Lists & Dictionaries

Python’s most powerful built-in data structures

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📖 Concept Recap

Lists are ordered, mutable sequences: [1, 2, 3]. Access by index. .append(), .remove(), .sort().
Dicts are key-value stores: {"name": "Alice", "age": 22}. Access by key. .get(key, default) is safer than [key].
List comprehension: [x*2 for x in numbers if x > 0] — one-line filtering and transformation.
Dict iteration: for key in d gives keys. for k, v in d.items() gives both.
Sorting with key: sorted(students, key=lambda s: s['gpa'], reverse=True)

👀 Worked Example

A shopping cart combining lists and dicts:

cart = [] products = { "apple": 1.20, "bread": 2.50, "milk": 3.00, "cheese": 4.75 } cart.append("apple") cart.append("bread") cart.append("milk") cart.append("apple") # duplicate! # Count items item_counts = {} for item in cart: item_counts[item] = item_counts.get(item, 0) + 1 print("Cart:", item_counts) # Calculate total total = sum(products[item] * count for item, count in item_counts.items()) print(f"Total: ${total:.2f}") # List comprehension — items over $2 pricey = [item for item, price in products.items() if price > 2] print("Items over $2:", pricey)

✏️ Guided

Exercise 1 — Student Roster Manager

Complete the roster manager by filling in the blanks.

students = ["Alice", "Bob", "Carol", "David", "Eve"]
grades = {"Alice": 92, "Bob": 78, "Carol": 88, "David": 95, "Eve": 71}

# 1. Add "Frank" with grade 84
students.___("Frank")
grades[___] = ___

# 2. Get all students with grades above 85
honor_students = [s for s in students if grades.get(s, 0) > ___]
print("Honor students:", honor_students)

# 3. Sort students by grade (highest first)
sorted_students = sorted(students, key=lambda s: grades.get(s, 0), reverse=___)
print("Ranked:", sorted_students)

# 4. Class average
average = sum(grades.values()) / len(___)
print(f"Class average: {average:.1f}")

Output will appear here...

💡 Hint: Use .append() to add to a list. reverse=True sorts highest-first. len(grades) for the count in the average calculation.

💪 Independent

Exercise 2 — Word Frequency Analyzer

Given the word list below, write code to find:

The unique words (no duplicates)
Word frequency (how many times each word appears)
The most common word
Words with more than 4 letters

words = ['python', 'data', 'science', 'python', 'AI', 'data', 'python', 'code']
# Your analysis here

Output will appear here...

💡 Hint: set(words) for unique words. Build frequency with a loop or {} and .get(). max(freq, key=lambda w: freq[w]) finds the most common. Use a list comprehension with len(w) > 4.

🔥 Challenge

Exercise 3 — Group by Grade

Write a function group_by_grade(grade_dict) that takes a dictionary of name: score pairs and returns a new dictionary grouping names by letter grade (A/B/C/D/F). Test with at least 8 students.

Expected output structure: {"A": ["Alice", "Carol"], "B": ["Bob"], ...}

# Your function here

# Test data:
students = {
    "Alice": 94, "Bob": 82, "Carol": 91, "David": 67,
    "Eve": 75, "Frank": 88, "Grace": 55, "Hana": 79
}
result = group_by_grade(students)
for grade, names in sorted(result.items()):
    print(f"{grade}: {names}")

Output will appear here...

💡 Hint: Start with an empty dict for each grade. Loop through students, determine their letter grade, then append to the right list. Use result.setdefault("A", []).append(name) to avoid KeyErrors.

🏆 Mini Project

Mini Project — Shopping Cart System

Build a complete shopping cart. Start with an inventory of 5 products (name, price, stock). Write these 4 functions:

add_to_cart(cart, product, quantity) — checks stock, adds to cart dict
remove_from_cart(cart, product) — removes entirely from cart
calculate_total(cart, inventory) — returns total price
print_receipt(cart, inventory) — prints a formatted receipt

Then simulate: add 3 items (one twice), remove 1, print the receipt.

inventory = {
    "apple":  {"price": 1.20, "stock": 50},
    "bread":  {"price": 2.50, "stock": 20},
    "milk":   {"price": 3.00, "stock": 15},
    "cheese": {"price": 4.75, "stock": 10},
    "pasta":  {"price": 1.80, "stock": 30},
}

cart = {}  # {product_name: quantity}

# Your functions here


# Simulation:
add_to_cart(cart, "apple", 3)
add_to_cart(cart, "bread", 1)
add_to_cart(cart, "milk", 2)
remove_from_cart(cart, "bread")
print_receipt(cart, inventory)

Output will appear here...

💡 Hint: The cart dict stores {"apple": 3}. In add_to_cart, check if quantity <= inventory[product]["stock"]. The receipt should show each item, quantity, unit price, line total, and a grand total.

✅ Lab 5 Complete!

You’ve mastered list comprehensions, dict operations, sorting with key functions, and built a complete data-driven shopping system. These skills are the foundation of data analysis.

Continue to Lab 6: String Methods →

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