Working with Lists and Dictionaries in Python

Introduction

Lists and dictionaries are two of the most powerful and widely used data structures in Python. They help in storing, organizing, and manipulating data efficiently.

A list is an ordered collection of items, which can be of different data types.
A dictionary is an unordered collection of key-value pairs, allowing fast lookups and modifications.

By the end of this module, you will understand how to create, modify, and manipulate lists and dictionaries, as well as apply these concepts in a Contact Book Mini Project.

Understanding Lists in Python

A list in Python is a collection of items stored in a single variable. Lists are mutable, meaning their contents can be changed after creation. Lists are useful for grouping related data and performing operations such as sorting, filtering, and iteration.

Creating a List

fruits = ["apple", "banana", "cherry"]
print(fruits)  # Output: ['apple', 'banana', 'cherry']

Lists can contain different data types, including numbers, strings, and even other lists.

Accessing List Elements

You can access elements using indexing (starting from 0) and negative indexing (from the end of the list).

print(fruits[0])  # Output: apple
print(fruits[-1])  # Output: cherry

Slicing allows you to access a subset of elements:

print(fruits[1:])  # Output: ['banana', 'cherry']

Modifying a List

Lists are mutable, meaning we can change their contents after creation.

fruits[1] = "blueberry"
print(fruits)  # Output: ['apple', 'blueberry', 'cherry']

Adding and Removing Elements

fruits.append("orange")  # Adds to the end
fruits.insert(1, "mango")  # Adds at index 1
print(fruits)  # Output: ['apple', 'mango', 'blueberry', 'cherry', 'orange']

fruits.remove("blueberry")  # Removes a specific element
fruits.pop()  # Removes the last element
print(fruits)  # Output: ['apple', 'mango', 'cherry']

Looping Through a List

for fruit in fruits:
    print(fruit)

List Comprehension

A concise way to create lists:

squares = [x**2 for x in range(1, 6)]
print(squares)  # Output: [1, 4, 9, 16, 25]

List comprehension allows efficient processing of large datasets.

Understanding Dictionaries in Python

A dictionary stores data in key-value pairs, making data retrieval fast and efficient. Unlike lists, dictionaries provide fast lookups and allow data to be accessed based on meaningful keys rather than numeric indexes.

Creating a Dictionary

person = {"name": "Alice", "age": 25, "city": "New York"}
print(person["name"])  # Output: Alice

Dictionaries allow storing various data types, including lists and even other dictionaries.

Adding and Modifying Entries

person["email"] = "alice@example.com"  # Adding a new key-value pair
person["age"] = 26  # Modifying an existing value

Removing Elements

del person["city"]  # Deletes the key 'city'
age = person.pop("age")  # Removes 'age' and returns its value

Looping Through a Dictionary

for key, value in person.items():
    print(f"{key}: {value}")

Using .items() ensures you retrieve both keys and values for processing.

Mini Project: Contact Book

Project Steps:

Create a dictionary to store contact details (name, phone, email).
Allow users to add, delete, update, and search for contacts.
Display all contacts in an organized manner.
Implement error handling for missing contacts.

Code Example:

contacts = {}

def add_contact(name, phone, email):
    contacts[name] = {"phone": phone, "email": email}

def remove_contact(name):
    if name in contacts:
        del contacts[name]

def search_contact(name):
    return contacts.get(name, "Contact not found!")

def display_contacts():
    for name, details in contacts.items():
        print(f"{name}: {details}")

add_contact("Alice", "123-456-7890", "alice@example.com")
add_contact("Bob", "987-654-3210", "bob@example.com")
print(search_contact("Alice"))
display_contacts()

Challenges & Enhancements:

✅ Add an update contact feature.
✅ Save contacts to a file for persistence.
✅ Implement a simple GUI using Tkinter.
✅ Add a search feature that finds contacts by partial name matching.

Conclusion

Lists and dictionaries are crucial for handling data efficiently in Python. Mastering these structures will help you work with real-world data and build more advanced applications. Lists allow you to store ordered collections, while dictionaries provide quick key-based access to data.

🚀 Next Up: We will explore Working with Loops and Iterations in Python!

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