Install
Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.
npx agentmarket install skill/beita6969-data-visualization-expert
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About
Use cases: data
Reviews
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Permissions
What this skill can do and what it asks for, from its SKILL.md. Checked Oct 25, 2026.
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Network hosts it talks to 1
codeload.github.com· found in install command
Files it touches
~/.claude/skills/data-visualization-expert
What's inside
- Skill name
data-visualization-expert- Description
- COPYRIGHT NOTICE
- License
- MIT
- Instructions
- 73 lines in SKILL.md · view on GitHub
Files (1)
- SKILL.md
SKILL.md (first lines)
<!-- # COPYRIGHT NOTICE # This file is part of the "Universal Biomedical Skills" project. # Copyright (c) 2026 MD BABU MIA, PhD <md.babu.mia@mssm.edu> # All Rights Reserved. # # This code is proprietary and confidential. # Unauthorized copying of this file, via any medium is strictly prohibited. # # Provenance: Authenticated by MD BABU MIA --> --- name: data-visualization-expert description: Generate insightful, publication-quality visualizations from complex datasets. keywords: - charts - plots - analysis - pandas - matplotlib - seaborn measurable_outcome: Create 3 high-resolution (300dpi) statistical plots (volcano, heatmap, scatter) within 15 minutes. license: MIT metadata: author: AI Agentic Skills Team version: "2.0.0" compatibility: - system: linux, macos allowed-tools: - run_shell_command - write_file - read_file --- # Data Visualization Expert A dedicated skill for transforming raw data (CSV, JSON, Excel) into compelling visual narratives. Specializes in statistical and scientific plotting. ## When to Use - **Reports:** Summarizing key metrics or KPIs. - **Exploration:** Initial data analysis (EDA) to find trends/outliers. - **Publication:** Generating figures for papers or presentations. - **Comparison:** Comparing models, cohorts, or experimental groups. ## Core Capabilities 1. **Code Generation:** Creates Python scripts (Matplotlib, Seaborn, Plotly) or R code (ggplot2). 2. **Style Enforcement:** Adheres to specific journal/company branding (fonts, colors). 3. **Data Cleaning:** Preprocesses data (handle missing values, normalize) for plotting. 4. **Artifact Management:** Saves plots as PNG/SVG/PDF files. ## Workflow 1. **Load Data:** Read input file (`pd.read_csv()`) and inspect columns/types. 2. **Clean & Transform:** Filter, pivot, or aggregate data as needed. 3. **Generate Plot:** Write plotting script with strict aesthetic controls. 4. **Save & Verify:** Execute script, check output file existence/size. ## Example Usage ```bash # Agent prompt: "Visualize the distribution of 'Age' vs 'Income' from customers.csv" # Triggers generation of `plot_age_income.py` using Seaborn scatterplot. ``` ## Guardrails - **Privacy:** Avoid plotting PII (names, emails) directly. - **Accuracy:** Ensure axes are labeled correctly with units. - **Readability:** Use appropriate scales (log vs linear) and avoid clutter. <!-- AUTHOR_SIGNATURE: 9a7f3c2e-MD-BABU-MIA-2026-MSSM-SECURE -->
From beita6969/ScienceClaw, MIT.
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Signals
- Stars
- 1,019
- Forks
- 109
- Open issues
- 1
- Last commit (this folder)
- Mar 12, 2026 (7 months ago)
From GitHub (fetched Oct 24, 2026).
Details
- License
- MIT
- Repository
- github.com/beita6969/ScienceClaw
- Website
- scienceclaw.science
- First seen
- Oct 24, 2026
- Last checked
- Oct 24, 2026
- Source
- GitHubgithub-graphql
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SkillAFreshness: A★ 1KClaude Code +9 - 0.608score
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Cite this page
data-visualization-expert skill. Agent Mart. https://agentmart.dev/skills/beita6969-data-visualization-expert (last updated 2026-10-24)