Jupyter Notebook Tutorial

Jupyter Notebook (formerly IPython Notebook) is an open-source interactive computing tool.

Jupyter Notebook organizes code, explanatory text, and execution results in the same Notebook document. The document is saved in JSON format and consists of multiple ordered cells. Each cell can run code, or write Markdown text, display mathematical formulas, charts, or other rich media content.

The Jupyter Notebook file extension is.ipynb。

Who is this tutorial for?

This tutorial is intended for readers who want to systematically get started with Jupyter Notebook, and no background in data science or scientific research is required.

If you have a basic understanding of Python syntax and want to more efficiently record ideas, run code, and present results during learning, experimentation, or analysis, then this tutorial is perfect for you.

  • Beginners who are just learning Python and want to write and run code while seeing results immediately
  • Developers transitioning from scripts or IDEs to data analysis and exploratory computing
  • Engineers and researchers who need to perform data analysis, experimental verification, or algorithm derivation
  • Technical writers who want to integrate code, explanations, and results into a reproducible document

Learning Path

This tutorial is organized in a progressive manner, suitable both for readers who have never been exposed to Jupyter Notebook and for users who wish to systematically sort out their knowledge structure. It is recommended to follow the sequence to avoid confusion caused by insufficient understanding of execution order and runtime environment.

  • Getting to Know Jupyter Notebook
    Understand what Jupyter Notebook is, what problems it can solve, and how it differs from traditional code editors.
  • Installation and Environment Startup
    Learn how to install Jupyter Notebook locally, and correctly start and manage the working directory.
  • Basic Notebook Operations
    Master the types of Cells, execution methods, execution order, and common shortcuts.
  • Markdown and Document Organization
    Learn to write explanatory documents in Notebook, making code and ideas clearly structured and more readable.
  • Practical Application Scenarios
    Understand the value of Notebook in real-world scenarios through simple data analysis and visualization examples.
  • Advanced Usage and Best Practices
    Learn about JupyterLab, Kernel management, and Notebook usage conventions to avoid common pitfalls.

Related Links

Official website:https://jupyter.org/

Documentation:https://docs.jupyter.org/

Other Extensions