Why You Should Stop Writing Loops in Pandas

Iterating through Pandas DataFrames with loops is a common but highly inefficient practice that significantly slows down code execution. Vectorized operations, such as using `np.where` or boolean indexing, can perform the same tasks thousands of times faster by processing entire columns at once. This approach encourages a professional, column-level thinking pattern instead of a row-by-row one. While the `.apply()` method appears cleaner than a loop, it still iterates row-by-row internally and should only be used as a last resort when true vectorization is not possible.