1.3 Decision Making & Loops

Decision Making & Loops in Python

Programs become useful when they can make decisions and repeat operations automatically. Python provides conditional statements for decision making and loops for repetition.

These concepts are fundamental to Data Science and Automation. They are used to filter records, validate data, process files, repeat calculations, and control program execution.

1. What Is Decision Making?

Decision making allows a program to execute different instructions depending on whether a condition is True or False.

For example, a program may need to determine whether a student has passed, whether a value is positive, or whether a file exists.

Real-World Logic

If marks are 40 or more:
    Student passes
Otherwise:
    Student fails

Python expresses this logic using conditional statements.

2. The if Statement

The if statement executes a block of code only when its condition evaluates to True.

Syntax

if condition:
    statement

Example

age = 20

if age >= 18:
    print("Eligible")

Since age >= 18 is true, the message is displayed.

3. The if-else Statement

Use if-else when there are two possible execution paths.

Syntax

if condition:
    statement_if_true
else:
    statement_if_false

Example

marks = 72

if marks >= 40:
    print("Pass")
else:
    print("Fail")

Exactly one of the two blocks is executed.

4. The if-elif-else Statement

When more than two conditions need to be checked, Python provides elif, which means else if.

Example: Grade Classification

marks = 86

if marks >= 90:
    grade = "A+"
elif marks >= 80:
    grade = "A"
elif marks >= 70:
    grade = "B"
elif marks >= 60:
    grade = "C"
else:
    grade = "D"

print(grade)

Python evaluates the conditions from top to bottom. Once a condition is true, its block executes and the remaining elif and else blocks are skipped.

5. Multiple Conditions

A conditional structure can contain multiple elif branches.

temperature = 32

if temperature < 0:
    print("Freezing")
elif temperature < 15:
    print("Cold")
elif temperature < 30:
    print("Moderate")
else:
    print("Hot")

6. Comparison Operators

Conditions commonly use comparison operators. A comparison produces a Boolean result: True or False.

Example

score = 75

print(score >= 40)
print(score == 100)

7. Logical Operators

Logical operators combine multiple conditions.

Using and

age = 25
has_id = True

if age >= 18 and has_id:
    print("Access allowed")

Using or

day = "Saturday"

if day == "Saturday" or day == "Sunday":
    print("Weekend")

Using not

logged_in = False

if not logged_in:
    print("Please log in")

8. Nested if Statements

An if statement inside another if statement is called a nested conditional.

age = 22
has_id = True

if age >= 18:

    if has_id:
        print("Entry allowed")
    else:
        print("ID required")

else:
    print("Entry not allowed")

Nested conditions are useful when a second decision depends on the result of a previous decision.

9. Conditional Expression

Python provides a compact one-line conditional expression for simple choices.

age = 20

status = "Adult" if age >= 18 else "Minor"

print(status)

This is sometimes called a ternary conditional expression.

10. Truthy and Falsy Values

Python evaluates objects in Boolean contexts such as if conditions.

Some values are considered falsy, including False, None, numeric zero, and empty containers or strings.

name = ""

if name:
    print("Name entered")
else:
    print("Name is empty")

Since the empty string is falsy, the else block runs.

11. What Are Loops?

A loop repeatedly executes a block of code.

Loops are useful when the same operation must be performed for multiple values, records, files, or iterations.

Without a Loop

print(1)
print(2)
print(3)
print(4)
print(5)

With a Loop

for number in range(1, 6):
    print(number)

The second approach is shorter, scalable, and easier to maintain.

12. The for Loop

A for loop iterates over the items of an iterable, such as a string, list, tuple, set, dictionary, or range.

Syntax

for variable in iterable:
    statement

Example

for number in [10, 20, 30]:
    print(number)

Output:

10
20
30

13. Using range()

The range() function generates a sequence of integers commonly used with for loops.

range(stop)

for number in range(5):
    print(number)

Output:

0
1
2
3
4

The stop value is not included.

range(start, stop)

for number in range(1, 6):
    print(number)

Output:

1
2
3
4
5

range(start, stop, step)

for number in range(2, 11, 2):
    print(number)

Output:

2
4
6
8
10

14. Counting Backwards with range()

A negative step can be used to generate a decreasing sequence.

for number in range(5, 0, -1):
    print(number)

Output:

5
4
3
2
1

15. Iterating Through a String

Strings are iterable, so a for loop can process one character at a time.

word = "Python"

for character in word:
    print(character)

Output:

P
y
t
h
o
n

16. Iterating Through a List

scores = [78, 91, 84, 67]

for score in scores:
    print(score)

This pattern is extremely common when processing datasets.

Data Science Example

sales = [1200, 1500, 1750, 900]

total = 0

for amount in sales:
    total += amount

print(f"Total sales: {total}")

Output:

Total sales: 5350

17. The while Loop

A while loop repeatedly executes a block as long as its condition remains true.

Syntax

while condition:
    statement

Example

count = 1

while count <= 5:
    print(count)
    count += 1

Output:

1
2
3
4
5

18. for Loop vs while Loop

19. Infinite while Loops

A while loop can continue forever if its condition never becomes false.

