How Microsoft’s New Python in Excel Transforms Data Analysis and Machine Learning

Microsoft partnered with Anaconda to let Python code run in Excel without any extra setup, aiming to help data professionals perform analysis and machine‑learning directly inside the spreadsheet.

According to Microsoft’s blog, Python runs in the Microsoft cloud; users type Python in a cell, the computation is performed remotely, and results—including plots and visualizations—are returned to the workbook.

This integration is significant because most enterprise data resides in Excel, and previously analysts struggled to use Python without add‑ins or complex configurations.

Third‑party components that paved the way

In 2014, Zoomer Analytics released Xlwings , a BSD‑licensed Python library that connects Excel to Python, enabling direct interaction between spreadsheets and Python applications.

In 2017, Continuum Analytics (the maker of Anaconda) launched Anaconda Fusion , linking the enterprise‑grade Anaconda distribution with Microsoft Excel 2016 and later, allowing data scientists to expose Python code from Jupyter notebooks to Excel users.

Other paid add‑ins such as PyXLL also facilitate Python‑Excel integration, until Microsoft introduced its own native solution.

What’s unique about Python in the new Excel?

Python in Excel is designed specifically for data analysts. A new PY function lets users write Python code directly in a cell, generating formulas, pivot tables, and charts.

Using Excel’s built‑in connector and Power Query, users can easily bring external data into Python workflows.

Microsoft also highlighted that enterprises can leverage popular Python libraries like scikit‑learn and statsmodels for machine‑learning, predictive analytics, regression, and time‑series modeling.

Practical use cases

1. Advanced visualizations – Create bar charts, line graphs, heatmaps, violin plots, and cluster maps with libraries such as Matplotlib and Seaborn.

2. Machine learning and forecasting – Apply scikit‑learn or statsmodels for regression, time‑series models, and other predictive techniques.

3. Data cleaning – Use advanced techniques such as missing‑value handling, format standardization, duplicate removal, and regex‑based transformations.

Anaconda powers Python in Excel

The Python engine runs the Anaconda distribution on Azure, providing pre‑installed libraries such as pandas, Matplotlib, and scikit‑learn, all vetted for security and compatibility.

Peter Wang, CEO and co‑founder of Anaconda, announced that this integration will bring a revolutionary change to millions of Excel users.

Security and isolation

Python code executes in isolated Azure container instances, leveraging Anaconda’s secure software supply chain. The code cannot access user identities, ensuring data privacy. Interaction with the workbook is limited to the built‑in xl() function for sending data and the =PY() function for receiving results.

Collaboration and governance

Workbooks containing Python can be shared safely; team members can collaborate via Microsoft Teams or Outlook, comment, @‑mention, and co‑edit. Sensitivity labels enforce organizational information‑protection policies.

Team effort and leadership

The project is a joint effort across Excel, Developer, Security, Azure, and Research teams, with Guido van Rossum, Python’s creator, providing architectural guidance.

Guido said, “Seeing Python and Excel finally come together is incredibly exciting. I expect both communities to explore new use‑cases that will boost our capabilities.”

How to try Python in Excel

The feature is currently available in the Windows Beta Channel for Excel on Windows 11 (version 16.0.16818.20000) and will roll out to other platforms later.

To experience it, join the Microsoft 365 Insider Program and select the Beta Channel Insider level. During the preview, Python in Excel is part of the Microsoft 365 subscription; some functionality may be limited after the preview ends.