R Projects For Dummies

Make the most of R's extensive toolset

R Projects For Dummies offers a unique learn-by-doing approach. You will increase the depth and breadth of your R skillset by completing a wide variety of projects. By using R's graphics, interactive, and machine learning tools, you'll learn to apply R's extensive capabilities in an array of scenarios. The depth of the project experience is unmatched by any other content online or in print. And you just might increase your statistics knowledge along the way, too!

R is a free tool, and it's the basis of a huge amount of work in data science. It's taking the place of costly statistical software that sometimes takes a long time to learn. One reason is that you can use just a few R commands to create sophisticated analyses. Another is that easy-to-learn R graphics enable you make the results of those analyses available to a wide audience.

This book will help you sharpen your skills by applying them in the context of projects with R, including dashboards, image processing, data reduction, mapping, and more.

• Appropriate for R users at all levels

• Helps R programmers plan and complete their own projects

• Focuses on R functions and packages

• Shows how to carry out complex analyses by just entering a few commands

If you're brand new to R or just want to brush up on your skills, R Projects For Dummies will help you complete your projects with ease.

Auteur

Joseph Schmuller, PhD, is a veteran of more than 25 years in Information Technology. He is the author of several books, including Statistical Analysis with R For Dummies and four editions of Statistical Analysis with Excel For Dummies. In addition, he has written numerous articles and created online coursework for Lynda.com.

Résumé
Make the most of R's extensive toolset

R Projects For Dummies offers a unique learn-by-doing approach. You will increase the depth and breadth of your R skillset by completing a wide variety of projects. By using R's graphics, interactive, and machine learning tools, you'll learn to apply R's extensive capabilities in an array of scenarios. The depth of the project experience is unmatched by any other content online or in print. And you just might increase your statistics knowledge along the way, too!

R is a free tool, and it's the basis of a huge amount of work in data science. It's taking the place of costly statistical software that sometimes takes a long time to learn. One reason is that you can use just a few R commands to create sophisticated analyses. Another is that easy-to-learn R graphics enable you make the results of those analyses available to a wide audience.

This book will help you sharpen your skills by applying them in the context of projects with R, including dashboards, image processing, data reduction, mapping, and more.

• Appropriate for R users at all levels
• Helps R programmers plan and complete their own projects
• Focuses on R functions and packages
• Shows how to carry out complex analyses by just entering a few commands
  If you're brand new to R or just want to brush up on your skills, R Projects For Dummies will help you complete your projects with ease.

Contenu

Introduction 1

About This Book 2

Part 1: The Tools of the Trade 2

Part 2: Interacting with a User 2

Part 3: Machine Learning 2

Part 4: Large(ish) Data Sets 2

Part 5: Maps and Images 2

Part 6: The Part of Tens 3

What You Can Safely Skip 3

Foolish Assumptions 3

Icons Used in This Book 3

Beyond the Book 4

Where to Go from Here 4

Part 1: the Tools of the Trade 5

Chapter 1: R: What It Does and How It Does It 7

Getting R 7

Getting RStudio 8

A Session with R 11

The working directory 11

Getting started 12

R Functions 15

User-Defined Functions 16

Comments 18

R Structures 18

Vectors 18

Numerical vectors 19

Matrices 21

Lists 24

Data frames 25

Of for Loops and if Statements 28

Chapter 2: Working with Packages 31

Installing Packages 31

Examining Data 33

Heads and tails 33

Missing data 33

Subsets 34

R Formulas 35

More Packages 36

Exploring the tidyverse 37

Chapter 3: Getting Graphic 43

Touching Base 43

Histograms 44

Density plots 45

Bar plots 47

Grouping the bars 49

Quick Suggested Project 51

Pie graphs 53

Scatterplots 53

Scatterplot matrix 55

Box plots 56

Graduating to ggplot2 57

How it works 58

Histograms 59

Bar plots 61

Grouped bar plots 62

Grouping yet again 64

Scatterplots 67

The plot thickens 68

Scatterplot matrix 72

Box plots 73

Part 2: Interacting with a User 77

Chapter 4: Working with a Browser 79

Getting Your Shine On 79

Creating Your First shiny Project 80

The user interface 83

The server 84

Final steps 85

Getting reactive 86

Working with ggplot 89

Changing the server 90

A few more changes 92

Getting reactive with ggplot 94

Another shiny Project 96

The base R version 97

The ggplot version 104

Suggested Project 106

Chapter 5: Dashboards How Dashing! 107

The shinydashboard Package 107

Exploring Dashboard Layouts 108

Getting started with the user interface 109

Building the user interface: Boxes, boxes, boxes 110

Lining up in columns 117

A nice trick: Keeping tabs 121

Suggested project: Add statistics 125

Suggested project: Place valueBoxes in tabPanels 126

Working with the Sidebar 126

The user interface 128

The server 131

Suggested project: Relocate the slider 133

Interacting with Graphics 135

Clicks, double-clicks, and brushes oh, my! 135

Why bother with all this? 138

Suggested project: Experiment with airquality 141

Part 3: Machine Learning 143

Chapter 6: Tools and Data for Machine Learning Projects 145

The UCI (University of California-Irvine) ML Repository 146

Downloading a UCI dataset 146

Cleaning up the data 148

Exploring the data 150

Exploring relationships in the data 152

Introducing the Rattle package 157

Using Rattle with iris 159

Getting and (further) exploring the data 159

Finding clusters in the data 162

Chapter 7: Decisions, Decisions, Decisions 167

Decision Tree Components 167 Roots and leaves 168</p...