📖
Introduction to programming with Python
  • Introduction to programming with Python 3
  • Preface
    • Common misconceptions about learning to program
    • The Hard truth about learning to program
    • Personal qualities for success
  • 1 - The way of the program
    • Python Programming Language
    • The first program
    • What is debugging?
    • Glossary
    • Exercises
  • 2 - Variables, expressions and statements
    • Values, types and variables
    • Common Built-in data types
    • Expressions
    • Code Format
    • Debugging
    • Glossary
    • Exercises
  • 3 - Functions
    • Python "built-in" Functions
    • Math Functions
    • Composition
    • User Defined Functions
    • PEP 8 Recommendations
    • Debugging
    • Glossary
    • Exercises
  • 4 - Conditionals
    • Boolean expressions
    • Conditional statements
    • PEP 8 Recommendations
  • 5 - Iteration
    • The while statement
    • The for statement
    • break and continue statements
    • Nested Loops
    • PEP 8 Recommendations
    • Debugging
    • Glossary
    • Exercises
  • 6 - A short introduction to testing: Building Reliable Software
  • 7 - A deeper dive into Strings, Lists and Tuples
    • More on Strings
    • More on Lists
    • More on Tuples
    • Debugging
    • Glossary
    • Exercises
  • 8 - A deeper look at Functions in Python
    • Function Preconditions and Postconditions
    • Positional and Keywords arguments
    • Nested Functions
    • Scope of a variable
    • Recursion
    • Functions' side effects
    • Glossary
    • Exercises
  • 9 - Code Documentation
    • Basics of Commenting Code
    • Documenting Code via Python Docstring
  • 10 - Sets and dictionaries
    • Sets
    • Dictionaries
    • Which data structure should I use?
    • Debugging
    • Glossary
    • Exercises
  • 11 - File I/O
    • Read/Write to a file
    • File management
    • Debugging
    • Glossary
    • Exercises
  • 12 - Handling Errors and Exceptions
  • 13 - Writing modules
  • 14 - Classes
    • Classes and Objects
    • Classes and Functions
    • Classes and Methods
    • Pythonic Magic: Understanding and Implementing Dunder Methods
    • Glossary
    • Exercises
  • 15 - Python's Type Hinting
  • Acknowledgements
Powered by GitBook
On this page
Edit on GitHub
  1. 3 - Functions

Math Functions

Python has a math module that provides most of the familiar mathematical functions. A module is a file that contains a collection of related functions.

Before we can use the module, we have to import it:

import math

This statement creates a module object named. The module object contains the functions and variables defined in the module. To access one of the functions, you have to specify the name of the module and the name of the function, separated by a dot (also known as a period). This format is called dot notation.

import math

# Example 1
ratio = signal_power / noise_power 
decibels = 10 * math.log10(ratio)

# Example 2
radians = 0.7 
height = math.sin(radians)

The first example computes the logarithm base 10 of the signal-to-noise ratio. The math module also provides a function called log that computes logarithms base e.

The second example finds the sine of radians. The name of the variable is a hint that sin and the other trigonometric functions (cos, tan, etc.) take arguments in radians. To convert from degrees to radians, divide by 360 and multiply by 2Ï€2 \pi2Ï€:

>>> degrees = 45 
>>> radians = degrees / 360.0 * 2 * math.pi 
>>> math.sin(radians) 
 0.707106781187 
>>>

The expression math.pi gets the variable pi from the math module. The value of this variable is an approximation of π\piπ, accurate to about 15 digits.

Exercise
PreviousPython "built-in" FunctionsNextComposition

Last updated 1 year ago

Explore the math module either by using the help function from the interpreter prompt or by visiting the .

official python documentation webpage