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up vote 2 down vote favorite. 1. Python has a lot of convenient data structures (lists, tuples, dicts, sets, etc) which can be used to make other 'conventional' data structures (Eg, I can use a Python list to create a stack and a collections.dequeue to make a queue, dicts to make trees and graphs, etc).p vote 2 down vote favorite. 1. Python has a lot of convenient data structures (lists, tuples, dicts, sets, etc) which can be used to make other 'conventional' data structures (Eg, I can use a Python list to create a stack and a collections.dequeue to make a queue, dicts to make trees and graphs, etc).
Therefore, whenever we refer to an âarray,â we mean a âNumPy array.â. Lists are another data structure, similar to NumPy arrays, but unlike NumPy arrays, lists are a part of core Python. Lists have a variety of uses. They are useful, for example, in various bookkeeping tasks that arise in computer programming.Like arrays, they are sometimes used to store data.ere we list some of the differences between Python lists and NumPy arrays, and why you might prefer to use one or the other depending on the circumstance. 1  The elements of a NumPy array must all be of the same type, whereas the elements of a Python list can be of completely different types.