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.
Stable Release
pip install pandas-ta-classicLatest Version
pip install -U git+https://github.com/xgboosted/pandas-ta-classicimport 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- 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
Complete documentation is available at: 🔗 https://xgboosted.github.io/pandas-ta-classic/
- 📖 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
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
We welcome contributions! Please see our contributing guidelines and issues page.
- Check existing issues first
- Provide reproducible code examples
- Include relevant error messages and data samples
For detailed information about changes, improvements, and new features, please see the CHANGELOG.md file.
Original TA-LIB | TradingView | Sierra Chart | MQL5 | FM Labs | Pro Real Code | User 42
If you find this library helpful, please consider:
This project is licensed under the MIT License - see the LICENSE file for details.
