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Introduction to Python Dictionaries

In Python, a dictionary is a versatile and powerful data structure that stores a collection of key-value pairs. Unlike sequences such as lists or tuples, which are indexed by a range of numbers, dictionaries are indexed by keys, allowing for fast and efficient lookups. Dictionaries are denoted by curly braces {} and consist of comma-separated key-value pairs in the format key: value. Each key in a dictionary must be unique, but values can be duplicated.

Dictionaries are often used to represent real-world data, such as user profiles, inventory items, or configuration settings, where each piece of data has a meaningful label (key) associated with it. In this tutorial, we will explore the various operations and methods related to dictionaries in Python, along with examples to illustrate their usage.

Creating Dictionaries

Method 1: Using Curly Braces

You can create a dictionary by enclosing key-value pairs within curly braces. Each pair is separated by a comma, and the key and value are separated by a colon. Here’s an example:

# Creating a dictionary of student information
student = {
    "name": "Alice",
    "age": 20,
    "major": "Computer Science",
    "GPA": 3.8

Method 2: Using the dict() Constructor

You can also create dictionaries using the built-in dict() constructor by passing a list of tuples containing key-value pairs. Here’s an example:

# Creating a dictionary using the dict() constructor
colors = dict([
    ("red", "#FF0000"),
    ("green", "#00FF00"),
    ("blue", "#0000FF")

Method 3: Using Dictionary Comprehensions

Dictionary comprehensions provide a concise way to create dictionaries using a loop. Here’s an example that creates a dictionary of squares:

# Creating a dictionary using dictionary comprehension
squares = {x: x ** 2 for x in range(1, 6)}

Accessing and Modifying Dictionary Elements

Accessing Values

You can access the values in a dictionary by referencing their keys within square brackets. If the key is not present, it will raise a KeyError exception. To avoid this, you can use the get() method, which returns a default value if the key is not found.

# Accessing values from a dictionary
print(student["name"])  # Output: Alice

# Using the get() method
print(student.get("age", 0))  # Output: 20
print(student.get("address", "Unknown"))  # Output: Unknown

Modifying Values

Dictionaries are mutable, meaning you can change their values after creation. To modify a value, reference its key and assign a new value to it.

# Modifying values in a dictionary
student["GPA"] = 3.9
print(student["GPA"])  # Output: 3.9

Dictionary Methods

Python provides several methods for working with dictionaries. Let’s explore some of the most commonly used methods.

keys(), values(), and items()

The keys() method returns a view of all the keys in the dictionary. Similarly, the values() method returns a view of all the values. The items() method returns a view of all the key-value pairs as tuples.

# Using keys(), values(), and items() methods
print(student.keys())    # Output: dict_keys(['name', 'age', 'major', 'GPA'])
print(student.values())  # Output: dict_values(['Alice', 20, 'Computer Science', 3.9])
print(student.items())   # Output: dict_items([('name', 'Alice'), ('age', 20), ('major', 'Computer Science'), ('GPA', 3.9)])

pop() and popitem()

The pop() method removes and returns the value associated with the specified key. If the key is not found, it raises a KeyError (unless a default value is provided). The popitem() method removes and returns the last key-value pair as a tuple.

# Using pop() and popitem() methods
age = student.pop("age")
print(age)          # Output: 20
print(student)      # Output: {'name': 'Alice', 'major': 'Computer Science', 'GPA': 3.9}

last_item = student.popitem()
print(last_item)    # Output: ('GPA', 3.9)
print(student)      # Output: {'name': 'Alice', 'major': 'Computer Science'}


The update() method merges the contents of one dictionary into another. If keys are already present in the target dictionary, their values are updated; otherwise, new key-value pairs are added.

# Using the update() method
new_info = {
    "age": 21,
    "email": ""
# Output: {'name': 'Alice', 'major': 'Computer Science', 'age': 21, 'email': ''}


The clear() method removes all key-value pairs from the dictionary, leaving it empty.

# Using the clear() method
print(student)  # Output: {}

Dictionary Comprehensions

Similar to list comprehensions, dictionary comprehensions allow you to create dictionaries using a concise syntax. The basic structure is {key_expression: value_expression for item in iterable}.

# Using dictionary comprehension to create a dictionary of even squares
even_squares = {x: x ** 2 for x in range(2, 11, 2)}
# Output: {2: 4, 4: 16, 6: 36, 8: 64, 10: 100}

Example 1: Creating a Frequency Counter

Dictionaries are commonly used to count the frequency of elements in a sequence. In this example, we’ll create a function that takes a string as input and returns a dictionary containing the frequency of each character.

def character_frequency(text):
    freq_counter = {}
    for char in text:
        if char.isalpha():
            char = char.lower()
            freq_counter[char] = freq_counter.get(char, 0) + 1
    return freq_counter

input_text = "Hello, world! This is a sample text."
result = character_frequency(input_text)
# Output: {'h': 2, 'e': 2, 'l': 3, 'o': 2, 'w': 1, 'r': 1, 'd': 1, 't': 5, 'i': 4, 's': 5, 'a': 2, 'm': 2, 'p': 1, 'x': 1}

Example 2: Building a Multi-Level Dictionary

Dictionaries can be nested within other dictionaries to represent complex data structures. Here’s an example of a multi-level dictionary representing a

book catalog.

books = {
    "fiction": {
        "science_fiction": ["Dune", "1984", "Brave New World"],
        "fantasy": ["The Hobbit", "A Song of Ice and Fire", "Harry Potter"]
    "non_fiction": {
        "science": ["Cosmos", "A Brief History of Time"],
        "history": ["Sapiens", "The Guns of August"]

# Accessing a specific book
print(books["fiction"]["fantasy"][0])  # Output: The Hobbit


Python dictionaries are versatile data structures that allow you to store and manipulate key-value pairs efficiently. In this tutorial, we covered the basics of creating dictionaries, accessing and modifying their elements, using dictionary methods, and creating dictionary comprehensions. Dictionaries are powerful tools for managing structured data and are widely used in various programming tasks. By understanding their capabilities and syntax, you can make your code more organized, readable, and efficient.

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