Python Fundamentals Revisited: Why Data Structures and Built-ins Matter Most

A data science learner returning to Python after SQL practice found that deliberately revisiting core concepts — lists, dictionaries, sets, loops, and functions — significantly improved their coding efficiency. Choosing the right data structure based on the question being asked, rather than habit, led to noticeably shorter and cleaner code. Built-in functions like sorted(), max(), and min() with the key argument replaced multi-line manual loops with single-line solutions. The author also reframed functions not just as tools for code reuse but as a way of naming and communicating intent, making scripts easier to read later. Switching from notebook-based coding to running scripts directly in the terminal was highlighted as an underrated but practical skill that surfaces errors more reliably.