As noted above, NumPy arrays behave a lot like other Python objects, for the sake of convenience. For instance, they can be indexed like lists; arr[0] accesses the first element of a NumPy array.

Gommers added, "Really long-term I expect the NumPy 'execution engine' (i.e., the C and Python code that does the heavy lifting for fast array operations) to become less and less relevant, and the ...

NumPy arrays require far less storage area than other Python lists, and they are faster and more convenient to use, making it a great option to increase the performance of Machine Learning models ...

A list is also an example of a variable that stores multiple values, but has some slight differences. When using lists in Python, you store a series of values each with a numbered index.