Project Jupyter is an open-source, open standards project which was developed to support interactive data science and scientific computing across multiple programming languages.
Project Jupyter supports three programming languages i.e Python, R programming, and Julia. You can execute Jupyter on your local machine without network access on your local machine.
Project Jupyter has developed and supports three products Jupyter Notebook, JupyterHub, and JupyterLab.
Jupyter Notebook is very popular among data scientists for data science projects. It’s an open-source web-based application that is used for creating and sharing documents related to code, text, visualizations, images. Initially, it was known as IPython Notebook.
You can use Jupyter Notebook for different activities related to data science such as data cleaning, data transformation, numerical simulations, statistical modeling, machine learning data analysis, and much more. Jupyter notebook provides an easy-to-use, user-friendly interface framework. You can use Jupyter for presentation and educational purposes apart from Integrated Development Environment for code development.
Jupyter Notebook has two major components cells and kernel. Data scientists can enter code or text information in the rectangular cells provided I the web browser. The web browser then sends this information to the kernel which processes the data and returns the result.
Jupyter Lab is an advanced version of Jupyter Notebook. It contains all the basic features of the legacy Jupyter Notebook such as notebook, text editor, terminal, file browser with improved user interface and advanced functionalities. You can perform different activities on documents using notebook, text editors, terminal, and custom components of Juoyter Lab.
Jupyter Lab supports different file formats such as text, CDV, images, PDF, JSON, Markdown, Vega. With Jupyter Lab you can use a text editor, notebook, terminal, data file viewer in a single browser window.
Jupyter hub is a multiuser server for Jupyter Notebook. It is the most flexible, customizable, and portable product of the Jupyter project which supports different infrastructures such as google cloud and virtual machines. Using Jupyter hub multiple students of the class, users of the science group can access the Jupyter notebook at a time by creating their own workspace.
Jupyter is one of the most powerful open source projects which provides advanced and easy-to-use functions that are very important for data science projects. Please do share your experience of using Jupyter in the comment section or you can reach out to us using the contact form.