the Full 24-Instrument Dataset at ImbalanceLabs.com](https://imbalancelabs.com/)**

---
### License & Legal Disclaimer
This sample dataset is provided under the CC-BY-4.0 license for research and analytical purposes. The data constitutes an Aggregated Liquidity and Orderbook Depth Index (Derived Data) — a proprietary, mathematically derived analytical product. It does not constitute financial advice. Imbalance Labs is not affiliated with any cryptocurrency exchange.