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Hands-On Data Structures and Algorithms with Python – Third Edition

You're reading from   Hands-On Data Structures and Algorithms with Python – Third Edition Store, manipulate, and access data effectively and boost the performance of your applications

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Product type Paperback
Published in Jul 2022
Publisher Packt
ISBN-13 9781801073448
Length 496 pages
Edition 3rd Edition
Languages
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Author (1):
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Dr. Basant Agarwal Dr. Basant Agarwal
Author Profile Icon Dr. Basant Agarwal
Dr. Basant Agarwal
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Toc

Table of Contents (17) Chapters Close

Preface 1. Python Data Types and Structures FREE CHAPTER 2. Introduction to Algorithm Design 3. Algorithm Design Techniques and Strategies 4. Linked Lists 5. Stacks and Queues 6. Trees 7. Heaps and Priority Queues 8. Hash Tables 9. Graphs and Algorithms 10. Searching 11. Sorting 12. Selection Algorithms 13. String Matching Algorithms 14. Other Books You May Enjoy
15. Index
Appendix: Answers to the Questions

Resolving collisions

Each position in the hash table is often called a slot or bucket that can store an element. Each data item in the form of a (key, value) pair is stored in the hash table at a position that is decided by the hash value of the key. Let’s take an example in which firstly we use the hashing function that computes the hash value by summing up the ordinal values of all the characters. Then, we compute the final hash value (in other words, the index position) by computing the total ordinal values of module 256. Here, we use 256 slots/buckets as an example. We can use any number of slots depending upon how many records we require in the hash table. We show a sample hash in Figure 8.5, which has key strings corresponding to data values, for example, the eggs key string has the corresponding data value 123456789.

This hash table uses a hashing function that maps the input string hello world to a hash value of 92, which finds a slot position in the hash table...

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