{"categories":[{"label":"Scientific/Engineering","url":"https://skillfed.io/packages/category/scientific-engineering/5"},{"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":"Provides 130+ technical analysis indicators and candlestick patterns for financial data analysis, callable directly on Pandas DataFrames or as standalone functions.","skillfed_tags":["technical-analysis","trading-signals","financial-data"],"use_cases":["Calculate moving averages, MACD, Bollinger Bands, and other standard indicators on OHLCV data for signal generation","Backtest trading strategies by applying multiple indicators via the DataFrame strategy method with multiprocessing","Detect candlestick patterns in price data for entry/exit signals (requires TA-Lib for full pattern library)","Build custom chained strategies by combining indicators with prefixes and suffixes for clarity","Analyze financial time series for volatility, momentum, and trend without leaving the Pandas ecosystem"],"what_it_does":"Pandas TA is a Pandas extension library that adds technical analysis capabilities to financial DataFrames. It wraps 130+ indicators (moving averages, momentum oscillators, volatility bands, volume measures, and trend tools) plus candlestick patterns. You call indicators either as methods on a DataFrame or as standalone functions, and results append as new columns. The library is a maintained fork of the original pandas-ta, updated to work with modern Python and Pandas versions.\n\nThe package is designed for traders and quantitative analysts building backtesting systems or signal generators. It integrates with Pandas workflows and optionally uses TA-Lib for accelerated computation if installed. It supports multiprocessing for strategy evaluation and allows custom indicators. Candlestick patterns require TA-Lib; without it, only built-in patterns are available.","worth_installing":"Yes, with conditions. Install if you need a lightweight, Pandas-native technical analysis toolkit for trading or financial analysis. The low dependency footprint and permissive license make it easy to integrate. However, maintenance is aging (last release 319 days ago), so verify that the indicator set and accuracy meet your specific requirements before relying on it for production trading. No known vulnerabilities."},"id":"ft-pandas-ta","links":{"html":"https://skillfed.io/packages/ft-pandas-ta","md":"https://skillfed.io/packages/ft-pandas-ta.md","pypi":"https://pypi.org/project/ft-pandas-ta/"},"maintenance":{"status":"aging"},"meta":{"latest_release":"2025-09-29","license_spdx":null,"license_treatment":"permissive","name":"ft-pandas-ta","python_support":"unspecified","summary":"An easy to use Python 3 Pandas Extension with 130+ Technical Analysis Indicators. Can be called from a Pandas DataFrame or standalone like TA-Lib. Correlation tested with TA-Lib."},"popularity":{"monthly_downloads":256885,"position":8454,"tier":"top_15000"},"security":{"n_vulnerabilities":0},"version":"0.3.16"}