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Python Data Types

Python ke sabhi built-in data types — int, float, str, bool, list, tuple, set, dict, None — ko deeply samjhein examples, diagrams aur comparisons ke saath.

Hindi: Data types matlab data ke prakar — jaise ek dukaan mein alag alag cheezein hoti hain (kapde, khaana, electronics), waise hi computer mein alag alag types ka data hota hai. Python mein har value ka ek type hota hai.

2. Numeric Types

Integer (`int`)

Hindi: Integer matlab poore number — bina decimal ke. Python mein integers ki size unlimited hai!

python example

# Integer examples
age = 25
population = 1_380_004_385    # India's population (underscores for readability)
negative = -42
big_number = 10 ** 100        # googol!

print(type(age))
print(type(big_number))

# Integer in different bases
decimal = 255
binary = 0b11111111           # binary (starts with 0b)
octal = 0o377                 # octal (starts with 0o)
hexadecimal = 0xFF            # hex (starts with 0x)

print(f"Decimal: {decimal}")
print(f"Binary:  {binary}")
print(f"Octal:   {octal}")
print(f"Hex:     {hexadecimal}")
print(f"All equal: {decimal == binary == octal == hexadecimal}")

Output

<class 'int'>
<class 'int'>
Decimal: 255
Binary:  255
Octal:   255
Hex:     255
All equal: True

Float (`float`)

Hindi: Float matlab decimal numbers — jaise price, height, percentage mein hote hain.

python example

# Float examples
pi = 3.14159265358979
temperature = -15.5
scientific = 1.5e10     # 1.5 × 10^10 = 15000000000.0
small = 2.5e-3          # 0.0025

print(f"Pi: {pi}")
print(f"Scientific: {scientific}")
print(f"Small: {small}")
print(f"Type: {type(pi)}")

# Float precision issue!
result = 0.1 + 0.2
print(f"0.1 + 0.2 = {result}")           # Not exactly 0.3!
print(f"Rounded: {round(result, 1)}")     # Use round() for precision

Output

Pi: 3.14159265358979
Scientific: 15000000000.0
Small: 0.0025
Type: <class 'float'>
0.1 + 0.2 = 0.30000000000000004
Rounded: 0.3

Complex (`complex`)

python example

# Complex numbers — used in engineering, signal processing
z1 = 3 + 4j
z2 = complex(2, -3)     # another way

print(f"z1 = {z1}")
print(f"z2 = {z2}")
print(f"Real part: {z1.real}")
print(f"Imaginary part: {z1.imag}")
print(f"Magnitude: {abs(z1)}")          # √(3² + 4²) = 5.0
print(f"Sum: {z1 + z2}")

Output

z1 = (3+4j)
z2 = (2-3j)
Real part: 3.0
Imaginary part: 4.0
Magnitude: 5.0
Sum: (5+1j)

Boolean (`bool`)

Hindi: Boolean sirf do values rakhta hai: True ya False. Yeh int ka subclass hai — True = 1, False = 0.

Example

# Boolean values is_raining = True is_sunny = False print(type(is_raining)) # <class 'bool'> # Booleans are integers! print(True + True) # 2 print(True * 5) # 5 print(False + 1) # 1 # Truthy and Falsy values print(bool(0)) # False print(bool(1)) # True print(bool("")) # False (empty string) print(bool("Hello")) # True print(bool([])) # False (empty list) print(bool([1, 2])) # True print(bool(None)) # False

Output

<class 'bool'>
2
5
1
False
True
False
True
False
True
False

Falsy Values Table

Value	Type	bool()
`0`	int	`False`
`0.0`	float	`False`
`""`	str	`False`
`[]`	list	`False`
`()`	tuple	`False`
`{}`	dict	`False`
`set()`	set	`False`
`None`	NoneType	`False`
Everything else	any	`True`

3. String (`str`)

Hindi: String matlab text — characters ka sequence. Python mein strings immutable hain (change nahi ho sakti).

python example

# String creation
name = "Rahul Kumar"
city = 'Mumbai'
multiline = """This is
a multiline
string"""

print(name)
print(city)
print(multiline)
print(type(name))

# String properties
print(f"Length: {len(name)}")
print(f"Upper: {name.upper()}")
print(f"Starts with R: {name.startswith('R')}")

Output

Rahul Kumar
Mumbai
This is
a multiline
string
<class 'str'>
Length: 11
Upper: RAHUL KUMAR
Starts with R: True

4. List (`list`)

Hindi: List ek ordered collection hai jisme alag alag types ke items ho sakte hain, aur yeh mutable hai (change ho sakti hai). Yeh Python ka sabse commonly used data type hai.

