Can you honestly say you'd prefer to be debug thousands of lines of SQL versus the usual <100 lines of Python/pandas that does the same thing? It's no contest. A histogram in pandas: df.col.hist(). Unique values: df.col.value_counts(). Off the top of your head, what is the cleanest way of doing this in SQL and how does it compare? How anyone can say that SQL is objectively better (in readability, density, any metric) other than the fact that they learned it first and now are frustrated that they have to learn another new tool baffles me.

I learned Pandas first. I have no issue with indexing, different ways of referencing cells, modifying individual rows and columns, numerous ways of slicing and dicing. It gets a little sprawling but there's a method to the madness. I can come back to it months later and easily debug. With SQL, it's just madness and 10x more verbose.