usamaahmedsh/elliott-wave-market-data-complete

Elliott Wave Market Data - Complete (Quality Validated) ✅

Production-ready, quality-validated OHLCV market data for training Elliott Wave pattern recognition neural networks.

🎯 Key Features

• —Quality Validated: Rigorous data quality checks applied
• —Complete Coverage: 1,403 unique instruments
• —Multi-Timeframe: 1h, 4h, 1d, 1wk data
• —22,546,189 Total Data Points

Dataset Statistics

Asset Classes

This dataset includes:

• —Commodities
• —Commodities Extended
• —Crypto
• —Crypto Extended
• —Emerging Markets
• —Etfs
• —Fixed Income
• —Forex
• —Forex Extended
• —Indices
• —Indices Extended
• —International
• —Leveraged
• —Nasdaq
• —Reits
• —Small Cap
• —Stocks
• —Thematic Etfs

Quality Validation

All data has passed these quality checks:

• —✅ OHLC consistency (High ≥ Low, etc.)
• —✅ No missing values in required fields
• —✅ No duplicate rows
• —✅ No zero/negative prices
• —✅ No negative volume
• —✅ Extreme outliers removed (>1000% single-bar moves)
• —✅ Minimum 50 bars per ticker/timeframe
• —✅ Valid datetime formatting
• —✅ No future dates

Data Schema

Usage

import pandas as pd

# Load all daily data
df = pd.read_parquet("hf://datasets/usamaahmedsh/elliott-wave-market-data-complete/market_data_1d.parquet")

# Filter by category
stocks = df[df['source_category'] == 'stocks']
crypto = df[df['source_category'] == 'crypto']

# Filter by ticker
aapl = df[df['ticker'] == 'AAPL']
btc = df[df['ticker'] == 'BTC-USD']

Data Sources

• —Primary: Yahoo Finance (via yfinance)
• —All data adjusted for splits/dividends

License

MIT License - Free for academic and commercial use.

Generated

2026-02-27 16:03 UTC