Book Image

R Programming By Example

By : Omar Trejo Navarro
Book Image

R Programming By Example

By: Omar Trejo Navarro

Overview of this book

R is a high-level statistical language and is widely used among statisticians and data miners to develop analytical applications. Often, data analysis people with great analytical skills lack solid programming knowledge and are unfamiliar with the correct ways to use R. Based on the version 3.4, this book will help you develop strong fundamentals when working with R by taking you through a series of full representative examples, giving you a holistic view of R. We begin with the basic installation and configuration of the R environment. As you progress through the exercises, you'll become thoroughly acquainted with R's features and its packages. With this book, you will learn about the basic concepts of R programming, work efficiently with graphs, create publication-ready and interactive 3D graphs, and gain a better understanding of the data at hand. The detailed step-by-step instructions will enable you to get a clean set of data, produce good visualizations, and create reports for the results. It also teaches you various methods to perform code profiling and performance enhancement with good programming practices, delegation, and parallelization. By the end of this book, you will know how to efficiently work with data, create quality visualizations and reports, and develop code that is modular, expressive, and maintainable.
Table of Contents (12 chapters)

Preparing, training, and testing data

As always, we will start by setting up our data. In this case, the data is the messages received by our fantasy company, The Cake Factory. These are in the client_messages.RDS file that we created in Chapter 4, Simulating Sales Data and Working with Databases. The data contains 300 observations for 8 variables: SALE_ID, DATE, STARS, SUMMARY, MESSAGE, LAT, LNG, and MULT_PURCHASES. During this chapter, we will work with the MESSAGE and MULT_PURCHASES variables.

We will set up our seed to have reproducible results. Keep in mind that this should be before every function call that involves some randomization. We will show it just once here to save space and avoid repeating ourselves, but keep that in mind when you are trying to generate reproducible results:

set.seed(12345)

Next, we need to make sure that we don't have any missing data in...