What file formats does this EDA skill support?

It supports a wide range of common data formats including CSV, Excel (.xlsx, .xls), JSON, Parquet, TSV, Feather, HDF5, Pickle, and more.

What kind of visualizations are generated?

The toolkit generates high-resolution (300 DPI) plots including distribution histograms with KDE overlays, correlation heatmaps, box/violin plots for outliers, and scatter matrices.

Are the reports generated by this skill shareable?

Yes, it produces professional markdown reports that integrate visualizations and automated insights, making them perfect for project documentation or sharing with team members.

Can it handle large datasets with over a million rows?

For very large datasets, the skill is designed to run analysis on sampled data first to provide quick exploration, while recommending distributed computing for full-scale processing.

Does this skill help with data cleaning?

While its primary focus is exploration, it automatically flags data quality issues like duplicates, missing values, and imbalances, providing specific recommendations for cleaning and feature engineering.

Exploratory Data Analysis Toolkit

Name: Exploratory Data Analysis Toolkit
Author: lifangda

bylifangda

•

Ciencia de Datos y ML

Automates comprehensive statistical analysis and visual profiling for diverse datasets to uncover hidden patterns, anomalies, and actionable insights.

This skill equips Claude with a robust suite of data science tools to perform automated Exploratory Data Analysis (EDA) on various file formats including CSV, Excel, Parquet, and JSON. It streamlines the analytical workflow by generating detailed statistical summaries, identifying outliers, detecting correlations, and producing production-ready visualizations. Designed for data scientists and analysts, it transforms raw data files into structured markdown reports and actionable intelligence, facilitating rapid data profiling and quality assessment directly within the Claude environment.

Características Principales

01Intelligent outlier detection and comprehensive data quality assessment

0216 GitHub stars

03Automated markdown report generation using professional insight templates

04Multi-format data support including CSV, Excel, JSON, Parquet, and HDF5

05High-quality visualization suite featuring heatmaps, scatter matrices, and box plots

06Automated statistical summaries, distribution analysis, and normality tests

Casos de Uso

01Statistical validation and hypothesis testing during scientific research or business analysis

02Initial data profiling for new datasets to identify quality issues and missing values

03Generating comprehensive visual data reports for stakeholders and project documentation

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add lifangda/claude-plugins exploratory-data-analysis

For use in Claude.ai and ChatGPT

Download Skill