Python Numeric Datatypes

In Python, numeric data types represent numbers and can be used for various mathematical operations. Here are the main numeric data types:

Integers (`int`):

- Integers are whole numbers without a fractional part.

				
					age = 25

Floats (`float`):

- Floats represent real numbers with a decimal point or in scientific notation.

				
					height = 5.9

Complex Numbers(`complex`):

- Complex numbers have a real and an imaginary part.

				
					complex_number = 3 + 4j

Basic Numeric Operations:

- Arithmetic Operations:

				
					a = 5
b = 2

# Addition
sum_result = a + b  # Outputs: 7

# Subtraction
diff_result = a - b  # Outputs: 3

# Multiplication
product_result = a * b  # Outputs: 10

# Division
division_result = a / b  # Outputs: 2.5

- Exponentiation and Modulus:

				
					# Exponentiation
power_result = a ** b  # Outputs: 25

# Modulus (remainder)
modulus_result = a % b  # Outputs: 1

Type Conversion:

- You can convert between numeric data types using type conversion functions like int(), float(), and complex().

				
					# Convert float to integer
x = int(5.9)  # Outputs: 5

# Convert integer to float
y = float(42)  # Outputs: 42.0

# Convert integer to complex
z = complex(3)  # Outputs: (3+0j)

Dictionaries (`dict`):

- Key-value pairs, used to store data in a structured way.

				
					person = {"name": "Alice", "age": 30, "city": "New York"}

Sets (`set`):

- Unordered collections of unique items.

				
					unique_numbers = {1, 2, 3, 4, 5}

None Type (`NoneType`):

- Represents the absence of a value or a null value.

				
					result = None

Type Conversion:

You can convert between different data types using functions like int(), float(), str(), etc.

				
					# Convert float to integer
x = int(5.9)  # Outputs: 5

# Convert integer to float
y = float(42)  # Outputs: 42.0

# Convert integer to complex
z = complex(3)  # Outputs: (3+0j)

Math Library:

Python provides a math library for more advanced mathematical functions.

				
					import math

# Square root
sqrt_result = math.sqrt(25)  # Outputs: 5.0

# Trigonometric functions
sin_result = math.sin(math.radians(30))  # Outputs: 0.49999999999999994

Understanding numeric data types and operations is crucial for performing mathematical calculations in Python. These types provide flexibility and precision for a wide range of applications, from basic arithmetic to complex scientific computations.