excel-expert

Parse and standardize Excel workbook data across multiple sheets into JSON or CSV.

Updated Jul 13, 2023
One-click install
npx skills add https://github.com/changgenglu/changgenglu-blog --skill excel-expert
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: excel-expert
Source: https://github.com/changgenglu/changgenglu-blog/tree/main/prompt_engineering/gemini/skills/excel-expert
Command: npx skills add https://github.com/changgenglu/changgenglu-blog --skill excel-expert

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill helps users parse and standardize data from Excel workbooks across multiple sheets, enabling reliable downstream analytics and integration with JSON/CSV formats.

Core Features & Use Cases

  • Multi-sheet parsing: read all worksheets from .xlsx/.xls files to preserve complete data context.
  • Data cleaning and normalization: convert NaN/None to "" and normalize IDs and dates for consistent keys.
  • Output formats: convert to structured JSON or CSV ready for loading into dashboards or data pipelines.

Quick Start

Create a workflow that takes an Excel file as input and returns a JSON object containing the first sheet's rows with normalized values.

Frequently Asked Questions about excel-expert

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

FAQPage Schema
How do I parse multiple sheets in an Excel workbook and convert them to JSON?

To convert Excel sheets to JSON, this Skill traverses all worksheets in .xlsx or .xls files, normalizes NaN values and IDs, and outputs structured JSON. It handles multi-sheet parsing and data cleaning to preserve complete data context for reliable downstream processing.

Can I convert Excel data to CSV while handling NaN and None values?

Yes, you can convert Excel data to CSV while applying strict data-cleaning rules. The Skill normalizes NaN and None values to empty strings and standardizes dates and IDs, ensuring consistent keys before exporting to CSV format ready for data pipelines.

Do I need pandas and openpyxl installed to parse .xlsx files?

Yes, you need pandas and openpyxl installed to parse .xlsx files. The Skill fulfills environment verification for these dependencies before reading worksheets, ensuring the multi-sheet traversal and data normalization processes run without missing library errors.

What is the best way to clean and normalize IDs from multiple Excel sheets?

The best way to clean IDs from multiple sheets is using automated normalization that traverses every worksheet, applies strict data-cleaning rules, and standardizes ID formats. This approach handles unexpected sheet structures robustly during data extraction.

How does Excel multi-sheet parsing handle unexpected sheet structures?

Excel multi-sheet parsing handles unexpected structures through robust error handling during worksheet traversal. It applies strict data-cleaning rules to normalize values safely, preventing pipeline failures when encountering misaligned columns or empty sheets during data extraction.