xlsx

Create, edit, and analyze Excel files with openpyxl and pandas.

1|Updated Jun 11, 2026
One-click install
npx skills add https://github.com/sergeyitaly/claude-skill-deployer --skill xlsx-sergeyitaly
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: xlsx
Source: https://github.com/sergeyitaly/claude-skill-deployer/tree/main/skills_library/xlsx
Command: npx skills add https://github.com/sergeyitaly/claude-skill-deployer --skill xlsx-sergeyitaly

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

This Skill eliminates the tedious manual work of creating, editing, and analyzing Excel spreadsheets, saving you hours of repetitive data entry, formula debugging, and formatting adjustments.

Core Features & Use Cases

  • Spreadsheet Creation & Editing: Create new .xlsx files from scratch or modify existing ones with openpyxl, preserving formulas and formatting.
  • Data Analysis & Cleaning: Use pandas to read, clean, and analyze messy tabular data from .csv, .tsv, or .xlsx files.
  • Financial Modeling: Build professional Excel models with industry-standard color coding, number formatting, and zero formula errors.
  • Use Case: Imagine you have a messy CSV of sales data with malformed rows. Use this Skill to clean it, load it into a properly formatted Excel file with formulas and professional styling, and recalculate all values.

Quick Start

Use the xlsx skill to open 'sales_data.csv', clean the malformed rows, and save it as a professionally formatted Excel file named 'sales_report.xlsx'.

Frequently Asked Questions about xlsx

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

FAQPage Schema
How do I automate cleaning messy CSV data and saving it as a formatted Excel file?

To clean messy CSV data and save it as a formatted Excel file, use pandas to read and clean the malformed rows, then load the data into a new .xlsx file with openpyxl to apply professional styling and formulas.

Can I preserve existing formulas and formatting when editing an .xlsx spreadsheet?

Yes, you can preserve formulas and formatting when editing an .xlsx spreadsheet by using the openpyxl library, which ensures that existing calculations and styles remain intact during modification.

What is the best way to build a financial model in Excel using Python?

The best way to build a financial model in Excel using Python is to apply openpyxl for industry-standard color coding, number formatting, and zero formula errors, ensuring professional-grade outputs.

Does this approach support recalculating formula values and validating errors in spreadsheet files?

Yes, this approach supports recalculating formula values and validating errors in spreadsheet files by integrating LibreOffice alongside openpyxl and pandas to ensure accurate computed results.

Can I read and analyze tabular data from .tsv or .csv files for data analysis?

Yes, you can read and analyze tabular data from .tsv or .csv files using pandas to manipulate the datasets, clean malformed rows, and prepare the data for spreadsheet conversion.

Why use openpyxl instead of just pandas for spreadsheet automation?

You use openpyxl instead of just pandas for spreadsheet automation because openpyxl specifically preserves complex formulas and applies detailed formatting to .xlsx files, whereas pandas focuses primarily on data manipulation.