Book Image

Practical Data Science Cookbook

By : Tony Ojeda, Sean Patrick Murphy, Benjamin Bengfort, Abhijit Dasgupta
Book Image

Practical Data Science Cookbook

By: Tony Ojeda, Sean Patrick Murphy, Benjamin Bengfort, Abhijit Dasgupta

Overview of this book

<p>As increasing amounts of data is generated each year, the need to analyze and operationalize it is more important than ever. Companies that know what to do with their data will have a competitive advantage over companies that don't, and this will drive a higher demand for knowledgeable and competent data professionals.</p> <p>Starting with the basics, this book will cover how to set up your numerical programming environment, introduce you to the data science pipeline (an iterative process by which data science projects are completed), and guide you through several data projects in a step-by-step format. By sequentially working through the steps in each chapter, you will quickly familiarize yourself with the process and learn how to apply it to a variety of situations with examples in the two most popular programming languages for data analysis—R and Python.</p>
Table of Contents (18 chapters)
Practical Data Science Cookbook
Credits
About the Authors
About the Reviewers
www.PacktPub.com
Preface
Index

Simulating multiple games with outcomes decided by calculations


It turns out that once we build a way to calculate the outcome of a single game, simulating multiple games doesn't require much more work. In fact, you just need a way to determine a schedule of games in advance, put the code we used in the last section into a loop, and then create a way to keep track of how many games each team has won or lost. This is exactly what we will do in this section.

Getting ready

If you completed the previous recipe, you should already have approximately a third of the code you will need for this section.

How to do it…

Perform the following steps to simulate multiple games using the same logic as in the previous recipe:

  1. As mentioned previously, the first thing we will need to do is create a schedule of games to know which teams are going to play each other. There are a few ways to do this, one of which is importing the actual season schedule. For illustrative purposes, we will generate our own schedule...