Python Lists: Storing Multiple Values in One Container

Lists: A New Data Type for Collections

So far, we've learned about individual data types:

• int: Stores one number (age = 25)
• str: Stores one text value (name = "John")
• bool: Stores one true/false value (is_student = True)

Individual data types work perfectly for storing single pieces of information, but imagine you're planning your birthday party and need to keep track of 20 guests' names - creating 20 separate variables like guest1, guest2, guest3... would be completely impractical and impossible to manage effectively. This is exactly where lists become essential, acting like a smart container that can hold multiple related values in a single variable at once.

Why Lists are Useful: Real-World Examples

Consider these everyday scenarios where you naturally group related items:

Shopping List Example

Instead of creating separate variables for each item in daily groceries list:

# Without lists - tedious and impractical
item1 = "milk"
item2 = "bread"
item3 = "eggs"
item4 = "apples"
item5 = "chicken"

You can use a single list:

# With lists - clean and organized
shopping_list = ["milk", "bread", "eggs", "apples", "chicken"]

More Real-World List Examples

• Student grades: [85, 92, 78, 96, 88] - All grades in one place
• Phone contacts: ["Mom", "Dad", "Best Friend", "Work"] - All contacts together
• Website URLs: ["google.com", "facebook.com", "youtube.com"] - Related links

Benefits of using lists:

• Organization: Keep related data together
• Flexibility: Add or remove items as needed
• Simplicity: One variable instead of many

Creating Lists in Python

Lists are created using square brackets [ ] with items separated by commas:

# Creating different types of lists
numbers = [1, 2, 3, 4, 5]                    # List of integers
names = ["Alice", "Bob", "Charlie"]          # List of strings  
grades = [85.5, 92.0, 78.5, 96.0]            # List of floats
flags = [True, False, True, False]           # List of booleans

# Mixed data types in one list
mixed = [25, "John", True, 85.5]            # Different Data types together

# Empty list
empty_list = []                             # No items yet

print(numbers)    # Output: [1, 2, 3, 4, 5]
print(names)      # Output: ['Alice', 'Bob', 'Charlie']
print(mixed)      # Output: [25, 'John', True, 85.5]

List Indexing: Like Train Bogies with ID Numbers

Think of a Python list like a train with multiple bogies (compartments). Each bogie has an ID number attached to it - just like real trains have S1, S2, S3, etc.

Python's indexing works the same way - it assigns ID numbers to each item in your list so you can identify and find them easily. The only difference is that Python starts counting from 0 instead of 1, like having bogies numbered 0, 1, 2, 3...

When you want to access a specific item from your list, you use the square brackets [] with the ID number - just like telling the train conductor "bring me the passenger from bogie number S2." Python looks at that ID number and fetches exactly what's stored in that position.

Just like you can walk through a train from either the front engine to the last bogie or backward from the last bogie to the front, Python lists also allow you to access the item in both directions - regular indexing starts from position 0 at the beginning, while negative indexing starts from -1 at the end and counts backward, making it super easy to grab items from the tail end of your list without having to know exactly how long the list is.