session-01-part-02.md

Session 1 | Part 2

In BDA, we will gradually build our own small libraries. First, let's recap the basics.

1. Goal

In this tutorial, you will practice core Python loop logic using:

• counters
• indexes
• for loops
• nested loops (matrix traversal)

2. Prerequisites

Before starting:

1. Open the session1 folder in Visual Studio Code.
2. Activate your virtual environment.
3. Open (or create) your solution files in:

session1/solutions/

3. Basics you should know

• counter: a variable that increases/decreases to track quantity.
• index: the position of an element in a list (starts at 0).
• pointer: in this class, we use this word like a position tracker (usually an index counter).
• range(len(data)): common pattern to iterate through list indexes.
• nested loop: a loop inside another loop (used for matrices).
• break: stops the current loop immediately.

4. Example 1: Count elements

Consider a list. Can you count all elements without using len()?

Create a file in your solutions/ folder with this code:

File: session1/solutions/exercise-01-02.py

data = [10, 20, 30, 40, 50]

count = 0
for item in data:
    count += 1

print(count)

Expected output:

5

Now wrap the same logic in a function:

File: session1/solutions/exercise-01-02.py

def my_len(data):
    count = 0
    for item in data:
        count += 1
    return count

Save this function in a different file in the same folder, for example exercise_01_02_lib.py.

Then import and use it from your main script:

File: session1/solutions/exercise-01-02.py

from exercise_01_02_lib import my_len

print(my_len([10, 20, 30]))

Expected output:

3

Note

What are the time and space complexities of my_len?

Show answer

Time: O(n)

Space: O(1)

If you do not get it, talk to Stelios.

5. Example 2: Sum elements

Let's sum all elements using a total variable.
File: session1/solutions/exercise-01-02.py. Fill in the missing code.

data = [10, 20, 30, 40, 50]

total = 0
...
print(total)

Expected output:

150

Solution

Show answer

count += 1 increments a counter, while total += item accumulates values.

data = [10, 20, 30, 40, 50]

total = 0
for item in data:
    total += item

print(total)

Good practice: wrap reusable logic into helper functions (for example exercise_01_02_lib.py) and import them into your main script.

Note

What are the time and space complexities of the script above?

Show answer

Time: O(n)

Space: O(1)

6. Example 3: Find position of a target value

Let's find the position of a target value.

File: session1/solutions/exercise-01-02.py. Fill up the missing code.

data = [10, 20, 30, 40, 50]

# We use `pointer` as an index counter (starting at 0).
pointer = 0
...

Expected output (0-based index, counting starts from 0):

2

Solution

Show answer

We use a position counter (pointer) and stop at the first match using break.

data = [10, 20, 30, 40, 50]

pointer = 0
for item in data:
    if item == 30:
        print(pointer)
        break
    pointer += 1

Another common way to work with positions is:

File: session1/solutions/exercise-01-02.py

data = [10, 20, 30, 40, 50]

for i in range(len(data)):
    print(i)

7. Example 4: Traverse a matrix with nested loops

Run this and explore the output.

File: session1/solutions/exercise-01-02.py

matrix = [
    [10, 20],
    [30, 40]
]

for row in matrix:
    print(row)
    for value in row:
        print(value)

Now track row and column indexes explicitly:

File: session1/solutions/exercise-01-02.py

matrix = [
    [10, 20],
    [30, 40]
]

row_index = 0
col_index = 0

for row in matrix:
    print("row:", row_index)
    for value in row:
        print("col:", col_index, "value:", value)
        col_index += 1
    # Reset col_index for each new row.
    col_index = 0
    row_index += 1

Expected output:

row: 0
col: 0 value: 10
col: 1 value: 20
row: 1
col: 0 value: 30
col: 1 value: 40

Note

Why do we set col_index = 0 after each row?

Show answer

• Because each new row starts from the first column again.
• If you do not reset it, column indexes continue from the previous row and become incorrect.

What are the time and space complexities of the script above?

Show answer

Time: O(r * c) where r is the number of rows and c is the number of columns.

Space: O(1)

8. Call Stelios for a quick challenge 🔥

Call Stelios for a quick challenge question before moving to the exercise.

9. Exercise

Add your answers to:

session1/solutions/

Tasks:

1. Write a function to count elements between 1 and 10 (inclusive) in data = [30, 6, 9, 12, 15, 8].
2. Write a function to sum all even numbers in the same list.
3. Write a function that returns the position of the first value equal to 12 in the same list. If the value is not found, return -1.
4. For the matrix below, print the position of 25 as coordinates [2, 2] in the matrix (row, column), using 1-based indexing.

File: session1/solutions/exercise-01-02.py

matrix = [
    [5, 10, 15],
    [20, 25, 30]
]

5. In one short comment, explain why resetting the column index is important in nested loops.
6. What are the time and space complexities of your script(s)?

10. Quiz

Complete the following quiz.

quizmd quizzes/python-loops-and-indexing-quiz.md

If you want to choose a theme:

quizmd --theme light quizzes/python-loops-and-indexing-quiz.md
quizmd --theme dark quizzes/python-loops-and-indexing-quiz.md

You are now ready to move to the next tutorial.