This repository contains my notes, code examples, and practice files for learning and implementing data structures and algorithms in Python. It includes content from Google Colab notebooks and solutions to various coding problems.
File Input, Output
- Inheritance, Polymorphism, Overriding
- Error, Exception handling
- Encoding, decoding
- File Input, Output Options
- Absolute Path and Relative Path
Web Crawling/Scraping
- Server and Clients
- Web
- Browser
- URI, URL, Domain, IP
- Protocols
- WWW, W3C
- HTML, Tag, HTML structure
- Web Crawling/Scraping basics
- Web Crawling package, BeautifulSoup
- User-Agent
Numpy
- Numpy functions
- Code examples
Pandas(Series)
- Pandas(Series) functions
- Code examples
Pandas(DataFrame)
- Pandas(Series) functions
- Code examples
Matplotlib, Seaborn, folium
- Matplotlib, Seaborn, folium functions
- Code examples
OpenAI API
- How to use OpenAI API
- Code examples
Data Structures
- Linked List
- Circular Linked List
- Stack
- Queue
- Circular Queue
- Hash table
- Tree
- Binary Tree
- Binary Tree Traversal
- DFS, BFS
- Binary Search Tree (BST)
Algorithms
- Greedy
- Sort
- Selection Sort
- Insertion Sort
- Bubble Sort
- Merge Sort
- Quick Sort
- The code in this repository is licensed under the MIT License, meaning you are free to use, modify, and distribute it with attribution.
- The notes and written content are licensed under Creative Commons Attribution 4.0 (CC BY 4.0). This means you may share and adapt them, as long as you provide proper credit.
If you use the notes, please include a statement like:
"Based on notes by GyuJin Lee (GitHub Profile), licensed under CC BY 4.0."