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xlsx

Create, edit, and analyze .xlsx, .csv, and .tsv files with pandas and openpyxl.

Updated Mar 15, 2025
Search Tags:#financial modeling#data analysis#pandas#openpyxl#formulas#spreadsheet#excel
One-click install
npx skills add https://github.com/mrdonlee/dotfiles --skill xlsx-mrdonlee
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: xlsx
Source: https://github.com/mrdonlee/dotfiles/tree/main/.agents/skills/xlsx
Command: npx skills add https://github.com/mrdonlee/dotfiles --skill xlsx-mrdonlee

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

This Skill streamlines the creation, editing, and analysis of spreadsheet files, automating complex tasks and ensuring data integrity.

Core Features & Use Cases

  • Data Manipulation: Use pandas for powerful data analysis, cleaning, and transformation.
  • Formula Management: Leverage openpyxl to create, edit, and manage Excel formulas, ensuring accuracy and dynamic updates.
  • Formula Recalculation & Validation: Utilize scripts/recalc.py to recalculate all formulas and identify/fix common Excel errors like #REF!, #DIV/0!, and #VALUE!.
  • Use Case: Automatically generate a financial projection model in Excel, complete with industry-standard formatting, complex formulas, and robust error checking, based on user-provided assumptions.

Quick Start

Use the xlsx skill to create a new spreadsheet with columns 'Name' and 'Value', add a row with 'Example' and '100', and save it as 'my_data.xlsx'.

Frequently Asked Questions about xlsx

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

FAQPage Schema
How do I automate Excel formula generation and recalculation in Python?▼

Automate Excel formula generation and recalculation by using Python with openpyxl to construct formulas and a recalculation script to validate and recalculate them via LibreOffice, identifying errors like #REF! and #DIV/0!.

What is the best way to build a financial modeling spreadsheet with Python?▼

Building a financial modeling spreadsheet with Python involves using pandas for data manipulation and openpyxl for formula generation, adhering to strict standards for color coding, number formatting, and formula construction.

Can I use pandas and openpyxl to edit existing .xlsx, .csv, and .tsv files?▼

Yes, you can use pandas and openpyxl to edit existing .xlsx, .csv, and .tsv files, leveraging pandas for data cleaning and transformation while openpyxl handles complex formula management and spreadsheet formatting.

Does this approach validate Excel formulas and fix common spreadsheet errors?▼

Yes, this approach validates Excel formulas and fixes common spreadsheet errors by utilizing a dedicated recalculation script to recalculate formulas and automatically identify issues like #REF!, #DIV/0!, and #VALUE!.

How do I apply industry-standard formatting to an Excel file using openpyxl?▼

Apply industry-standard formatting to an Excel file using openpyxl by programmatically setting strict financial modeling rules for color coding, number formatting, and robust formula construction within your Python workflow.

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