Python Data Types — Complete Beginner-to-Interview Guide

Introduction

Python is a dynamically typed language, meaning:

You don’t need to declare data types explicitly
The type is decided at runtime

Example:


x = 10      # int
x = "Hi"    # str

Python provides built-in data types to store and manipulate different kinds of data efficiently.

Categories of Python Data Types

Python data types are commonly grouped into:

Numeric Types
Text Type
Sequence Types
Set Types
Mapping Type
Boolean Type
None Type

1️⃣ Numeric Data Types

a) `int` (Integer)

Stores whole numbers (positive, negative, zero).


age = 30
count = -5

Retrieve / Use


print(age)
print(age + 5)

b) `float`

Stores decimal numbers.


price = 99.99
temperature = -10.5


print(price)
print(price * 2)

c) `complex`

Stores complex numbers.


z = 3 + 4j
print(z.real)
print(z.imag)

2️⃣ Text Data Type — `str`

Stores text (immutable).


name = "Vinod"
message = 'Hello Python'

Access characters


print(name[0])     # V
print(name[-1])    # d

String operations


print(name.upper())
print(name.lower())
print(len(name))

3️⃣ Sequence Data Types

a) `list` — Ordered & Mutable

Used when:

Data can change
Order matters


fruits = ["apple", "banana", "orange"]

Access


print(fruits[0])

Add


fruits.append("mango")

Update


fruits[1] = "grape"

Remove


fruits.remove("apple")

b) `tuple` — Ordered & Immutable

Used when:

Data should not change


coordinates = (10, 20)


print(coordinates[0])

⚠️ Cannot modify:


# coordinates[0] = 50  ❌ error

c) `range`

Used for sequences of numbers.


nums = range(1, 6)


for i in nums:
    print(i)

4️⃣ Set Data Types

a) `set` — Unordered & Unique

Used when:

You want unique values
Order doesn’t matter


ids = {1, 2, 3, 3, 4}
print(ids)   # duplicates removed

Add / Remove


ids.add(5)
ids.remove(2)

b) `frozenset` — Immutable Set


fs = frozenset([1, 2, 3])

Cannot modify:


# fs.add(4) ❌

5️⃣ Mapping Data Type — `dict`

Stores key–value pairs.


user = {
    "name": "Vinod",
    "age": 35,
    "city": "Cupertino"
}

Access


print(user["name"])
print(user.get("age"))

Add / Update


user["country"] = "USA"
user["age"] = 36

Remove


del user["city"]

Iterate


for key, value in user.items():
    print(key, value)

6️⃣ Boolean Data Type — `bool`

Stores True or False.


is_active = True
is_admin = False

Used in conditions:


if is_active:
    print("User is active")

7️⃣ None Data Type — `None`

Represents absence of value.


result = None


if result is None:
    print("No result found")

8️⃣ Checking Data Types

Use type():


x = 10
print(type(x))

Use isinstance() (recommended):


isinstance(x, int)

9️⃣ Mutable vs Immutable (Very Important)

Type	Mutable
int, float, str	❌
list, dict, set	✅
tuple, frozenset	❌

Example:


a = 10
b = a
b = 20
# a is still 10


lst1 = [1, 2]
lst2 = lst1
lst2.append(3)
# lst1 is also changed

🔟 Common Interview Examples

Store user info


user = {"name": "Vinod", "age": 35}

Store multiple users


users = [
    {"name": "A", "age": 30},
    {"name": "B", "age": 25}
]

Unique values


unique_ids = set([1, 2, 2, 3])

1️⃣1️⃣ Summary Table

Data Type	Use Case
int	Whole numbers
float	Decimal values
str	Text
list	Ordered, changeable data
tuple	Fixed data
set	Unique values
dict	Key–value data
bool	Conditions
None	No value

1️⃣2️⃣ Interview One-Line Summary ⭐

Python data types define how data is stored and manipulated, ranging from numeric and text types to collections like lists, sets, and dictionaries, with mutable and immutable behaviors.