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Basic Data Types and Structures in Python

In programming, data types tell Python what kind of information is stored in a variable. Just like filling out a form — your name (text), age (a number), whether you're a student (yes/no) — Python needs to know the type of data it's dealing with.

Character

String

Integer

Float

Double

Boolean

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Basic Data Types — String (str)

String (str)

→ Used for text

A sequence of characters enclosed in quotes (" " or ' ').

• Used in messages, user input, and filenames

• Multiline: use triple quotes (""" or ''')

• Concatenate with the + operator

Examples:

"Hello, world!"

'Python is fun!'

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Basic Data Types — Integer (int)

Integer (int)

→ Whole numbers

A whole number — no decimal points.

• Used for counting, indexing, and math

• Large integers can use underscores for readability

Examples:

42, -7, 1000

1_000_000 (same as 1000000)

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Quick Check: Which can be initialized as an int?

6.09

4.0

3E10

10^5

1.0009

5*4.0

19865339

Think about what makes a number an integer — discuss with your partner!

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Basic Data Types — Float & Double

Float

→ 32-bit decimal (≈7 decimal places)

A number with decimal points.

Used in scientific calculations, percentages, and measurements.

Examples: 3.14, -0.5, 2.0

⚠ Important: Python uses the keyword float but internally saves with double precision!

Double

→ 64-bit decimal (≈15 decimal places)

More precision than a float.

Wider usage due to higher accuracy, but takes more memory.

Examples: 3.14, -0.5, 2.0

In Python, float and double are the same — Python defaults to double precision.

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Double vs. Float — Discussion

Which has higher precision?

Which takes up more memory?

Does Python have doubles and floats? Explain.

Does Java have doubles and floats? Explain.

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Basic Data Types — Character (char)

Character (char)

→ A single character

Holds exactly one character.

Strings are essentially a series of characters.

⚠ In Java/C++, characters use single quotes.

In Python, a single-char string serves the same purpose.

Examples: "c", "$", "@"

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Basic Data Structures — Lists

List → A collection of items that can change�

• Holds any data type, including strings�

• Each item has an index starting at 0�

• You can add, remove, and modify elements�

• Use .index() to find the position of a value

sports_cars = ["Ferrari", "Lamborghini", "Koenigsegg", "Pagani", "Bugatti"]�lambo_index = sports_cars.index("Lamborghini") # → 1

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Basic Data Structures — Dictionaries

Dictionary → A collection of key-value pairs

• Stores data as key: value pairs — keys must be unique�

• Great alternative to lists when you need labelled lookup�

• Lookup is O(1) vs O(n) for lists — much faster at scale

player = {"name": "Alex", "level": 10, "active": True}�player["level"] # → 10�player["score"] = 250 # add a new key

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Takeaways: Lists vs. Dictionaries

Feature	List	Dictionary
Key-based lookup	✗ (index only)	✓ (unique keys)
Lookup time	O(n)	O(1)
Mutable	✓	✓
Maintains insertion order	✓ (Python 3.7+)	✓ (Python 3.7+)

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Time Complexity — Big O Notation

Big O notation describes how an algorithm's runtime grows as input size increases. It tracks two key variables: memory and speed.

O(1)

Constant Time

Runtime does not change with input size.

Example: Accessing arr[0] or dict[key]

O(log n)

Logarithmic Time

Runtime increases slowly as input grows.

Example: Binary search

O(n)

Linear Time

Runtime grows proportionally to input size.

Example: Looping through an array

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Basic Data Types — Boolean (bool)

Boolean (bool)

→ True or False

A statement that returns either True or False.

Stored in binary: 0 = False, 1 = True.

Used when:

• Code execution depends on a condition

• You need if/else decision-making

• Validating user input

Examples: True, False

if is_logged_in: ...

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Example Code — All Data Types

This code implements all the data types covered today. What do you think it outputs?

name = "Alice"�age = 17�gpa = 3.85�is_student = True�subjects = ["Math", "CS", "Physics"]�info = {"school": "BinaryTree", "grade": 11}��print(f"Name: {name}, Age: {age}, GPA: {gpa}")

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Practice Question

Which data type is most appropriate for tracking whether a user is currently logged in, and why?

String

Integer

Boolean

Object

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Practice Question

In an online store class, which variable would most likely be a float?

stock_quantity

product_name

product_price

is_discounted

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Practice Question

Which variable type would be least appropriate for storing a list of newsletter subscribers?

Set

List

Tuple

Dictionary

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Functions

Encapsulating reusable logic in Python

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Practice Question

Which statement is true about variable types in the provided code?

final_price is a String because it is formatted for printing.

item_discount should be an Integer — discounts are whole numbers.

subtotal is a Float because it represents total price before discount.

item_name is a Float because it represents the name of an item.

Instructor-led — walk through the code together before revealing the answer.

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Practice Question

Which of the following are correct statements about variable types and functions in Python? (Select all that apply)

A function can return any type, including complex structures like lists and dicts.

A Boolean can only store True or False and is used in conditional expressions.

str is best suited for representing numerical values in math calculations.

A function can modify an argument if it is passed by reference.

int can store floats — it rounds to the nearest integer.

list is mutable — its elements can be changed after creation.

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Week 1 Wrap-Up

Last Thoughts

Review the practice questions in these slides.

Reach out if you have any further questions.

Look out for mid-week practice resources on more complex applications of today's topics.

Thank you!