Python Archives - Azad Chouhan

Master Python Numbers & Math Operations: Beginner’s Friendly Guide

azad chouhan — Mon, 20 Oct 2025 12:43:43 +0000

When I first started coding in Python, I felt puzzled by how numbers behaved — especially floats and the differences between operators. Understanding Python numbers and math operations is one of the most useful skills for anyone learning Python. This article explains number types, arithmetic operators, common pitfalls, and a small mini-project to practice. It uses simple language and practical examples.

1. What Are Python Number Types?

Before doing math, know the main number types in Python:

Integers (`int`)

Whole numbers with no decimals, for example 5, -10, 100. Use ints when counting or indexing.

Floating-point numbers (`float`)

Numbers with decimals, like 3.14 or -0.5. Use floats for averages, percentages, and measurements.

Complex numbers (`complex`)

Numbers with a real and imaginary part (e.g., 2 + 3j). These are used in advanced math or scientific code. Most beginners only need int and float.

Tip: For everyday scripts, start with int and float. You can learn complex numbers later.

2. Basic Arithmetic Operators in Python

These are the core operators you’ll use to do math:

Operator	Meaning
`+`	Addition
`-`	Subtraction
`*`	Multiplication
`/`	Division (returns a float)
`//`	Floor (integer) division
`%`	Modulus (remainder)
`**`	Exponentiation (power)

Quick examples

a = 10
b = 3

print(a + b)   # 13
print(a - b)   # 7
print(a * b)   # 30
print(a / b)   # 3.3333333333333335  (float)
print(a // b)  # 3  (floor division)
print(a % b)   # 1  (remainder)
print(a ** b)  # 1000  (10 to the power of 3)

Note: The regular division operator / returns a float. If you expect an integer, use //.

3. Type Conversion & Useful Number Functions

You will often convert types or use built-in functions for numbers:

Type conversion (casting)

x = "5"
y = int(x)     # converts "5" to 5

z = 2.8
w = int(z)     # converts 2.8 to 2 (drops decimals)

Useful functions

abs(number) – absolute value
round(number, ndigits) – round to decimals
pow(base, exponent) – power (or use **)

Caution: Converting floats to ints removes the fractional part. If you need precision, plan accordingly.

4. Common Pitfalls & Gotchas

These are mistakes many beginners make (I used to do these too):

Floating-point precision

print(0.1 + 0.2)   # 0.30000000000000004

Floats are stored in binary, which can create small rounding errors. For ordinary scripts this is usually fine; for money or critical calculations consider the decimal module.

Floor division with negatives

-5 // 2 gives -3 because floor division rounds down, not toward zero.

Mixing types

Mixing int, float, and complex can lead to automatic conversions (for example, int + float → float).

5. Simple Project: Mini Calculator

Try this small script to practice numbers and math operators:

def mini_calc():
    print("Welcome to Mini-Calculator")
    num1 = float(input("Enter first number: "))
    num2 = float(input("Enter second number: "))

    print("Addition: ", num1 + num2)
    print("Subtraction: ", num1 - num2)
    print("Multiplication: ", num1 * num2)
    print("Division: ", num1 / num2 if num2 != 0 else "Cannot divide by zero")
    print("Floor Division: ", num1 // num2 if num2 != 0 else "Undefined")
    print("Modulus (remainder): ", num1 % num2 if num2 != 0 else "Undefined")
    print("Power: ", num1 ** num2)

if __name__ == "__main__":
    mini_calc()

Run the script and test different values (negatives, floats, zeros) to observe behavior.

6. Why this knowledge helps

Understanding numbers and math operations helps in many areas: data analysis, scripts, web apps, budgeting tools and more. It saves debugging time and builds confidence to move on to loops, conditions, and data processing.

Final thoughts

Numbers and math operations are basic but essential. Practice small scripts, try different inputs, and you’ll quickly feel comfortable. If you want, I can prepare a printable cheat-sheet of number types and operators.

If you enjoyed learning about Python numbers, you might also like our next guide —

How to Work with Strings in Python (Beginner-Friendly Guide)

It’s a simple and clear tutorial that explains how to handle text in Python with practical examples.

The post Master Python Numbers & Math Operations: Beginner’s Friendly Guide appeared first on Azad Chouhan.

