xlsx

Create and edit Excel .xlsx files with pandas and openpyxl.

31|9|Updated Feb 12, 2026
One-click install
npx skills add https://github.com/codemo1991/nanobot-webui --skill xlsx-codemo1991
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: xlsx
Source: https://github.com/codemo1991/nanobot-webui/tree/main/nanobot/skills/xlsx
Command: npx skills add https://github.com/codemo1991/nanobot-webui --skill xlsx-codemo1991

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires openpyxl, pandas, python-docx, python-pptx, lxml, defusedxml, and includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill streamlines complex spreadsheet tasks, from data cleaning and formula creation to advanced financial modeling, eliminating manual errors and saving significant time.

Core Features & Use Cases

  • Formula Generation: Creates accurate Excel formulas for calculations, saving you from manual formula writing and debugging.
  • Data Cleaning & Restructuring: Fixes messy tabular data, standardizes formats, and reorganizes data for analysis.
  • Financial Modeling: Builds dynamic financial models with industry-standard formatting and error-free formulas.
  • Use Case: You have a sales report with inconsistent date formats and missing values. Use this Skill to clean the data, standardize dates, fill missing values, and calculate the quarterly growth rate using correct Excel formulas.

Quick Start

Use the xlsx skill to create a new spreadsheet with columns A1, B1, C1 and rows of data.

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 data cleaning in spreadsheets?

Automating Excel formula generation and data cleaning involves using Python libraries like pandas and openpyxl to standardize formats, fill missing values, and compute formulas programmatically. This ensures zero formula errors and professional formatting for financial models.

What is the best way to build a financial model in an xlsx file using Python?

Building a financial model in an xlsx file with Python uses openpyxl and pandas to add columns, compute formulas, and apply formatting dynamically. It eliminates manual spreadsheet errors and enforces industry-standard formatting for financial reporting.

Do I need LibreOffice to recalculate Excel formulas generated by Python?

Yes, recalculating Excel formulas generated by Python requires LibreOffice. The process uses a specific recalculation script to ensure that computed formula values update correctly within the xlsx file after programmatic modifications.

Can I convert between tabular file formats like CSV and xlsx automatically?

Yes, you can convert between tabular file formats automatically. The process uses pandas and openpyxl to parse source files, restructure tabular data, and export accurately formatted xlsx files without manual intervention.

How do I fix messy tabular data with inconsistent date formats for analysis?

Fixing messy tabular data with inconsistent dates uses pandas to standardize formats, fill missing values, and reorganize columns. This data cleaning process prepares the dataset for accurate analysis and formula calculations.

Does openpyxl support generating charts and formatting cells dynamically?

Yes, openpyxl supports generating charts and formatting cells dynamically. It manipulates spreadsheet properties programmatically to create visual data representations and apply professional formatting standards to financial models.