data-analysis

Analyze CSV, JSON, and Parquet datasets with exploratory analysis and visualizations.

Updated Nov 7, 2025

Search Tags:#reporting #visualization #statistics #data-analysis #EDA #machine-learning

Ready to run

npx skills add https://github.com/Wesley1600/ClaudeCodeFrameWork --skill data-analysis-wesley1600

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: data-analysis
Source: https://github.com/Wesley1600/ClaudeCodeFrameWork/tree/main/skills/data-analysis
Command: npx skills add https://github.com/Wesley1600/ClaudeCodeFrameWork --skill data-analysis-wesley1600

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill helps analysts transform raw datasets into actionable insights by performing exploratory data analysis (EDA), generating visuals, and producing data-driven reports.

Core Features & Use Cases

Load datasets from CSV, JSON, Parquet and prepare them for analysis
Perform EDA, compute descriptive statistics, and identify correlations
Create visualizations (charts, heatmaps) and export analysis reports
Build and compare models or forecasts when needed

Quick Start

Load a dataset path or CSV/JSON content and run an initial exploratory analysis to generate summaries and visuals.

Frequently Asked Questions about data-analysis

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

FAQPage Schema

How do I analyze a CSV or JSON dataset to find patterns and correlations?▼

Exploratory data analysis identifies patterns and correlations by loading CSV, JSON, or Parquet files, computing descriptive statistics, and visualizing relationships through charts and heatmaps to reveal actionable insights from raw data.

Can I create visualizations and reports from my data automatically?▼

Yes. The Skill generates charts, heatmaps, and statistical summaries, then exports analysis reports to HTML, PDF, or interactive dashboards for immediate sharing and decision-making.

What file formats does data analysis support for loading datasets?▼

Data analysis supports CSV, JSON, and Parquet formats, allowing you to load structured datasets directly and prepare them for exploration, validation, and modeling without manual reformatting.

How do I detect anomalies or build predictive models from my data?▼

After exploratory analysis and validation, the Skill builds and compares predictive models or forecasts, enabling anomaly detection and forward-looking insights across business analytics, quality assurance, and forecasting scenarios.

Do I need statistical knowledge to perform exploratory data analysis?▼

The Skill automates EDA by computing descriptive statistics, correlations, and visualizations, so you can extract insights without deep statistical expertise; it handles the technical computation while you focus on interpreting results.

What's the best approach to transform raw data into actionable business reports?▼

Load your dataset, run automated exploratory analysis to identify trends and anomalies, create visualizations for clarity, then export to HTML or PDF reports that stakeholders can act on immediately.