Pandas Ta

This wraps pandas-ta, a library with 130+ technical indicators that bolt onto any OHLCV DataFrame via `df.ta.rsi()` or `df.ta.macd()`. It covers the usual suspects: RSI, MACD, Bollinger Bands, plus stuff like SuperTrend and Ichimoku. The Strategy class is handy for running multiple indicators in one shot instead of chaining method calls. The docs lean heavy into crypto with specific guidance on volatility adjustments (wider Bollinger Bands, shorter RSI periods) and timeframe selection for different trading styles. Column names must be lowercase and you'll want a DatetimeIndex for time-aware indicators like VWAP. Good for backtesting or building signal logic without reinventing TA math.

skills.sh installs: 636
GitHub stars: 519
last updated: Aug 21, 2026

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Install

$ npx -y skills add agiprolabs/claude-trading-skills --skill pandas-ta --agent claude-code

Installs into .claude/skills of the current project.

Files

pandas-ta — Technical Analysis for Crypto Markets

pandas-ta is a Python library that extends pandas DataFrames with 130+ technical analysis indicators accessible via df.ta. It covers trend, momentum, volatility, volume, and overlap indicator categories — all callable with a single method on any OHLCV DataFrame.

Installation

uv pip install pandas-ta pandas httpx

Quick Start

import pandas as pd
import pandas_ta as ta

# Assume df is a DataFrame with columns: open, high, low, close, volume
# All lowercase column names required

# Single indicator
df["rsi"] = df.ta.rsi(length=14)
df["atr"] = df.ta.atr(length=14)

# Multiple indicators via strategy
df.ta.strategy(ta.Strategy(
    name="Quick Check",
    ta=[
        {"kind": "rsi", "length": 14},
        {"kind": "macd", "fast": 12, "slow": 26, "signal": 9},
        {"kind": "bbands", "length": 20, "std": 2.0},
    ]
))

OHLCV DataFrame Format

pandas-ta expects a DataFrame with lowercase column names:

import pandas as pd

df = pd.DataFrame({
    "open": [...],
    "high": [...],
    "low": [...],
    "close": [...],
    "volume": [...]
}, index=pd.DatetimeIndex([...]))

SKILL.md on GitHub