data-analysis

Name: data-analysis
Availability: InStock
Author: easyspace-ai

Load Excel and CSV files into DuckDB for SQL queries and statistics.

Updated Apr 7, 2026

Search Tags:#analysis #data #sql #statistics #excel #csv #duckdb

Ready to run

npx skills add https://github.com/easyspace-ai/minote --skill data-analysis-easyspace-ai

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: data-analysis
Source: https://github.com/easyspace-ai/minote/tree/main/skills/public/data-analysis
Command: npx skills add https://github.com/easyspace-ai/minote --skill data-analysis-easyspace-ai

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

Data scientists and teams waste time analyzing scattered Excel/CSV files; this Skill provides a DuckDB-based workflow to inspect schemas, run SQL queries, compute statistics, and export results in multiple formats.

Core Features & Use Cases

Inspect Excel/CSV file structures (sheets, columns, types, row counts)
Execute arbitrary SQL queries against uploaded data across multiple files
Generate statistical summaries (means, percentiles, null counts) and top values
Support multi-sheet Excel workbooks (each sheet becomes a table)
Export results to CSV, JSON, or Markdown
Cache loaded data for fast subsequent analyses

Quick Start

Upload your Excel or CSV data to /mnt/user-data/uploads and start by inspecting the schema, then run queries to summarize and export results.

Frequently Asked Questions about data-analysis

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

FAQPage Schema

How do I query Excel and CSV files with SQL?▼

To query Excel and CSV files with SQL, load your uploaded data into DuckDB for in-process analytics, inspect the schema, and execute arbitrary SQL statements across multiple files.

Can I analyze multiple sheets in an Excel workbook using SQL?▼

Yes, you can analyze multi-sheet Excel workbooks by loading them into DuckDB, where each sheet automatically becomes a separate table available for cross-sheet SQL querying and statistical summaries.

How do I get statistical summaries and top values from CSV data?▼

Get statistical summaries from CSV data by loading the file into DuckDB to compute means, percentiles, null counts, and top values, then export the analysis results to CSV, JSON, or Markdown formats.

Does this approach handle large CSV or Excel files efficiently?▼

Yes, this approach handles large Excel and CSV files efficiently by parsing binary Excel streams with OpenPyXL and caching loaded data in DuckDB for fast subsequent repeat analyses.

What is the best way to inspect the schema of uploaded CSV and Excel files?▼

The best way to inspect the schema of uploaded CSV and Excel files is loading them into DuckDB to automatically reveal columns, data types, sheet names, and row counts before running queries.

Do I need DuckDB and OpenPyxl to analyze Excel files?▼

Yes, you need DuckDB and OpenPyxl installed, as OpenPyxl parses binary Excel streams and DuckDB executes the in-process SQL queries required for cross-file data exploration and export.