Jupyter Setup

2. Jupyter Setup#

Jupyter Notebook is a crucial component of the Python ecosystem and is widely used by the data science and machine learning communities for its ability to combine code, notes, analysis and visualization seamlessly in one document. Alternatively, you can use Google Colab, which is a cloud version of Jupyter Notebook.

Note

Some prefer Anaconda, which is a huge bundle of tools and libraries. With some command line skills, Jupyter Notebook standalone is leaner, faster, avoids licensing concerns, mirrors real-world Python workflows, and is simply better project control. The popular code editor/IDE VS Code can also run Jupyter Notebooks, but the user experience differs.

Tool

What it is

What it does

Jupyter Notebook

An interactive notebook interface

Interactive execution

VS Code

A general-purpose code editor/IDE

Write and manage code

Anaconda

A Python distribution + environment manager

Install and manage packages, including Jupyter

Google Colab

A cloud-hosted Jupyter Notebook service

Runs Jupyter notebooks in cloud/browser

The best way to install and configure Jupyter Notebook is to create a Python virtual environment. To do that, you need to use the Command Line Interface (CLI) on your computer. To install and start using Jupyter Notebook, follow the four steps below:

  1. Install Python

  2. Create project directory

  3. Create Python virtual environment (.venv) in the project folder

  4. Start Jupyter Notebook

  5. Create and edit notebooks