trading-visualization

Name: trading-visualization
Availability: InStock
Author: agiprolabs

Generate trading charts with Matplotlib and mplfinance.

266|54|Updated Mar 11, 2026

Search Tags:#charts #visualization #performance analysis #matplotlib #trading #mplfinance

Ready to run

npx skills add https://github.com/agiprolabs/claude-trading-skills --skill trading-visualization

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: trading-visualization
Source: https://github.com/agiprolabs/claude-trading-skills/tree/main/skills/trading-visualization
Command: npx skills add https://github.com/agiprolabs/claude-trading-skills --skill trading-visualization

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires mplfinance, matplotlib, scipy, and includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill provides the tools and code to create professional, publication-quality trading charts, enabling deeper analysis of market data and strategy performance.

Core Features & Use Cases

Diverse Chart Types: Generate candlesticks, equity curves, drawdowns, return distributions, correlation heatmaps, and more.
Customizable Styling: Adheres to a dark-theme convention common in trading platforms, with options for customization.
Use Case: Analyze a trading strategy's performance by generating an equity curve with a drawdown panel, and visualize its risk by plotting the return distribution with VaR and CVaR.

Quick Start

Generate a candlestick chart with 20 and 50-period EMAs using the provided price data.

Frequently Asked Questions about trading-visualization

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I generate professional trading charts like candlesticks and equity curves in Python?▼

You generate professional trading charts using Matplotlib and mplfinance to plot candlesticks, equity curves, drawdowns, and return distributions. This Skill provides customizable scripts supporting dark-theme styling and multi-panel layouts for publication-quality financial visualizations.

Can I plot a return distribution with VaR and CVaR using matplotlib?▼

Yes, you can plot return distributions with VaR and CVaR using matplotlib. The Skill leverages scipy alongside matplotlib for advanced statistical plotting, enabling you to visualize trading strategy risk through return distribution charts.

What's the best way to visualize strategy drawdowns alongside an equity curve?▼

The best way to visualize drawdowns is by generating a multi-panel layout with an equity curve and a dedicated drawdown panel. The Skill uses mplfinance and matplotlib to create these professional charts with custom dark-theme styling.

Does this mplfinance visualization approach support correlation heatmaps for multiple assets?▼

Yes, this mplfinance visualization approach supports correlation heatmaps for multiple assets. The Skill generates diverse chart types including correlation heatmaps, candlesticks, and return distributions using scipy and matplotlib.

Do I need scipy installed to create trading charts with this Skill?▼

Yes, you need scipy installed to use this Skill for advanced statistical plotting. Along with mplfinance and matplotlib, scipy is a required dependency for generating charts like return distributions and correlation heatmaps.