Data Structures for Coding Interviews in Python

Get a firm grasp on the inner workings of the most common data structures. Tackle common interview coding problems and analyze your solutions.

Beginner

228 Lessons

30h

Certificate of Completion

Get a firm grasp on the inner workings of the most common data structures. Tackle common interview coding problems and analyze your solutions.

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Mock Interview

Explanations

AI-POWERED

Code Feedback

Mock Interview

This course includes

168 Playgrounds

65 Challenges

24 Quizzes

This course includes

168 Playgrounds

65 Challenges

24 Quizzes

Course Overview

Data structures are amongst the most fundamental concepts of Computer Science. The data structure chosen can make or break an entire computer program. Consequently, they are also largely categorized as a vital benchmark of computer science knowledge when it comes to industry interviews. This course contains a detailed review of all the common data structures and provides implementation level details in Python to allow readers to become well equipped. Now with more code solutions, lessons, and illustrations ...Show More

Course Content

Introduction to Complexity Measures

Comparing Algorithms Example: Measuring Time Complexity of For Loop Example: Measuring Time Complexity of a Nested For Loop

Complexity Quiz: Test your understanding of complexity

Introduction to Lists

Lists Arrays

Lists vs Arrays in Python

Challenge: Remove Even Integers From List

Solution: Remove Even Integers From List Challenge: Merge Two Sorted Lists Solution: Merge Two Sorted Lists Challenge: Find Two Numbers That Add Up to K Solution: Find Two Numbers That Add Up to K Challenge: Product of Array Except Self Solution: Product of Array Except Self Challenge: Find Minimum Value in List Solution: Find Minimum Value in List Challenge: First Non-Repeating Integer in a List Solution: First Non-Repeating Integer in a List Challenge: Find Second Maximum Value in a List Solution: Find Second Maximum Value in a List Challenge: Rotate List Solution: Rotate List Challenge: Rearrange Positive & Negative Values Solution: Rearrange Positive & Negative Values Challenge: Rearrange Sorted List in Max/Min Form Solution: Rearrange Sorted List in Max/Min Form Challenge: Maximum Sublist Solution: Maximum Sublist Lists Quiz: Test your understanding of Lists

Introduction to Linked Lists

Singly Linked Lists (SLL)Linked Lists vs. Lists Basic Linked List Operations Singly Linked List Insertion

Singly Linked List Deletion Doubly Linked Lists (DLL)Singly Linked Lists vs. Doubly Linked Lists Challenge: Insertion at Tail Solution: Insertion at Tail Challenge: Search in a Singly Linked List Solution: Search in a Singly Linked List Challenge: Deletion by Value Solution: Deletion by Value Challenge: Find the Length of a Linked List Solution: Find the Length of a Linked List

Challenge: Reverse Linked List Solution: Reverse Linked List Challenge: Linked List Cycle Solution: Linked List Cycle Challenge: Middle of the Linked List Solution: Middle of the Linked List Challenge: Remove Duplicates from a Linked List Solution: Remove Duplicates from a Linked List Challenge: Union and Intersection of Linked Lists Solution: Union and Intersection of Linked Lists Challenge: Return the Nth Node from End Solution: Return the Nth Node from End Challenge: Find If a Doubly Linked List Is a Palindrome Solution: Find If a Doubly Linked List Is a Palindrome Linked Lists Quiz: Test your understanding of Linked Lists

Introduction to Stacks and Queues

What is a Stack?Stack (Implementation)What is a Queue?Queue (Implementation)

Challenge: Generate Binary Numbers From 1 to n Using a Queue Solution: Generate Binary Numbers From 1 to n Using a Queue Challenge: Implement Two Stacks Using One List Solution: Implement Two Stacks Using One List

Challenge: Reverse First k Elements of Queue Solution: Reverse First k Elements of Queue

Challenge: Implement Queue Using Stacks Solution: Implement Queue Using Stacks Challenge: Sort Values in a Stack Solution: Sort Values in a Stack Challenge: Evaluate Postfix Expression Using a Stack Solution: Evaluate Postfix Expression Using a Stack Challenge: Next Greater Element Using a Stack Solution: Next Greater Element Using a Stack Challenge: Find the Celebrity Solution: Find the Celebrity Challenge: Valid Parentheses Solution: Valid Parentheses Challenge: Min Stack Solution: Min Stack Stack/Queue Quiz: Test your understanding of Stack/Queue

