[vnpc1]

> With a notebook, you get the chance to load the data, view it, clean it where needed, view it again, analyze it, model it and do anything else you need to it.

In a good data-oriented IDE like RStudio you get to do all of those things and write code which can be saved as plain text and can be version controlled well under git which you can't do well with Jupyter.

R folks have to be the best indicator in this case because they have access to a good IDE and they have good support for Jupyter. Their use is overwhelmingly in plain text files in RStudio, a small portion of rmarkdown notebooks and pretty much no one user R in Jupyter.

[nestorD]

Yes! Rstudio is the one thing I miss most when doing datascience in python.

Notebooks give me some of the interactivity but the experience degrades significantly.

The spyder IDE seem like an okayish replacement but some of the library I use expect you to have html display (within a notebook) to give you full functionalities which is not yet available in spyder.

[tastyminerals]

Have you tried Orange. It has scripting capabilities.

[nestorD]

No but, looking at some screenshot + descriptions, it seems to get me further from the code which does not seem like what I am looking for

Rstudio gives you the experience of a classical IDE + easy data exploration which I found to be productive from the exploratory stages (where I need to see my data and the effect of my code) to the clean-up phase (where I refactor my file).