How to Work with Strings in Python (Beginner-Friendly Guide)

azad chouhan — Wed, 15 Oct 2025 15:25:24 +0000

If you are learning Python, one of the first things you’ll come across is strings. Strings are everywhere in Python — from printing messages to taking user input. In simple terms, a string in Python is a sequence of characters enclosed within quotes.When I first started learning Python, I was surprised by how flexible and easy it was to handle text data. In this guide, I’ll walk you through how to create, manipulate, and format strings in Python using simple examples.

What is a String in Python?

A string is a collection of characters like letters, numbers, and symbols. You can create a string using single quotes (' ') or double quotes (" ").

name = "Python"
greeting = 'Hello, World!'

Both of these are valid strings in Python.

How to Access Characters in a String

Every character in a Python string has a position, known as an index. Python uses zero-based indexing, which means counting starts from 0.

word = "Python"
print(word[0])  # Output: P
print(word[5])  # Output: n

You can also use negative indexing to access characters from the end.

print(word[-1])  # Output: n
print(word[-2])  # Output: o

String Slicing in Python

Python makes it easy to extract parts of a string using slicing.

text = "Learning Python"
print(text[0:8])   # Output: Learning
print(text[:8])    # Output: Learning
print(text[9:])    # Output: Python

Slicing helps you get the exact part of a string you need without looping.

Common String Methods in Python

Python provides many built-in string methods to make text handling easier. Here are some commonly used ones:

message = " hello python "

print(message.upper())     # HELLO PYTHON
print(message.lower())     # hello python
print(message.strip())     # hello python
print(message.replace("python", "world"))  # hello world
print(message.split())     # ['hello', 'python']

These methods help in cleaning, formatting, and modifying text data quickly.

Joining and Formatting Strings

You can combine multiple strings using the + operator or f-strings.

first = "Python"
second = "Programming"

# Using +
result = first + " " + second
print(result)  # Output: Python Programming

# Using f-string
name = "Azad"
print(f"Hello, {name}! Welcome to Python.")

F-strings are my personal favorite since they make the code more readable and concise.

String Immutability in Python

One thing you should remember — strings in Python are immutable. That means you cannot change a string after it’s created.

text = "Python"
text[0] = "J"   # This will give an error

If you want to modify a string, you must create a new string.

Useful String Operations

Some other powerful string operations in Python include:

len() – returns the length of a string
in / not in – checks for substring existence
count() – counts occurrences of a substring

s = "I love Python programming"
print(len(s))           # 25
print("Python" in s)    # True
print(s.count("o"))     # 3

Conclusion

Working with strings in Python is simple once you understand the basics. From creating and slicing to formatting and joining, strings are one of the most powerful features in Python.

If you’re new to programming, practice different string operations daily. Trust me, mastering strings will make your Python journey much easier and more enjoyable.

The post How to Work with Strings in Python (Beginner-Friendly Guide) appeared first on Azad Chouhan.

Python Operators Explained Simply: A Complete Beginner’s Guide

azad chouhan — Mon, 13 Oct 2025 17:27:18 +0000

When I first started learning Python, I used to get confused about operators — those little symbols like +, -, or ==. They looked simple but did a lot behind the scenes. If you’re also starting out and wondering what Python operators are and how they work, this guide will make it crystal clear.Let’s break it down step by step — in plain English, without complicated tech jargon.

What Are Python Operators?

In simple words, operators in Python are symbols or keywords that perform operations on values or variables.

Think of them as tools that tell Python what action to take. For example:

a = 10
b = 5
print(a + b)  # Output: 15

Here, the + operator adds two numbers. Easy, right?

Types of Python Operators

Python gives us different types of operators to perform various tasks. Let’s understand each one with simple examples.

1. Arithmetic Operators

These are used for basic math operations — addition, subtraction, multiplication, etc.

Operator	Description	Example
+	Addition	10 + 5 = 15
–	Subtraction	10 – 5 = 5
*	Multiplication	10 * 5 = 50
/	Division	10 / 5 = 2.0
%	Modulus (Remainder)	10 % 3 = 1
**	Exponentiation	2 ** 3 = 8
//	Floor Division	10 // 3 = 3

When I learned these, I practiced with small examples daily. That’s the best way to remember them.

2. Comparison Operators

Comparison operators help you compare two values. They return either True or False.

