What is a Dictionary?
A dictionary in Python is a collection that maps unique keys to values. Unlike lists or tuples, where data is accessed by index, dictionaries allow data access by a unique key. Dictionaries are defined with curly braces `{}` and pairs of keys and values separated by colons `:`.
Basic Syntax
my_dict = {
"name": "Alice",
"age": 30,
"city": "New York"
}
In this example:
- `"name"`, `"age"`, and `"city"` are the keys. - `"Alice"`, `30`, and `"New York"`
are the values associated with these keys.
Properties of Dictionaries
1. Key-Value Pairs: Each item in a dictionary is stored as a pair, with a unique key that maps to a particular value.
2. Mutable: Dictionaries can be modified, allowing the addition, removal, or updating of items.
3. Unordered (as of Python 3.6) Dictionaries maintain insertion order (as of Python 3.7), but they’re primarily accessed by keys rather than position.
Examples on Dictionaries in python
Real-Life Example 1: Storing User Profiles
Let’s say you’re managing user profiles in a web application. A dictionary can store each user’s information, allowing you to quickly retrieve and update data by key.
user_profile = {
"username": "johndoe",
"email": "johndoe@example.com",
"age": 25,
"active": True
}
print(user_profile["email"]) # Output: johndoe@example.com
Using dictionaries, you can quickly access specific attributes of the user by referencing the associated keys (like `"email"`).
Common Dictionary Operations
Python dictionaries support various operations for creating, accessing, updating, and removing key-value pairs.
Accessing Values
Retrieve values by referencing their keys.
print(user_profile["username"]) # Output: johndoe
If a key doesn’t exist, you can use `get()` to avoid errors and provide a default value:
print(user_profile.get("location", "Unknown")) # Output: Unknown
Adding and Updating Values
You can add new key-value pairs or update existing ones directly.
user_profile["age"] = 26 # Update existing key user_profile["location"] = "NYC" # Add new key
Removing Items
Remove items using `pop()` (to get the removed value) or `del`.
user_profile.pop("active") # Removes the "active" key
del user_profile["location"] # Deletes the "location" key
Example 2: Inventory Management
In an inventory system, you might use dictionaries to track items and their quantities in stock. Here, the item name serves as the key, and its quantity as the value.
inventory = {
"apple": 50,
"banana": 20,
"orange": 30
}
# Update quantity
inventory["banana"] += 10
print(inventory) # Output: {'apple': 50, 'banana': 30, 'orange': 30}
Dictionaries make it easy to manage and update stock quantities, as each item can be accessed and modified by its unique key.
Dictionary Methods
Here are some helpful dictionary methods for working with dictionaries:
1. keys(): Returns all the keys in the dictionary.
print(inventory.keys()) # Output: dict_keys(['apple', 'banana', 'orange'])
2. values(): Returns all values in the dictionary.
print(inventory.values()) # Output: dict_values([50, 30, 30])
3. items(): Returns a list of `(key, value)` pairs, useful for iterating.
for item, quantity in inventory.items():
print(item, quantity)
# Output:
# apple 50
# banana 30
# orange 30
4. update(): Merges another dictionary into the current one, updating values if keys match.
new_stock = {"apple": 10, "grape": 40}
inventory.update(new_stock)
print(inventory) # Output: {'apple': 10, 'banana': 30, 'orange': 30, 'grape': 40}
Example 3: Student Grades System
A school system might store students’ grades in a dictionary, with each student’s name as the key and their grade as the value.
grades = {
"Alice": 88,
"Bob": 95,
"Charlie": 72
}
# Update Alice's grade
grades["Alice"] = 90
# Print each student's grade
for student, grade in grades.items():
print(f"{student}: {grade}")
# Output:
# Alice: 90
# Bob: 95
# Charlie: 72
This structure allows for quick lookups, updates, and iterating over student data.
Nested Dictionaries
Dictionaries can contain other dictionaries as values, which is useful for representing complex data structures, like storing each user’s complete profile in a nested dictionary.
users = {
"madhu": {"age": 28, "city": "Bangalore"},
"babu": {"age": 34, "city": "Los Angeles"},
}
Access nested data
print(users["madhu"]["city"]) # Output: Bangalore
When to use Dictionaries in Python
1. Data with Unique Identifiers: Dictionaries are excellent when each piece of data is uniquely identified by a key (e.g., usernames, product IDs).
2. Efficient Lookups: With O(1) average time complexity for lookups, dictionaries are efficient for retrieving data by key.
3. Flexible Structures: Dictionaries can represent a wide range of data structures and enable easy access and modification.
Summary
- Dictionaries store key-value pairs, making them ideal for mappings.
- Real-world applications include user profiles, inventory management, and structured data storage.
- They support fast lookups and are mutable, allowing easy modification of data.
Dictionaries provide flexibility and efficiency for handling complex data in Python. Let me know if you’d like more advanced examples or any specific functionality explained further!