data-analyst

Analyze CSV, Excel, JSON, and SQL datasets to generate visual insights and reports.

Updated May 9, 2026
One-click install
npx skills add https://github.com/HwFee/AgentProject --skill data-analyst-hwfee
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: data-analyst
Source: https://github.com/HwFee/AgentProject/tree/main/skills/data-analyst
Command: npx skills add https://github.com/HwFee/AgentProject --skill data-analyst-hwfee

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Data analysts often spend hours turning raw data into visuals and comprehensive reports. This Skill streamlines data analysis by providing a repeatable workflow for loading, exploring, and summarizing datasets.

Core Features & Use Cases

  • Load and clean data from CSV, Excel, JSON, or SQL sources
  • Generate charts, dashboards, and narrative reports
  • Run basic statistical summaries and SQL queries on datasets
  • Use cases include ad-hoc analysis, KPI reporting, and stakeholder dashboards

Quick Start

Load a dataset and generate an interactive visualization plus a concise report.

Frequently Asked Questions about data-analyst

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

FAQPage Schema
How do I generate visual insights and reports from a CSV file?▼

You can generate visual insights from a CSV file by loading it into the workflow to produce charts, statistical summaries, and narrative reports using pandas and matplotlib.

Can I run SQL queries directly on my datasets for ad-hoc analysis?▼

Yes, you can run SQL queries directly on datasets. It supports SQL sources alongside CSV, Excel, and JSON formats to facilitate ad-hoc data exploration and KPI reporting.

Does this data analysis workflow support Excel and JSON file formats?▼

Yes, this data analysis workflow supports Excel and JSON file formats. It loads, cleans, and processes these files to create visualizations and stakeholder dashboards.

What is the best way to create a stakeholder dashboard from raw data?▼

The best way to create a stakeholder dashboard is to load raw data and let the workflow generate interactive visualizations and concise narrative reports using seaborn and matplotlib.

Do I need to clean my data before generating statistical summaries?▼

No, you do not need to clean your data beforehand. The workflow includes a data loading and cleaning step to prepare raw datasets before generating statistical summaries and charts.