exploratory-data-analysis

What problem does it solve?

Analyzing diverse scientific data files to understand their structure, quality, and characteristics is a time-consuming and complex task, often requiring specialized knowledge of numerous file formats and programming libraries. This Skill automates comprehensive exploratory data analysis (EDA).

Core Features & Use Cases

• 200+ File Format Support: Automatically detect and analyze a vast array of scientific data formats across chemistry, bioinformatics, microscopy, and more.
• Automated Data Quality Reports: Generate detailed Markdown reports with format-specific analysis, quality metrics, and downstream analysis recommendations.
• Downstream Analysis Guidance: Receive suggestions for appropriate preprocessing steps, analytical methods, and visualization approaches.
• Use Case: When you receive a new .fastq file from a sequencing experiment, use this skill to automatically generate a comprehensive report detailing sequence counts, length distributions, quality scores, and recommendations for variant calling or assembly.

Quick Start

Analyze the scientific data file 'experiment_results.csv' and provide a detailed report.