Python users can use the Pandas library to read data from various file formats (CSV, Excel, SQL databases), perform data cleaning (removing duplicates, converting data types, and handling ...

Still using Excel for your data analysis? Learn how to leverage Python so you can work with larger datasets and automate repetitive tasks.

Python libraries like Pandas, NumPy, SciPy, and Matplotlib streamline data cleaning, statistical analysis, and visualization directly within Excel.

Pandas makes it easy to quickly load, manipulate, align, merge, and even visualize data tables directly in Python.

Excel gets containerized, cloud-based Python analytics and visualization powers Visualization and analytics tools available in preview, but may be paywalled.

This will enable users to perform complex statistical analysis, advanced visualizations, predictive analytics, and machine learning in Excel.

Some members of the Microsoft 365 Insiders program can now try out the combination of Python, Excel and the Anaconda Python repository.