matplotlib
Creates and customizes scientific plots with Matplotlib, with fine control over plot elements, and exports to PNG, PDF or SVG for publication.
- Kind
- Skill
- Works with
- Claude Code, Codex, Cursor, Gemini / Antigravity
- Source
- Scientific Agent Skills (K-Dense) @ 5f2bc0341354
- Path
- skills/matplotlib/SKILL.md
- Jobs
- Implementation
- Topics
- Data analysis & BI
Credit
- Made by
- K-Dense-AI
- Original
- github.com/K-Dense-AI/scientific-agent-skills/blob/5f2bc03413…
- License
- MIT
Listed by Skill Manifest; not made by us.
InstallInstall it by hand, following the source.
gh skill install K-Dense-AI/scientific-agent-skills matplotlib
Install factsScanned 2 Nov 2026
- Adds
- .claude/skills/matplotlib/ (the skill folder)
- 4 file(s) the skill refers to
- Runs scripts
- Yes
- scripts/plot_template.py
- scripts/style_configurator.py
- allowed-tools includes Bash
- shell block in the text
- Uses the network
- Yes
- downloads Python packages
- Needs secrets
- None found
- Source revision
- 5f2bc0341354
- Licence
- MIT
- Last activity
- 26 Oct 2026
- Review
- Reviewed
Found by a static scan of the stored text; nothing is run. “None found” is not a guarantee, so read what you install before you run it.
- Only the main file is read; other files in the folder are not scanned
# Matplotlib ## Overview Matplotlib is Python's foundational visualization library for creating static, animated, and interactive plots. This skill provides guidance on using matplotlib effectively, covering both the pyplot interface (MATLAB-style) and the object-oriented API (Figure/Axes), along with best practices for creating publication-quality visualizations. ## When to Use This Skill This skill should be used when: - Creating any type of plot or chart (line, scatter, bar, histogram, heatmap, contour, etc.) - Generating scientific or statistical visualizations - Customizing plot appearance (colors, styles, labels, legends) - Creating multi-panel figures with subplots - Exporting visualizations to various formats (PNG, PDF, SVG, etc.) - Building interactive plots or animations - Working with 3D visualizations - Integrating plots into Jupyter notebooks or GUI applications ## Setup For project work, install Matplotlib with uv: ```bash uv add "matplotlib==3.11.2" numpy scipy ``` For notebook interactivity: ```bash uv add "matplotlib==3.11.2" ipympl ``` Then enable the widget backend in Jupyter with `%matplotlib widget` or `%matplotlib ipympl`. …