Python Dictionary

Introduction

Dictionaries in Python are an unordered collection of items, where each item is a pair of a key and a value. Dictionaries are mutable, meaning their contents can be changed. They are commonly used for storing and managing data in key-value pairs, which allows for efficient data retrieval.

Python Dictionary Data Structure

A dictionary in Python is an unordered collection of key-value pairs. Dictionaries are defined using curly braces {} with keys and values separated by a colon :.

Key Points:

• Unordered collection
• Mutable (can be changed)
• Keys must be unique and immutable (e.g., strings, numbers, tuples)
• Values can be of any type and can be duplicated

Create Dictionary

Dictionaries can be created by placing key-value pairs inside curly braces {} or using the dict() function.

Example

# Creating a dictionary using curly braces
my_dict = {"name": "Alice", "age": 25, "city": "New York"}

# Creating a dictionary using the dict() function
another_dict = dict(name="Bob", age=30, city="San Francisco")

Access Dictionary Items

Dictionary items can be accessed using their keys.

Example

# Accessing an item by key
print(my_dict["name"])  # Output: Alice

# Accessing an item using the get() method
print(my_dict.get("age"))  # Output: 25

Add Dictionary Items

You can add items to a dictionary by assigning a value to a new key.

Example

# Adding a new key-value pair
my_dict["job"] = "Engineer"
print(my_dict)  # Output: {'name': 'Alice', 'age': 25, 'city': 'New York', 'job': 'Engineer'}

Change Dictionary Items

You can change the value of specific items by accessing them via their keys.

Example

# Changing the value of an existing key
my_dict["age"] = 26
print(my_dict)  # Output: {'name': 'Alice', 'age': 26, 'city': 'New York', 'job': 'Engineer'}

Remove Dictionary Items

Items can be removed from a dictionary using methods like pop(), popitem(), del, and clear().

Example

# Using pop() to remove an item by key
my_dict.pop("city")
print(my_dict)  # Output: {'name': 'Alice', 'age': 26, 'job': 'Engineer'}

# Using popitem() to remove the last inserted item
my_dict.popitem()
print(my_dict)  # Output: {'name': 'Alice', 'age': 26}

# Using del to remove an item by key
del my_dict["age"]
print(my_dict)  # Output: {'name': 'Alice'}

# Using clear() to remove all items
my_dict.clear()
print(my_dict)  # Output: {}

Loop Dictionaries

You can loop through a dictionary to access keys, values, or both.

Example

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

# Looping through keys
for key in my_dict:
    print(key)
# Output:
# name
# age
# city

# Looping through values
for value in my_dict.values():
    print(value)
# Output:
# Alice
# 25
# New York

# Looping through key-value pairs
for key, value in my_dict.items():
    print(f"{key}: {value}")
# Output:
# name: Alice
# age: 25
# city: New York

Dictionary Comprehension

Dictionary comprehension provides a concise way to create dictionaries.

Example

# Creating a dictionary of squares
squares = {x: x**2 for x in range(5)}
print(squares)  # Output: {0: 0, 1: 1, 2: 4, 3: 9, 4: 16}

Copy Dictionary

Dictionaries can be copied using the copy() method or the dict() function.

Example

# Using the copy() method
original_dict = {"name": "Alice", "age": 25}
copied_dict = original_dict.copy()
print(copied_dict)  # Output: {'name': 'Alice', 'age': 25}

# Using the dict() function
copied_dict = dict(original_dict)
print(copied_dict)  # Output: {'name': 'Alice', 'age': 25}

Nested Dictionaries

Dictionaries can contain other dictionaries, which are called nested dictionaries.

Example

nested_dict = {
    "person1": {"name": "Alice", "age": 25},
    "person2": {"name": "Bob", "age": 30}
}
print(nested_dict["person1"]["name"])  # Output: Alice

Dictionary Methods

Python provides various built-in methods for dictionaries.

Common Dictionary Methods

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

# items() - Returns a view object with key-value pairs
print(my_dict.items())  # Output: dict_items([('name', 'Alice'), ('age', 25), ('city', 'New York')])

# keys() - Returns a view object with all the keys
print(my_dict.keys())  # Output: dict_keys(['name', 'age', 'city'])

# values() - Returns a view object with all the values
print(my_dict.values())  # Output: dict_values(['Alice', 25, 'New York'])

# update() - Updates the dictionary with the specified key-value pairs
my_dict.update({"job": "Engineer"})
print(my_dict)  # Output: {'name': 'Alice', 'age': 25, 'city': 'New York', 'job': 'Engineer'}

# fromkeys() - Creates a new dictionary with specified keys and values
new_dict = dict.fromkeys(["name", "age", "city"], "unknown")
print(new_dict)  # Output: {'name': 'unknown', 'age': 'unknown', 'city': 'unknown'}

Python Dictionary Methods Table

Python dictionaries provide a variety of methods to manipulate and operate on key-value pairs. These methods make it easy to perform common tasks such as adding, removing, and accessing elements in a dictionary. Below is a list of some commonly used dictionary methods, along with their descriptions and links to detailed guides for each method.

Performance Considerations

• Time Complexity: Common operations like accessing, inserting, and deleting items have an average time complexity of O(1) because dictionaries use hash tables.
• Memory Usage: Dictionaries can use more memory than other data structures because they need to store additional information for each key-value pair.

Conclusion

Dictionaries are a powerful and flexible data structure in Python, allowing for efficient storage and retrieval of data using key-value pairs. Understanding how to create, access, modify, and use dictionaries, along with their associated methods and performance considerations, is essential for effective Python programming. Whether you’re working with simple dictionaries or complex nested structures, Python’s dictionary operations provide the tools you need to manage your data efficiently.