A professional data visualization toolkit for generating publication-quality static charts and interactive web plots using Python's leading libraries.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install python-dataviz
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install python-dataviz using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is Python Data Visualization?
The python-dataviz skill provides a robust environment for generating high-quality visual data representations. By leveraging industry-standard libraries like matplotlib, seaborn, and plotly, this tool allows users to transform raw datasets into meaningful insights. Whether you need static SVG files for academic papers or interactive HTML dashboards for web applications, this Openclaw Skills addition streamlines the entire plotting workflow.
Built for developers and data scientists, it handles everything from basic bar charts to complex statistical distributions and 3D animations. It integrates seamlessly with pandas and NumPy, ensuring that your data processing pipeline flows directly into your visualization layer without friction.
Python Data Visualization Use Cases
- Generating publication-quality static charts for reports or scientific papers.
- Creating interactive web-based visualizations with hover effects and zoom capabilities.
- Automating the production of statistical plots like heatmaps, violin plots, and regression lines.
- Producing infographics and data components for digital marketing or dashboards.
- Visualizing complex datasets directly from CSV, dictionaries, or NumPy arrays.
How Python Data Visualization Works
- Initialize the environment by activating the pre-configured virtual environment within the Openclaw Skills workspace.
- Prepare data using standard formats like Pandas DataFrames, NumPy arrays, or Python dictionaries.
- Select the appropriate library (matplotlib for control, seaborn for aesthetics, or plotly for interactivity) based on the visualization goal.
- Configure plot parameters such as figure size, DPI, color palettes, and axis labels.
- Execute the rendering process and export the final visualization to formats like PNG, SVG, PDF, or HTML.
Python Data Visualization Setup
To begin using this skill within your Openclaw Skills setup, navigate to the skill directory and initialize the environment:
cd skills/python-dataviz
python3 -m venv .venv
source .venv/bin/activate
pip install .
Ensure you have the core dependencies installed to handle all export formats including kaleido for static plotly exports.
Python Data Visualization Data Schema & Taxonomy
The skill processes various data structures and generates high-resolution output files. Below is the metadata and file organization schema:
| Feature | Supported Formats / Tools |
|---|---|
| Input Data | CSV, JSON, NumPy Arrays, Python Dictionaries |
| Static Export | PNG (Raster), SVG (Vector), PDF |
| Interactive Export | HTML (Self-contained) |
| Styling Engines | Seaborn themes, Matplotlib stylesheets, Custom Hex codes |
| Plot Types | Distribution, Comparison, Relationship, Composition |
Python Data Visualization Advanced Features
- Multi-panel figure layouts and complex subplots for comparative analysis.
- Advanced statistical visualization including KDE, swarm plots, and correlation heatmaps.
- Full color theory support with custom palettes and seaborn's husl/muted/deep themes.
- 3D plotting and animations via the plotly framework for web-friendly interactivity.
- Automated high-resolution export (300+ DPI) tailored for professional publication standards.
SKILL.md
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