2 2 6 Dictionaries Explained

Key Concepts

Dictionaries in Python are a collection of key-value pairs. They are unordered, mutable, and indexed by keys. The key concepts related to dictionaries include:

• Creating Dictionaries
• Accessing Values
• Adding and Modifying Entries
• Removing Entries
• Dictionary Methods

1. Creating Dictionaries

Dictionaries are created using curly braces {} or the dict() constructor. Each key-value pair is separated by a colon :, and pairs are separated by commas.

Example:

my_dict = {
    'name': 'Alice',
    'age': 25,
    'city': 'New York'
}
    

2. Accessing Values

Values in a dictionary can be accessed using their keys. If the key does not exist, a KeyError is raised. You can also use the get() method, which returns None if the key is not found.

Example:

name = my_dict['name']  # Accessing value using key
age = my_dict.get('age')  # Accessing value using get() method
    

3. Adding and Modifying Entries

You can add new key-value pairs to a dictionary by assigning a value to a new key. Existing keys can be modified by reassigning their values.

Example:

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

4. Removing Entries

Entries can be removed from a dictionary using the del statement or the pop() method. The pop() method removes the key-value pair and returns the value.

Example:

del my_dict['city']  # Removing an entry using del
email = my_dict.pop('email')  # Removing an entry using pop()
    

5. Dictionary Methods

Python provides several built-in methods for dictionaries, such as keys(), values(), and items(). These methods return views of the dictionary's keys, values, and key-value pairs, respectively.

Example:

keys = my_dict.keys()  # Returns a view of the dictionary's keys
values = my_dict.values()  # Returns a view of the dictionary's values
items = my_dict.items()  # Returns a view of the dictionary's key-value pairs
    

Understanding dictionaries is crucial for managing and organizing data efficiently in Python. By mastering these concepts, you can create, manipulate, and access data in a flexible and powerful way.