skills.rest
SciMate-AI
SciMate-AIOFFICIAL
Explore all skills by this author →
GitHub

matplotlib

Create publication-quality plots with matplotlib's OO API and export to PNG, PDF, or SVG.

1|Updated Mar 11, 2026
Search Tags:#python#styling#visualization#plotting#matplotlib#data-visualization#3d-plot
One-click install
npx skills add https://github.com/SciMate-AI/scicli --skill matplotlib-scimate-ai
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: matplotlib
Source: https://github.com/SciMate-AI/scicli/tree/main/internal/skills/bundled/claude-scientific-skills/skills/matplotlib
Command: npx skills add https://github.com/SciMate-AI/scicli --skill matplotlib-scimate-ai

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

Create high-fidelity, customizable visualizations with Python's matplotlib to replace manual plotting and enable precise, publication-ready figures.

Core Features & Use Cases

  • Low-level plotting primitives for full control over Figure/Axes elements (lines, markers, grids, text).
  • Supports a wide range of plot types (line, scatter, bar, histogram, heatmap, contour, 3D) and export options (PNG, PDF, SVG).
  • Real-world workflow: produce multi-panel scientific figures with consistent styling, save reusable styles, and integrate with NumPy/Pandas data.

Quick Start

Install matplotlib and run the sample script to generate a basic line plot.

Frequently Asked Questions about matplotlib

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

FAQPage Schema
How do I create publication-quality scientific plots with Python?▼

Create publication-quality scientific plots in Python using matplotlib's OO API for precise control over Figure and Axes elements. This Skill generates customizable line, scatter, bar, histogram, heatmap, contour, and 3D visualizations for research workflows.

What plot types can I generate for data visualization using matplotlib?▼

Data visualization with matplotlib supports line, scatter, bar, histogram, heatmap, contour, and 3D plots. You can apply custom styling, color mapping, and layout configurations to produce consistent, publication-ready scientific figures.

Can I export matplotlib figures to PDF and SVG formats?▼

Yes, you can export matplotlib figures to PDF, PNG, and SVG formats. This allows you to save high-fidelity visualizations directly from your Python scripts for inclusion in publications, presentations, or further vector editing.

Do I need NumPy and SciPy to generate multi-panel scientific figures?▼

NumPy and SciPy are required dependencies for generating multi-panel scientific figures. This Skill integrates with NumPy and Pandas data arrays to apply consistent styling across multiple axes and produce complex layout configurations.

Why use the matplotlib OO API instead of standard plotting functions?▼

Using the matplotlib OO API provides low-level control over Figure and Axes primitives like lines, markers, grids, and text. This approach is necessary for creating reusable style sheets and complex, multi-panel layouts that standard plotting functions cannot easily achieve.

What are the limitations of matplotlib for 3D plotting?▼

Matplotlib supports 3D plotting for scientific workflows, but it is primarily designed for 2D publication-ready figures. For complex 3D visualizations requiring advanced rendering or interactivity, consider specialized alternative tools within the same data visualization category.

Related Skills

Explore More Data & Analytics Skills→
jkitchinjkitchin
34

python-plotting

Select and apply Matplotlib, Seaborn, or Plotly for Python visualizations.

Community
Intermediate
Victory-HugoVictory-Hugo
1

scientific-visualization

Generate publication-ready multi-panel figures using Matplotlib, Seaborn, and Plotly with PDF/PNG/SVG export.

Community
Intermediate
jkitchinjkitchin
34

video-assembly

Assemble six-scene MP4 videos from images and narrated audio using ffmpeg.

Community
Advanced
Ritabrata-ChakrabortyRitabrata-Chakraborty

seaborn

Generate statistical visualizations like scatter plots and heatmaps with Matplotlib and Pandas.

Community
Advanced