Jupyter came from the scientific community (originally the IPython Notebook - IPython itself was made by a physics grad student).
The use case is basically a scientific journal. You collect data. Analyze it. Make plots. Write notes (e.g. with equations, or diagrams). All in one place.
Then you can share the notebook with anyone else. If they have similar data (in the same format), they can execute the notebook on their data and get the plots all in one place.
It's great for data oriented work. It was never meant as an IDE replacement, nor as a general purpose development environment.
In a previous job I had set up a notebook to analyze some of the models our team produced - it was essentially a Q/A notebook that generated data from our models, algorithmically looked for unphysicalities in our models, and plotted any it found.
The rest of my team used it for the models they were working on. The alternative/old way was just too painful (lots of manual steps).
But although reuse by others is a touted feature, it's not really that important. It's incredibly useful for one's own workflow. Think of the convoluted Excel sheets people often have at engineering companies. They get new data, copy and paste it into Excel, and get new plots. This is no different.
The use case is basically a scientific journal. You collect data. Analyze it. Make plots. Write notes (e.g. with equations, or diagrams). All in one place.
Then you can share the notebook with anyone else. If they have similar data (in the same format), they can execute the notebook on their data and get the plots all in one place.
It's great for data oriented work. It was never meant as an IDE replacement, nor as a general purpose development environment.