Example

# List creation fruits = ["apple", "banana", "mango", "orange"] numbers = [1, 2, 3, 4, 5] mixed = [42, "hello", 3.14, True, None] # mixed types! nested = [[1, 2], [3, 4], [5, 6]] # nested list print(fruits) print(f"Type: {type(fruits)}") print(f"Length: {len(fruits)}") # Accessing elements print(f"First: {fruits[0]}") # indexing print(f"Last: {fruits[-1]}") # negative index print(f"Slice: {fruits[1:3]}") # slicing # Modifying list (mutable) fruits.append("grapes") # add to end fruits.insert(1, "cherry") # insert at position fruits.remove("banana") # remove by value popped = fruits.pop() # remove and return last print(fruits) print(f"Popped: {popped}")

Output

['apple', 'banana', 'mango', 'orange']
Type: <class 'list'>
Length: 4
First: apple
Last: orange
Slice: ['banana', 'mango']
['apple', 'cherry', 'mango', 'orange']
Popped: grapes

5. Tuple (`tuple`)

Hindi: Tuple list ki tarah hi hai lekin immutable hai — ek baar banao, change nahi hoga. Use it for data that shouldn't change (like coordinates, RGB colors, dates).

Example

# Tuple creation coordinates = (28.6139, 77.2090) # Delhi coordinates rgb_red = (255, 0, 0) days = ("Mon", "Tue", "Wed", "Thu", "Fri", "Sat", "Sun") single = (42,) # single-element tuple — comma required! empty = () print(coordinates) print(type(coordinates)) print(f"Length: {len(days)}") # Accessing elements print(f"Latitude: {coordinates[0]}") print(f"Monday: {days[0]}") print(f"Last day: {days[-1]}") # Tuple unpacking lat, lon = coordinates print(f"Lat: {lat}, Lon: {lon}") # Try to modify — will fail! # rgb_red[0] = 128 # ❌ TypeError: 'tuple' object does not support item assignment print("Tuples are immutable — cannot modify!")

Output

(28.6139, 77.209)
<class 'tuple'>
Length: 7
Latitude: 28.6139
Monday: Mon
Last day: Sun
Lat: 28.6139, Lon: 77.209
Tuples are immutable — cannot modify!

6. Dictionary (`dict`)

Hindi: Dictionary ek key-value store hai — jaise real dictionary mein word → meaning hoti hai. Python dict mein koi bhi key aur koi bhi value rakh sakte hain.

Example

# Dictionary creation student = { "name": "Priya Sharma", "roll_no": 2301, "grade": "10th", "marks": [85, 92, 78, 96, 88], "is_active": True } print(student) print(f"Type: {type(student)}") print(f"Name: {student['name']}") print(f"Marks: {student['marks']}") # Get with default phone = student.get("phone", "Not available") print(f"Phone: {phone}") # Add/update student["email"] = "priya@school.com" student["grade"] = "11th" # update existing # Delete del student["is_active"] # Iterate print("\nAll key-value pairs:") for key, value in student.items(): print(f" {key}: {value}")

Output

{'name': 'Priya Sharma', 'roll_no': 2301, 'grade': '10th', 'marks': [...], 'is_active': True}
Type: <class 'dict'>
Name: Priya Sharma
Marks: [85, 92, 78, 96, 88]
Phone: Not available

All key-value pairs:
  name: Priya Sharma
  roll_no: 2301
  grade: 11th
  marks: [85, 92, 78, 96, 88]
  email: priya@school.com

7. Set (`set`)

Hindi: Set ek unordered collection hai jisme duplicate values nahi hoti. Use it for unique items, membership testing, and set operations (union, intersection).

Example

# Set creation fruits = {"apple", "banana", "mango", "apple", "banana"} print(fruits) # duplicates removed! print(type(fruits)) # Creating from list (remove duplicates) numbers = [1, 2, 2, 3, 3, 3, 4, 4, 4, 4] unique = set(numbers) print(f"Original: {numbers}") print(f"Unique: {unique}") # Set operations a = {1, 2, 3, 4, 5} b = {4, 5, 6, 7, 8} print(f"Union (|): {a | b}") # all elements print(f"Intersection (&): {a & b}") # common elements print(f"Difference (a-b): {a - b}") # in a but not b print(f"Symmetric diff (^): {a ^ b}") # not in both # Membership test — O(1)! Very fast print(f"3 in a: {3 in a}") print(f"9 in a: {9 in a}")

Output

{'apple', 'banana', 'mango'}
<class 'set'>
Original: [1, 2, 2, 3, 3, 3, 4, 4, 4, 4]
Unique: {1, 2, 3, 4}
Union (|): {1, 2, 3, 4, 5, 6, 7, 8}
Intersection (&): {4, 5}
Difference (a-b): {1, 2, 3}
Symmetric diff (^): {1, 2, 3, 6, 7, 8}
3 in a: True
9 in a: False

8. NoneType (`None`)

Hindi: None Python ka null value hai — matlab "kuch nahi" ya "value nahi hai abhi." Yeh ek special singleton object hai.

python example

# None usage
result = None
print(result)
print(type(result))

# Common uses of None
def find_user(user_id):
    # Simulate database search
    if user_id == 1:
        return {"name": "Rahul", "id": 1}
    return None    # not found

user = find_user(1)
print(f"Found: {user}")

user = find_user(99)
if user is None:    # always use 'is None', not '== None'
    print("User not found!")

