Types of Data Structures - rnakidi/dsa GitHub Wiki
Essential Data Structures for Efficient Programming
Understanding data structures is critical to writing efficient and scalable code. Here's a quick overview of some foundational structures every programmer should know:
1️⃣ Array: Fixed-size collection, perfect for quick access using indexes.
2️⃣ Queue: First In, First Out (FIFO), ideal for task scheduling.
3️⃣ Tree: Hierarchical structure, great for representing relationships like organizational charts.
4️⃣ Matrix: A grid-like 2D array, commonly used in tabular data and image processing.
5️⃣ Graph: Nodes connected by edges, excellent for mapping relationships like social networks.
6️⃣ Linked List: Dynamic sequence of nodes, perfect for flexible insertion/removal of elements.
7️⃣ Max Heap: A tree structure where the largest element is always at the root, useful in priority tasks.
8️⃣ Stack: Last In, First Out (LIFO), crucial for undo operations or managing recursive calls.
9️⃣ Trie: A tree for string storage with shared prefixes, perfect for autocomplete and search.
🔟 HashMap: Key-value pair structure, offers fast data retrieval.
1️⃣1️⃣ HashSet: Stores unique elements, great for eliminating duplicates.
Each data structure has its unique use case, helping you solve problems more efficiently.