Types of Operators in Python: A Beginner’s Guide

Python provides a variety of operators to perform different operations on values and variables. These include arithmetic operators for calculations, relational operators for comparisons, logical operators to combine conditions, and assignment operators to update values. Python also offers bitwise, identity, and membership operators for specific tasks. Learning these types of operators helps you write precise and efficient code. 

In this guide, you'll read more about the main types of operators in Python. We'll cover arithmetic, relational, logical, and assignment operators in detail. You’ll also explore bitwise, identity, and membership operators, along with operator precedence. Examples, tables, and charts are included to make these concepts easy to understand and apply in your programs. 

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Types of Operators in Python 

Let’s take a quick overview of types of operators in Python. After we will explore all types in detail. 

Arithmetic Operators: The Foundation of Calculation 

Arithmetic operators are the most familiar category for anyone who has taken a math class. These are the tools you use to perform basic mathematical calculations like addition, subtraction, multiplication, and division. They form the bedrock of numerical computation in Python. 

In Python, these operators work as you would expect with numbers (integers and floats). Let's explore each one with simple examples. Assume we have two variables for our examples: a = 13 and b = 5. 

Code Examples in Action 

Let's see these operators at work in Python code. 

Addition, Subtraction, and Multiplication 

These are the most straightforward operators. 

Python 
a = 13 
b = 5 
 
print(f"Addition: {a + b}") 
print(f"Subtraction: {a - b}") 
print(f"Multiplication: {a * b}") 
 

Output: 

Addition: 18 
Subtraction: 8 
Multiplication: 65 
 

Division vs. Floor Division 

It's important to see the difference between these two. Standard division (/) always returns a floating-point number. Floor division (//) returns an integer by discarding the decimal part. 

Python 
a = 13 
b = 5 
 
print(f"Standard Division: {a / b}") 
print(f"Floor Division: {a // b}") 
 

Output: 

Standard Division: 2.6 
Floor Division: 2 
 

Modulus and Exponentiation 

The modulus operator is incredibly useful for tasks like checking if a number is even or odd. Exponentiation is for calculating powers. 

Python 
a = 13 
b = 5 
 
print(f"Modulus (Remainder): {a % b}") 
print(f"Exponentiation (Power): {2 ** 3}") # 2 to the power of 3 
 

Output: 

Modulus (Remainder): 3 
Exponentiation (Power): 8 
 

Understanding these arithmetic operators is a critical first step in mastering the different types of operators in Python. 

Also Read: Step-by-Step Guide to Learning Python for Data Science 

Assignment Operators: Storing and Updating Values 

The next major category is the assignment operator in Python. These operators are used to assign or update the value of a variable. The most basic assignment operator is the equals sign (=), which you've already seen. It simply stores the value on the right in the variable on the left. 

Beyond the simple equals sign, Python provides several compound assignment operators. These are convenient shorthands that combine an arithmetic operation with an assignment. For example, instead of writing x = x + 10, you can simply write x += 10. This makes your code cleaner and more concise. 

Let's look at the primary assignment operators. 

Code Examples in Action 

Here’s how you would use these operators in a real script. We'll initialize a variable and then update it using different compound operators. 

Python 
# Start with a base value 
score = 100 
print(f"Initial score: {score}") 
 
# Add points 
score += 20 
print(f"Score after adding 20: {score}") 
 
# Subtract points 
score -= 10 
print(f"Score after subtracting 10: {score}") 
 
# Double the score 
score *= 2 
print(f"Score after multiplying by 2: {score}") 
 
# Halve the score 
score /= 2 
print(f"Score after dividing by 2: {score}") 
 

Output: 

Initial score: 100 
Score after adding 20: 120 
Score after subtracting 10: 110 
Score after multiplying by 2: 220 
Score after dividing by 2: 110.0 
 

Notice that using the /= operator converted our score variable from an integer to a float. This is an important behavior to remember. Mastering the assignment operator in Python is key to managing state within your programs. 

Also Read: Top 36+ Python Projects for Beginners and Students to Explore in 2025 

Comparison (Relational) Operators: The Basis of Decision Making 

Comparison operators, also known as relational operators, are used to compare two values. The result of a comparison is always a Boolean value, which is either True or False. These operators are the heart of decision-making in programming. You use them constantly in if statements and while loops to control your program's flow. 

Understanding these operators is essential for writing code that can react differently to different inputs. Let's review the six main comparison operators. 

Code Examples in Action 

Let's see how Python evaluates expressions using these operators. 

Python 
a = 10 
b = 20 
c = 10 
 
# Equal to and Not equal to 
print(f"Is a equal to b? {a == b}") 
print(f"Is a equal to c? {a == c}") 
print(f"Is a not equal to b? {a != b}") 
 
# Greater than and Less than 
print(f"Is a greater than b? {a > b}") 
print(f"Is b less than or equal to 20? {b <= 20}") 
 

Output: 

Is a equal to b? False 
Is a equal to c? True 
Is a not equal to b? True 
Is a greater than b? False 
Is b less than or equal to 20? True 
 

These True and False values are what allow you to create logic, for example: 

Python 
age = 25 
if age >= 18: 
    print("You are eligible to vote.") 
else: 
    print("You are not eligible to vote.") 
 

This is a practical demonstration of why comparison operators are a fundamental part of the types of operators in Python. 

Also Read: Understanding Python Data Types 

Logical Operators: Combining Conditional Statements 

Logical operators are used to combine conditional statements. They allow you to check multiple conditions at the same time. This is incredibly powerful for creating complex decision-making logic. There are three logical operators in Python: and, or, and not. 

