Professional data visualization using Python (matplotlib, seaborn, plotly). Create publication-quality static charts, statistical visualizations, and interac...
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Select your agent
Option 1: Install via CLI (recommended)
Recommended (no pre-install needed)
npx clawhub@latest --dir ~/.claude/skills install python-datavizOr via clawhub CLI (if already installed)
clawhub --dir ~/.claude/skills install python-datavizβ οΈ Requires Node.js 18+. No Node? Use Option 2 below to download the ZIP instead. Install Node.js β
Option 2: Manual install (no Node required)
Download the ZIP, extract it, and place the folder at the path below. Restart your agent to activate.
Install path
~/.claude/skills/python-dataviz/π‘Extract and place the folder at the path above, then restart your agent.
Category
πData & AnalyticsPlatforms
What Python Dataviz can do for your AI workflow
Professional data directly from your Claude conversation
Works across Claude, Cursor, OpenClaw β install once, use everywhere
Trusted by 6,158+ developers worldwide
One-command installation β no complex setup required
Combine with other skills to build powerful multi-step AI workflows
Try these prompts with your AI agent after installing Python Dataviz
Help me get started with Python Dataviz
Explains what Python Dataviz does, walks through the setup, and runs a quick demo based on your current project
Use Python Dataviz to professional data visualization using Python (matplotlib, seaborn, ...
Invokes Python Dataviz with the right parameters and returns the result directly in the conversation
What can I do with Python Dataviz in my data & analytics workflow?
Lists the top use cases for Python Dataviz, with example commands for each scenario
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Python Dataviz extends your AI assistant with the ability to professional data visualization using Python (matplotlib, seaborn, plotly). Create publication-quality static charts, statistical visualizations, and interac... Rather than leaving your conversation to handle this manually, you can ask your Claude agent directly β and it will take care of the task end-to-end, using Python Dataviz as its underlying capability.
Python Dataviz works across Claude, Cursor, OpenClaw through the Model Context Protocol (MCP) β an open standard that lets AI clients share tools and skills without lock-in. Because MCP is platform-agnostic by design, you install Python Dataviz once and it becomes available across all your AI clients. Whether you're working in Claude for focused sessions or Cursor for integrated workflows, the skill behaves consistently.
Python Dataviz installs like any other MCP skill: drop the folder into `~/.claude/skills/python-dataviz/` for global access, or `.claude/skills/python-dataviz/` to keep it scoped to one project. After a quick restart of Claude, you can trigger it explicitly with `/python-dataviz`, or let the AI decide when it's the right tool for your request.
Python Dataviz has been installed 6,158 times, making it one of the more actively used skills in the Data & Analytics category. The install rate suggests it solves a real, recurring need rather than a niche edge case. Like all skills on DiscoverAISkills, it is free to install and use. The broader AI skills ecosystem continues to expand as developers contribute new capabilities across categories like developer tools, data analysis, writing, automation, and more.
Place the skill folder at ~/.claude/skills/python-dataviz/ for personal use (all projects), or .claude/skills/python-dataviz/ for project-specific use. Restart your AI client, then invoke with /python-dataviz or let the AI discover it automatically.
Python Dataviz supports Claude, Cursor, OpenClaw. It integrates seamlessly with these AI platforms to extend their capabilities.
Python Dataviz is free to install. Check the repository for licensing information.
Professional data visualization using Python (matplotlib, seaborn, plotly). Create publication-quality static charts, statistical visualizations, and interac...
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Automate my data & analytics tasks using Python Dataviz
Identifies repetitive steps in your workflow and sets up Python Dataviz to handle them automatically
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