Exploratory Data Analysis
Helps with data, analysis as part of data analysis and analytics workflows workflows.
Install on your platform
We auto-selected Claude Code based on this skill’s supported platforms.
Run in terminal (recommended)
claude mcp add braselog-exploratory-data-analysis npx -- -y @trustedskills/braselog-exploratory-data-analysis
Or manually add to ~/.claude/settings.json
{
"mcpServers": {
"braselog-exploratory-data-analysis": {
"command": "npx",
"args": [
"-y",
"@trustedskills/braselog-exploratory-data-analysis"
]
}
}
}Requires Claude Code (claude CLI). Run claude --version to verify your install.
About This Skill
What it does
This skill performs exploratory data analysis (EDA) on datasets provided as CSV files. It automatically identifies and summarizes key statistical properties, including distributions, correlations, and potential outliers. The goal is to provide initial insights into the dataset's structure and characteristics before further modeling or analysis.
When to use it
- You have a new dataset and want a quick overview of its contents.
- Before building machine learning models, you need to understand data distributions and relationships.
- To identify potential data quality issues like missing values or outliers.
- When exploring the feasibility of using a dataset for a specific project.
Key capabilities
- CSV file input
- Statistical summary generation (e.g., mean, median, standard deviation)
- Distribution visualization
- Correlation analysis
- Outlier detection
Example prompts
- "Analyze this CSV file and tell me about the data."
- "Perform exploratory data analysis on 'customer_data.csv' and highlight any potential outliers."
- "What are the correlations between different columns in 'sales_data.csv'?"
Tips & gotchas
- The skill requires a valid CSV file as input. Ensure the file is properly formatted before providing it to the agent.
Tags
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Security Audits
| Gen Agent Trust Hub | Pass |
| Socket | Pass |
| Snyk | Pass |
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