Pandas TA Classic - Technical Analysis Library

Pandas TA Classic is an easy-to-use library that leverages the Pandas package with 143 indicators and utility functions and 62 TA Lib candlestick patterns (205 total). Many commonly used indicators are included, such as: Simple Moving Average (sma), Moving Average Convergence Divergence (macd), Hull Exponential Moving Average (hma), Bollinger Bands (bbands), On-Balance Volume (obv), Aroon & Aroon Oscillator (aroon), Squeeze (squeeze) and many more.

This is the classic/community maintained version of the popular pandas-ta library.

🚀 Quick Start

Installation

Stable Release

pip install pandas-ta-classic

Latest Version

pip install -U git+https://github.com/xgboosted/pandas-ta-classic

Basic Usage

import pandas as pd
import pandas_ta_classic as ta

# Load your data
df = pd.read_csv("path/to/symbol.csv")
# OR if you have yfinance installed
df = df.ta.ticker("aapl")

# Calculate indicators
df.ta.sma(length=20, append=True)        # Simple Moving Average
df.ta.rsi(append=True)                   # Relative Strength Index  
df.ta.macd(append=True)                  # MACD
df.ta.bbands(append=True)                # Bollinger Bands

# Or run a strategy with multiple indicators
df.ta.strategy("CommonStrategy")         # Runs commonly used indicators

📊 Features

• 143 Technical Indicators & Utilities across 9 categories (Candles, Momentum, Overlap, Trend, Volume, etc.)
• 62 TA Lib Candlestick Patterns for comprehensive pattern recognition
• 205 Total Indicators & Patterns - the most comprehensive Python TA library
• Strategy System with multiprocessing support for bulk indicator processing
• Pandas DataFrame Extension for seamless integration (df.ta.indicator())
• TA Lib Integration - automatically uses TA Lib versions when available
• Vectorbt Integration - compatible with popular backtesting framework
• Custom Indicators - easily create and chain your own indicators

📚 Documentation

Complete documentation is available at: 🔗 https://xgboosted.github.io/pandas-ta-classic/

Quick Links

• 📖 Usage Guide - Programming conventions and basic usage
• 🏗️ Strategy System - Multiprocessing and bulk indicator processing
• 📊 Indicators Reference - Complete list of all 143 indicators & 62 patterns
• 🔧 DataFrame API - Properties and methods reference
• 📈 Performance Metrics - Backtesting and performance analysis
• 💡 Examples - Jupyter notebooks and code examples

🐍 Python Version Support

Pandas TA Classic supports Python 3.9 through 3.13 following a rolling support policy for the latest stable version plus 4 preceding minor versions.

Note: TA Lib installation enables all candlestick patterns: pip install TA-Lib

🤝 Contributing

We welcome contributions! Please see our contributing guidelines and issues page.

Reporting Issues

• Check existing issues first
• Provide reproducible code examples
• Include relevant error messages and data samples

📋 Changelog

For detailed information about changes, improvements, and new features, please see the CHANGELOG.md file.

🔗 Sources

Original TA-LIB | TradingView | Sierra Chart | MQL5 | FM Labs | Pro Real Code | User 42

❤️ Support

If you find this library helpful, please consider:

📄 License

This project is licensed under the MIT License - see the LICENSE file for details.