Exploratory Data Analysis

소개

This skill provides a powerful framework for analyzing scientific datasets across disciplines such as chemistry, bioinformatics, imaging, and spectroscopy. It automatically detects and interprets over 200 file formats, performing deep metadata extraction, statistical summaries, and data integrity assessments. By generating detailed markdown reports, the skill helps researchers understand their data's structure and quality, offering actionable recommendations for visualization and downstream analysis while streamlining the transition from raw data to actionable insights.

주요 기능

• Automatic detection and analysis of 200+ scientific file formats across multiple domains
• Domain-specific guidance for chemistry, genomics, microscopy, and spectroscopy
• Comprehensive metadata extraction and format-specific data quality assessment
• 2,066 GitHub stars
• Automated generation of detailed markdown reports including statistical summaries
• Actionable recommendations for data preprocessing, visualization, and tools

사용 사례

• Analyzing the structure and content of a scientific data file before starting a project
• Assessing data quality and completeness to identify potential outliers or missing values
• Generating comprehensive documentation reports for complex laboratory datasets