• and: Returns True if both conditions on its left and right are True. 
• or: Returns True if at least one of the conditions on its left or right is True. 
• not: Inverts the Boolean value. It makes a True statement False and a False statement True. 

Let's look at their truth tables. 

and Operator 

or Operator 

Code Examples in Action 

Here's how you might use these operators to check for application eligibility. 

Python 
age = 22 
has_good_credit = True 
 
# Using the 'and' operator 
if age >= 18 and has_good_credit: 
    print("Application for loan approved.") 
else: 
    print("Application for loan denied.") 
 
# Using the 'or' operator 
is_weekend = True 
has_holiday_pass = False 
 
if is_weekend or has_holiday_pass: 
    print("You get a discount on your ticket!") 
else: 
    print("No discount applicable.") 
 
# Using the 'not' operator 
is_logged_in = False 
 
if not is_logged_in: 
    print("Please log in to see your profile.") 
 

Output: 

Application for loan approved. 
You get a discount on your ticket! 
Please log in to see your profile. 
 

Logical operators are the glue that holds your program's logic together, making them one of the most important types of operators in Python to master. 

Also Read: Data Science for Beginners: Prerequisites, Learning Path, Career Opportunities and More 

Specialized Operators: Bitwise, Membership, and Identity 

Beyond the common operators, Python has several specialized sets for more advanced or specific tasks. While you may not use these every day as a beginner, knowing they exist is important. 

Membership Operators 

These are very intuitive and useful. Membership operators test whether a value is found within a sequence, like a string, list, or tuple. 

• in: Returns True if a value is found in the sequence. 
• not in: Returns True if a value is not found in the sequence. 

Python 
my_favorite_fruits = ["apple", "banana", "orange"] 
 
print(f"Is 'banana' a favorite fruit? {'banana' in my_favorite_fruits}") 
print(f"Is 'grape' a favorite fruit? {'grape' in my_favorite_fruits}") 
print(f"Is 'grape' not a favorite fruit? {'grape' not in my_favorite_fruits}") 
 

Output: 

Is 'banana' a favorite fruit? True 
Is 'grape' a favorite fruit? False 
Is 'grape' not a favorite fruit? True 
 

Identity Operators 

Identity operators compare the memory location of two objects, not just their values. This is a subtle but critical difference from the == operator. 

• is: Returns True if two variables point to the exact same object in memory. 
• is not: Returns True if two variables point to different objects. 

Python 
x = ["apple", "banana"] 
y = ["apple", "banana"] 
z = x 
 
# '==' checks for equality of values 
print(f"Does x equal y? {x == y}") 
 
# 'is' checks for identity (same object in memory) 
print(f"Is x the same object as y? {x is y}") 
print(f"Is x the same object as z? {x is z}") 
 

Output: 

Does x equal y? True 
Is x the same object as y? False 
Is x the same object as z? True 
 

Bitwise Operators 

Bitwise operators act on operands at the binary level. They are used in lower-level programming, networking, and cryptography. As a beginner, you only need to be aware of them. The main ones are & (AND), | (OR), ^ (XOR), and ~ (NOT). 

Also Read: Comprehensive Guide to Binary Code: Basics, Uses, and Practical Examples 

Precedence of Operators in Python: The Order of Operations 

When you have multiple operators in a single expression, how does Python know which one to perform first? It follows a set of rules called operator precedence. This is similar to the PEMDAS/BODMAS rule you learned in math class (Parentheses, Exponents, Multiplication/Division, Addition/Subtraction). 

Understanding the precedence of operators in Python is crucial for writing correct and bug-free code. An expression like 10 + 5 * 2 is not evaluated left-to-right. Python knows that multiplication has higher precedence than addition, so it calculates 5 * 2 first, and then adds 10 to get 20. 

The table below shows the order of precedence for the most common operators, from highest to lowest. 

Code Examples in Action 

Let's see how precedence affects the outcome of an expression. 

Python 
# Without parentheses 
result1 = 10 + 5 * 2 
# Python evaluates 5 * 2 first, then 10 + 10 
print(f"Result 1 (10 + 5 * 2): {result1}") 
 
# With parentheses 
result2 = (10 + 5) * 2 
# The parentheses force the addition to be evaluated first 
print(f"Result 2 ((10 + 5) * 2): {result2}") 
 
# Complex example 
result3 = 100 / 5 + 3 * 2 ** 2 
# 1. Exponent: 2 ** 2 = 4 
# 2. Division/Multiplication: 100 / 5 = 20.0 and 3 * 4 = 12 
# 3. Addition: 20.0 + 12 = 32.0 
print(f"Result 3: {result3}") 
 

Output: 

Result 1 (10 + 5 * 2): 20 
Result 2 ((10 + 5) * 2): 30 
Result 3: 32.0 
 

When in doubt, always use parentheses () to make the order of operations explicit. It makes your code easier to read and guarantees it will be evaluated correctly. This is a key skill when working with the different types of operators in Python. 

Conclusion 

Mastering operators is non-negotiable for any aspiring Python developer. They are the core syntax that allows you to manipulate data, control program flow, and implement logic. From the simple addition of two numbers to combining complex conditional checks, every line of functional code you write will rely on them. 

In this guide, we have explored all the major types of operators in Python, including Arithmetic, Assignment, Comparison, Logical, and more specialized ones. We also demystified the precedence of operators in Python, giving you the knowledge to write predictable and accurate code. By practicing with these fundamental tools, you are building a solid foundation for your entire programming journey. 

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