1
Connect
Read worksheet ranges, tables, and named cells into Python so the application can work from live workbook data.
Python for Excel
Build interactive applications and custom functions that run directly in your workbook.
No separate Python installation. Application source stays with the workbook.
Workbook inputsAssumptions, formulas, and published outputs stay in Excel.
Task pane appControls, charts, and workflow logic live beside the workbook.
Custom functionsPublish reusable Python calculations back to worksheet formulas.
From function to application
Build the app in the task pane. Connect it to Excel.
Start with a worksheet function or build a richer task-pane experience with controls, charts, and workflow logic. The workbook remains the familiar data and delivery layer.
2
Build
Author custom functions, notebook logic, and interactive task-pane UI with integrated AI assistance when you need it.
3
Deliver
Publish values and Python functions back to Excel, save the source with the workbook, and open the result in a simplified Run mode.
Built for the handoff
The author sees a development environment. The user sees an application.
The value is not only running Python in Excel. It is packaging a model so another person can operate it without maintaining the implementation.
Build and maintain
- Edit reactive Python cells
- Use AI to generate and revise code
- Inspect dependencies and errors
- Publish workbook values and functions
Operate the model
- Change workbook assumptions
- Use controls and defined workflows
- View charts, tables, and explanations
- Work without editing Python source
Initial use cases
Build applications where Excel is still the right interface.
The strongest fit is a repeatable analytical workflow with bounded workbook inputs, meaningful Python logic, and users who need a familiar delivery format.
Forecasting and planning
Turn assumptions, scenarios, and Python models into reusable planning tools for finance and operations teams.
Risk and simulation
Give colleagues a controlled interface for Monte Carlo analysis, valuation, stress testing, and scenario comparison.
Optimization
Build allocation, scheduling, pricing, and resource-planning applications around familiar worksheet inputs.
Statistical analysis
Package repeatable tests, forecasts, diagnostics, and visualizations so others can run them without editing code.
Engineering calculators
Combine workbook assumptions with Python calculations, validation, interactive controls, and documented outputs.
Data-quality review
Create focused review applications that surface exceptions, reconcile results, and publish controlled outputs to Excel.
AI-assisted authoring
Use AI to build the application. Keep the resulting logic inspectable.
The notebook includes AI authoring capabilities for generating, explaining, debugging, and revising code. The durable output is the notebook and workbook application—not a transient chat answer.
See the notebook workflow →Example author request
“Use the assumptions table to build a five-year forecast, validate missing inputs, and publish the summary to Excel.”
Review generated notebook changes, run them against workbook data, and save the working application.
Supporting utilities
Focused tools for other spreadsheet tasks.
Start with a function. Grow into an application.
Use the Python for Excel add-in in your workbook or explore the notebook workflow in a browser.