exploratory-data-analysis

Automate exploratory data analysis by running this Skill on your scientific data files to auto-detect formats and generate structured markdown reports containing metadata, quality metrics, and downstream recommendations.

Generate a data quality report by applying format-aware analysis to microscopy and spectroscopy files, which produces structured summaries and quality metrics in a markdown report.

This EDA tool supports 200+ file formats across bioinformatics, chemistry, proteomics, and microscopy, automatically detecting the file type to apply format-specific metadata extraction and analysis.

You can run exploratory data analysis on large multi-format scientific datasets because the Skill uses robust sampling and error handling to guide downstream analysis without failing on mixed file types.

Detect the file format of scientific data by inputting your files into the analyzer, which identifies the type, extracts format-specific metadata, and outputs actionable downstream recommendations in a markdown report.

Limitations when generating markdown reports include relying on sampling for large multi-format datasets and requiring specific dependencies like pandas, numpy, and biopython for full format-aware analysis.