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Everyday data structures

You're reading from   Everyday data structures A practical guide to learning data structures simply and easily

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Product type Paperback
Published in Mar 2017
Publisher Packt
ISBN-13 9781787121041
Length 344 pages
Edition 1st Edition
Languages
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Author (1):
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William Smith William Smith
Author Profile Icon William Smith
William Smith
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Table of Contents (14) Chapters Close

Preface 1. Data Types: Foundational Structures 2. Arrays: Foundational Collections FREE CHAPTER 3. Lists: Linear Collections 4. Stacks: LIFO Collections 5. Queues: FIFO Collections 6. Dictionaries: Keyed Collections 7. Sets: No Duplicates 8. Structs: Complex Types 9. Trees: Non-Linear Structures 10. Heaps: Ordered Trees 11. Graphs: Values with Relationships 12. Sorting: Bringing Order Out Of Chaos 13. Searching: Finding What You Need

Visual graph concepts

It is sometimes easier to grasp the concept of graph data structures using visual representations of some collections. Consider the following diagram:

Visual graph concepts

This is a basic graph consisting of eleven nodes and twelve edges. Sets N and E can be described as follows:

N = {2, 3, 4, 5, 9, 11, 19, 38, 52, 77, 97}

E = {2:38, 2:77, 2:97, 3:19, 4:77, 5:2, 5:19, 11:2, 11:4, 11:5, 11:52, 77:9}

Note that, in this example, there are only unidirectional edges between nodes. This is perfectly acceptable, but graphs are much more powerful when bidirectional nodes are permitted. Consider the following example:

Visual graph concepts

This is the same graph we saw earlier, but set E now contains several new reciprocal edges between existing nodes. Sets N and E can now be described as follows:

N = {2, 3, 4, 5, 9, 11, 19, 38, 52, 77, 97}

E = {2:5, 2:38, 2:77, 2:97, 3:19, 4:11, 4:77, 5:2, 5:19, 11:2, 11:4, 11:5, 11:52, 77:9, 97:2}

Finally, edges between nodes can also be defined with a particular value. Consider the...

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