[manifoldgeo]

I think this may have less to do with "python-brain" and more with "data-science brain". If a person is well-versed in data science concepts and has been trained to use Pandas DataFrames and Series for everything, that's what they'll lean on. After all, it's some kind of in-memory object that can hold many values and has a way to label them with column labels and indices.

Chances are somewhat good that these people weren't computer science majors to begin with. For example, math or biology majors who have moved away from R to Python might know a great deal about data but not much about compsci.

For people who use Python in a DevOps context, they'll likely be exposed to more OOP concepts and lean more heavily on classes.

[throwaway894345]

Yeah, I've seen a lot of people write absurd dataframe monstrocities that ended up being slower than the naive Python loop-over-a-list solution never mind 10X the code. But I've also seen plenty of non-data-science examples.