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Technical analysis indicators built on Pandas
What it is
A technical analysis library in Python for feature engineering from financial time series data built on Pandas and Numpy. It implements 43 indicators across volume, volatility, trend, momentum and other categories, including Bollinger Bands, MACD, ATR, OBV and moving averages, each exposed through a class with methods returning computed columns from OHLCV inputs. Quant developers and researchers working in Python who want to derive indicator features from price and volume data will find it straightforward to adopt. The library provides calculations only, so strategy logic, backtesting and data sourcing must be handled elsewhere.
At a glance
Worth watchingOur rating, based on popularity, maintenance and how ready it is for real use.
| Best for | Developers |
|---|---|
| Used for | Data analysis, Strategy research |
| Markets | Multi-market |
| Stack | Python |
| Learning curve | Easy to start |
| Practical value | Medium practical value |
| Cost | Free and open source |
| Hardware | No GPU needed |
| Maintenance | No commits in over six months |
GitHub stars, last 30 days
Daily snapshots since 2026-09-12 (up to 30 days): +16 over the period, now 5,235. Gaps mean no snapshot was taken that day.
Technical Analysis Library using Pandas (Python).