This repo contains various Python Jupyter notebooks I have created to experiment and learn with the core libraries essential for working with data in Python and work through exercises, assignments, ...

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. Most people have ...

JupyterLab, the next-generation user interface for Jupyter Notebooks, provides an extensible environment for data science, scientific computing, and machine learning. Jupyter Notebooks allows users to ...

The problem with notebooks is that they're much better for experimental data science work than they are for production data engineering work. That's my own opinion, of course. But I stand by it.

Jupyter Notebook is a powerful tool, but it can be supercharged with the right extensions. From productivity boosters like Nbextensions and IPyWidgets to specialized tools like Nbgrader and ...

On its own, the Jupyter Notebook/JupyterLab container has enough features to satisfy your note-taking and coding needs, but its utility jumps to the next level once you integrate it with other ...

Jupyter is more of a data science notebook, and the tools and features are geared to research or data science projects that require sharing and visualizing data.