---
id: ft-pandas-ta
version: "0.3.16"
license: The MIT License (MIT)
license_treatment: permissive
maintenance: aging
---

# ft-pandas-ta — 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.

License: permissive · Maintenance: aging · Downloads: 256.9K/mo

## What it is and 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.

The 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.

Use it for:

- 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

## Worth the install?

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

Provides 130+ technical analysis indicators and candlestick patterns for financial data analysis, callable directly on Pandas DataFrames or as standalone functions.

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.

## Install

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

## Installing ft-pandas-ta

Before you install: Low friction install with only numpy and pandas as runtime dependencies. Maintenance status is aging—last release was 319 days ago—but the package is actively maintained by the Freqtrade team as a fork of the discontinued original project.

License in practice: MIT license permits commercial and private use with minimal restrictions, making it suitable for both open-source and proprietary trading systems.

Quickstart:

import pandas as pd
import numpy as np

df = pd.read_csv('ohlcv_data.csv')
df.set_index(pd.DatetimeIndex(df['datetime']), inplace=True)

# Calculate indicators and append to DataFrame
df.ta.sma(append=True)
df.ta.bbands(append=True)

DataFrame index must be a DatetimeIndex for some indicators like VWAP. TA-Lib must be installed separately to access all candlestick patterns.

Verify before relying:

- Whether all 130+ indicators are fully functional or if some require optional TA-Lib installation
- Performance characteristics when processing large datasets or using multiprocessing strategy mode
- Accuracy correlation with TA-Lib for shared indicators beyond what the description claims
- Specific parameter values and defaults for commonly used indicators like sma, macd, bbands

## Package facts

- License: The MIT License (MIT) (permissive)
- Python support: unspecified
- Install friction: low
- Maintenance: aging
- Downloads: 256.9K/month (top 15,000 on PyPI)
- Known vulnerabilities: none known

## Tags

technical analysis indicators python, pandas financial indicators, trading signals candlestick patterns, ta-lib alternative python, moving averages bollinger bands, financial data analysis library, stock market indicators, technical-analysis, trading-signals, financial-data

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