Can I use this for grant proposals?

Yes, the skill is designed to produce clear, professional-grade visuals that meet the rigorous requirements of grant applications and professional presentations.

How does it ensure charts are accessible?

The skill automatically uses color-blind friendly palettes and ensures that font sizes and line weights remain legible and grayscale-compatible.

Does it handle statistical significance in charts?

Yes, it follows best practices by adding significance asterisks to plots and including p-values within the captions.

What file formats does the Data Visualization skill support?

The skill prioritizes high-resolution vector formats like PDF and SVG for publication quality, but can also generate 300 DPI raster images.

Is this skill suitable for exploratory data analysis (EDA)?

Absolutely. It includes specific patterns for distribution checks, including histograms, density plots, and Q-Q plots for normality.

Data Visualization

Name: Data Visualization
Author: astoreyai

byastoreyai

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数据科学与机器学习

Generates publication-quality scientific figures and data visualizations following academic design standards.

关于

The Data Visualization skill empowers Claude to automate the creation of sophisticated, high-resolution figures optimized for research manuscripts, grant proposals, and professional presentations. It streamlines the plotting process from exploratory data analysis to final production, ensuring all visuals adhere to rigorous design principles such as color-blind friendly palettes, appropriate statistical representations (95% CI), and specific font requirements. Whether you need distribution checks with Q-Q plots or complex relationship mapping through scatter plots, this skill ensures your data is presented with clarity, precision, and professional aesthetic.

主要功能

Implements best practices for statistical reporting, including error bars and significance asterisks.
Optimizes visual accessibility using color-blind friendly palettes and grayscale compatibility.
2 GitHub stars
Supports a wide array of plot types including violin plots, box plots, and time-series line graphs.
Enforces academic standards with high-resolution (300+ DPI) and vector format (PDF, SVG) exports.
Automates exploratory data analysis with automated histograms and normality distribution checks.

使用场景

Preparing high-impact figures for peer-reviewed journal manuscripts and academic submissions.
Conducting rapid exploratory data analysis to identify trends and correlations in complex datasets.
Generating professional visual assets for grant applications and stakeholder presentations.

关于

主要功能

Implements best practices for statistical reporting, including error bars and significance asterisks.
Optimizes visual accessibility using color-blind friendly palettes and grayscale compatibility.
2 GitHub stars
Supports a wide array of plot types including violin plots, box plots, and time-series line graphs.
Enforces academic standards with high-resolution (300+ DPI) and vector format (PDF, SVG) exports.
Automates exploratory data analysis with automated histograms and normality distribution checks.

使用场景

Preparing high-impact figures for peer-reviewed journal manuscripts and academic submissions.
Conducting rapid exploratory data analysis to identify trends and correlations in complex datasets.
Generating professional visual assets for grant applications and stakeholder presentations.