02 - Variables and Data Types

A simple picture

A variable is like a name sticker on a box. The sticker helps us find the value inside. The data type tells Python what kind of value it is, just as a label may say “books,” “toys,” or “water.”

Variables

A variable is a readable name attached to a value. Python creates or updates the name when you assign with =.

customer_name = "Meera"
items = 3
print(customer_name, items)

A variable does not permanently lock a type:

value = 10
value = "ten"

This flexibility is useful, but clear programs usually keep one meaning for a variable.

Common built-in types

int - whole numbers 

age = 28
temperature_change = -4

Use integers for counts, indexes, and whole-number measurements.

float - decimal numbers 

price = 149.50
average = 82.75

Floating-point arithmetic can contain tiny precision differences. For beginner calculations, it is enough to understand that floats represent approximate decimal values.

complex - real and imaginary parts 

signal = 3 + 4j
print(signal.real, signal.imag)

Complex numbers are used in scientific and engineering calculations; they are not needed for most business programs.

bool - true or false 

is_logged_in = True
has_paid = False

Booleans are often produced by comparisons and used in conditions.

str - text 

employee_code = "007"

The quotes make this text. Keeping a code as a string preserves leading zeroes.

None - absence of a value 

middle_name = None

None is not zero, an empty string, or False. It means that a value is missing or not available. Check it with is None.

Optional preview: types used in later courses

These additional types are useful for files, networks, and advanced APIs. You do not need them in the Basic projects:

raw_data = b"ABC"       # bytes: fixed binary data
editable_data = bytearray(b"ABC")  # bytearray: changeable binary data
unique_values = frozenset({1, 2, 3}) # frozenset: an unchangeable set

Use ordinary strings, lists, sets, and dictionaries for the Basic projects. Binary data and immutable sets are useful when working with files, networks, or advanced APIs.

Inspecting types 

print(28, type(28))
print(19.5, type(19.5))
print(True, type(True))
print("Python", type("Python"))
print(None, type(None))

type() is useful while learning and debugging. In larger programs, choose clear data models rather than repeatedly checking types.

Real-world example 

product_name = "Notebook"
product_code = "N-007"
unit_price = 45.50
quantity = 4
in_stock = True
supplier_note = None

Each type matches the meaning of the field. product_code is text even though it contains digits.

Optional preview: values that can and cannot change

Mutable and immutable values

Numbers, booleans, strings, and tuples cannot be changed in place. Lists and dictionaries can be changed; they are introduced later. This difference matters when multiple names refer to the same collection.

Important fact: quotation marks change meaning. 25 is an integer that can be used as a quantity; "25" is text made from the characters 2 and 5.

Bug Hunter

Bug 1 — missing quotation marks 

city = Chennai
print(city)

Bug 2 — a code is not a quantity 

student_code = 007
print(student_code)

Python 3 does not allow a decimal integer literal with a leading zero. A student code is an identifier, so store it as text.

Bug 3 — unclear meaning 

x = "Notebook"
y = 45.50

The code runs, but another learner cannot easily understand the names.

Show Bug Hunter fixes 
city = "Chennai"

student_code = "007"

product_name = "Notebook"
unit_price = 45.50
Optional deeper look: how does Python know a type?

Every Python value is an object that remembers its own type. A variable name does not have a permanently fixed type; the name refers to an object, and the object has the type. That is why type(value) can inspect the value at runtime.

Common mistakes

  • Treating a phone number as a number and losing leading zeroes.
  • Using 0 when “not provided” should be None.
  • Assuming a decimal is always exact.
  • Giving vague names such as x and data when the meaning is known.

Practice

Try these problems on this page. For every answer, write down why you chose the data type.

Problems

  1. Choose types for a name, age, salary, employee code, active status, and missing value.
  2. Print the type of an integer, decimal, boolean, string, and None.
  3. Store the length and width of a rectangle using numeric variables, then print both types.
  4. Store a phone number that begins with zero without losing that zero.
  5. Store whether an item is available using the boolean value True.
  6. Predict the type of six different values before using type() to check.
  7. Explain why a postal code and a quantity may look similar but need different types.
  8. Create variables for a product record and display all fields.
  9. Store a missing middle name with None, then print the value and its type.
  10. Design the data types for a student record and justify each choice.
Show hints
  1. Think about the operations each field needs.
  2. Use type(value).
  3. Whole measurements can use int; measurements with decimal parts can use float.
  4. Put the phone number inside quotes.
  5. Use a clear name such as is_available and store True.
  6. Quoted values are strings; comparisons produce booleans.
  7. A postal code is an identifier, not a quantity to calculate.
  8. Use clear names such as product_name and unit_price.
  9. Use middle_name = None, then print middle_name and type(middle_name).
  10. Make a small table with field, type, and reason.
Show solution ideas
  1. Use str, int, float, str, bool, and None respectively.
  2. Put each value into print(type(value)).
  3. Store values such as length = 10 and width = 4.5, then use type().
  4. phone_number = "0123456789".
  5. free_delivery = order_total >= free_delivery_limit.
  6. 42 is int, 4.2 is float, True is bool, text is str, and None is NoneType.
  7. A postal code must preserve formatting; a quantity is used in arithmetic.
  8. Store the fields in separate variables and use an f-string.
  9. if value is None: print("Missing").
  10. Choose types based on meaning and describe the reason in comments.

Homework

Design a data model for an online order using at least eight variables. Add a comment explaining the type chosen for each value.

Checkpoint

Choose suitable types for a person’s name, age, salary, employee code, account status, and missing middle name. Explain each choice.