# None as default parameter
def greet(name=None):
    if name is None:
        name = "Guest"
    return f"Hello, {name}!"

print(greet())
print(greet("Anjali"))

Output

None
<class 'NoneType'>
Found: {'name': 'Rahul', 'id': 1}
User not found!
Hello, Guest!
Hello, Anjali!

9. Mutable vs Immutable Types

IMMUTABLE (cannot change after creation)

┌──────────────────────────────────────────┐

│ int, float, complex, bool │

│ str │

│ tuple │

│ frozenset │

│ bytes │

└──────────────────────────────────────────┘

MUTABLE (can change after creation)

┌──────────────────────────────────────────┐

│ list │

│ dict │

│ set │

│ bytearray │

└──────────────────────────────────────────┘

Example

# Immutable — modifying creates a new object s = "Hello" original_id = id(s) s += " World" print(f"Same object? {id(s) == original_id}") # False — new object! # Mutable — modifying in place lst = [1, 2, 3] original_id = id(lst) lst.append(4) print(f"Same object? {id(lst) == original_id}") # True — same object!

Output

Same object? False
Same object? True

10. Comprehensive Data Type Comparison

Type	Ordered	Mutable	Duplicates	Syntax	Access
`int`	N/A	❌	N/A	`42`	N/A
`float`	N/A	❌	N/A	`3.14`	N/A
`str`	✅	❌	✅	`"hello"`	`s[0]`
`list`	✅	✅	✅	`[1,2,3]`	`l[0]`
`tuple`	✅	❌	✅	`(1,2,3)`	`t[0]`
`dict`	✅(3.7+)	✅	Keys: ❌	`{k:v}`	`d[k]`
`set`	❌	✅	❌	`{1,2,3}`	N/A
`frozenset`	❌	❌	❌	`frozenset()`	N/A
`bool`	N/A	❌	N/A	`True`	N/A
`NoneType`	N/A	❌	N/A	`None`	N/A

11. Type Checking

Example

data = [42, "hello", 3.14, True, [1, 2], {"a": 1}, (1, 2), {3, 4}, None] for item in data: print(f"{str(item):<20} → type: {type(item).__name__:<12} | isinstance int: {isinstance(item, int)}")

Output

42                   → type: int          | isinstance int: True
hello                → type: str          | isinstance int: False
3.14                 → type: float        | isinstance int: False
True                 → type: bool         | isinstance int: True
[1, 2]               → type: list         | isinstance int: False
{'a': 1}             → type: dict         | isinstance int: False
(1, 2)               → type: tuple        | isinstance int: False
{3, 4}               → type: set          | isinstance int: False
None                 → type: NoneType     | isinstance int: False

Hindi: bool ka isinstance(True, int) True aata hai kyunki bool aslmein int ka subclass hai Python mein!

Real-World Example: E-commerce Product

Example

# Representing a product with appropriate data types product = { "id": 1001, # int "name": "WoHo Wireless Headphones", # str "price": 2499.99, # float "in_stock": True, # bool "quantity": 50, # int "tags": {"electronics", "audio", "wireless"}, # set (unique tags) "colors": ["Black", "White", "Blue"], # list (ordered, duplicates ok) "specs": { # dict (key-value) "brand": "WoHo", "model": "WH-1000", "battery_hours": 30, "weight_grams": 254 }, "dimensions": (18.5, 17.0, 8.5), # tuple (fixed, immutable) "discount": None # NoneType (no discount) } # Display product info print(f"Product: {product['name']}") print(f"Price: ₹{product['price']}") print(f"In Stock: {'Yes' if product['in_stock'] else 'No'}") print(f"Colors: {', '.join(product['colors'])}") print(f"Tags: {product['tags']}") print(f"Discount: {'None available' if product['discount'] is None else product['discount']}") print(f"\nSpecifications:") for spec, value in product['specs'].items(): print(f" {spec}: {value}")

Output

Product: WoHo Wireless Headphones
Price: ₹2499.99
In Stock: Yes
Colors: Black, White, Blue
Tags: {'electronics', 'audio', 'wireless'}
Discount: None available

Specifications:
  brand: WoHo
  model: WH-1000
  battery_hours: 30
  weight_grams: 254

Practice Exercises

Exercise 1 — Type Identification

What is the data type of each? Write your answers then verify with type():

Example

x1 = 42 x2 = 42.0 x3 = "42" x4 = True x5 = [42] x6 = (42,) x7 = {42} x8 = {"num": 42} x9 = None

Exercise 2 — Choose the Right Type

For each, which data type is best and why?

