Python for AI ML - Day 8: Dictionaries in Python

Welcome to Day 8 of your AI/ML journey! Today, we’ll dive deep into dictionaries, one of Python’s most powerful data structures. Dictionaries store data as key-value pairs, making them ideal for fast lookups, structured data, and real-world applications like JSON processing. By the end of this guide, you’ll master dictionary creation, manipulation, methods, and use cases.

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What Are Dictionaries?

• Unordered Collection: Items are stored without a fixed order (though Python 3.7+ preserves insertion order).

• Mutable: You can modify, add, or remove items after creation.

• Key-Value Pairs: Each item has a unique key (immutable: strings, numbers, tuples) and an associated value (any data type).

• Optimized for Speed: Keys are hashed for O(1) average time complexity lookups.

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Creating Dictionaries

1. Basic Syntax

Use curly braces {} with key: value pairs:

student = {
    "name": "Alice",
    "age": 25,
    "courses": ["Math", "Physics"]
}

2. Empty Dictionary

empty_dict = {}
# or
empty_dict = dict()

3. Using the dict() Constructor

Convert lists of tuples or keyword arguments:

# From tuples
country_codes = dict([("USA", 1), ("India", 91)])
# From keyword arguments
config = dict(debug=True, max_connections=10)

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Accessing Values

1. Square Brackets []

Retrieve values using keys. Raises KeyError if the key is missing:

print(student["name"])  # Output: Alice
# print(student["grade"])  # KeyError: 'grade'

2. get() Method

Safely retrieve values with an optional default:

print(student.get("age"))       # Output: 25
print(student.get("grade", "N/A"))  # Output: N/A (default if key missing)

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Adding/Updating Entries

1. Add a New Key-Value Pair

student["country"] = "Canada"

2. Update an Existing Key

student["age"] = 26

3. Bulk Updates with update()

Merge another dictionary or list of tuples:

student.update({"country": "Canada", "gpa": 3.8})
# Or
student.update([("country", "Canada"), ("gpa", 3.8)])

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Removing Entries

1. del Keyword

Delete a specific key:

del student["courses"]  # Removes "courses" key

2. pop() Method

Remove a key and return its value:

age = student.pop("age")  # Returns 25

3. popitem()

Remove and return the last inserted item (Python 3.7+):

key, value = student.popitem()  # Removes ("gpa", 3.8)

4. clear()

Empty the dictionary:

student.clear()  # {}

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Dictionary Methods

Nested Dictionaries

Dictionaries can contain other dictionaries, lists, or objects:

employees = {
    "emp1": {
        "name": "Alice",
        "role": "Engineer"
    },
    "emp2": {
        "name": "Bob",
        "role": "Manager"
    }
}
print(employees["emp1"]["name"])  # Output: Alice

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Dictionary Operations

1. Check Key Existence

if "name" in student:
    print("Key exists!")

2. Length

print(len(student))  # Output: 3

3. Merge Dictionaries (Python 3.9+)

dict1 = {"a": 1, "b": 2}
dict2 = {"c": 3}
merged = dict1 | dict2  # {"a":1, "b":2, "c":3}

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Dictionary Comprehensions

Create dictionaries dynamically:

squares = {x: x**2 for x in range(1, 6)}
# Output: {1:1, 2:4, 3:9, 4:16, 5:25}

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Use Cases

1. JSON Data: Represent API responses or configurations.

2. Caching: Store computed values for fast retrieval.

3. Counting: Track frequencies of items (e.g., word counts).

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Practice Exercise

1. Create a nested dictionary for a library catalog with books (title, author, year).

2. Add a new book, update the year of an existing one, and remove a book using pop().

3. Use a dictionary comprehension to map numbers 1-10 to their square roots (round to 2 decimals).

Solution:

# 1. Create library catalog
library = {
    "book1": {
        "title": "Python Crash Course",
        "author": "Eric Matthes",
        "year": 2019
    },
    "book2": {
        "title": "Deep Learning",
        "author": "Ian Goodfellow",
        "year": 2016
    }
}

# 2. Add/update/remove
library["book3"] = {"title": "AI for Everyone", "author": "Andrew Ng", "year": 2021}
library["book1"]["year"] = 2023
library.pop("book2")

# 3. Square roots
import math
sqrt_dict = {x: round(math.sqrt(x), 2) for x in range(1, 11)}

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Key Takeaways

• Dictionaries store key-value pairs for efficient data retrieval.

• Use get() to safely access values and update() for bulk changes.

• Nested dictionaries model complex, hierarchical data.

• Methods like keys(), values(), and items() are essential for iteration.