Jupiter Notebook and Jupiter Lab

Jupyter Notebook is a web-based interactive computational environment for creating Jupyter notebook documents. It supports several languages like Python (IPython), Julia, R, etc. and is mostly used for data analysis, data visualization, and other interactive, exploratory computing. For beginners in data science, jupyter notebook is more preferred; it only consists of a file browser and a (notebook) editor view, which is easier to use. When you get familiar with it and need more features(which we will talk about later), you can then definitely switch to JupyterLab.

JupyterLab is the next-generation user interface, including notebooks. It has a modular structure, where you can open several notebooks or files (e.g., HTML, Text, Markdowns, etc.) as tabs in the same window. It offers more of an IDE-like experience. JupyterLab uses the same Notebook server and file format as the classic Jupyter Notebook to be fully compatible with the existing notebooks and kernels. The Classic Notebook and Jupyterlab can run side to side on the same computer. One can easily switch between the two interfaces. The interface of both Lab and notebook are similar, except the panel of the file system on the left side in Jupyter lab.

Some differences are

JupyterLab runs in a single tab, with sub-tabs displayed within that one tab, Jupyter Notebook opens new notebooks in new tabs. So JupyterLab feels more like an IDE; in Notebook notebooks, it feels more standalone. All the files are opened as different tabs in your webbrowser. It depends on you what you prefer more.

There’s a huge difference when you open a CSV file in any of them, and CSV is one thing you will see a lot while doing data science. Let me show you the difference when you open a CSV file in notebook and Lab.

See, in the jupyter notebook, it shows the CSV file as it is with the delimiter provided by the creator of the CSV file; let's see what’s the case in Lab.

See, in jupyter Lab, when you open a CSV file, it is represented entirely just like a CSV file looks like(a .xlsx file); jupyterlab also has an option of delimiter; usually, a CSV file is a comma-separated, but even if its space-separated or ab separated you can mention it in the delimiter option given in jupyterlab.

Conclusion

At last, I would like to say both notebook and Lab are both very good to work with, very user-friendly, great UI. All Thanks to the developers of Jupyter! Use any one of them according to your comfort level. Signing off. Happy Learning.

References:

https://medium.com/analytics-vidhya/why-switch-to-jupyterlab-from-jupyter-notebook-c6d98362945b#:~:text=Jupyter%20Notebook%20is%20a%20web,for%20creating%20Jupyter%20notebook%20documents.&text=JupyterLab%20is%20the%20next%2Dgeneration,tabs%20in%20the%20same%20window.