exploratory-data-analysis
Perform comprehensive exploratory data analysis on scientific data files across 200+ file formats. This skill should be used when analyzing any scientific data file to understand its structure, content, quality, and characteristics. Automatically detects file type and generates detailed markdown reports with format-specific analysis, quality metrics, and downstream analysis recommendations. Covers chemistry, bioinformatics, microscopy, spectroscopy, proteomics, metabolomics, and general scientific data formats.
npx skills add LeonChaoX/qinyan-academic-skills --skill exploratory-data-analysis --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Exploratory Data Analysis ## Overview Perform comprehensive exploratory data analysis (EDA) on scientific data files across multiple domains. This skill provides automated file type detection, format-specific analysis, data quality assessment, and generates detailed markdown reports suitable for documentation and downstream analysis planning. **Key Capabilities:** - Automatic detection and analysis of 200+ scientific file formats - Comprehensive format-specific metadata extraction - Data quality and integrity assessment - Statistical summaries and distributions - Visualization recommendations - Downstream analysis suggestions - Markdown report generation ## When to Use This Skill Use this skill when: - User provides a path to a scientific data file for analysis - User asks to "explore", "analyze", or "summarize" a data file - User wants to understand the structure and content of scientific data - User needs a comprehensive report of a dataset before analysis - User wants to assess data quality or completeness - User asks what type of analysis is appropriate for a file ## Supported File Categories The skill has comprehensive coverage of scientific file formats organized into six m
- Overview
- When to Use This Skill
- Supported File Categories
- 1. Chemistry and Molecular Formats (60+ extensions)
- 2. Bioinformatics and Genomics Formats (50+ extensions)
- 3. Microscopy and Imaging Formats (45+ extensions)
- 4. Spectroscopy and Analytical Chemistry Formats (35+ extensions)
- 5. Proteomics and Metabolomics Formats (30+ extensions)
- 6. General Scientific Data Formats (30+ extensions)
- Workflow
- Step 1: File Type Detection
- Step 2: Load Format-Specific Information
- Step 3: Perform Data Analysis
- Step 4: Generate Comprehensive Report
Basic usage python scripts/eda_analyzer.py data.csv Specify output file python scripts/eda_analyzer.py data.csv output_report.md The script will:
What does the exploratory-data-analysis skill do?
Perform comprehensive exploratory data analysis on scientific data files across 200+ file formats. This skill should be used when analyzing any scientific data file to understand its structure, content, quality, and characteristics. Automatically detects file type and generates detailed markdown reports with format-specific analysis, quality metrics, and downstream analysis recommendations. Covers chemistry, bioinformatics, microscopy, spectroscopy, proteomics, metabolomics, and general scientific data formats.
How do I install it?
Run `npx skills add LeonChaoX/qinyan-academic-skills --skill exploratory-data-analysis --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From LeonChaoX/qinyan-academic-skills, a repository with 759 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.