Operator	Meaning	Example
==	Equal to	5 == 5 → True
!=	Not equal to	5 != 3 → True
>	Greater than	7 > 5 → True
<	Less than	3 < 8 → True
>=	Greater or equal to	5 >= 5 → True
<=	Less or equal to	4 <= 6 → True

I often use these in if-else statements to control the flow of a program.

3. Logical Operators

These operators are used to combine conditions.

Operator	Description	Example
and	Returns True if both conditions are True	(5 > 2 and 3 < 6) → True
or	Returns True if any condition is True	(5 < 2 or 3 < 6) → True
not	Reverses the result	not(5 > 2) → False

4. Assignment Operators

Used to assign values to variables.

Operator	Example	Same As
=	x = 5	Assign value 5 to x
+=	x += 3	x = x + 3
-=	x -= 3	x = x – 3
*=	x *= 3	x = x * 3
/=	x /= 3	x = x / 3

5. Bitwise Operators

Bitwise operators work with bits (0s and 1s). You’ll use them rarely, but they’re important in advanced programming.

& – AND
| – OR
^ – XOR
~ – NOT
<< – Left shift
>> – Right shift

6. Membership Operators

Used to check if a value exists in a sequence (like a list or string).

Operator	Example	Result
in	‘a’ in ‘apple’	True
not in	‘b’ not in ‘apple’	True

I use this often while checking if a user input exists in a list.

7. Identity Operators

Used to check if two variables point to the same object in memory.

Operator	Example	Result
is	x is y	True if same object
is not	x is not y	True if different objects

Why Are Python Operators Important?

Without operators, coding would be like trying to write sentences without verbs. They make your code perform actions, calculate values, and make decisions. If you want to become a good Python programmer, you must understand them well.

My Personal Tip

When I was learning Python, I created a small “operator notebook.” Every time I learned a new operator, I’d note its example and output. Within a week, I could use all of them without looking up Google. Try doing the same — it works wonders!

Conclusion

So that’s a complete and simple guide on Python operators. You’ve now learned what they are, their types, and how to use them in real Python code.

Keep practicing small examples every day, and soon you’ll find operators easy and fun to use. If you’re serious about mastering Python, this is one of the best starting points.

The post Python Operators Explained Simply: A Complete Beginner’s Guide appeared first on Azad Chouhan.

Understanding Python Variables and Data Types — A Beginner-Friendly Guide

azad chouhan — Sun, 12 Oct 2025 16:57:09 +0000

If you are new to programming, Python is a great place to start. Before writing bigger programs, you should learn two basic ideas: variables and data types. This guide explains both in simple language so you can begin coding with confidence.

What is a Variable in Python?

A variable is like a labeled box that holds information. You give the box a name and put a value inside it. For example:

name = "John"
age = 25

Here, name holds text (a string) and age holds a number (an integer). In Python you do not have to tell the language the type — Python figures it out. This feature is called dynamically typed.

Simple Rules for Naming Variables

Start with a letter or underscore (_).
Do not start with a number.
Use only letters, numbers, and underscores.
Names are case-sensitive: Name and name are different.

Tip: Use clear names like user_name or total_price so your code is easy to read.

Common Python Data Types (with examples)

Python has several built-in data types. Below are the most common ones you will use as a beginner.

1. Numbers (int, float, complex)

int is for whole numbers, float is for decimals, and complex is for complex numbers.

x = 5
y = 3.14
z = 2 + 3j

2. Strings (str)

Strings hold text and are placed inside quotes. You can use single or double quotes:

message = 'Hello, Python'
name = "Alice"

3. Boolean (bool)

Boolean values are True or False. They are useful for decisions in code.

is_active = True

4. List

A list stores multiple items in order. Lists are changeable (mutable).

fruits = ["apple", "banana", "cherry"]

5. Tuple

A tuple is like a list but cannot be changed (immutable).

coords = (10, 20)

6. Dictionary (dict)

Dictionaries store data as key-value pairs. This is useful when you want to look up values by name.

student = {"name": "John", "age": 21}

7. Set

A set is an unordered collection of unique items. Duplicates are removed automatically.

numbers = {1, 2, 3, 3}  # becomes {1,2,3}

Check a Variable’s Type

Use the type() function to see what type a variable holds:

x = 5
print(type(x))  # >

Why Data Types Matter

Data types help you avoid errors. For example, you cannot add text and numbers directly:

age = 25
print("I am " + age)  # This will cause an error

Convert the number to a string first:

print("I am " + str(age))

