How do I use the new Python in Excel integration for advanced Data Science forecasting?

All answers to this question.

I’ve been experimenting with Python in Excel for a few months now. It’s fantastic for visualization because you can use Seaborn and Matplotlib directly in the grid. To run a Random Forest, you just use the =PY() function. The integration uses an Anaconda distribution running in the Microsoft Cloud, which means your local machine isn't doing the heavy lifting. Regarding privacy, the data is sent to a secure container and isn't used to train any models, but you should still check with your IT department if you're handling sensitive PII (Personally Identifiable Information).

   Answered 2025-02-08 by Kimberly Adams

Does the Python integration support external API calls? I’d love to pull real-time weather data into my sales forecast model without having to set up a separate Power BI or Python script.

   Answered 2025-02-11 by Brian O'Connor

• Brian, unfortunately, external network calls are disabled in Python in Excel for security reasons. You have to use Power Query to pull the API data into a table first, and then point your Python code to that table. It’s a bit of an extra step, but it keeps the environment secure. I’ve used this method to pull stock prices and then run a Monte Carlo simulation in Python to predict portfolio risk, all within a standard .xlsx file.

     Commented 2025-02-14 by James Wilson

The best part is that you can return Python objects as Excel values. Converting a dataframe into an Excel table with one click is a massive workflow improvement for us.

   Answered 2025-02-17 by Sarah Connor

• Exactly, Sarah. Being able to toggle between a "Python Object" and "Excel Value" makes it so much easier to present the final results to stakeholders who don't know how to code.

     Commented 2025-02-20 by Kimberly Adams