Vectorisation vs apply

Column arithmetic runs on whole arrays at once. An apply with a lambda runs your Python function per row and is typically an order of magnitude slower.

Conditional logic vectorises too: np.where for two branches, np.select for several, and boolean masks with .loc for targeted assignment.

Rule of thumb: if you are writing a for loop over rows, or apply(axis=1), there is nearly always a vectorised equivalent.