There is also negative indexing which starts from -1 enabling you to access elements from the last to first. The index value starts from 0 and goes on until the last element called the positive index. There are addresses assigned to every element of the list, which is called as Index. Lists are used to store data of different data types in a sequential manner. So now that you know what are the types available to you, why don’t we move ahead to the Data Structures and implement them using Python.Īs the name suggests, these Data Structures are built-in with Python which makes programming easier and helps programmers use them to obtain solutions faster. The most prominent Data Structures are Stack, Queue, Tree, Linked List and so on which are also available to you in other programming languages. Python allows its users to create their own Data Structures enabling them to have full control over their functionality. These structures are called List, Dictionary, Tuple and Set. Python has implicit support for Data Structures which enable you to store and access data. It is one of the most basic concepts that beginners get to know about when learning the Best Python Course Online for exams like PCEP, PCAP, PCPP. Data Structures allows you to organize your data in such a way that enables you to store collections of data, relate them and perform operations on them accordingly. Organizing, managing and storing data is important as it enables easier access and efficient modifications. The article has been broken down into the following parts: ![]() ![]() With that being said, let us go through the topics we will cover in Data Structures in Python. So how do you achieve this? We use something called Data Structures. But to make all of this possible, data plays a very important role which means that this data should be stored efficiently and the access to it must be timely. ![]() Python has been used worldwide for different fields such as making websites, artificial intelligence and much more.
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