data-analysis

Analyze Excel and CSV files with DuckDB SQL queries and statistical summaries.

1|Updated Feb 27, 2026

Search Tags:#SQL #data analysis #Excel #DuckDB #CSV

Ready to run

npx skills add https://github.com/9Ashwin/aswin-skills --skill data-analysis-9ashwin

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: data-analysis
Source: https://github.com/9Ashwin/aswin-skills/tree/main/skills/data-analysis
Command: npx skills add https://github.com/9Ashwin/aswin-skills --skill data-analysis-9ashwin

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires duckdb, openpyxl, pandas, and includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill streamlines the process of analyzing Excel and CSV files, providing a powerful tool for data exploration, statistical summaries, and result visualization without the need for manual data processing.

Core Features & Use Cases

Excel/CSV Analysis: Analyze data from Excel workbooks and CSV files using DuckDB.
SQL Queries: Execute SQL queries to extract and manipulate data.
Statistical Summaries: Generate statistical summaries for numeric and string columns.
Data Visualization: Export results to CSV, JSON, or Markdown for further analysis or reporting.
Use Case: For a user with a sales dataset, this Skill can quickly compute total revenue by category, average order values, and monthly trends, all with a simple SQL query.

Quick Start

Use the data-analysis skill to inspect the structure of your Excel file 'sales_data.xlsx'.

Frequently Asked Questions about data-analysis

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

FAQPage Schema

How do I analyze Excel and CSV files using SQL without a database server?▼

You can analyze Excel and CSV files using SQL by loading them into DuckDB's in-process engine, which executes queries directly on local files. This approach allows schema inspection, data manipulation, and statistical summaries without requiring a separate database server setup.

What is the best way to automate statistical summaries for structured data?▼

Automating statistical summaries for structured data involves using SQL queries against in-memory datasets to compute metrics for numeric and string columns. This process generates statistical aggregations that can be exported as JSON or Markdown for reporting.

Can I run SQL queries directly on Excel workbooks for data exploration?▼

Yes, you can run SQL queries directly on Excel workbooks by utilizing an in-process analytical engine like DuckDB. This allows you to extract, filter, and manipulate workbook data programmatically for rapid data exploration and trend analysis.

How do I export SQL query results to Markdown or JSON from a CSV file?▼

To export SQL query results to Markdown or JSON from a CSV file, execute the desired query using an in-process SQL engine and specify the output format. This transforms raw structured data into formatted reports for analysis and visualization.

Does DuckDB support schema inspection for local CSV and Excel files?▼

Yes, DuckDB supports schema inspection for local CSV and Excel files, allowing you to automatically detect column types and structures. This enables immediate SQL querying and statistical analysis without manual schema definition or data preprocessing.