The Basics: Why Data Structures Matter
Data structures are Python’s way of organizing your data efficiently. Whether you’re dealing with a simple list of items or complex relationships, there’s a structure to handle it.
Lists: The Flexible Storage
Lists are ordered, mutable (changeable), and can hold multiple data types. Think of them as shopping lists you can update on the fly.
fruits = ["apple", "banana", "cherry"]
fruits.append("orange") # Adds "orange" to the list
Tuples: Lock It In
Tuples are like lists but immutable (unchangeable), so once you’ve added data, it’s set in stone. Useful for data that shouldn’t change.
dimensions = (1920, 1080)
Sets: Unique and Unordered
Sets only store unique values and have no particular order, so they’re perfect for filtering out duplicates.
unique_numbers = {1, 2, 3, 3, 4} # Stores only {1, 2, 3, 4}
Dictionaries: Key-Value Pairs
Dictionaries let you store data with labels (keys) attached, making them ideal for structured information.
user = {"name": "Alice", "age": 30}
print(user["name"]) # Outputs: Alice
Closing Thoughts: Organized, Efficient, Powerful
With lists, tuples, sets, and dictionaries, you’re equipped to handle all kinds of data with ease.
Happy coding! 🥂
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