Book Image

Practical Data Science Cookbook, Second Edition - Second Edition

By : Prabhanjan Narayanachar Tattar, Bhushan Purushottam Joshi, Sean Patrick Murphy, ABHIJIT DASGUPTA, Anthony Ojeda
Book Image

Practical Data Science Cookbook, Second Edition - Second Edition

By: Prabhanjan Narayanachar Tattar, Bhushan Purushottam Joshi, Sean Patrick Murphy, ABHIJIT DASGUPTA, Anthony Ojeda

Overview of this book

As increasing amounts of data are generated each year, the need to analyze and create value out of it is more important than ever. Companies that know what to do with their data and how to do it well will have a competitive advantage over companies that don’t. Because of this, there will be an increasing demand for people that possess both the analytical and technical abilities to extract valuable insights from data and create valuable solutions that put those insights to use. Starting with the basics, this book covers how to set up your numerical programming environment, introduces you to the data science pipeline, and guides 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 using the two most popular programming languages for data analysis—R and Python.
Table of Contents (17 chapters)
Title Page
Credits
About the Authors
About the Reviewer
www.PacktPub.com
Preface

Screening stocks and analyzing historical prices


When we are looking for stocks to invest in, we need to have a way to narrow the list down. In other words, we need to eliminate stocks that we don't think will be good investments. The definition of a good investment varies from person to person, but in this section, we will use some basic criteria to reduce our master list of stocks to just a few that we think might make good prospects. Once comfortable with the process, we encourage you to modify the criteria based on your own opinion of what defines a stock worth investing in. Once we have our prospects, we will analyze their historical prices and see what conclusions we can draw from them.

Getting ready

We will start with the finviz dataset as it was at the end of the previous section, along with the sector and industry averages columns, the binary undervalued columns, and the index values that summed up the values in the binary columns.

In addition to the packages we have used so far in...