Python Operators and Data Types: A Practical Guide with Code Examples

Introduction: Python's clear syntax and rich data types make it popular among programmers. This article explores basic operators and common data types with over ten practical code examples.

1️⃣ Arithmetic Operators

# Example 1: Addition

a = 5

b = 3

sum_ = a + b  # Result: 8

# Example 2: Division (float)

c = 10

d = 3

quotient = c / d  # Result: 3.3333333333333335

# Example 3: Modulus

remainder = c % d  # Result: 1

2️⃣ Relational Operators

# Example 4: Equality

e = 5

f = 5

equality = e == f  # Result: True

# Example 5: Inequality

inequality = e != f  # Result: False

# Example 6: Greater than

comparison = e > f  # Result: False

3️⃣ Logical Operators

# Example 7: Logical AND

g = True

h = False

and_result = g and h  # Result: False

# Example 8: Logical OR

or_result = g or h  # Result: True

# Example 9: Logical NOT

not_result = not g  # Result: False

4️⃣ Assignment Operators

# Example 10: Simple assignment

i = 10

i = i + 2  # Equivalent to i += 2, i becomes 12

# Example 11: Compound assignment (multiplication)

j = 3

j *= 5  # j becomes 15

5️⃣ Data Types & Operations

# Example 12: String concatenation

str1 = "Hello"

str2 = "World"

concatenation = str1 + " " + str2  # Result: 'Hello World'

# Example 13: List element addition

my_list = [1, 2, 3]

my_list.append(4)  # my_list becomes [1, 2, 3, 4]

# Example 14: Dictionary item modification

my_dict = {'name': 'Alice', 'age': 25}

my_dict['age'] = 30  # my_dict becomes {'name': 'Alice', 'age': 30}

# Example 15: Tuple immutability

my_tuple = (1, 2, 3)

# my_tuple[0] = 4 # This would raise TypeError because tuples are immutable

6️⃣ Type Conversion

# Example 16: Integer to string

num = 123

str_num = str(num)  # Result: '123'

# Example 17: String to float

str_float = "3.14"

float_val = float(str_float)  # Result: 3.14

Conclusion: Python's operators and data types are powerful and flexible. By practicing these examples, you can deepen your understanding and apply these fundamentals to write efficient, robust code. Continued practice will strengthen your programming foundation for higher‑level topics.