How Can Data Structures Be Made Interesting Using Python?

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In this article, we’ll be looking into the usage of PYTHON with Data Structures.

What is the purpose of Data? Data plays an important role in any business sector. It must be stored and arranged for processing. How can data be arranged or stored? Data can be arranged or stored using the concept of Data Structures. What are Data Structures? Data structures are the ways in which data can be stored so that it can be used efficiently. Many enterprise applications use different types of data structures to some degree. Data Structures can be incorporated with many programming languages, including PYTHON.

PYTHON
PYTHON is an Object Oriented Programming language. PYTHON is an open-source platform, i.e. it is accessible free of cost. Python is a great choice for server-side web development, software development, mathematics, and system scripting. It's popular for Rapid Application Development and as a scripting or glue language to tie existing components together because of its high-level, built-in data structures, dynamic typing, and dynamic binding. You can reduce program maintenance costs with Python ...
... due to its easily learned-syntax and emphasis on readability.

PYTHON in Data Structures
Python gives its users the ability to create custom data structures, giving them complete control over how they work.

Data Structures in PYTHON are classified into User-Defined and Built-In Data Structures.

Built-In Data Structures
Python has a few built-in data structures that make programming easier and help programmers obtain solutions faster. Let's discuss each of them in detail.
The different types of Built-In Data Structures in PYTHON are listed below.
i) List
ii) Tuples
iii) Dictionary
iv) Sets

We’ll now look into the relevant explanation of the above-listed concepts.

i) Lists
Lists are used to store data of different types in a sequential manner. They are perfect for organizing information and keeping track of things. Every element in a list has an address, called an index. The index value starts from 0 and goes up to the last element. There's also negative indexing, which starts from -1. Elements are accessed from the last.
ii) Tuples
They are a sequence of data. However, tuples cannot be changed once they are created, unless the data inside the tuple is mutable. In that case, the tuples are mutable.

iii) Dictionary
A dictionary is a data structure that stores key-value pairs.

iv) Sets
Sets are a collection of unique elements that are unordered. This means that even if data is repeated more than once, it will only be entered into the set once. This is similar to the sets you have learned about in arithmetic. The operations are also the same as with arithmetic sets. An example program would help you understand better.

User-Defined Data Structures
If you want to create a custom data type, you can do so by deriving it from an existing data type. This is called a user-defined data type (UDT).
Below listed are the types of User-Defined Data Structures in PYTHON.
i) Stack
ii) Queue
iii)Tree
iv) Linked List
v) Graph
vi) Hash Map

i) Stack
Stacks are based on the principle of last-in-first-out (LIFO). The last entered data will be the first to get accessed.
The operations of the Stack are pop, push, and accessing the elements.
The TOP of the stack is the pointer to the current position. The most common applications of Stacks are recursive programming, reversing a string, etc.
ii) Queue
A queue is a linear data structure that is based on the principle of first-in, first-out (FIFO). This means that the data that is entered first will be accessed first. This queue is built using an array structure, and you can perform operations from either end of the queue (head-tail or front-back). Operations like adding and deleting elements are called en-queue and de-queue, and you can access elements in the queue too. Queues are used in applications of Traffic Congestion.
iii) Trees
Trees are non-linear data structures with a root and nodes. The root is the node where the data originates, and the nodes are the other data points. The node before is the parent, and the node after is called the child. There are levels a tree has to show the depth of information. The last nodes are called the leaves. Trees can be used in a lot of real-world applications, such as HTML pages. They can help distinguish which tag comes under which block and are also efficient for searching purposes.
iv) Linked List
Linked lists are linear Data Structures that are not stored consecutively, but are linked with each other using pointers. A node in a linked list is made up of data and a pointer called next. These structures are commonly used in image-viewing applications, music player applications, and so on.
v) Graph
Graphs are used to store data collections of points called vertices (nodes) and edges (edges). Graphs can be referred to as the most accurate representation of a real-world map. They are used to find the distance between two points.
vi) Hash Map
HashMaps are similar to dictionaries in Python. They can be used to implement applications such as phonebooks, populate data according to lists, and more.

With these, the different types of Data Structures in PYTHON are concluded.

Advantages of PYTHON
Some of the advantages of PYTHON are listed below.
i) Availability: You can write a Python program on your Windows machine and share it with someone who is using a Mac, and it will still run properly for them.
ii) Library Availability: There are over 250,000 Python packages available for you to download and use in your projects from the Python Package Index.
iii) Object Oriented
iv) Has Built-In Data Structure

Disadvantages of PYTHON
i) Python is an excellent choice for server-side programming, but it's not used as often for client-side programming or applications for smartphones. One example of a Python-based smartphone app is called Carbonnelle.
ii) You may already know that Python is dynamically-typed. This means that you don't need to declare the type of variable while writing the code. Python uses duck-typing. This implies that it can raise run-time errors.
iii) Although Python's database access layers are not as developed as JDBC (Java DataBase Connectivity) and ODBC (Open DataBase Connectivity), they are still useful. However, they are used less often in huge enterprises.

Conclusion
In this article, we have briefed the definition of PYTHON, and we have looked into the classification of different types of Data Structures in PYTHON. PYTHON can be used as a programming language to master the concept of the Best Data Structures and Algorithms Course (DSA). Where does the concept of DSA pitch in? DSA is an important concept to be mastered to get placed in top-notch product-based organizations. At SkillSlash, an online based learning platform, candidates are trained on DSA from scratch. Skillslash also offers Data Science Course In Hyderabad and a Full Stack Developer Course In Bangalore. If you want to get into the tech domain, there’s no better support system than Skillslash. Get in touch with the student support team to know more.

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