In Python, numbers are a fundamental data type used for math, logic, and data manipulation. Python supports multiple types of numeric values, including integers, floating-point numbers, and complex numbers.

This article covers:

• Numeric types in Python

• Type conversion

• Math operations

• Common pitfalls

• Tips and complete examples

Numeric Types in Python

Python supports three built-in numeric types:

Integers (int)

Integers are whole numbers without decimals.

x = 10
y = -3
z = 0

There is no limit on integer size in Python 3 — they can grow as large as memory allows.

Floating-Point Numbers (float)

Floats are real numbers with decimal points.

pi = 3.14159
temperature = -20.5

Scientific Notation:

avogadro = 6.022e23   # 6.022 × 10^23

Complex Numbers (complex)

Complex numbers have a real and imaginary part.

z = 2 + 3j
print(z.real)  # 2.0
print(z.imag)  # 3.0

Useful in advanced mathematics and signal processing.

Checking Number Types

Use type() or isinstance():

x = 42
print(type(x))               # <class 'int'>
print(isinstance(x, int))    # True

Type Conversion

Use these functions to convert between types:

float(3)        # 3.0
int(3.9)        # 3 (truncates decimal)
complex(2)      # (2+0j)
str(42)         # "42"

Beware: converting from float to int truncates, not rounds.

int(3.9)  # Output: 3

➕ Arithmetic Operators

Python supports all basic arithmetic operations:

Built-in Math Functions

Python includes useful built-in functions:

abs(-7)        # 7
round(3.1415, 2)  # 3.14
pow(2, 3)      # 8

Math Module

For advanced math, use the math module:

import math

print(math.sqrt(16))     # 4.0
print(math.floor(3.9))   # 3
print(math.ceil(3.1))    # 4
print(math.pi)           # 3.141592653589793

Example: Simple Calculator

# A simple calculator
a = float(input("Enter first number: "))
b = float(input("Enter second number: "))

print(f"Addition: {a + b}")
print(f"Subtraction: {a - b}")
print(f"Multiplication: {a * b}")
print(f"Division: {a / b}")

Tips for Working with Numbers

• Use float() when working with decimals or division.

• Use round() for precision formatting in financial calculations.

• Prefer math.isclose(a, b) for comparing floating-point numbers (avoids rounding errors).

• Use int() carefully — it truncates decimals, which can lead to bugs.

⚠️ Common Pitfalls

What's Next?

Once you're comfortable with numbers:

• Explore the decimal module for precision math (e.g. for finance)

• Learn the fractions module for rational numbers

• Understand numeric data in NumPy for scientific computing

 Summary