---
id: pandas-ta-classic
version: "0.6.52"
license: MIT
license_treatment: permissive
maintenance: active
---

# pandas-ta-classic — 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.

License: permissive · Maintenance: active · Downloads: 208.8K/mo

## What it is and 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.

The 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 6–230×, 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.

Use it for:

- 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

## Worth the install?

AI-flagged interpretation of the facts above — verify before relying.

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.

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.

## Install

pip install pandas-ta-classic
uv add pandas-ta-classic
poetry add pandas-ta-classic

## Installing pandas-ta-classic

Before you install: Low friction install with only numpy and pandas as runtime dependencies. Actively maintained with a recent release 51 days ago and 419 repository stars. Supports modern Python versions (3.10–3.14) and offers optional numba acceleration for performance-critical indicators.

License in practice: MIT license permits unrestricted commercial and private use, modification, and distribution with minimal restrictions, making it suitable for proprietary trading systems and closed-source applications.

Quickstart:

pip install pandas-ta-classic

import pandas as pd
import pandas_ta_classic as ta

df = pd.read_csv("data.csv")
df.ta.sma(length=20, append=True)
df.ta.rsi(append=True)
df.ta.macd(append=True)

Requires Python 3.10 or later. Optional TA-Lib and tulipy can accelerate some indicators but are not required.

Verify before relying:

- Whether the 6–230× numba speedup claims are measured on typical trading datasets or synthetic benchmarks
- Specific performance characteristics of the 62 native candlestick patterns versus TA-Lib implementations
- How the fluent API chaining (v0.6+) handles error propagation and state management across chained calls

## Package facts

- License: MIT (permissive)
- Python support: supports_current
- Install friction: low
- Maintenance: active
- Downloads: 208.8K/month (top 15,000 on PyPI)
- Known vulnerabilities: none known

## Tags

technical analysis indicators pandas, candlestick patterns python, moving averages RSI MACD, trading indicators library, financial data analysis pandas, bollinger bands volume indicators, ta-lib alternative python, technical-analysis, trading-indicators, pandas-extension

[View on SkillFed](https://skillfed.io/packages/pandas-ta-classic) · [View on PyPI](https://pypi.org/project/pandas-ta-classic/)