For example, this code creates an infinite loop:

count = 1

while count <= 5:
    print(count)

The value of count never changes, so the condition remains true.

Correct Version

count = 1

while count <= 5:
    print(count)
    count += 1

20. The break Statement

break immediately terminates the nearest enclosing loop.

for number in range(1, 11):

    if number == 6:
        break

    print(number)

Output:

1
2
3
4
5

Practical Example

values = [10, 25, 30, -1, 45, 50]

for value in values:

    if value == -1:
        break

    print(value)

The loop stops when the sentinel value -1 is found.

21. The continue Statement

continue skips the remaining statements in the current iteration and proceeds to the next iteration.

for number in range(1, 6):

    if number == 3:
        continue

    print(number)

Output:

1
2
4
5

Data Cleaning Example

values = [10, None, 25, None, 40]

for value in values:

    if value is None:
        continue

    print(value)

Missing values are skipped in this simple example.

22. The pass Statement

pass performs no operation. It acts as a placeholder where Python syntax requires a statement.

for number in range(5):

    if number == 3:
        pass

    print(number)

Unlike continue, pass does not skip the rest of the loop iteration.

23. Nested Loops

A loop placed inside another loop is called a nested loop.

for row in range(1, 4):

    for column in range(1, 4):

        print(row, column)

The inner loop runs completely for every iteration of the outer loop.

Multiplication Table Example

for number in range(1, 6):

    for multiplier in range(1, 6):

        print(number * multiplier, end=" ")

    print()

Nested loops are useful for matrix processing, tabular data, combinations, and many algorithmic tasks.

24. else with Loops

Python allows an else block to be associated with a loop. The loop's else block executes when the loop finishes normally rather than through break.

Example

for number in range(1, 4):

    print(number)

else:

    print("Loop completed")

Output:

1
2
3
Loop completed

When break Is Used

for number in range(1, 6):

    if number == 3:
        break

    print(number)

else:

    print("Loop completed")

Here, the loop's else block does not execute because the loop terminated using break.

25. Getting Index and Value with enumerate()

The built-in enumerate() function is useful when a loop needs both the position and the value of each item.

subjects = ["Python", "Statistics", "Data Science"]

for index, subject in enumerate(subjects):
    print(index, subject)

Output:

0 Python
1 Statistics
2 Data Science

Start Index from 1

for number, subject in enumerate(subjects, start=1):
    print(number, subject)

26. Iterating Over Multiple Sequences with zip()

zip() allows corresponding items from multiple iterables to be processed together.

names = ["Alex", "Jordan", "Taylor"]
scores = [85, 92, 78]

for name, score in zip(names, scores):
    print(f"{name}: {score}")

Output:

Alex: 85
Jordan: 92
Taylor: 78

This pattern is particularly useful when processing related sequences.

27. Loop Control Summary

28. Data Science Example — Classifying Scores

Conditions and loops can be combined to classify a collection of scores.

scores = [92, 76, 48, 35, 81, 67]

for score in scores:

    if score >= 90:
        grade = "A+"

    elif score >= 80:
        grade = "A"

    elif score >= 60:
        grade = "B"

    elif score >= 40:
        grade = "C"

    else:
        grade = "F"

    print(f"{score}: {grade}")

This demonstrates how iteration and conditional logic can work together to process multiple records.

29. Data Filtering with Conditions

A common Data Science operation is selecting values that satisfy a condition.

sales = [1200, 800, 2500, 950, 3100]

for amount in sales:

    if amount >= 2000:
        print(amount)

Only sales values meeting the threshold are displayed.

30. Automation Example — Processing Files

Loops are frequently used in automation to process multiple items.

files = [
    "report.csv",
    "sales.csv",
    "students.csv"
]

for filename in files:

    print(f"Processing {filename}")

Later, this pattern can be combined with Python's pathlib, os, and other libraries to perform actual file operations.

31. Searching with a Loop

A loop can search through values and stop when the desired item is found.

names = ["Alex", "Jordan", "Taylor", "Morgan"]

target = "Taylor"

for name in names:

    if name == target:
        print("Found:", name)
        break

The break statement prevents unnecessary iterations after the target is found.

32. Practical Program — Number Analyzer

The following program accepts several numbers and determines whether each number is positive, negative, or zero.

numbers = [12, -5, 0, 27, -9, 18]

for number in numbers:

    if number > 0:
        print(f"{number}: Positive")

    elif number < 0:
        print(f"{number}: Negative")

    else:
        print(f"{number}: Zero")

This combines:

• Lists
• for loops
• if-elif-else
• Comparison operators
• f-string formatting

33. Common Mistakes in Conditions and Loops

34. Python Interview Questions

35. Examination Questions

Multiple Choice Questions

for i in range(3):
    print(i)

Short Answer Questions

1. Explain the purpose of the if-elif-else structure.
2. Differentiate between for and while loops.
3. Explain break, continue, and pass.
4. Explain the three forms of range() with examples.
5. What is a nested loop? Give one practical application.

36. Practical Challenge

37. Decision Making & Loops Quick Reference