![]() Now that we have a basic understanding of Jupyter Notebook and JupyterLab, let’s dive into the key differences between the two. Key Differences Between Jupyter Notebook and JupyterLab JupyterLab aims to provide a more integrated and extensible environment for working with Jupyter Notebooks and other Jupyter components. Launched in 2018, it offers all the familiar building blocks of the classic Jupyter Notebook (notebook, terminal, text editor, file browser, rich outputs, etc.) in a flexible and powerful user interface. JupyterLab is the next-generation web-based user interface for Project Jupyter. The name “Jupyter” is a combination of three programming languages: Julia, Python, and R, highlighting its support for multiple languages through the use of different kernels. ![]() It was first introduced in 2014 as part of the IPython project and later evolved into a separate project under the name Jupyter. Jupyter Notebook is a widely adopted web-based interface for creating and sharing documents that contain live code, equations, visualizations, and narrative text. The primary purpose of these tools is to provide an interactive environment for data exploration, analysis, and visualization. Jupyter Notebook and JupyterLab are both open-source web applications that allow you to create and share documents containing live code, equations, visualizations, and narrative text. Introduction to Jupyter Notebook and JupyterLab Both these tools have become indispensable in the world of data science, and understanding their differences can help you choose the right one for your projects. ![]() In this blog post, we will explore two such tools: Jupyter Notebook and JupyterLab. ![]() As a software engineer working closely with data scientists, I have often seen the need for powerful tools that can streamline the process of data analysis and visualization. ![]()
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