{"categories":[{"label":"Scientific/Engineering","url":"https://skillfed.io/packages/category/scientific-engineering/6"},{"label":"Information Analysis","url":"https://skillfed.io/packages/category/scientific-engineering-information-analysis/2"},{"label":"Financial","url":"https://skillfed.io/packages/category/office-business-financial"},{"label":"Investment","url":"https://skillfed.io/packages/category/office-business-financial-investment"}],"enrichment":{"capability":"Pandas TA Classic provides 193 technical indicators and 62 native candlestick patterns as a Pandas DataFrame extension, enabling technical analysis workflows without requiring TA-Lib.","skillfed_tags":["technical-analysis","trading-indicators","pandas-extension"],"use_cases":["Build moving average crossover trading strategies by chaining sma() calls and comparing signals on historical price data","Detect candlestick patterns (doji, engulfing, hammer) on OHLC data using native Python implementations without external C libraries","Backtest momentum indicators (RSI, MACD, Stochastic) on multi-timeframe data to identify entry and exit points","Accelerate indicator computation on large datasets using optional numba for hot-loop functions like Supertrend or RSX","Verify custom indicator implementations against TA-Lib or tulipy using the built-in oracle test suite","Integrate technical signals into a vectorbt backtesting pipeline for performance analysis and optimization"],"what_it_does":"Pandas TA Classic is a Pandas DataFrame extension that adds 193 technical indicators and 62 native candlestick patterns to your trading and financial analysis workflows. It works by attaching methods to pandas DataFrames (e.g., `df.ta.sma()`, `df.ta.rsi()`), making indicators accessible directly on your price data without external dependencies like TA-Lib. The library includes common indicators such as Simple Moving Average, MACD, Bollinger Bands, and On-Balance Volume, plus less common ones like Hull Exponential Moving Average and Squeeze.\n\nThe package depends only on numpy and pandas at runtime, keeping installation lightweight. It offers optional integrations: TA-Lib can accelerate 34 core indicators when installed, numba can speed up specific hot-loop indicators by 6\u2013230\u00d7, and tulipy serves as a parity oracle for testing. All candlestick patterns are implemented natively in Python, so you never need TA-Lib just to use CDL patterns. The library supports fluent API chaining to combine multiple indicators in one expression and includes a strategy system for bulk processing.","worth_installing":"Yes. Pandas TA Classic is actively maintained, has no known vulnerabilities, installs with minimal friction (only numpy and pandas), and offers a comprehensive set of 253 indicators and patterns under a permissive MIT license. It is production-ready (Development Status 5) and suitable for both research and commercial trading systems. Install it if you need technical analysis indicators in pandas workflows and want to avoid TA-Lib compilation or licensing complexity."},"id":"pandas-ta-classic","links":{"html":"https://skillfed.io/packages/pandas-ta-classic","md":"https://skillfed.io/packages/pandas-ta-classic.md","pypi":"https://pypi.org/project/pandas-ta-classic/"},"maintenance":{"status":"active"},"meta":{"latest_release":"2026-06-24","license_spdx":null,"license_treatment":"permissive","name":"pandas-ta-classic","python_support":"supports_current","summary":"Technical Analysis Indicators - Pandas TA Classic is an easy to use Python 3 Pandas Extension with a comprehensive collection of indicators and TA-Lib patterns."},"popularity":{"monthly_downloads":208792,"position":9525,"tier":"top_15000"},"security":{"n_vulnerabilities":0},"version":"0.6.52"}