NEAR Historical Level 2 Orderbook Data
NEAR-USDT·Hyperliquid DEX·5-Minute Bars·10-Level Depth
Study NEAR Protocol's sharded architecture impact on perpetual futures liquidity. NEAR depth data captures orderbook dynamics during chain abstraction updates and AI-integration announcements — modeling how developer-focused L1 ecosystems affect market microstructure.
📅Data Range
Mar 1, 2025 → Feb 28, 2026
📊Rows (5m)
~96,000
💾Size
~9 MB
🔢Columns
47
Quick Start
import pandas as pd# Load the institutional NEAR orderbook depth datasetdf = pd.read_parquet('near_l2_depth_5m.parquet')print(df[['timestamp', 'bid_volume_level_1', 'ask_volume_level_1']].head())What Your Data Looks Like
NEAR Sample Data Preview
| timestamp | close_price | bid_volume_level_1 | ask_volume_level_1 | bid_distance_level_1 |
|---|---|---|---|---|
| 2025-06-15 12:00:00 | 7.85 | 6200.0 | 5750.5 | 3.1 |
| 2025-06-15 12:05:00 | 7.90 | 6500.2 | 5550.3 | 3.0 |
| 2025-06-15 12:10:00 | 7.87 | 5980.7 | 6050.1 | 3.2 |
| 2025-06-15 12:15:00 | 7.95 | 6850.4 | 5300.8 | 2.8 |
| 2025-06-15 12:20:00 | 7.92 | 6350.1 | 5700.6 | 2.9 |
Dataset Schema
| Column | Type | Description |
|---|---|---|
| timestamp_utc | DateTime | ISO 8601 UTC timestamp of bar open |
| instrument_symbol | String | Trading pair (e.g., BTC-USDT) |
| open_price | Float | Mid-price at bar open |
| high_price | Float | Highest mid-price in bar |
| low_price | Float | Lowest mid-price in bar |
| close_price | Float | Mid-price at bar close |
| interval_traded_volume | Float | Taker flow volume proxy |
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Frequently Asked Questions
What is the NEAR (NEAR Protocol) orderbook dataset?+
The NEAR dataset contains historical Level 2 orderbook depth data for the NEAR-USDT perpetual futures market on Hyperliquid DEX. It includes 96,000 rows of 5-minute bars with 47 columns capturing bid/ask volumes and distances at 10 depth levels — providing institutional-grade microstructure intelligence for NEAR Protocol. Study NEAR Protocol's sharded architecture impact on perpetual futures liquidity. NEAR depth data captures orderbook dynamics during chain abstraction updates and AI-integration announcements — modeling how developer-focused L1 ecosystems affect market microstructure.
How large is the NEAR dataset?+
The NEAR 5-minute dataset contains approximately 96,000 rows and is approximately 9 MB in compressed CSV format. Each row has 47 columns including OHLCV prices, cumulative bid and ask volumes at 10 depth levels, and bid/ask distances measured in basis points from mid-price.
What time period does the NEAR data cover?+
The NEAR dataset covers the period from Mar 1, 2025 to Feb 28, 2026 — approximately 12 months of continuous 5-minute bars sourced from Hyperliquid DEX perpetual futures. This provides a full market cycle of NEAR Protocol orderbook microstructure data for backtesting and quantitative research.