Days of the week (fixed, ordered)
A shopping cart (ordered, modifiable)
Username → email mapping
Unique visitor IDs
Whether user is logged in

Exercise 3 — Set Operations

Given two lists of students:

Section A: ["Rahul", "Priya", "Amit", "Neha", "Karan"]
Section B: ["Priya", "Vikram", "Neha", "Sunita", "Karan"]

Find: students in both sections, only in A, only in B, in either section.

Interview Questions

Q1. What is the difference between a list and a tuple in Python? > Both are ordered sequences, but lists are mutable (can be modified) while tuples are immutable. Lists use [], tuples use (). Use tuples for fixed data (coordinates, RGB values), lists for collections that change. Tuples are slightly faster and can be used as dictionary keys.

Q2. When would you use a set instead of a list? > When you need unique elements, fast membership testing (O(1) vs O(n)), or set operations (union, intersection, difference). Sets don't maintain order and don't support indexing.

Q3. What is the difference between == and is for None checking? > Always use is None (not == None). is checks identity (same object in memory). Since None is a singleton, x is None is the correct and faster check. == None can be overridden by __eq__ in custom classes.

Q4. Are booleans a subtype of integers in Python? > Yes! bool is a subclass of int. True == 1 and False == 0. You can do arithmetic with booleans: True + True == 2. isinstance(True, int) returns True.

Q5. What is the difference between a dict and a set (both use {})? How does Python distinguish them? > An empty {} creates a dict, not a set! Use set() for an empty set. For non-empty: {1, 2, 3} is a set (values only), {"a": 1} is a dict (key-value pairs). Python identifies them by the presence of colons (:) in key-value pairs.

⚠️ Common Mistakes

1. Empty `{}` ko set samajhna ❌

python example

# ❌ Galat — yeh dict hai, set nahi!
empty = {}
print(type(empty))   # <class 'dict'>

# ✅ Sahi — empty set banane ke liye set() use karo
empty_set = set()
print(type(empty_set))   # <class 'set'>

2. Single-element tuple mein comma bhoolna ❌

python example

# ❌ Galat — yeh int hai, tuple nahi!
not_a_tuple = (42)
print(type(not_a_tuple))   # <class 'int'>

# ✅ Sahi — trailing comma zaroori hai!
actual_tuple = (42,)
print(type(actual_tuple))   # <class 'tuple'>

3. Float comparison `==` se karna ❌

python example

# ❌ Galat — floating point precision issue!
print(0.1 + 0.2 == 0.3)   # False 😱

# ✅ Sahi — round() ya math.isclose() use karo
import math
print(math.isclose(0.1 + 0.2, 0.3))   # True ✅

4. `== None` use karna instead of `is None` ❌

python example

# ❌ Galat — == override ho sakta hai custom classes mein
if x == None:
    pass

# ✅ Sahi — is None use karo (identity check)
if x is None:
    pass

5. Mutable default arguments use karna ❌

python example

# ❌ Galat — same list share hogi har function call mein!
def add_item(item, items=[]):
    items.append(item)
    return items

# ✅ Sahi — None use karo as default
def add_item(item, items=None):
    if items is None:
        items = []
    items.append(item)
    return items

6. String ko modify karne ki koshish karna ❌

Example

# ❌ Galat — strings immutable hain! name = "Rahul" # name[0] = "r" # TypeError! # ✅ Sahi — naya string banao name = "r" + name[1:] # "rahul"

7. List copy karte waqt reference copy karna ❌

Example

# ❌ Galat — dono same list ko point karenge! original = [1, 2, 3] copy = original copy.append(4) print(original) # [1, 2, 3, 4] 😱 original bhi change! # ✅ Sahi — shallow copy banao copy = original.copy() # ya original[:]

✅ Key Takeaways

🔢 Python mein har cheez ek object hai — integers, strings, functions sab objects hain with a type
📦 Numeric types: int (unlimited size), float (decimal), complex (engineering), bool (True/False — int ka subclass)
📝 Strings immutable hain — modify karne pe naya object banta hai, purana change nahi hota
📋 List vs Tuple: List mutable hai ([]), Tuple immutable hai (()). Fixed data ke liye tuple, changeable data ke liye list
🗂️ Dictionary key-value pairs store karta hai — Python 3.7+ mein insertion order maintain hota hai
🎯 Set mein duplicates nahi hote — fast membership testing O(1) aur mathematical set operations ke liye best
🚫 None ka matlab "no value" — always check with is None, never == None
🔒 Immutable types: int, float, str, tuple, frozenset, bytes — inhe dictionary keys ki tarah use kar sakte ho
🔓 Mutable types: list, dict, set, bytearray — in-place modify ho sakte hain, careful with references!
🧪 Type checking: type() exact type batata hai, isinstance() inheritance bhi check karta hai — prefer isinstance()

❓ FAQ

Q1. Python mein dynamically typed ka kya matlab hai? > Python mein aapko variable ka type declare nahi karna padta. x = 10 likhne pe Python khud samajh jata hai ki yeh int hai. Same variable ko baad mein x = "hello" bhi assign kar sakte ho — type runtime pe decide hota hai, compile time pe nahi.

