Python Tutorial - Part 3: Collections and Data Structures

In this third installment of our Python tutorial series, we'll explore Python's built-in collection types that allow you to store and organize multiple pieces of data.

Lists

Lists are ordered collections of items that can be changed (mutable).

fruits = ["apple", "banana", "orange"]
numbers = [1, 2, 3, 4, 5]
mixed_list = ["hello", 42, 3.14, True]

# Accessing elements
print(fruits[0])  # "apple"
print(fruits[-1]) # "orange" (last element)

# Adding elements
fruits.append("grape")

Tuples

Tuples are ordered collections that cannot be changed (immutable).

coordinates = (10, 20)
colors = ("red", "green", "blue")

# Accessing elements (same as lists)
print(coordinates[0])  # 10

# Tuples are immutable - this would cause an error:
# coordinates[0] = 15  # TypeError!

Dictionaries

Dictionaries store data in key-value pairs.

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

# Accessing values
print(person["name"])     # "Alice"
print(person.get("age"))  # 25

# Adding new key-value pairs
person["job"] = "Developer"

Working with Collections

Iterating through collections

# Lists and tuples
for fruit in fruits:
    print(fruit)

# Dictionaries
for key, value in person.items():
    print(f"{key}: {value}")

Length and membership

print(len(fruits))           # Number of items
print("apple" in fruits)     # Check if item exists
print("name" in person)      # Check if key exists

What's Next?

In Part 4, we'll learn about control flow: if statements, loops, and functions. These are the building blocks that make your Python programs dynamic and interactive!

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