Does the skill help with making charts accessible?

Yes, it includes guidance on using perceptually uniform, colorblind-friendly colormaps and adding patterns or hatching to ensure data remains readable for all users.

How does this handle overlapping labels or titles?

The skill encourages the use of layout managers like constrained_layout and tight_layout to automatically prevent elements from overlapping.

Can I create 3D visualizations with this skill?

Yes, it provides implementation patterns for 3D scatter plots, surface plots, and wireframes using the Axes3D projection.

Can I export high-resolution figures for academic journals?

Absolutely. The skill includes best practices for exporting in vector formats (PDF/SVG) and high-DPI raster formats (300 DPI PNG) with optimized padding.

Does this skill support the Object-Oriented Matplotlib API?

Yes, it specifically recommends and provides patterns for the Object-Oriented (OO) interface, as it offers more explicit control and better maintainability for complex figures.

Matplotlib Scientific Visualization

Name: Matplotlib Scientific Visualization
Author: BbgnsurfTech

byBbgnsurfTech

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Ciencia de Datos y ML

Generates professional, publication-quality plots and charts using Python's foundational visualization library.

Acerca de

This skill empowers Claude to create a wide range of static, animated, and interactive visualizations using Matplotlib. It provides expert guidance on choosing between the pyplot interface and the object-oriented API, ensuring clean, maintainable code for everything from simple line plots to complex multi-panel scientific figures. By following best practices for layout, colormaps, and accessibility, this skill helps users transform raw data into clear, informative, and visually appealing insights suitable for both screen and print.

Características Principales

Advanced multi-panel layouts using GridSpec and Subplot Mosaic
Standardized creation of line, scatter, bar, histogram, and 3D plots
Implementation of the robust Object-Oriented (Figure/Axes) interface
High-resolution exports for publications in PNG, PDF, and SVG formats
Dynamic styling with rcParams and colorblind-friendly colormaps
3 GitHub stars

Casos de Uso

Creating automated data analysis dashboards and reports
Visualizing complex mathematical functions or high-dimensional datasets
Generating publication-quality figures for research papers and journals

Acerca de

Características Principales

Advanced multi-panel layouts using GridSpec and Subplot Mosaic
Standardized creation of line, scatter, bar, histogram, and 3D plots
Implementation of the robust Object-Oriented (Figure/Axes) interface
High-resolution exports for publications in PNG, PDF, and SVG formats
Dynamic styling with rcParams and colorblind-friendly colormaps
3 GitHub stars

Casos de Uso

Creating automated data analysis dashboards and reports
Visualizing complex mathematical functions or high-dimensional datasets
Generating publication-quality figures for research papers and journals