Numeric Types in Python

Numeric types are among the most fundamental data types in Python. They allow developers to represent and perform operations on numeric values such as integers, decimal numbers, and even complex numbers. Python provides three distinct numeric types:

• int – Integer values
• float – Floating-point decimal values
• complex – Complex numbers with real and imaginary parts

This article explores each of these types in detail, including syntax, behavior, and practical examples.

1. int – Integer Type

The int type represents whole numbers (both positive and negative) without any decimal part. Python integers are of arbitrary precision, meaning they can be very large, limited only by memory.

Characteristics:

• No fractional part
• Supports binary, octal, and hexadecimal literals
• Commonly used in counting, indexing, and integer arithmetic

Example 1: Basic Integer Assignment and Arithmetic

a = 10
b = 4
print(a + b)      # Output: 14

This demonstrates basic addition using integer values.

Example 2: Integer Division and Floor Division

a = 10
print(a / 3)      # Output: 3.333...
print(a // 3)     # Output: 3 (floor division)

Note that / returns a float, while // returns an int by removing the fractional part.

Example 3: Working with Binary, Octal, and Hexadecimal

bin_num = 0b1010       # binary (10)
oct_num = 0o12         # octal (10)
hex_num = 0xA          # hexadecimal (10)
 
print(bin_num + oct_num + hex_num)  # Output: 30

Python allows integer literals in various bases using prefixes like 0b, 0o, and 0x.

2. float – Floating-Point Numbers

The float type is used to represent decimal or real numbers with a fractional component. Python floats are based on the IEEE 754 double-precision format.

Characteristics:

• Represent numbers with decimals (e.g., 3.14, -0.5)
• Subject to rounding errors due to binary representation
• Useful in scientific, financial, and statistical computations

Example 1: Basic Float Assignment and Operations

pi = 3.14159
radius = 5
area = pi * radius ** 2
print("Area:", area)

Calculates the area of a circle using floating-point arithmetic.

Example 2: Rounding and Formatting

value = 10 / 3
print(round(value, 2))     # Output: 3.33
print(f"{value:.4f}")      # Output: 3.3333

Shows how to round and format float values for presentation.

Example 3: Scientific Notation

mass = 5.97e24       # Earth's mass in kilograms
speed = 3.0e8        # Speed of light in m/s
energy = mass * speed ** 2
print("E =", energy)

Demonstrates how to use exponential notation for large or small values.

3. complex – Complex Numbers

The complex type is used to represent numbers with a real and an imaginary part. This is useful in fields like electrical engineering, control systems, and quantum physics.

Characteristics:

• Written in the form a + bj, where a is the real part and b is the imaginary part
• The imaginary unit in Python is j (not i)
• Python includes built-in support for arithmetic and mathematical operations with complex numbers

Example 1: Declaring and Printing a Complex Number

z = 3 + 4j
print("Real part:", z.real)
print("Imaginary part:", z.imag)

Accesses and displays the real and imaginary components of the complex number.

Example 2: Complex Number Arithmetic

z1 = 2 + 3j
z2 = 1 - 1j
result = z1 * z2
print("Multiplication:", result)

Performs multiplication between two complex numbers.

Example 3: Using cmath Module

import cmath
 
z = 1 + 1j
polar = cmath.polar(z)
print("Polar coordinates:", polar)

Uses the cmath module for advanced complex math operations, such as converting to polar coordinates.

Summary

Python makes working with numeric types straightforward, but precision, formatting, and type interaction must be handled carefully.

In the next section, we’ll explore Python’s text type — str — and how to work with strings effectively.