What problem does it solve? Building professional spreadsheets programmatically requires knowing which Python library fits each task, how to write formulas, charts, and formatting correctly, and how to handle large files or financial model structures without errors. ## Core Features & Use Cases - Spreadsheet Generation: Create .xlsx files with openpyxl or xlsxwriter including formulas, number formats, conditional formatting, data validation, freeze panes, and charts. - Financial Models: Ready-made recipes for 3-statement models, DCF, LBO, comparable company analysis, and M&A accretion/dilution models with input/output cell conventions. - Pivot Summaries & Sensitivity Grids: Build pivot-table-style summaries with pandas or SUMIFS formulas, plus one-way and two-way data table equivalents for sensitivity analysis. - Google Sheets & PDF Export: Generate Google Sheets via gspread, upload .xlsx to Drive, and export to PDF using LibreOffice CLI with print layout settings. - Use Case: Ask for a DCF valuation model for a public company and receive a formatted multi-sheet workbook with assumptions, projections, terminal value, and a WACC sensitivity grid. ## Quick Start Create an Excel financial model for Tesla with a 5-year DCF, formatted assumptions sheet, and a sensitivity table of WACC versus terminal growth.
