Willing to get started with JupyterLab? Keep reading! A Brief Introduction to Jupyter Notebook Released in 2018, JupyterLab offers a flexible user interface and more features than the classic Jupyter Notebook, and it’s certainly the present and the future of Project Jupyter. In this article, we will introduce you to JupyterLab, the next generation of Jupyter Notebook, probably the most popular IDE for data science. There are many IDEs particularly well-suited for data science, including DataCamp’s Workspace. Writing, testing, and debugging code, as well as editing functionalities, such as syntax highlighting, bracket-matching, and code autocompletion, are among the most common features of modern IDEs.

IDEs increase programmer productivity by putting together multiple utilities into a single interface. IDEs are designed to enable programmers to write code and develop software applications more efficiently.

Just as GPS makes taxi drivers’ life easier, so does Integrated Development Environments (also known as IDEs) for programmers. True, a software developer with no programming language is like a taxi driver with no car. It’s impossible to understand software development without programming languages.

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