Introduction to Graphs

What is a Graph?Types of Graphs Representation of Graphs

Graph Implementation Complexities of Graph Operations What is a Bipartite Graph?Graph Traversal Algorithms Challenge: Implement Breadth-First Search Solution: Implement Breadth-First Search Challenge: Implement Depth-First Search Solution: Implement Depth-First Search Challenge: Detect Cycle in a Directed Graph Solution: Detect Cycle in a Directed Graph Challenge: Find a Mother Vertex in a Directed Graph Solution: Find a Mother Vertex in a Directed Graph Challenge: Count the Number of Edges in an Undirected Graph Solution: Count the Number of Edges in an Undirected Graph Challenge: Check If a Path Exists between Two Vertices Solution: Check If a Path Exists between Two Vertices Challenge: Graph Valid Tree Solution: Graph Valid Tree Challenge: Find the Shortest Path between Two Vertices Solution: Find the Shortest Path between Two Vertices Challenge: Remove Edge from a Directed Graph Solution: Remove Edge from a Directed Graph Graph Quiz: Test your understanding of Graphs

Introduction to Trees

38 Lessons

Trie

14 Lessons

Introduction to Heap

12 Lessons

Introduction to Hashing

33 Lessons

10.

Summary of Data Structures

2 Lessons

Course Author

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Frequently Asked Questions

What are the data structures for coding interviews in Python?

For coding interviews in Python, focus on these essential data structures:

Lists: Used for dynamic arrays that support fast access, insertion, and deletion.
Dictionaries: Implement hash tables for efficient key-value storage and lookups.
Sets: Store unique elements and provide fast membership checks.
Tuples: Immutable sequences used for fixed-size collections.
Queues and stacks: Use collections.deque for double-ended queues, which can also efficiently implement stacks and queues.
Heaps: Use heapq for priority queues.
Linked lists, trees, and graphs: Implement manually using classes to handle more complex problems.

Mastering these structures and their operations will prepare you well for Python coding interviews.

Can I use Python for DSA in an interview?

Yes, you can use Python for DSA in interviews. Python is highly popular for its simple syntax, readability, and powerful built-in libraries, which make implementing data structures and algorithms easier. It offers built-in support for lists, dictionaries, sets, and other data structures, along with libraries like collections and heapq for more advanced needs. Python’s versatility and ease of use make it a great choice for demonstrating problem-solving skills in interviews.

How to prepare for a coding interview in Python

To prepare for a coding interview in Python, focus on mastering key data structures (like lists, dictionaries, sets, and heaps) and algorithms (such as sorting, searching, and dynamic programming). Practice solving problems on platforms like LeetCode or HackerRank to build familiarity with Python’s syntax and libraries. Understand time and space complexities and review Python-specific features like list comprehensions, generator expressions, and built-in functions. Regularly simulate coding interviews to improve your problem-solving speed and communication skills.

Is Python a good choice for coding interviews?

Yes, Python is an excellent choice for coding interviews. Its clean and concise syntax allows you to write and debug code quickly, making it ideal for solving complex problems under time constraints. Python’s extensive standard library provides built-in data structures (like lists, dictionaries, and sets) and algorithms, which help simplify implementations. It’s widely accepted in interviews across various companies, and many interviewers are familiar with its capabilities, making it a strong option for effectively demonstrating problem-solving skills.

What are the five data types in Python?

The five primary data types in Python are as follows:

Integers (int): Represent whole numbers, such as 1, 42, or -7.
Floating-point numbers (float): Represent decimal numbers, such as 3.14, 0.001, or -2.5.
Strings (str): Represent sequences of characters, such as “hello”, “Python”, or “123”.
Booleans (bool): Represent truth values, either True or False.
NoneType (None): Represents the absence of a value or a null value, expressed as None.

These basic data types form the foundation for handling and manipulating data in Python.