Quick Reference Table

Data Type	Example	Description
int	10	Whole number
float	3.14	Decimal number
str	“Hello”	Text
bool	True	True or False
list	[1,2,3]	Ordered, changeable collection
tuple	(1,2,3)	Ordered, fixed collection
dict	{“a”:1}	Key-value pairs
set	{1,2,3}	Unique items

Conclusion

Variables and data types are the foundation of Python programming. Practice by creating different variables and trying small examples. Over time, understanding these basics will make building larger programs much easier.

The post Understanding Python Variables and Data Types — A Beginner-Friendly Guide appeared first on Azad Chouhan.

Best Python IDEs in 2025: Which One Should You Use?

azad chouhan — Sat, 11 Oct 2025 07:47:14 +0000

If you’ve just started learning Python or even if you’re already coding for years, one common question always comes up — “Which Python IDE should I use?”

I’ve personally tried many editors while learning Python, and trust me, choosing the right IDE can make a big difference. It doesn’t just affect your coding speed but also how smoothly you debug and test your projects. Let’s break this down in simple words so you can easily pick one that fits your needs.

What is an IDE in Python?

IDE stands for Integrated Development Environment. In simple terms, it’s a software application that helps you write, edit, run, and debug your Python code all in one place.

A good Python IDE offers features like:

Code completion
Syntax highlighting
Debugging tools
Version control integration
Project management support

Think of it as your coding workspace — a comfortable place where everything you need is right at your fingertips.

Top Python IDEs You Can Use in 2025

After some hands-on experience and research, here are the best Python IDEs that most developers (including me) prefer in 2025.

1. PyCharm (Best for Professionals)

PyCharm by JetBrains is one of the most popular Python IDEs out there. I personally love how smart it feels — it highlights errors instantly, gives code suggestions, and helps organize projects easily.

Advanced debugging tools
Smart code completion
Version control (Git, SVN) integration
Web frameworks support like Django and Flask

Best for: Experienced programmers and professionals working on large projects.

2. Visual Studio Code (Best for Beginners and Pros Alike)

If you want something lightweight yet powerful, VS Code is perfect. It’s free, customizable, and supports tons of Python extensions.

I’ve been using VS Code for small projects and tutorials — it loads fast and works smoothly even on mid-range laptops.

Easy-to-use interface
Supports multiple languages
Python debugging and linting support
Large extension marketplace

Best for: Beginners, students, and intermediate programmers.

3. Jupyter Notebook (Best for Data Science)

If your main focus is data analysis, machine learning, or visualization, then Jupyter Notebook is your go-to IDE.

You can write code, visualize data, and add notes — all in one notebook-style environment.

Interactive data visualization
Markdown support for documentation
Integration with popular libraries like Pandas, NumPy, and Matplotlib

Best for: Data scientists, researchers, and educators.

4. Spyder (Best for Scientific Computing)

Spyder is specially built for scientific and analytical work. It’s simple, open-source, and comes with powerful libraries built-in.

Variable explorer
Integrated IPython console
Real-time code analysis

Best for: Scientists, engineers, and data analysts.

5. Thonny (Best for Absolute Beginners)

If you’re just starting your Python journey, Thonny is a great option. It’s clean, easy to use, and helps you understand Python step-by-step.

Simple interface
Step-through debugger
Pre-installed with Python

Best for: School students and complete beginners.

How to Choose the Right Python IDE

Here’s my honest advice: don’t overthink it. Start with something simple like VS Code or Thonny if you’re new. Once you get comfortable, try PyCharm for professional work or Jupyter if you’re diving into data science.

The best IDE depends on your goal — whether it’s web development, automation, or machine learning.

Final Thoughts

Finding the right IDE isn’t about what’s “best” overall — it’s about what’s best for you. I personally switch between PyCharm and VS Code depending on the project.

So, experiment with a few, stick to the one that feels comfortable, and let your coding journey begin smoothly.

The post Best Python IDEs in 2025: Which One Should You Use? appeared first on Azad Chouhan.

