Jupyter Notebook is not a full-blown development environment for Python. Many of the features you would expect to find in an IDE—e.g., interactive debugging, code completion, and module ...

The best way to do this is by either running Python in the terminal or a Jupyter notebook.

For instance, PyXLL-Jupyter can integrate data from your Excel workbook into a Jupyter Notebook using a single command. This enables you to analyze massive datasets quickly.

Because of the client/server architecture, it is very simple to share notebooks with other users. You can — in theory — use Jupyter for anything you could use Python for.

Image: Jupyter Notebook Jupyter is a browser-based, open-source data science notebook tool that supports Python, Julia, and other dynamic programming languages such as R, Scilab and Octane.