ohlcv-processing
OHLCV Processing — Market Data Preparation
Clean, consistent OHLCV data is the foundation of every trading analysis. Garbage in, garbage out — a single anomalous candle can trigger false signals, corrupt indicator calculations, and produce misleading backtest results. This skill covers the full data preparation pipeline: validation, cleaning, resampling, normalization, and multi-source merging.
Why this matters: Crypto OHLCV data is messier than traditional markets. 24/7 trading means no official close, DEX aggregators disagree on prices, low-liquidity tokens produce impossible candles, and API outages create gaps. Every analysis workflow should start with this pipeline.
Quick Start
1. Install Dependencies
uv pip install pandas numpy httpx
2. Standard OHLCV DataFrame Format
All processing functions expect this canonical format:
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