When I learned to program I was working as a scientist. I was relying on OriginLab (a scientific version of Excel) for my data analysis and it was a real pain. I decided to start using python for analysis and plotting and started with scripts and terminal interactivity, but found it too clunky. Jupyter feels more interactive when you are working with data because you need to explore the data and experiment with data manipulation in a way I found quite natural to do in a notebook.
Since then I've moved into software development where I rely on my IDE for any coding that involves working with more than a few modules. And as I got better working with an IDE I did gravitate toward making a script for certain kinds of tasks where I use to reach for a notebook, but there are still many data analysis tasks that I would much prefer a notebook for.
It's also quite nice to share a notebook with someone to show them how you arrived at your conclusions, and it's nice for them to be able to take your analysis and modify it or test their own ideas on top of yours. Obviously the notebooks are not great for collaboration without some fiddling around with git, but they are still very good for this kind of collaboration.
Since then I've moved into software development where I rely on my IDE for any coding that involves working with more than a few modules. And as I got better working with an IDE I did gravitate toward making a script for certain kinds of tasks where I use to reach for a notebook, but there are still many data analysis tasks that I would much prefer a notebook for.
It's also quite nice to share a notebook with someone to show them how you arrived at your conclusions, and it's nice for them to be able to take your analysis and modify it or test their own ideas on top of yours. Obviously the notebooks are not great for collaboration without some fiddling around with git, but they are still very good for this kind of collaboration.