DevOps Articles

5 common Python pitfalls for data preparation

Python is a powerful language for data preparation, but there are some common mistakes or pitfalls folks may encounter. In this blog post, I’ll discuss five of the most common issues folks encounter when using Python for data preparation.

This set of objects and values are known as “falsy” and will evaluate to false.

The all() method returns true if all elements of the iterable are true (or if the iterable is empty). Don’t think of it as “Return true if all the elements of the iterable are true,” but instead “Return true if there are no false elements in the iterable.”