Jupyter notebooks have become an essential tool for many data science workflows over the years. This includes performing data mining, analysis, processing, modeling, and general day-to-day experimental tasks performed during the life cycle of every data science project.
Jupyter (image provided by the author)
Despite its popularity, many data scientists have pointed out its numerous shortcomings, such as here and