Q2. type() aur isinstance() mein kya difference hai? > type(x) exact type batata hai. isinstance(x, int) check karta hai ki x us type ka hai YA uska subclass hai. Example: type(True) returns bool, lekin isinstance(True, int) returns True kyunki bool int ka subclass hai. Best practice: isinstance() use karo.

Q3. Mutable aur immutable mein practically kya farak padta hai? > Immutable objects ko dictionary keys ya set elements ki tarah use kar sakte ho (kyunki inki hash value change nahi hoti). Mutable objects ke saath reference sharing ka issue aata hai — agar ek variable se change karo toh dusre mein bhi reflect hota hai. Function arguments mein bhi mutable defaults se bugs aa sakte hain.

Q4. Kab list use karein aur kab tuple? > List use karo jab data change ho sakta hai — shopping cart items, user inputs, dynamic collections. Tuple use karo jab data fixed ho — coordinates (x, y), RGB colors (255, 0, 0), database records, function se multiple values return karna. Tuples thode faster bhi hote hain aur less memory lete hain.

Q5. Empty set kaise banayein jab {} dict banta hai? > set() constructor use karo. {} hamesha empty dict banata hai Python mein. Non-empty set ke liye {1, 2, 3} likh sakte ho, lekin empty ke liye sirf set() kaam karega. Similarly, frozenset() se empty frozenset banta hai.

Q6. Python mein integer ki maximum size kya hai? > Python 3 mein integers ki koi fixed size nahi hai — yeh arbitrary precision hain! Aap 10 ** 1000 bhi calculate kar sakte ho bina overflow ke. Yeh C/Java se different hai jahan int 32-bit ya 64-bit hota hai. Python internally memory dynamically allocate karta hai.

Q7. None aur 0 ya empty string "" mein kya farak hai? > None ka matlab hai "koi value hi nahi hai" — yeh absence of value represent karta hai. 0 ek valid integer value hai, "" ek valid (empty) string hai. Function jo kuch return nahi karta woh implicitly None return karta hai. Teeno falsy hain (bool() se False dete hain), lekin meaning alag hai.

Q8. Kya hum apne custom data types bana sakte hain? > Haan! Python mein classes use karke apne custom types bana sakte ho. class Student: likhke apna type define karo. Custom classes by default mutable hoti hain. @dataclass decorator use karke quickly structured data types bana sakte ho. Advanced: __hash__ aur __eq__ define karke apni class ko hashable (set/dict key usable) bana sakte ho.

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Python Notes

Python Data Types

Python ke sabhi built-in data types — int, float, str, bool, list, tuple, set, dict, None — ko deeply samjhein examples, diagrams aur comparisons ke saath.

Hindi: Data types matlab data ke prakar — jaise ek dukaan mein alag alag cheezein hoti hain (kapde, khaana, electronics), waise hi computer mein alag alag types ka data hota hai. Python mein har value ka ek type hota hai.

2. Numeric Types

Integer (`int`)

Hindi: Integer matlab poore number — bina decimal ke. Python mein integers ki size unlimited hai!

python example

# Integer examples
age = 25
population = 1_380_004_385    # India's population (underscores for readability)
negative = -42
big_number = 10 ** 100        # googol!

print(type(age))
print(type(big_number))

# Integer in different bases
decimal = 255
binary = 0b11111111           # binary (starts with 0b)
octal = 0o377                 # octal (starts with 0o)
hexadecimal = 0xFF            # hex (starts with 0x)

print(f"Decimal: {decimal}")
print(f"Binary:  {binary}")
print(f"Octal:   {octal}")
print(f"Hex:     {hexadecimal}")
print(f"All equal: {decimal == binary == octal == hexadecimal}")

Output

<class 'int'>
<class 'int'>
Decimal: 255
Binary:  255
Octal:   255
Hex:     255
All equal: True

Float (`float`)

Hindi: Float matlab decimal numbers — jaise price, height, percentage mein hote hain.

python example

# Float examples
pi = 3.14159265358979
temperature = -15.5
scientific = 1.5e10     # 1.5 × 10^10 = 15000000000.0
small = 2.5e-3          # 0.0025

print(f"Pi: {pi}")
print(f"Scientific: {scientific}")
print(f"Small: {small}")
print(f"Type: {type(pi)}")

# Float precision issue!
result = 0.1 + 0.2
print(f"0.1 + 0.2 = {result}")           # Not exactly 0.3!
print(f"Rounded: {round(result, 1)}")     # Use round() for precision

