🔢 Python Numbers – Everything You Need to Know (With Examples)

---

🪲 Introduction – Why Numbers Matter in Python

Whether you’re calculating scientific values, building finance apps, or analyzing data—numbers are at the core of Python programming. Python provides powerful tools to handle integers, floating points, complex numbers, and even fractions and decimals.

In this guide, you’ll learn:

• 📌 What types of numbers Python supports
• 🧠 How numeric operations work
• 💡 Best practices for working with each number type
• ✅ Practical examples with line-by-line explanations

---

🔑 Numeric Types in Python

Python categorizes numbers into the following core types:

Type	Description	Example
int	Integer (whole numbers)	5, -2, 0
float	Floating point numbers (with decimals)	3.14, -0.5
complex	Complex numbers with real and imaginary parts	3+4j, 2j
Decimal	Fixed-precision floating point from decimal module	Decimal('1.10')
Fraction	Rational numbers from fractions module	Fraction(3, 4)
bool	Boolean values (special case of integers: True=1, False=0)	True, False

📘 Python integers support unlimited precision, so large calculations like 2**1000 are possible without overflow.

---

🧪 Numeric Literals

Literal	Interpretation
123, -24, 0	Integer literals
3.14, 1e-10	Floating point (exponent supported)
0x9ff	Hexadecimal
0o377	Octal
0b101010	Binary
3+4j	Complex

📅 Any number with a decimal or exponent is a float, otherwise it’s an int.

---

➕ Arithmetic Operations with Explanation

a = 10      # Assign integer value 10 to variable 'a'
b = 3       # Assign integer value 3 to variable 'b'
print(a + b)    # 13: Adds a and b
print(a - b)    # 7: Subtracts b from a
print(a * b)    # 30: Multiplies a and b
print(a / b)    # 3.333...: Divides a by b (float result)
print(a // b)   # 3: Floor division, drops decimal part
print(a % b)    # 1: Modulo, remainder of a divided by b
print(a ** b)   # 1000: a raised to the power of b

---

🧠 Floating Point Precision

print(0.1 + 0.2 == 0.3)  # False: due to binary float inaccuracy

💭 To fix this, use decimal.Decimal:

from decimal import Decimal
print(Decimal('0.1') + Decimal('0.2') == Decimal('0.3'))  # True

---

⚙️ Math Functions

import math
print(math.sqrt(16))        # 4.0: square root
print(math.floor(2.9))      # 2: round down
print(math.ceil(2.1))       # 3: round up
print(math.pow(2, 3))       # 8.0: same as 2 ** 3
print(abs(-10))             # 10: absolute value

---

🔍 Complex Numbers

c = 3 + 4j
print(c.real)  # 3.0: real part
print(c.imag)  # 4.0: imaginary part

Use cmath for complex-specific math:

import cmath
print(cmath.sqrt(-1))  # 1j

---

📆 Fractions and Decimals

➕ Fractions

from fractions import Fraction
f = Fraction(3, 4)
print(f + Fraction(1, 4))  # 1

💵 Decimals

from decimal import Decimal
price = Decimal('19.99') + Decimal('0.01')
print(price)  # 20.00

---

🧠 Summary – Recap & Key Takeaways

Python provides robust numeric types and operations suitable for simple calculations to advanced scientific computing.

🔹 Key Takeaways:

• Python has built-in support for int, float, and complex
• Use Decimal for financial accuracy
• Use Fraction for rational math
• Precision errors occur with binary float
• math and cmath provide advanced math tools

💡 Real-World Relevance:

• Used in finance apps, simulations, machine learning, and data analytics

---

❓ FAQ – Python Numbers

🤔 What is the difference between int and float?

int is for whole numbers, float includes decimals.

🚫 Why is 0.1 + 0.2 != 0.3?

Because of binary floating-point inaccuracies. Use Decimal for precision.

🤑 Can I use really large integers in Python?

Yes. Python supports arbitrarily large integers like 2 ** 10000.

🫹 How do I represent exact fractions?

Use the fractions.Fraction class for precise rational arithmetic.

👀 Can I do trigonometry or log operations?

Yes, use the math or cmath modules for advanced functions.

---

Share Now :