7. Dictionaries and Mapping

Dictionaries are mapping containers for fast lookup, record-like data, counting, grouping, and key-value relationships.

• Dictionaries map keys to values

• Keys must be hashable so Python can locate values efficiently

• Dictionary methods support lookup, mutation, iteration, and transformation

• Comprehensions build dictionaries from existing data

• Lookup-heavy programs often depend on dictionary design

Video

Python Tutorial for Beginners 5: Dictionaries by Corey Schafer

Learning Goals

By the end of this chapter, you will be able to:

1. Create, access, update, and delete entries in a Python dictionary

2. Use dictionary methods such as .get(), .keys(), .values(), .items(), and .update()

3. Write dictionary comprehensions and choose clear key-value structures

4. Use dictionary patterns for counting, grouping, inversion, and sorted summaries

5. Explain why dictionaries depend on hashable values

Chapter Flow

• 7.1. Dictionaries
• 7.2. Core Operations
• 7.3. Dictionary Patterns
• 7.4. Assignments
  • 7.4.1. Preview Questions
  • 7.4.2. Homework
  • 7.4.3. Lab

Glossary

Term	Definition
dictionary	A mutable mapping that stores key-value pairs with O(1) average lookup by key
key	The identifier used to access a value in a dictionary; must be hashable and unique
value	The data associated with a key; can be any Python object
hash table	The underlying data structure enabling O(1) average lookup in dictionaries
Counter	A dict subclass from collections that counts element frequencies
defaultdict	A dict subclass from collections that auto-creates a default value for missing keys
comprehension	A concise one-expression syntax for building dictionaries from iterables
memoization	Caching previously computed results in a dictionary to avoid redundant computation

Chapter Overview Slides