How to Install Python on Windows, Mac, and Linux (Step-by-Step Guide for Beginners)

azad chouhan — Fri, 10 Oct 2025 18:01:50 +0000

Python is one of the most popular programming languages in the world. Whether you’re starting your coding journey or planning to build a new project, you’ll need to install Python first. In this guide, I’ll walk you through how to install Python on Windows, Mac, and Linux easily — step by step.

Why Install Python?

Python is widely used for web development, data analysis, AI, automation, and more. I personally started learning Python a few years ago, and I can say that setting it up properly in the beginning saves a lot of headaches later. So, let’s get your system ready for coding.

1. How to Install Python on Windows

Step 1: Download Python

Go to the official Python website and download the latest version for Windows. Make sure you choose the right version based on your system (64-bit or 32-bit).

Step 2: Run the Installer

After downloading, open the installer. Before clicking “Install Now,” check the box that says “Add Python to PATH.” This step is very important as it allows you to run Python from the command prompt easily.

Step 3: Verify Installation

Once the installation is done, open your Command Prompt and type:

python --version

If you see the Python version number, you’re good to go!

2. How to Install Python on Mac

Step 1: Check If Python Is Already Installed

Most Mac systems come with Python pre-installed. You can check by opening the Terminal and typing:

python3 --version

If you get a version number, you already have Python installed. But it might be outdated.

Step 2: Install the Latest Python Version

To get the latest version, visit Python Downloads for Mac and install the newest release. Follow the on-screen steps to complete the setup.

Step 3: Verify Installation

After installation, open Terminal again and type:

python3 --version

This will confirm that Python is installed correctly on your Mac.

3. How to Install Python on Linux

Step 1: Check If Python Is Installed

Linux usually includes Python by default. Open your Terminal and type:

python3 --version

If Python is not installed, you can easily install it with a simple command.

Step 2: Install Python Using Terminal

Use one of the following commands based on your Linux distribution:

sudo apt install python3      # For Ubuntu/Debian
sudo dnf install python3      # For Fedora
sudo yum install python3      # For CentOS

Step 3: Verify Installation

After installation, check again using:

python3 --version

If you see the version number, you’ve successfully installed Python on Linux.

Tips After Installing Python

Install pip: Pip helps you install Python libraries. It usually comes with Python, but you can verify using pip --version.
Use a Code Editor: I recommend using VS Code or PyCharm for writing and running Python code easily.
Try a Simple Program: Open your terminal and type python, then write:
```
print("Hello, Python!")
```

Final Thoughts

Installing Python is the first step toward becoming a programmer. Once it’s installed, you can explore endless possibilities like web apps, automation scripts, or even AI tools. I remember my first Python project — a simple calculator — and it made me realize how powerful yet beginner-friendly Python truly is.

So go ahead, install Python on your system, and start experimenting today!

The post How to Install Python on Windows, Mac, and Linux (Step-by-Step Guide for Beginners) appeared first on Azad Chouhan.

What is Python? A Complete Beginner’s Guide to Learn Python in 2025

azad chouhan — Thu, 09 Oct 2025 17:16:33 +0000

Introduction: What is Python and Why Everyone is Talking About It?

If you’ve been around the tech world lately, you’ve probably heard people talk about Python. When I first started learning about coding, Python was the one name that kept coming up. It made me curious — what makes Python so popular?

Python is a high-level, easy-to-learn programming language used for web development, data science, automation, and artificial intelligence. It’s known for its simple syntax that looks more like English, which makes it perfect for beginners.

Whether you want to become a software developer, data analyst, or just automate boring tasks, learning Python is a great first step.

Why Python is the Best Language for Beginners

When I started with Python, what stood out to me was how readable it is. You don’t need to memorize complicated symbols or rules. You can write a program with just a few lines of code and still get powerful results.

1. Easy to Read and Write

Python’s syntax is clean and simple. It feels like writing plain English, which makes it easy to understand even if you’re not a tech expert.

2. Huge Community Support

Whenever I got stuck, I found countless tutorials, forums, and videos ready to help. Python has one of the largest coding communities, so you’ll never feel lost.

3. Versatile and Powerful

Python isn’t limited to one thing. You can use it for web development, machine learning, data analysis, automation, and even game development.

4. Great Career Opportunities

Companies like Google, Netflix, and Spotify use Python daily. Learning Python can open doors to many high-paying tech jobs.

Popular Uses of Python in Real Life

One thing that amazed me about Python is how widely it’s used. You interact with Python every day, even if you don’t realize it.