Output

Pi: 3.14159265358979
Scientific: 15000000000.0
Small: 0.0025
Type: <class 'float'>
0.1 + 0.2 = 0.30000000000000004
Rounded: 0.3

Complex (`complex`)

python example

# Complex numbers — used in engineering, signal processing
z1 = 3 + 4j
z2 = complex(2, -3)     # another way

print(f"z1 = {z1}")
print(f"z2 = {z2}")
print(f"Real part: {z1.real}")
print(f"Imaginary part: {z1.imag}")
print(f"Magnitude: {abs(z1)}")          # √(3² + 4²) = 5.0
print(f"Sum: {z1 + z2}")

Output

z1 = (3+4j)
z2 = (2-3j)
Real part: 3.0
Imaginary part: 4.0
Magnitude: 5.0
Sum: (5+1j)

Boolean (`bool`)

Hindi: Boolean sirf do values rakhta hai: True ya False. Yeh int ka subclass hai — True = 1, False = 0.

Example

Output

<class 'bool'>
2
5
1
False
True
False
True
False
True
False

Falsy Values Table

Value	Type	bool()
`0`	int	`False`
`0.0`	float	`False`
`""`	str	`False`
`[]`	list	`False`
`()`	tuple	`False`
`{}`	dict	`False`
`set()`	set	`False`
`None`	NoneType	`False`
Everything else	any	`True`

3. String (`str`)

Hindi: String matlab text — characters ka sequence. Python mein strings immutable hain (change nahi ho sakti).

python example

# String creation
name = "Rahul Kumar"
city = 'Mumbai'
multiline = """This is
a multiline
string"""

print(name)
print(city)
print(multiline)
print(type(name))

# String properties
print(f"Length: {len(name)}")
print(f"Upper: {name.upper()}")
print(f"Starts with R: {name.startswith('R')}")

Output

Rahul Kumar
Mumbai
This is
a multiline
string
<class 'str'>
Length: 11
Upper: RAHUL KUMAR
Starts with R: True

4. List (`list`)

Hindi: List ek ordered collection hai jisme alag alag types ke items ho sakte hain, aur yeh mutable hai (change ho sakti hai). Yeh Python ka sabse commonly used data type hai.

Example

Output

['apple', 'banana', 'mango', 'orange']
Type: <class 'list'>
Length: 4
First: apple
Last: orange
Slice: ['banana', 'mango']
['apple', 'cherry', 'mango', 'orange']
Popped: grapes

5. Tuple (`tuple`)

Hindi: Tuple list ki tarah hi hai lekin immutable hai — ek baar banao, change nahi hoga. Use it for data that shouldn't change (like coordinates, RGB colors, dates).

Example

Output

(28.6139, 77.209)
<class 'tuple'>
Length: 7
Latitude: 28.6139
Monday: Mon
Last day: Sun
Lat: 28.6139, Lon: 77.209
Tuples are immutable — cannot modify!

6. Dictionary (`dict`)

Hindi: Dictionary ek key-value store hai — jaise real dictionary mein word → meaning hoti hai. Python dict mein koi bhi key aur koi bhi value rakh sakte hain.

Example

Output

{'name': 'Priya Sharma', 'roll_no': 2301, 'grade': '10th', 'marks': [...], 'is_active': True}
Type: <class 'dict'>
Name: Priya Sharma
Marks: [85, 92, 78, 96, 88]
Phone: Not available

All key-value pairs:
  name: Priya Sharma
  roll_no: 2301
  grade: 11th
  marks: [85, 92, 78, 96, 88]
  email: priya@school.com

7. Set (`set`)

Hindi: Set ek unordered collection hai jisme duplicate values nahi hoti. Use it for unique items, membership testing, and set operations (union, intersection).

Example

Output

{'apple', 'banana', 'mango'}
<class 'set'>
Original: [1, 2, 2, 3, 3, 3, 4, 4, 4, 4]
Unique: {1, 2, 3, 4}
Union (|): {1, 2, 3, 4, 5, 6, 7, 8}
Intersection (&): {4, 5}
Difference (a-b): {1, 2, 3}
Symmetric diff (^): {1, 2, 3, 6, 7, 8}
3 in a: True
9 in a: False

8. NoneType (`None`)

Hindi: None Python ka null value hai — matlab "kuch nahi" ya "value nahi hai abhi." Yeh ek special singleton object hai.

python example

# None usage
result = None
print(result)
print(type(result))

# Common uses of None
def find_user(user_id):
    # Simulate database search
    if user_id == 1:
        return {"name": "Rahul", "id": 1}
    return None    # not found

user = find_user(1)
print(f"Found: {user}")

user = find_user(99)
if user is None:    # always use 'is None', not '== None'
    print("User not found!")

