More information can be found on the documentation page. While developing you need to manually enable your extensions with the frontend. For JupyterLab, this is done by the command: jupyter ...

Originally developed for data science applications written in Python, R, and Julia, Jupyter Notebook is useful in all kinds of ways for all kinds of projects: Data visualizations.

Introduction to Python for Data Analysis¶. Recall that R is a statistical programming language—a language designed to do things like t-tests, regression, and so on.The core of R was developed during ...

Jupyter Notebooks are ideal for performing exploratory data analysis (EDA). You can load data into Pandas DataFrames and use various functions to explore, clean, and manipulate data. Visualization ...

Leafmap is a Python package for interactive mapping and geospatial analysis with minimal coding in a Jupyter environment. It is a spin-off project of the geemap Python package, which was designed ...

Jupyter Notebooks, even though tightly tied to data science darling programming language Python, can now be done with .NET languages C# or F#. The popular notebooks provide interactive environments -- ...