What this book covers
Chapter 1, Getting Started, builds a background for the aspects of data structures that are important to develop basics of R, as well as why they are important.
Chapter 2, Algorithm Analysis, talks about motivation, basic notation, and fundamental techniques for algorithm analysis.
Chapter 3, Linked Lists, builds a foundation of linked lists and will cover multiple variants of linked lists, such as linear linked lists, doubly linked lists, and circular linked lists.
Chapter 4, Stacks and Queues, introduces you to array-based and linked list-based stacks and queues and their implementation in R.
Chapter 5, Sorting Algorithms, explains various sorting algorithms, such as insertion sort, bubble sort, selection sort, and shell sort, and provides an empirical comparison between different algorithms.
Chapter 6, Exploring Search Options, provides details about search operations carried out on both vectors and lists, including linked lists. It also introduces you to self-organizing lists and hashing concepts.
Chapter 7, Indexing, covers indexing concepts, which are essential in file structuring, and organize large amounts of data on disk. It will also cover ISAM, 2-3 trees, B-tree, and B+ tree in detail.
Chapter 8, Graphs, builds a foundation for the graph data structure and its implementation. It also covers various algorithms for traversals, shortest-paths problems, and minimum-cost spanning trees in detail.
Chapter 9, Programming and Randomized Algorithms, extends the concept of a static data structure to randomize data structure, such as randomized skip lists. The chapter will also introduce programming concepts and several applications of it.
Chapter 10, Functional Data Structures, introduces you to functional data structures and lazy evaluation. It will also cover functional stacks and queues in R.
