skills.rest
Zeyuyang-0420
Zeyuyang-0420COMMUNITY
Explore all skills by this author →
GitHub

exploratory-data-analysis

Detect scientific data file types and generate markdown analysis reports.

Updated May 8, 2026
Search Tags:#data analysis#file analysis#data exploration#scientific data#markdown reporting
One-click install
npx skills add https://github.com/Zeyuyang-0420/bio-ai-research-skills --skill exploratory-data-analysis-zeyuyang-0420
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: exploratory-data-analysis
Source: https://github.com/Zeyuyang-0420/bio-ai-research-skills/tree/main/categories/data-analysis-visualization/exploratory-data-analysis
Command: npx skills add https://github.com/Zeyuyang-0420/bio-ai-research-skills --skill exploratory-data-analysis-zeyuyang-0420

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires biopython, pandas, numpy, scikit-learn, mdanalysis, rdkit, pybigwig, pybedtools, pyranges, pysam, cyvcf2, HTSeq, pybigtools, pybbi, loompy, scanpy, pyreadr, rpy2, pyteomics, pymzml, nmrglue, cclib, h5py, pandas, numpy, scipy, pymatplotlib, pyqt5, soundfile, scipy.io, astropy.io.fits, asdf, uproot, pyhdf, gdal, netCDF4, xarray, pygrib, cfgrib, hdf5storage, and includes scripts (resource) and references (resource) and assets (resource) components.

What problem does it solve?

This Skill automates the process of exploring and understanding scientific data files across various formats, saving you time and reducing errors.

Core Features & Use Cases

  • File Type Detection: Automatically identifies the format of scientific data files.
  • Format-Specific Analysis: Performs in-depth analysis based on the detected file format.
  • Data Quality Assessment: Evaluates the quality and integrity of the data.
  • Markdown Reporting: Generates comprehensive reports detailing the file's structure, content, and analysis results.
  • Use Case: If you have a large dataset in a specific scientific format (e.g., FASTQ, CSV, TIFF), use this Skill to quickly get an overview of the data, check for errors, and make informed decisions about further analysis.

Quick Start

Use the exploratory-data-analysis skill to analyze the file 'dataset.hdf5'.

Frequently Asked Questions about exploratory-data-analysis

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I perform exploratory data analysis on scientific data files?▼

Exploratory data analysis on scientific data files is performed by automatically detecting the file type, executing format-specific analysis on structure and content, and generating a detailed markdown report with quality assessment and analysis recommendations.

Can I analyze genomics and proteomics file formats like FASTQ, VCF, and mzML together?▼

Yes, you can analyze genomics and proteomics file formats together. The skill automatically detects formats and uses specific libraries like pysam, cyvcf2, and pymzml to perform format-specific analysis on diverse scientific data files.

What is the best way to check data quality and structure for large scientific datasets?▼

The best way to check data quality and structure for large scientific datasets is to use an automated tool that evaluates data integrity, identifies format-specific errors, and outputs a markdown report detailing file content and analysis recommendations.

Do I need specific Python libraries installed to analyze HDF5 and netCDF files?▼

Yes, you need specific Python libraries installed to analyze HDF5 and netCDF files. The skill requires dependencies like h5py, netCDF4, and xarray to perform format-specific analysis and generate reports on these scientific data structures.

Does this data exploration tool support astronomical FITS files and climate datasets?▼

Yes, this data exploration tool supports astronomical FITS files and climate datasets. It utilizes libraries such as astropy.io.fits for astronomy data and cfgrib or xarray for climate datasets to perform format-specific analysis and generate markdown reports.

Related Skills

Explore More Data & Analytics Skills→
jadzoghaibjadzoghaib

exploratory-data-analysis

Analyze scientific files to generate markdown reports on structure and quality.

Community
Intermediate
luokai25luokai25

data-scientist

Automate data analysis and predictive modeling with Pandas, NumPy, Scikit-learn, and XGBoost.

Community
Advanced
gracefullightgracefullight

matplotlib

Generate static, animated, and interactive plots with Matplotlib.

Community
Advanced
RamanEbrahimiRamanEbrahimi
3

anndata

Handle and analyze annotated matrices in single-cell genomics with Python.

Community
Advanced