# None as default parameter
def greet(name=None):
    if name is None:
        name = "Guest"
    return f"Hello, {name}!"

print(greet())
print(greet("Anjali"))

Output

None
<class 'NoneType'>
Found: {'name': 'Rahul', 'id': 1}
User not found!
Hello, Guest!
Hello, Anjali!

9. Mutable vs Immutable Types

IMMUTABLE (cannot change after creation)

┌──────────────────────────────────────────┐

│ int, float, complex, bool │

│ str │

│ tuple │

│ frozenset │

│ bytes │

└──────────────────────────────────────────┘

MUTABLE (can change after creation)

┌──────────────────────────────────────────┐

│ list │

│ dict │

│ set │

│ bytearray │

└──────────────────────────────────────────┘

Example

Output

Same object? False
Same object? True

10. Comprehensive Data Type Comparison

Type	Ordered	Mutable	Duplicates	Syntax	Access
`int`	N/A	❌	N/A	`42`	N/A
`float`	N/A	❌	N/A	`3.14`	N/A
`str`	✅	❌	✅	`"hello"`	`s[0]`
`list`	✅	✅	✅	`[1,2,3]`	`l[0]`
`tuple`	✅	❌	✅	`(1,2,3)`	`t[0]`
`dict`	✅(3.7+)	✅	Keys: ❌	`{k:v}`	`d[k]`
`set`	❌	✅	❌	`{1,2,3}`	N/A
`frozenset`	❌	❌	❌	`frozenset()`	N/A
`bool`	N/A	❌	N/A	`True`	N/A
`NoneType`	N/A	❌	N/A	`None`	N/A

11. Type Checking

Example

data = [42, "hello", 3.14, True, [1, 2], {"a": 1}, (1, 2), {3, 4}, None] for item in data: print(f"{str(item):<20} → type: {type(item).__name__:<12} | isinstance int: {isinstance(item, int)}")

Output

42                   → type: int          | isinstance int: True
hello                → type: str          | isinstance int: False
3.14                 → type: float        | isinstance int: False
True                 → type: bool         | isinstance int: True
[1, 2]               → type: list         | isinstance int: False
{'a': 1}             → type: dict         | isinstance int: False
(1, 2)               → type: tuple        | isinstance int: False
{3, 4}               → type: set          | isinstance int: False
None                 → type: NoneType     | isinstance int: False

Hindi: bool ka isinstance(True, int) True aata hai kyunki bool aslmein int ka subclass hai Python mein!

Real-World Example: E-commerce Product

Example

Output

Product: WoHo Wireless Headphones
Price: ₹2499.99
In Stock: Yes
Colors: Black, White, Blue
Tags: {'electronics', 'audio', 'wireless'}
Discount: None available

Specifications:
  brand: WoHo
  model: WH-1000
  battery_hours: 30
  weight_grams: 254

Practice Exercises

Exercise 1 — Type Identification

What is the data type of each? Write your answers then verify with type():

Example

x1 = 42 x2 = 42.0 x3 = "42" x4 = True x5 = [42] x6 = (42,) x7 = {42} x8 = {"num": 42} x9 = None

Exercise 2 — Choose the Right Type

For each, which data type is best and why?

Days of the week (fixed, ordered)
A shopping cart (ordered, modifiable)
Username → email mapping
Unique visitor IDs
Whether user is logged in

Exercise 3 — Set Operations

Given two lists of students:

Section A: ["Rahul", "Priya", "Amit", "Neha", "Karan"]
Section B: ["Priya", "Vikram", "Neha", "Sunita", "Karan"]

Find: students in both sections, only in A, only in B, in either section.

Interview Questions

⚠️ Common Mistakes

1. Empty `{}` ko set samajhna ❌

python example

# ❌ Galat — yeh dict hai, set nahi!
empty = {}
print(type(empty))   # <class 'dict'>

# ✅ Sahi — empty set banane ke liye set() use karo
empty_set = set()
print(type(empty_set))   # <class 'set'>

2. Single-element tuple mein comma bhoolna ❌

python example

# ❌ Galat — yeh int hai, tuple nahi!
not_a_tuple = (42)
print(type(not_a_tuple))   # <class 'int'>

# ✅ Sahi — trailing comma zaroori hai!
actual_tuple = (42,)
print(type(actual_tuple))   # <class 'tuple'>

3. Float comparison `==` se karna ❌

python example

# ❌ Galat — floating point precision issue!
print(0.1 + 0.2 == 0.3)   # False 😱

# ✅ Sahi — round() ya math.isclose() use karo
import math
print(math.isclose(0.1 + 0.2, 0.3))   # True ✅

4. `== None` use karna instead of `is None` ❌

python example

# ❌ Galat — == override ho sakta hai custom classes mein
if x == None:
    pass

# ✅ Sahi — is None use karo (identity check)
if x is None:
    pass

5. Mutable default arguments use karna ❌

python example

# ❌ Galat — same list share hogi har function call mein!
def add_item(item, items=[]):
    items.append(item)
    return items

