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One coherent Python workspace
Keep code, Markdown, intermediate results, diagnostics, charts, and controls together in one reactive notebook instead of distributing substantial Python logic around the worksheet grid.
Boardflare Python for Excel
Python notebooks in Excel
Give substantial Python work its own reactive notebook—connected to live workbook data, worksheet outputs, and reusable functions.
Sales Scenario AnalysisWorkbook + reactive notebookTry live demo →
Used by professionals at organizations including…
Why a notebook?
Give the Python program a home that matches its complexity.
Excel remains useful for data, assumptions, review, and delivery. The notebook gives substantial Python logic a coherent programming and analytical surface beside it.
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Excel can consume the notebook
Read live workbook data, publish selected results back to cells, and expose centralized Python logic through BF.FUNCTION() when worksheet users need it.
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The notebook can become the interface
Build and understand the analysis in the notebook. If it becomes a repeatable tool, optional App mode can present the same notebook with a simpler operating surface.
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Portable Python source
The notebook is represented as Python source, so the code can be reviewed, diffed, backed up, and version controlled when your workflow calls for normal software practices.
Portable source describes the notebook architecture. Boardflare does not currently claim a complete built-in Git synchronization workflow.
How it works
Excel and Python keep distinct, complementary roles.
Use the workbook for the spreadsheet work people already understand. Use the notebook for the transformations, models, validation, explanations, charts, and controls that benefit from Python.
See the notebook workflow →Excel workbookdata · assumptions · review
↔Reactive Python notebookcode · Markdown · charts · controls
Notebook resultsExcel outputs + functionsOptional App mode
What people build
Use the notebook when the Python work has multiple moving parts.
Start with recognizable analytical problems rather than isolated APIs or package demos.
Forecasting and scenarios
Keep workbook assumptions, multi-step forecasting, simulation, diagnostics, charts, and reusable projection logic in one analysis.
View example →Reconciliation and controls
Combine cleanup, tolerance logic, control totals, exception routing, and workbook-facing review outputs without scattering the implementation.
View example →Data cleaning and reshaping
Use pandas for normalization, joins, grouping, reshaping, and reconciliation while Excel remains the source-data and review surface.
View example →Optimization and scientific analysis
Put constraints, numerical methods, uncertainty, diagnostics, and interactive controls next to the code and explanation that produce them.
View example →
Live demo
See a full analysis, not just a code snippet.
The Curve Fitting example combines worksheet observations, SciPy estimation, uncertainty controls, diagnostics, charts, and published predictions in one notebook.
Try Curve Fitting →One implementation, worksheet-wide reuse
Write the complex calculation once in Python. Call it from Excel.
BF.FUNCTION() lets the notebook own the implementation while worksheet users call that implementation where they need it. The Python does not have to be repeated across the cells that use it.
Notebook source
bf.publish(functions={'project_arr': project_arr})
Worksheet use:
=BF.FUNCTION("project_arr", A1, B1)Ask AI to revise the notebook“Add a validation check for missing prices and explain any exceptions.”Result: normal notebook Python you can inspect, run, test, and save.
AI-assisted authoring
Use AI to help write the Python—not to replace the Python.
Draft, revise, explain, and debug notebook code with AI assistance. The durable result remains ordinary inspectable source rather than an opaque answer that must be regenerated every time the workbook runs.
See AI authoring →Different programming surfaces
Notebook or worksheet cells?
Microsoft Python in Excel and Boardflare both connect Python to a workbook. The main difference is where the Python program lives.
Python in worksheet cells
Python is entered through the worksheet cell model and results return through the workbook grid. That is a natural fit when native Microsoft integration matters and the calculation belongs in the grid.
Python in a reactive notebook
The notebook is the primary home for code, explanation, intermediate results, charts, controls, and reusable logic, while Excel remains connected to the work.
Other Boardflare Excel tools
Focused tools for specific spreadsheet workflows.
Try the notebook approach in Excel.
Open the notebook beside a workbook, connect live Excel data, and see whether a notebook is the better home for your Python work.