The feature of Excel that's underestimated/overlooked by skilled programmers of Python/R is that spreadsheets immediately expose an editable visual spatial canvas datagrid GUI.
I have decades of programming C/C++/C#/Python/etc and yet I create new spreadsheets and use them every day.
Spreadsheets are much faster than wiring up a datagrid in C# or C++ Qt gui widget editor or any other "true" programming language. Spreadsheets are also faster than using Python package Pandas to import a csv into a dataframe and view it in a Jupyter notebook. And last time I checked, displaying an output grid of cells in Jupyter is read-only and not 2-way editable like Excel.
And yes, the complaint is that "MS Excel calculations are not auditable, repeatable, version controlled, etc". All true, but it still doesn't change the fact that Python doesn't have an instant datagrid GUI. UI affordances also matter in viewing science data sets as well as financial budgets.
And I was wondering if people like in the non-engineering but scientific fields, as the ones discussed in post, are exposed to the alternatives during their formation years.
If one chooses to use Excel because its the best tool great, but if its because its the perceived only option that's probably counterproductive.
I've had my education in a engineering focused campus so that may skew it, but even not IT related area had programming courses to, at least, learn the basics.
Do the newer researcher still show reluctance to move from Excel or is it an old guard kind of deal?