Bitcoin Market and Mining Dataset with Energy and Efficiency Metrics

This dataset was manually constructed by aggregating and engineering multiple categories of Bitcoin-related data from different sources. It includes: - Market data (e.g., Open, Close, Volume, Fees, Transactions) collected from [Mempool](https://mempool.space/it/)- Energy data (e.g., estimated power consumption, efficiency metrics) retrieved via the [Electricity Maps API](https://portal.electricitymaps.com/docs/getting-started#geolocation)- Technical financial indicators (e.g., EMA, MACD, RSI, VWAP, TRIX, Bollinger Bands Width) computed using the [FinTa](https://github.com/peerchemist/finta) Python library- Derived metrics (e.g., momentum, volatility, normalization functions) calculated with custom Python functions The dataset is structured with one row per day and includes both raw values and engineered features. It offers a detailed overview of Bitcoin's economic, market, and energy dimensions. This dataset is suitable for use in machine learning models, time series forecasting, and the study of relationships between Bitcoin market behavior and its underlying energy consumption patterns.