How to Represent Data Structure in Python

Data structure organises and stores data to facilitate quick access and modification. Python has several ways to represent different data structures, each with its own built-in functions and methods for manipulating the data. Here are a few examples: 

• Arrays: Python lists can be used to represent arrays. You can use the append(), insert(), remove(), and pop() functions to add and remove elements from a list. 
• Linked Lists: Python does not have a built-in linked list data structure, but classes can create a linked list. 
• Stacks: You can use a Python list to represent a stack, using the append() and pop() methods to add and remove elements from the stack. 
• Queues: Python lists can also represent a queue, but the deque class from the collections module is more efficient. Element addition to the back of the queue is accomplished using the append() function. 
• Trees: Python does not have a built-in tree data structure, but classes can create a tree. 

You may have a look at the code given below for representing data structure in Python. 

Fig : Preview of the output that you will get on running this code from your IDE.

Code

Instructions

Follow the steps carefully to get the output easily.

1. Install python on your IDE(Any of your favorite IDE).
2. Copy the snippet using the 'copy' and paste it in your IDE.
3. Add print statement at the end of the code after pasting the code(like 'print(myList)' and also refer preview of the output).
4. Run the file to generate the output.

I hope you found this useful.

I found this code snippet by searching for 'how to represent data-structure in python' in kandi. You can try any such use case!

Environment Tested

I tested this solution in the following versions. Be mindful of changes when working with other versions.

1. The solution is created in PyCharm 2021.3.
2. The solution is tested on Python 3.9.7.

Using this solution, we are able to represent data structure in python with simple steps. This process also facilities an easy way to use, hassle-free method to create a hands-on working version of code which would help us to represent data structure in python.

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