# ✅ Sahi — None use karo as default
def add_item(item, items=None):
    if items is None:
        items = []
    items.append(item)
    return items

6. String ko modify karne ki koshish karna ❌

Example

# ❌ Galat — strings immutable hain! name = "Rahul" # name[0] = "r" # TypeError! # ✅ Sahi — naya string banao name = "r" + name[1:] # "rahul"

7. List copy karte waqt reference copy karna ❌

Example

✅ Key Takeaways

🔢 Python mein har cheez ek object hai — integers, strings, functions sab objects hain with a type
📦 Numeric types: int (unlimited size), float (decimal), complex (engineering), bool (True/False — int ka subclass)
📝 Strings immutable hain — modify karne pe naya object banta hai, purana change nahi hota
📋 List vs Tuple: List mutable hai ([]), Tuple immutable hai (()). Fixed data ke liye tuple, changeable data ke liye list
🗂️ Dictionary key-value pairs store karta hai — Python 3.7+ mein insertion order maintain hota hai
🎯 Set mein duplicates nahi hote — fast membership testing O(1) aur mathematical set operations ke liye best
🚫 None ka matlab "no value" — always check with is None, never == None
🔒 Immutable types: int, float, str, tuple, frozenset, bytes — inhe dictionary keys ki tarah use kar sakte ho
🔓 Mutable types: list, dict, set, bytearray — in-place modify ho sakte hain, careful with references!
🧪 Type checking: type() exact type batata hai, isinstance() inheritance bhi check karta hai — prefer isinstance()

❓ FAQ

Exam Focus

Revise definitions, diagrams, examples, and short-answer points for Python Data Types.

Interview Use

Prepare one clear explanation, one practical example, and one common mistake for this Python Master Course topic.

Search Terms

python-master-course, python master course, python, master, course, basics, data, types

Continue learning this concept

PreviousPython Comments NextPython Input and Output

2. Numeric Types

Integer (int)

Float (float)

Complex (complex)

Boolean (bool)

Falsy Values Table

3. String (str)

4. List (list)

5. Tuple (tuple)

6. Dictionary (dict)

7. Set (set)

8. NoneType (None)

9. Mutable vs Immutable Types

IMMUTABLE (cannot change after creation)

MUTABLE (can change after creation)

10. Comprehensive Data Type Comparison

11. Type Checking

Real-World Example: E-commerce Product

Practice Exercises

Exercise 1 — Type Identification

Exercise 2 — Choose the Right Type

Exercise 3 — Set Operations

Interview Questions

⚠️ Common Mistakes

1. Empty {} ko set samajhna ❌

2. Single-element tuple mein comma bhoolna ❌

3. Float comparison == se karna ❌

4. == None use karna instead of is None ❌

5. Mutable default arguments use karna ❌

6. String ko modify karne ki koshish karna ❌

7. List copy karte waqt reference copy karna ❌

✅ Key Takeaways

❓ FAQ

Continue learning this concept

2. Numeric Types

Integer (int)

Float (float)

Complex (complex)

Boolean (bool)

Falsy Values Table

3. String (str)

4. List (list)

5. Tuple (tuple)

6. Dictionary (dict)

7. Set (set)

8. NoneType (None)

9. Mutable vs Immutable Types

IMMUTABLE (cannot change after creation)

MUTABLE (can change after creation)

10. Comprehensive Data Type Comparison

11. Type Checking

Real-World Example: E-commerce Product

Practice Exercises

Exercise 1 — Type Identification

Exercise 2 — Choose the Right Type

Exercise 3 — Set Operations

Interview Questions

⚠️ Common Mistakes

1. Empty {} ko set samajhna ❌

2. Single-element tuple mein comma bhoolna ❌

3. Float comparison == se karna ❌

4. == None use karna instead of is None ❌

5. Mutable default arguments use karna ❌

6. String ko modify karne ki koshish karna ❌

7. List copy karte waqt reference copy karna ❌

✅ Key Takeaways

❓ FAQ

Continue learning this concept

Integer (`int`)

Float (`float`)

Complex (`complex`)

Boolean (`bool`)

3. String (`str`)

4. List (`list`)

5. Tuple (`tuple`)

6. Dictionary (`dict`)

7. Set (`set`)

8. NoneType (`None`)

1. Empty `{}` ko set samajhna ❌

3. Float comparison `==` se karna ❌

4. `== None` use karna instead of `is None` ❌

Integer (`int`)

Float (`float`)

Complex (`complex`)

Boolean (`bool`)

3. String (`str`)

4. List (`list`)

5. Tuple (`tuple`)

6. Dictionary (`dict`)

7. Set (`set`)

8. NoneType (`None`)

1. Empty `{}` ko set samajhna ❌

3. Float comparison `==` se karna ❌

4. `== None` use karna instead of `is None` ❌