In Python, numbers are a fundamental data type used to represent numerical values. Python supports several types of numbers, each serving different purposes and having distinct characteristics. Here’s an overview of the main numeric data types in Python:

Integer (int)

Integers are whole numbers, positive or negative, without decimals.

x = 10
y = -5
z = 0

Floating-Point (float)

Floating-point numbers are numbers with a decimal point or an exponent notation.

a = 3.14
b = -0.001
c = 2.0

Complex Numbers (complex)

Complex numbers are numbers with a real and imaginary part represented as a + bj, where a and b are floats and j is the imaginary unit.

d = 2 + 3j
e = -1j

Operations on Numbers

Python supports various operations on numeric data types:

• Arithmetic Operations: Addition (+), Subtraction (-), Multiplication (*), Division (/), Floor Division (//), Modulus (%), Exponentiation (**).

x = 10
y = 3
print(x + y)   # Output: 13
print(x - y)   # Output: 7
print(x * y)   # Output: 30
print(x / y)   # Output: 3.3333333333333335
print(x // y)  # Output: 3 (floor division)
print(x % y)   # Output: 1 (remainder)
print(x ** y)  # Output: 1000 (exponentiation)

• Conversion between Types: You can convert numeric types using built-in functions like int(), float(), and complex().

num_int = 10
num_float = float(num_int)     # Converts int to float
num_complex = complex(num_int) # Converts int to complex

Built-in Functions

Python provides several built-in functions for numeric operations:

• abs(): Returns the absolute value of a number.
• round(): Rounds a number to a specified precision.
• max() and min(): Returns the maximum or minimum of two or more numbers.
• pow(): Returns the value of x to the power of y.
• sum(): Returns the sum of all elements in an iterable (e.g., list, tuple).

print(abs(-5))         # Output: 5
print(round(3.14159, 2))  # Output: 3.14 (round to 2 decimal places)
print(max(1, 2, 3))    # Output: 3 (maximum of the numbers)
print(min(-1, 0, 1))   # Output: -1 (minimum of the numbers)
print(pow(2, 3))       # Output: 8 (2 raised to the power of 3)
print(sum([1, 2, 3, 4]))  # Output: 10 (sum of elements in the list)

Precision and Limitations

• Precision: Floating-point arithmetic may not always yield exact results due to limitations in how computers represent real numbers.

print(0.1 + 0.2)   # Output: 0.30000000000000004 (floating-point precision issue)

• Large Numbers: Python supports arbitrarily large integers (limited by available memory) and handles overflow automatically.

large_num = 1234567890123456789012345678901234567890

Summary

Understanding Python’s numeric data types and their operations is essential for performing calculations, manipulating data, and writing efficient programs. Python’s flexibility with numbers, including support for complex numbers and arbitrary precision integers, makes it suitable for a wide range of computational tasks.