Module 2 of 6 · 30 minutes

Data structures, logic and functions

Real data comes in collections. This module gives you the tools to store, loop over and make decisions about it.

Learning objectives

Create, index and slice lists
Use dictionaries — the same shape as JSON
Write if/elif/else conditions
Loop with for, enumerate and list comprehensions
Define and call functions

2.1 Lists

reviews = ["Love it", "Arrived damaged", "Great value", "Too small"]
print(reviews[0])        # first item: "Love it"
print(reviews[-1])       # last item: "Too small"
print(len(reviews))      # 4
reviews.append("Would buy again")
print(reviews[1:3])      # slice: ["Arrived damaged", "Great value"]

List positions count from 0 at the front and from −1 at the back. Slices take a range.

2.2 Dictionaries

A dictionary maps keys to values — the same shape as JSON, which is how AI APIs send and receive data.

order = {"id": "GFY-10422", "item": "Bamboo board", "qty": 2, "price": 24.99}
print(order["item"])                 # "Bamboo board"
order["status"] = "dispatched"       # add a key
total = order["qty"] * order["price"]
print(order.get("discount", 0))      # safe lookup with a default: 0

A dictionary maps keys to values — exactly the shape of the JSON that AI APIs send and receive.

2.3 Conditions

rating = 2
if rating >= 4:
    sentiment = "positive"
elif rating == 3:
    sentiment = "neutral"
else:
    sentiment = "negative"
print(sentiment)

Indentation (four spaces) matters in Python: it shows which lines belong to the if.

2.4 Loops

for review in reviews:
    print(review.upper())

# loop with a counter
for i, review in enumerate(reviews, start=1):
    print(i, review)

# list comprehension: build a new list in one line
lengths = [len(r) for r in reviews]
short = [r for r in reviews if len(r) < 12]

2.5 Functions

Functions package code you'll reuse. You'll write one later to call an AI model.

def classify_rating(rating):
    # Return a sentiment label for a 1-5 star rating.
    if rating >= 4:
        return "positive"
    if rating == 3:
        return "neutral"
    return "negative"

ratings = [5, 2, 3, 4, 1]
labels = [classify_rating(r) for r in ratings]
print(labels)    # ['positive', 'negative', 'neutral', 'positive', 'negative']

A function takes inputs, runs its logic, and returns a result you can reuse anywhere.

Exercise: count the complaints

Given a list of review dictionaries like {"text": "Arrived damaged", "stars": 1}, write a function that returns how many reviews have 2 stars or fewer, and a list of their texts.

Show a solution

reviews = [
    {"text": "Love it", "stars": 5},
    {"text": "Arrived damaged", "stars": 1},
    {"text": "Too small", "stars": 2},
]

def complaints(reviews):
    bad = [r["text"] for r in reviews if r["stars"] <= 2]
    return len(bad), bad

print(complaints(reviews))   # (2, ['Arrived damaged', 'Too small'])

Key takeaways

Lists hold ordered items; index from 0, and -1 is the last.
Dictionaries map keys to values, like JSON.
Indentation defines code blocks.
List comprehensions build lists concisely.
Functions package reusable logic.