Jupyterlab and Jupyter notebook Tutorial

Jupyter is an open-source tool for creating and sharing documents that contain live code, visualizations, equations, and text. What is Jupyter Notebook? A simple, interactive environment to write and run code. Each document (called a notebook) is saved as a .ipynb file. Useful for quick prototyping, data exploration, and teaching. A cell in Jupyter Notebook is a container where you can write and run code, markdown, or raw text. Start Jupyter Notebook by typing: conda install jupyter followed by: jupyter notebook What is JupyterLab? JupyterLab is the next-generation interface for Jupyter, offering a more advanced and flexible workspace. Why We Use JupyterLab: Multi-Panel Interface: Open notebooks, terminals, text editors, and outputs side by side. Better Navigation: File browsing and workspace management are easier. Extensions: Customize with themes and advanced plugins. Integrated Tools: Combine notebooks with terminals and markdown in one window. Start JupyterLab: conda install jupyterlab jupyter lab Key Differences: Feature Jupyter Notebook JupyterLab Interface Single document view Multi-tab, multi-panel Customization Limited Extensive via extensions Performance Lightweight Slightly heavier Use Case Quick tasks, tutorials Large projects, workflows When to Use What: Jupyter Notebook: Simple analysis, tutorials, and quick checks. JupyterLab: Complex projects, interactive dashboards, and better organization. We will use JupyterLab because it provides: Better Workflow – Manage multiple notebooks and files in one view. Scalability – Ideal for data science and machine learning projects. Future-Proofing – JupyterLab is actively developed and might eventually replace Jupyter Notebook (My personal opinion).

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