Book Image

Modern Python Cookbook. - Second Edition

By : Steven F. Lott
Book Image

Modern Python Cookbook. - Second Edition

By: Steven F. Lott

Overview of this book

Python is the preferred choice of developers, engineers, data scientists, and hobbyists everywhere. It is a great language that can power your applications and provide great speed, safety, and scalability. It can be used for simple scripting or sophisticated web applications. By exposing Python as a series of simple recipes, this book gives you insight into specific language features in a particular context. Having a tangible context helps make the language or a given standard library feature easier to understand. This book comes with 133 recipes on the latest version of Python 3.8. The recipes will benefit everyone, from beginners just starting out with Python to experts. You'll not only learn Python programming concepts but also how to build complex applications. The recipes will touch upon all necessary Python concepts related to data structures, object oriented programming, functional programming, and statistical programming. You will get acquainted with the nuances of Python syntax and how to effectively take advantage of it. By the end of this Python book, you will be equipped with knowledge of testing, web services, configuration, and application integration tips and tricks. You will be armed with the knowledge of how to create applications with flexible logging, powerful configuration, command-line options, automated unit tests, and good documentation.
Table of Contents (18 chapters)
16
Other Books You May Enjoy
17
Index

Average of values in a counter

The statistics module has a number of useful functions. These are based on having each individual data sample available for processing. In some cases, however, the data has been grouped into bins. We might have a collections.Counter object instead of a simple list. Rather than a collection of raw values, we now have a collection of (value, frequency) pairs.

Given frequency information, we can do essential statistical processing. A summary in the form of (value, frequency) pairs requires less memory than raw data, allowing us to work with larger sets of data.

Getting ready

The general definition of the mean is the sum of all of the values divided by the number of values. It's often written like this:

We've defined some set of data, C, as a sequence of n individual values, . The mean of this collection, , is the sum of the values divided by the number of values, n.

There's a tiny change in this definition...