Chapter 3 — Control Flow: Selections and Loops

Programs make decisions and repeat work. This chapter covers conditional statements (if/elif/else), loops (while, for), and the random module — essential tools for transforming and simulating data.

Learning Objectives

Build Boolean expressions with and, or, not.
Write if, if-else, and multi-way if-elif-else statements.
Use conditional expressions for concise logic.
Generate random numbers with the random module.
Write while and for loops, including nested loops.
Control loops with break and continue.
Recognize and minimize floating-point accumulation errors.

Prerequisites / Imports

Uses the standard random module.

In [1]:

import random
random.seed(42)

1 Boolean Expressions and Logical Operators

Comparisons produce Booleans; combine them with and, or, not.

In [1]:

score = 78
print(60 <= score < 90)          # chained comparison
print(score >= 90 or score < 60)
print(not score == 100)

True
False
True

2 if, if-else, and if-elif-else

Indentation defines the block. Multi-way branching uses elif.

In [1]:

score = 78
if score >= 90:
    grade = 'A'
elif score >= 80:
    grade = 'B'
elif score >= 70:
    grade = 'C'
elif score >= 60:
    grade = 'D'
else:
    grade = 'F'
print('Grade:', grade)

Grade: C

3 Common Selection Errors

Using = (assignment) instead of == (comparison) is a classic bug. Mismatched indentation changes meaning. Always test boundary values.

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# Correct comparison
x = 5
if x == 5:
    print('x is 5')

x is 5

4 Conditional Expressions

A one-line x if condition else y returns a value.

In [1]:

age = 17
status = 'adult' if age >= 18 else 'minor'
print(status)

minor

5 Generating Random Numbers

The random module is indispensable for simulation and synthetic data.

In [1]:

print('random float [0,1):', random.random())
print('random int 1..6:', random.randint(1, 6))
print('choice:', random.choice(['heads','tails']))
print('sample of 3:', random.sample(range(1, 50), 3))

random float [0,1): 0.6394267984578837
random int 1..6: 1
choice: tails
sample of 3: [16, 15, 9]

6 while Loops

while repeats as long as a condition holds. Use it for sentinel-controlled or unknown-iteration tasks.

In [1]:

# Countdown with a while loop
n = 5
while n > 0:
    print(n)
    n -= 1
print('Liftoff!')

5
4
3
2
1
Liftoff!

7 for Loops

for iterates over a sequence or range. It is the workhorse for processing collections.

In [1]:

for i in range(5):
    print(i, 'squared =', i*i)

0 squared = 0
1 squared = 1
2 squared = 4
3 squared = 9
4 squared = 16

In [1]:

# Accumulating a sum
total = 0
for i in range(1, 101):
    total += i
print('Sum 1..100 =', total)

Sum 1..100 = 5050

8 Nested Loops

Loops inside loops handle grids and combinations. Keep nesting shallow for readability.

In [1]:

# Multiplication table (3x5)
for i in range(1, 4):
    row = []
    for j in range(1, 6):
        row.append(i * j)
    print(row)

[1, 2, 3, 4, 5]
[2, 4, 6, 8, 10]
[3, 6, 9, 12, 15]

9 break and continue

break exits the enclosing loop; continue skips to the next iteration.

In [1]:

# Find first number divisible by 7 between 1 and 100
for n in range(1, 101):
    if n % 7 == 0:
        print('First multiple of 7:', n)
        break

First multiple of 7: 7

In [1]:

# Skip odd numbers, print evens up to 10
for n in range(11):
    if n % 2 != 0:
        continue
    print(n)

10 Minimizing Numerical Errors

Repeatedly adding small floats accumulates error. Prefer larger increments or use math.fsum.

In [1]:

# Naive accumulation
s = 0.0
for _ in range(100000):
    s += 0.0001
print('naive sum:', s)

# Accurate accumulation
import math
s2 = math.fsum([0.0001] * 100000)
print('fsum:     ', s2)

naive sum: 9.999999999990033
fsum:      10.0

Case Study: Loan Approval Decision Logic

Apply rule-based approval to a small synthetic set of applicants and count outcomes.

In [1]:

random.seed(0)
applicants = []
for i in range(10):
    applicants.append({
        'id': i+1,
        'credit': random.randint(500, 850),
        'income': random.randint(20000, 120000),
        'dti': round(random.uniform(0.05, 0.45), 2),
    })

def decide(a):
    if a['credit'] >= 700 and a['dti'] < 0.36 and a['income'] >= 30000:
        return 'approve'
    elif a['credit'] >= 650 and a['dti'] < 0.43:
        return 'manual review'
    else:
        return 'deny'

results = {}
for a in applicants:
    decision = decide(a)
    results[decision] = results.get(decision, 0) + 1
    print(f"Applicant {a['id']:>2}: credit={a['credit']} income=${a['income']} dti={a['dti']} -> {decision}")

print('\nSummary:', results)

Applicant  1: credit=697 income=$119346 dti=0.41 -> manual review
Applicant  2: credit=520 income=$53936 dti=0.44 -> deny
Applicant  3: credit=748 income=$73075 dti=0.42 -> manual review
Applicant  4: credit=655 income=$82468 dti=0.19 -> manual review
Applicant  5: credit=611 income=$86150 dti=0.11 -> deny
Applicant  6: credit=571 income=$119064 dti=0.09 -> deny
Applicant  7: credit=628 income=$89804 dti=0.44 -> deny
Applicant  8: credit=808 income=$39262 dti=0.17 -> approve
Applicant  9: credit=537 income=$109651 dti=0.18 -> deny
Applicant 10: credit=786 income=$33199 dti=0.19 -> approve

Summary: {'manual review': 3, 'deny': 5, 'approve': 2}

Exercises

Classify a BMI value as underweight, normal, overweight, or obese using if-elif-else.
Simulate rolling two dice 1000 times and count how many doubles occur.
Determine whether a year is a leap year (divisible by 4, not 100 unless also 400).
Print all prime numbers between 2 and 50 using nested loops and break.
Use a while loop to sum integers until the running total exceeds 100.
Generate 20 random salaries and count how many exceed $60,000.
Rewrite a simple if-else as a conditional expression.
Show the difference between naive float summation and math.fsum for 0.1 added 1,000,000 times.
Write a number-guessing loop with a fixed target (no input()); print each guess until correct.
Use nested loops to print a 4x4 grid of random 0/1 values.

Python Data Science: From Foundations to Applications — Chapter 3