Create, edit, analyze, and format Excel spreadsheets using pandas and openpyxl.
npx skills add https://github.com/haposoft/cafekit --skill hapo-xlsx
Please help me install this Agent Skill. Skill: hapo:xlsx Source: https://github.com/haposoft/cafekit/tree/main/packages/spec/src/claude/skills/xlsx Command: npx skills add https://github.com/haposoft/cafekit --skill hapo-xlsx
This Skill addresses the challenge of manually creating, editing, and analyzing complex Excel spreadsheets by providing automated tools for formula calculation, data manipulation, and formatting.
To create a new Excel file with basic sales data, use the following command: /hapo:xlsx "Create a new sales data sheet for Q1 2023."
High-intent search queries and answers about installing and using this skill.
Automating Excel spreadsheet creation and data analysis is done using pandas and openpyxl to generate, edit, and format .xlsx files. It supports data-driven workflows for financial modeling and project management with live formula recalculations.
Yes, building financial models with live formula recalculation in .xlsx files is fully supported. The Skill uses openpyxl to construct robust formulas that dynamically update, ensuring your spreadsheet calculations remain accurate when underlying data changes.
Yes, formatting and styling for existing Excel spreadsheets is supported. You can apply professional formatting, including color coding and specific number formatting, directly to .xlsx, .csv, and .tsv files to improve data visualization and readability.
The best way to manipulate spreadsheet data for administrative processes is using pandas for data manipulation and statistical analysis. This approach automates editing and formatting tasks across .xlsx and .csv files, streamlining project tracking and administrative workflows.
Yes, pandas and openpyxl are required dependencies to analyze sales data in Excel. Pandas handles the core data manipulation and statistical analysis, while openpyxl manages the reading, writing, and formatting of the .xlsx spreadsheet structure.
When working with .csv and .tsv files for financial modeling, limitations include the lack of native support for live spreadsheet formulas and advanced cell styling. The tool mitigates this by automating conversion and formatting within pandas and openpyxl environments.
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