Python Data Types Tutorial
Data types in Python define the type of value stored in a variable. Python is dynamically typed, meaning you don’t need to declare the type explicitly; it is assigned automatically.
1. Basic Data Types in Python
2. Numeric Data Types
(a) Integer (int)
x = 100
print(type(x)) # Output: <class 'int'>
(b) Floating Point (float)
pi = 3.1415
print(type(pi)) # Output: <class 'float'>
(c) Complex Numbers (complex)
z = 2 + 3j
print(type(z)) # Output: <class 'complex'>
3. Boolean Data Type (bool)
Boolean values represent True or False.
is_active = True
print(type(is_active)) # Output: <class 'bool'>
print(10 > 5) # Output: True
print(10 == 20) # Output: False
✅ Booleans are often used in conditions and loops.
4. String Data Type (str)
Strings store sequences of characters.
text = "Hello, Python!"
print(type(text)) # Output: <class 'str'>
# Multi-line String
multiline = """This is
a multi-line string."""
✅ Strings support indexing, slicing, and various methods for manipulation.
5. Sequence Data Types
(a) List (list)
- Ordered, mutable (changeable), allows duplicates
- Defined using
[]brackets
numbers = [1, 2, 3, 4, 5]
print(type(numbers)) # Output: <class 'list'>
numbers.append(6) # Add element
print(numbers) # Output: [1, 2, 3, 4, 5, 6]
(b) Tuple (tuple)
- Ordered, immutable (cannot be changed), allows duplicates
- Defined using
()brackets
coordinates = (10, 20, 30)
print(type(coordinates)) # Output: <class 'tuple'>
# Accessing elements
print(coordinates[0]) # Output: 10
✅ Tuples are useful when data should not be modified.
(c) Range (range)
Used to generate a sequence of numbers.
r = range(5) # Creates sequence: 0,1,2,3,4
print(list(r)) # Output: [0, 1, 2, 3, 4]
✅ Often used in loops.
6. Set Data Types
(a) Set (set)
- Unordered, mutable, no duplicate values
- Defined using
{}brackets
fruits = {"apple", "banana", "cherry"}
print(type(fruits)) # Output: <class 'set'>
fruits.add("orange") # Add an element
print(fruits)
fruits.remove("banana") # Remove an element
print(fruits)
✅ Sets are useful when duplicates are not allowed.
(b) Frozen Set (frozenset)
- Immutable version of set
fset = frozenset({1, 2, 3})
# fset.add(4) # Error: frozenset is immutable
print(fset)
✅ Useful when an immutable collection of unique values is needed.
7. Dictionary Data Type (dict)
- Stores key-value pairs
- Unordered, mutable
person = {"name": "Alice", "age": 25, "city": "New York"}
print(type(person)) # Output: <class 'dict'>
print(person["name"]) # Output: Alice
# Adding a new key-value pair
person["email"] = "alice@example.com"
print(person)
# Removing a key-value pair
del person["age"]
print(person)
✅ Dictionaries are great for structured data storage.
8. Type Conversion (Type Casting)
Python allows explicit and implicit type conversion.
(a) Implicit Type Conversion (Done automatically by Python)
x = 10 # int
y = 3.5 # float
result = x + y # int + float = float
print(result) # Output: 13.5
print(type(result)) # Output: <class 'float'>
(b) Explicit Type Conversion (Done manually by the user)
a = "100"
b = int(a) # Convert string to int
print(type(b)) # Output: <class 'int'>
x = 3.14
y = str(x) # Convert float to string
print(type(y)) # Output: <class 'str'>
9. Mutable vs Immutable Data Types
✅ Mutable types can be modified in place.
❌ Immutable types create a new object when changed.
10. Checking Data Types (type())
Use type() to check a variable’s data type.
x = 42
print(type(x)) # Output: <class 'int'>
y = [1, 2, 3]
print(type(y)) # Output: <class 'list'>
z = (10, 20)
print(type(z)) # Output: <class 'tuple'>
Conclusion
- Python provides several data types, including numbers, strings, lists, tuples, sets, and dictionaries.
- Lists and dictionaries are mutable, while strings and tuples are immutable.
- Type conversion helps in changing data types when needed.
🚀 Mastering data types is essential for writing efficient Python programs!
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