Data Structures in Python: Comprehensive 6 Steps Guide

Introduction

Python is a broadly functional programming language used for almost everything. The data structures and algorithms in Python have gained popularity recently with the rise of Machine Learning and Artificial Intelligence, making code writing easy and efficient. Different data structures in Python help in solving complex problems. One of the main reasons for its popularity is that Python code is interpreted. By this, we mean that each line of a Python code is compiled, resulting in simpler and more efficient debugging.

Understanding data structures and algorithms through Python in depth allows you to explore Data Analytics and Data Science topics. Knowledge of built in data structures in Python enables learning data structures & algorithms in Python from scratch. Python has dynamic semantics, meaning that you do not need to initialize anything before using it. Let’s go into further details to know about the basic data structures in Python.

1. What Are Data Structures In Python?
2. Data Structures And Algorithms In Python
3. Lists
4. Dictionary
5. Tuples
6. Sets

1. What Are Data Structures In Python?

Data structures in Python are the building blocks or raw material for any software program. Python developers have a sound understanding of implementing data structures in Python. It  is a simple programming language to adapt to. Beginners must know about data structures and algorithms in Python, which will help them in the long run. Thorough knowledge about all data structures in Python enables learners to understand Python codes for ML as well. If you are interested in knowing how to learn data structures in Python, continue reading this blog.

2. Data Structures And Algorithms In Python

There are four data structures libraries in Python, which are, namely, lists, tuples, sets, and dictionaries. Let’s understand different types of data structures in Python with examples.

3. Lists

Lists store data sequentially and contain heterogeneous data types. Lists are immutable, meaning that you can have different data types and change the data according to your requirement. You can use three functions to add data elements into lists – append(), extend(), and insert().

• Code example:

Line 1: #List Declaration

            Line 2: L = [3, “a”, “string”, 1+1]

            Line 3: print L

            Line 4: # add 4 to the above list

            Line 5: L.append(4)

            Line 6: print L

             Line 7: # Using pop() in the above list to delete the last element

             Line 8: L.pop()

             Line 9: print L

Output:

[3, ‘z’, ‘string’, 2]

[3, ‘z’, ‘string’, 2, 4]

[3, ‘z’, ‘string’, 2]

4. Dictionary

A dictionary is a data structure in Python holding key-value pairs. It is unordered, and we can change the dictionary value since it is mutable. Keys are distinct indexes that help to access or change the dictionary values. A dictionary has no duplicate members.

• Code example:

Line 1: #declare dictionary

             Line 2: thisdict = {

             Line 3: “branch”: “Arts”,

             Line 4: “name”: “Tony”,

             Line 5: “year”: 2002

             Line 6: }

             Line 7: #change values

             Line 8: thisdict[“year”] = 2020

Output:

{‘branch’: ‘Arts’, ‘name’: ‘Tony’, ‘year’: 2020}

5. Tuples

Tuples are similar to lists. But, they have parenthesis and are non-mutable. The data inside a tuple cannot be altered. If you try to change their data, you get a warning. Tuples and lists are accessed in the same way.

• Code example:

Line 1: tup = (3, “z”, “string”, 2+3)

             Line 2: print tup

             Line 3: print tup[1]

Output:

(3, ‘z’, ‘string’, 5)

z

6. Sets

A set is an unordered collection of unique and mutable elements. A set does not possess a key-value pair. A dictionary contains key-value pairs. Methods like add(), remove() and discard() are used in sets. Along with this, some basic set operations like union, intersection, and difference are used.

• Code example:

             Line 1: # Creation of two sets

             Line 2: set1 = set()

             Line 3: set2 = set()

             Line 4: # Add elements to 1

             Line 5: for i in range(1, 3):

             Line 6: set1.add(i)

             Line 7: # Add elements to 2

             Line 8: for i in range(2, 6):

             Line 9: set2.add(i)

             Line 10: print(“Set 1 is “, set1)

             Line 11: print(“Set 2 is”, set2)

Output:

(‘Set1 = ‘, set([1, 2]))

(‘Set2 = ‘, set([2, 3, 4, 5]))

Conclusion

In this article, we answered the question, ‘How to implement data structures in Python?’ Pioneering the above four data structures programs in Python allows learners to explore advanced data structures in Python. Python has great industrial demand but learners must have the best resources to learn data structures and algorithms in Python. 

Jigsaw Academy offers a Full Stack Data Science Program (FSDS), an excellent choice to upskill your technology stack. This course provides a joint certification by NASSCOM FutureSkills & Jigsaw Academy and offers industry-relevant content for data structures and algorithms made easy in Python. This online course is 6-month-long, taught by industry experts and SMEs. Learners do not need to worry about the best book for data structures and algorithms in Python as this course covers everything they need.

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