Python's Surprising Behaviors That Can Silently Corrupt Data Work

A DEV Community article examines counterintuitive Python behaviors that matter for data science and machine learning work. It shows how repeating a list with the multiplication operator creates several rows that reference the same object, so editing one cell alters others. It also explains how a mutable default argument in a function persists between calls, causing results to leak across experiments. The author notes that such bugs can produce plausible but wrong results, which can be worse than outright crashes. Standard fixes are offered, such as building lists with a comprehension and using a None default. The article also begins discussing how True, 1, and 1.0 collide as dictionary keys, continuing into further examples.