Web Development – Frameworks like Django and Flask help create websites and web apps.
Data Science & Machine Learning – Python powers data analysis, visualization, and AI tools.
Automation – You can automate simple tasks like sending emails or organizing files.
Cybersecurity – Ethical hackers use Python for testing and securing systems.
App Development – You can build mobile and desktop apps using Python libraries.

How to Start Learning Python as a Beginner

If you’re just starting out, here’s a simple plan that helped me:

Install Python – Visit python.org and download the latest version.
Start with Basics – Learn about variables, loops, and functions.
Practice Daily – Consistency is key. Spend at least 30 minutes coding every day.
Work on Small Projects – Build a calculator or a to-do app to test your skills.
Join Online Communities – Connect with others on Reddit, Stack Overflow, or Discord groups.

There are hundreds of free Python tutorials and courses online. Start small and focus on writing simple programs.

Benefits of Learning Python in 2025

With AI, automation, and data science taking over the world, Python has become more relevant than ever.

Some key benefits of learning Python now include:

High demand in job markets
Easier transition into other programming languages
Endless learning resources available
Great for freelancers and developers alike

Conclusion: Why You Should Start Learning Python Today

To sum it up, Python is simple, powerful, and beginner-friendly. It doesn’t matter if you’ve never written a single line of code — This can be your gateway to the tech world.

When I started, I didn’t know much about programming. But Python made me feel confident enough to keep going. If you’re serious about learning coding, there’s no better place to start.

The post What is Python? A Complete Beginner’s Guide to Learn Python in 2025 appeared first on Azad Chouhan.

Python Archives - Azad Chouhan

Master Python Numbers & Math Operations: Beginner’s Friendly Guide

1. What Are Python Number Types?

Integers (int)

Floating-point numbers (float)

Complex numbers (complex)

2. Basic Arithmetic Operators in Python

Quick examples

3. Type Conversion & Useful Number Functions

Type conversion (casting)

Useful functions

4. Common Pitfalls & Gotchas

Floating-point precision

Floor division with negatives

Mixing types

5. Simple Project: Mini Calculator

6. Why this knowledge helps

Final thoughts

How to Work with Strings in Python (Beginner-Friendly Guide)

What is a String in Python?

How to Access Characters in a String

String Slicing in Python

Common String Methods in Python

Joining and Formatting Strings

String Immutability in Python

Useful String Operations

Conclusion

Python Operators Explained Simply: A Complete Beginner’s Guide

What Are Python Operators?

Types of Python Operators

1. Arithmetic Operators

2. Comparison Operators

3. Logical Operators

4. Assignment Operators

5. Bitwise Operators

6. Membership Operators

7. Identity Operators

Why Are Python Operators Important?

My Personal Tip

Conclusion

Understanding Python Variables and Data Types — A Beginner-Friendly Guide

What is a Variable in Python?

Simple Rules for Naming Variables

Common Python Data Types (with examples)

1. Numbers (int, float, complex)

2. Strings (str)

3. Boolean (bool)

4. List

5. Tuple

6. Dictionary (dict)

7. Set

Check a Variable’s Type

Why Data Types Matter

Quick Reference Table

Conclusion

Best Python IDEs in 2025: Which One Should You Use?

What is an IDE in Python?

Top Python IDEs You Can Use in 2025

1. PyCharm (Best for Professionals)

2. Visual Studio Code (Best for Beginners and Pros Alike)

3. Jupyter Notebook (Best for Data Science)

4. Spyder (Best for Scientific Computing)

5. Thonny (Best for Absolute Beginners)

How to Choose the Right Python IDE

Final Thoughts

How to Install Python on Windows, Mac, and Linux (Step-by-Step Guide for Beginners)

Why Install Python?

1. How to Install Python on Windows

Step 1: Download Python

Step 2: Run the Installer

Step 3: Verify Installation

2. How to Install Python on Mac

Step 1: Check If Python Is Already Installed

Step 2: Install the Latest Python Version

Step 3: Verify Installation

3. How to Install Python on Linux

Step 1: Check If Python Is Installed

Step 2: Install Python Using Terminal

Step 3: Verify Installation

Tips After Installing Python

Integers (`int`)

Floating-point numbers (`float`)

Complex numbers (`complex`)