Ggplot2
Generates interactive visualizations from R data using ggplot2, enabling insightful data exploration and clear communication of findings.
Install on your platform
We auto-selected Claude Code based on this skill’s supported platforms.
Run in terminal (recommended)
claude mcp add ggplot2 npx -- -y @trustedskills/ggplot2
Or manually add to ~/.claude/settings.json
{
"mcpServers": {
"ggplot2": {
"command": "npx",
"args": [
"-y",
"@trustedskills/ggplot2"
]
}
}
}Requires Claude Code (claude CLI). Run claude --version to verify your install.
About This Skill
What it does
The ggplot2 skill enables AI agents to create visually appealing and informative statistical graphics in R. It leverages the popular ggplot2 package, allowing for the generation of a wide variety of plots including scatterplots, histograms, bar charts, and boxplots. Agents can use this skill to explore data patterns, communicate findings effectively, and build interactive visualizations.
When to use it
- Data Exploration: Generate quick visualizations to understand the distribution and relationships within a dataset.
- Report Generation: Create professional-looking plots for inclusion in reports or presentations.
- Interactive Dashboards: Build dynamic dashboards where users can interact with data through visual representations.
- Scientific Research: Produce publication-quality figures for scientific papers and research projects.
Key capabilities
- Generates various plot types (scatterplots, histograms, bar charts, boxplots).
- Utilizes the
ggplot2R package. - Creates visually appealing and informative graphics.
- Supports data exploration and communication of findings.
Example prompts
- "Create a scatterplot showing the relationship between X and Y in this dataset."
- "Generate a histogram of the 'age' column from my data."
- "Produce a bar chart comparing sales across different product categories."
Tips & gotchas
- Requires an R environment to be available for the AI agent.
- The quality of the visualization depends on the structure and cleanliness of the input dataset.
Tags
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