Microsoft has announced a significant evolution in the analytical capabilities within Excel by releasing a public preview of Python in Excel.

This evolution will make it possible for users to natively combine Python and Excel analytics within the same workbook, with no setup needed. Users can type the coding language directly into a cell where the calculations run in the Microsoft Cloud and results are then returned to the worksheet, which also includes plots and visualizations.

Users will have access to analytics via the coding language for visualizations, cleaning data, ML, predictive analytics and more. Users can create end-to-end solutions and leverage various forms of analysis that are now offered through this evolution. Types of analysis possible with these enhancements include; advanced visualizations using Python charting libraries like Matplotlib and seaborn; ML, predictive analytics and forecasting leveraging libraries such as scikit-learn and statsmodels; and data cleaning for pattern-based transformations.

Additionally, Python in Excel utilizes Python analytics via Anaconda, a repository used by tens of millions of data practitioners worldwide.

This enhancement is currently available in preview to users running the Beta Channel in Windows, in the Microsoft 365 Insiders program. Starting in Excel for Windows first, the feature will look to be rolled out to other platforms at a later date.

Tejas Varia, principal, tax data and analytics at KPMG, said: “KPMG and Microsoft are making significant investments to deliver advanced cloud-based tax technologies. At KPMG, we’re excited about the impact Python in Excel will have for our Tax clients. Backed by the data and security promises enabled by Microsoft cloud, Python has the potential to enhance the Excel experience for advanced analytics while providing companies with transparency, simplicity and deeper insights into their financials.”

Greg Barnes, executive director of data and analytics at McKinney, said: “The ability to run Python in Excel simplifies McKinney’s reporting workflows. We used to manipulate data structures, filter and aggregate data in a Jupyter Notebook and build visuals in Excel. Now we can manage the entire workflow in Excel. This is going to make Excel that much more powerful and make Python more accessible across the organization. Python support is the most exciting update for Excel in my career!”