Introduction to Jupyter

Goals:

• Introduce what Jupyter is and why it’s useful

• Differentiate between Jupyter Notebooks and Jupyter Labs and when to use each

• Identify cell types in a notebook and how they’re used

• Things to be

What is Jupyter?

Jupyter, formerly known as an ipython notebook, is a popular tool used in data science and data analysis.

• An open-source, browser-based, web application with a wide variety of functions

  • Allows users to create and share computational documents, called notebooks

    • Notebooks facilitate the development of live code that can then be run in a number of different coding languages.

    • Code can be run step by step in “chunks” called cells.

    • Users can combine live code cells with other cells - Markdown text, images, plots, and other rich media in a single interactive canvas.

    • Can produce a wide variety of interactive output including HTML, videos, LaTeX, and custom MIME types.

    • Can be shared through e-mail, GitHub, or other cloud storage and sharing services.

    • Easily exported to other formats like, books, slides, web apps, static web pages, or PDF documents.

  • Allows users to run code and share ideas and share in a “live” and easily available format.

• Requires a kernel to launch

Jupyter Notebooks

Jupyter Notebooks are just the Notebook application itself Simple interface where users can open and run notebooks Straightforward linear flow, where you can create and run cells in a single notebook Beginners may find Notebooks easier to use, initially Lacks some of the functionality of Jupyter Lab Supports extensions, but the process of installing and managing them more difficult. Available extensions is smaller compared to JupyterLab. Does not have a built-in terminal or text editor. Users need to rely on external tools or extensions for these tasks.

Notebook cell types

By default, there are 4 types of Notebook cells:

• Markdown

• Code

• NBConvert

• Heading

Jupyter Labs