In Python, data types define the type of value a variable can hold. Python provides several built-in data types, categorized into different groups. Understanding these types is essential for effective programming.
1. Basic Data Types
1.1 Numeric Types
Python supports three main numeric types:
- Integer (
int): Whole numbers (e.g.,10,-5) - Floating-Point (
float): Decimal numbers (e.g.,3.14,-2.5) - Complex (
complex): Numbers with real and imaginary parts (e.g.,2 + 3j)
Example:
x = 10 # int
y = 3.14 # float
z = 2 + 3j # complex
print(type(x), type(y), type(z))
Operations on Numeric Types:
# Arithmetic operations
print(10 + 5) # Addition
print(10 - 5) # Subtraction
print(10 * 5) # Multiplication
print(10 / 2) # Division
print(10 % 3) # Modulus
print(10 ** 2) # Exponentiation
1.2 Boolean Type
- Boolean (
bool): RepresentsTrueorFalse
Example:
is_python_fun = True
print(type(is_python_fun)) # Output: <class 'bool'>
Booleans are often used in conditions and logical operations.
x = 10
y = 20
print(x > y) # Output: False
print(x == y) # Output: False
print(x != y) # Output: True
2. Sequence Data Types
2.1 Strings (str)
A string is a sequence of characters enclosed in quotes.
Example:
text = "Hello, Python!"
print(type(text))
String Operations:
text = "Python"
print(text[0]) # Access first character
print(text[1:4]) # Substring (slicing)
print(len(text)) # Length of string
print(text.lower()) # Convert to lowercase
print(text.upper()) # Convert to uppercase
print(text.replace("P", "J")) # Replace character
2.2 Lists (list)
A list is an ordered, mutable collection of items.
Example:
fruits = ["apple", "banana", "cherry"]
print(fruits[0]) # Access first item
fruits.append("orange") # Add item to list
print(fruits)
List Operations:
numbers = [1, 2, 3, 4, 5]
numbers.insert(2, 10) # Insert 10 at index 2
numbers.remove(3) # Remove 3 from the list
numbers.sort() # Sort the list
print(numbers)
2.3 Tuples (tuple)
A tuple is an ordered, immutable collection of items.
Example:
coordinates = (10, 20)
print(coordinates[0]) # Access first item
Tuples are faster and safer than lists for immutable collections.
3. Set and Dictionary
3.1 Sets (set)
A set is an unordered collection of unique items.
Example:
numbers = {1, 2, 3, 3, 4}
print(numbers) # Output: {1, 2, 3, 4} (removes duplicates)
Sets support mathematical operations like union, intersection, and difference.
A = {1, 2, 3, 4}
B = {3, 4, 5, 6}
print(A | B) # Union
print(A & B) # Intersection
print(A - B) # Difference
3.2 Dictionaries (dict)
A dictionary stores key-value pairs.
Example:
student = {"name": "Alice", "age": 21}
print(student["name"]) # Output: Alice
Dictionary Operations:
student["grade"] = "A" # Add a new key-value pair
del student["age"] # Remove a key-value pair
print(student.keys()) # Get all keys
print(student.values()) # Get all values
4. Type Conversion
Python allows type conversion between compatible types.
Example:
x = 5 # int
y = float(x) # Convert to float
z = str(x) # Convert to string
print(type(y), type(z))
Some common conversions:
print(int("10")) # Convert string to int
print(float("5.5")) # Convert string to float
print(list("hello")) # Convert string to list
5. Summary
✅ Learned about Python’s data types: numeric, boolean, sequences, sets, and dictionaries
✅ Explored operations and conversions between data types
✅ Practiced using lists, tuples, and dictionaries
