data-analysis

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

Updated Aug 23, 2026
One-click install
npx skills add https://github.com/ainlper/dra-drb2 --skill data-analysis-ainlper
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: data-analysis
Source: https://github.com/ainlper/dra-drb2/tree/main/deer-flow/skills/public/data-analysis
Command: npx skills add https://github.com/ainlper/dra-drb2 --skill data-analysis-ainlper

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

This Skill streamlines the process of analyzing Excel and CSV files, allowing users to perform complex data analysis tasks like schema inspection, SQL queries, statistical summaries, and exporting results.

Core Features & Use Cases

  • Data Analysis: Analyze Excel and CSV files with DuckDB's SQL engine.
  • Schema Inspection: Inspect file structure, including sheets, columns, types, and row counts.
  • SQL Queries: Execute arbitrary SQL queries against uploaded data.
  • Statistical Summaries: Generate statistical summaries for numeric and string columns.
  • Export Results: Export results to CSV, JSON, or Markdown.
  • Use Case: A user with sales data in Excel can quickly generate a summary report, including average sales per category, and export it to a CSV file for further analysis.

Quick Start

Use the data-analysis skill to generate a statistical summary for the 'sales.xlsx' file.

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 queries?

To analyze Excel and CSV files using SQL queries, this Skill loads your data into DuckDB, an in-memory columnar database, allowing you to execute arbitrary SQL statements directly against the file contents.

Can I generate a statistical summary for columns in a CSV file?

You can generate a statistical summary for numeric and string columns in a CSV file by loading it into the DuckDB engine, which automatically calculates and returns the descriptive statistics for your dataset.

Does this data analysis tool require Python and DuckDB to run?

Yes, this data analysis tool requires both Python and DuckDB installed in your environment, as it relies on DuckDB's columnar in-memory SQL database engine to automate the querying and statistical analysis process.

What's the best way to inspect the schema of an Excel file before querying?

The best way to inspect an Excel file's schema is using the schema inspection feature, which displays the file structure including sheet names, column names, data types, and row counts before you execute SQL queries.

How do I export SQL query results to CSV, JSON, or Markdown?

You can export SQL query results to CSV, JSON, or Markdown formats by running your queries through the DuckDB engine, which provides built-in export functionality to output your analyzed data in your chosen format.

Is DuckDB suitable for financial reporting and administrative data analysis?

DuckDB is suitable for financial reporting and administrative data analysis because its in-memory columnar SQL engine efficiently handles Excel and CSV files, providing fast schema inspection and statistical summaries for reporting tasks.