Master Jupyter in Minutes: Easy Installation Guide!

Introduction

Jupyter has become an essential tool for data scientists, developers, and researchers worldwide, thanks to its interactive computing environment. It allows users to create and share documents containing live code, equations, visualizations, and narrative text.

In this tutorial, we’ll walk you through a step-by-step guide on how to master Jupyter. We will explore about how to install Jupyter Notebook and JupyterLab on your computer, so you can boost your productivity and create powerful data-driven projects.

Overview of Jupyter

Jupyter is an open-source project that supports interactive computing across multiple programming languages. The project has two primary components:

• Jupyter Notebook: An interactive web-based application that allows users to create and share documents containing live code, equations, visualizations, and narrative text.
• JupyterLab: An extensible environment that provides all the features of Jupyter Notebook, plus additional tools for interactive computing and data science.

Python Vs Jupyter

Jupyter and Python are distinct but complementary tools in the world of programming and data science. Python is a high-level, versatile programming language known for its readability and extensive library support. It is widely used in various fields, including data analysis, web development, and artificial intelligence.

On the other hand, Jupyter is an interactive computing environment that allows users to create and share documents containing live code, equations, visualizations, and narrative text. While Jupyter supports multiple programming languages (referred to as “kernels”), Python is one of the most popular choices due to its power and ease of use.

In essence, Python is the programming language, while Jupyter provides a user-friendly platform for writing, running, and sharing Python code.

Supply Chain Relevance

Jupyter’s relevance to supply chain management is undeniable, as it empowers professionals to streamline their analytical workflows and gain insights into the intricacies of their supply chains. If you master Jupyter interactive computing environment, supply chain experts can quickly create, test, and refine data models, optimize logistics, and analyze complex data sets. These capabilities enable them to identify bottlenecks, forecast demand, and make data-driven decisions that improve efficiency and reduce costs.

Check out our post on Python in a demand planning context

With Jupyter Notebook and JupyterLab, supply chain managers have the perfect tools to stay ahead of the competition and drive their businesses toward success.

Prerequisites for Installing Jupyter

Before you start installing Jupyter, ensure you have the following software on your computer:

• A compatible operating system (Windows, macOS, or Linux)
• Python (version 3.3 or later)

Installing Jupyter Notebook

Install Python and Pip

First, you need to install Python and Pip (Python’s package manager) on your computer. You can download Python from the official website (https://www.python.org/downloads/) and follow the installation instructions for your operating system. Make sure to check the option “Add Python to PATH” during the installation process.

Install Jupyter Notebook

Open a terminal or command prompt and run the following command to install Jupyter Notebook:

pip install notebook

This command installs Jupyter Notebook and its dependencies on your computer.

Installing JupyterLab

To install JupyterLab, open a terminal or command prompt and run the following command

pip install jupyterlab

This command installs JupyterLab and its dependencies on your computer.

Running Jupyter Notebook and JupyterLab

To launch Jupyter Notebook, open a terminal or command prompt, navigate to your desired working directory, and run the following command

jupyter notebook

Alternatively you can type the below into your browser:

http://localhost:8888/tree

To launch JupyterLab, open a terminal or command prompt, navigate to your desired working directory, and run the following command

jupyter lab

Both Jupyter Notebook and JupyterLab will open in your default web browser, providing an interactive computing environment for your projects.

Conclusion

Congratulations! You have successfully mastered Jupyter and installed Notebook and JupyterLab on your computer. Now you can enjoy the powerful interactive computing and data science features provided by these tools. Start exploring, creating, and sharing your projects with ease using the Jupyter ecosystem. Happy coding!