[Packt] R Graph Essentials

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책은 2014년에 출간되었어요

R_Graph_Essentials_David Alexander Lillis

R Graph Essentials

Use R's powerful graphing capabilities to design and create professional-level graphics

David Alexander Lillis

About the Author

David Alexander Lillis is an experienced researcher and statistician, having worked in research evaluation, agricultural and forestry statistics, and education research and statistics. 

Currently, David delivers lectures in mathematics, statistics, and research methods at the New Zealand Institute of Sport in New Zealand.

He is the owner and Director of Sigma Statistics and Research Limited, a New Zealand-based consultancy specializing in training, software development, data analysis, and statistical modelling using R. David holds an Honor's degree and Master's degree in Physics and Mathematics, and a PhD from Curtin University in Perth, Australia.

About the Reviewers

Mzabalazo Z. Ngwenya has worked extensively in the field of statistical consulting and currently works as a biometrician. 

He holds an MSc degree in Mathematical Statistics from the University of Cape Town, and is currently pursuing a PhD. His research interests include statistical computing, machine learning, and spatial statistics.

Previously, he was involved in reviewing Learning RStudio for R Statistical Computing, Mark P.J. van der Loo and Edwin de Jonge, Packt Publishing; R Statistical Application Development by Example Beginner's Guide, Prabhanjan Narayanachar Tattar, Packt Publishing; and Machine Learning with R, Brett Lantz, Packt Publishing.

Donato Teutonico has several years of experience in the modeling and simulation of drug effects and clinical trials in industrial and academic settings. He received his Pharm.D. degree from the University of Turin, Italy, specializing in Chemical and Pharmaceutical Technology, and his PhD in Pharmaceutical Sciences from Paris-Sud University, France.

He is the author of two R packages for Pharmacometrics: CTS template and panels-for-pharmacometrics; both are available on Google code. He is also the author of Instant R Starter, Packt Publishing.

Tengfei Yin earned his BS degree in Biological Science and Biotechnology from Nankai University in China and a PhD in Molecular, Cellular and Developmental Biology (MCDB) with a focus on computational biology and bioinformatics from Iowa State University. 

His research interests include information visualization, high-throughput biological data analysis, data mining, machine learning, and applied statistical genetics. He has developed and maintained several software packages in R and Bioconductor.

Table of Contents

Preface 1

Chapter 1: Base Graphics in R – One Step at a Time 5

Learning basic graphics techniques 6

Creating and joining points 10

Creating scatterplots and line plots 12

Colors in R 14

Passing parameter values to titles and labels 15

Including a regression line 18

Graphing mathematical functions 19

R provides many options 20

Creating graphs with several curves 22

Customizing your axes 23

Creating axis labels 24

Creating multiple graphs on the same page 27

Saving your graphs 28

Including mathematical expressions on your plots 30

Summary 32

Chapter 2: Advanced Functions in Base Graphics 33

Reading datasets into R 34

Including a regression line and residuals 34

A medical dataset to create graphs 41

Creating complex multiple axes 43

Superposing graphs 46

Creating point labels 47

Including a grid on your graph 48

Shading and coloring your graph 50

Using polygon() to shade under a normal curve 55

Creating bar charts 58

Including a legend 62

Creating histograms 66

Creating boxplots 74

Creating pie charts 76

Creating dotcharts 80

R's color palettes 88

Using smoothers on your graph 88

Creating scatterplot matrices 89

Writing functions to create graphs 91

Including error bars on your graph 92

Summary 94

Chapter 3: Mastering the qplot Function 95

About qplot 95

The qplot syntax 96

Producing scatterplots using qplot 96

Subsetting your data before graphing 98

Mapping aesthetics to categorical variables 100

Controlling colors on your graph 102

Setting up graphs as objects 105

Creating facet plots 106

Creating line graphs using qplot 108

Creating multiple curves simultaneously 111

Including smoothed curves 112

Creating histograms with qplot 118

Creating facet plots for histograms 120

Creating kernel density plots 121

Creating bar charts 124

Creating boxplots 127

Creating graphs with dates 130

Summary 138

Chapter 4: Creating Graphs with ggplot 139

Getting started with ggplot 140

Mapping color, shape, and size to a variable 144

Modifying the plotting background 146

Controlling the legend name and legend labels 148

Modifying the x and y axes 149

Creating attractive color schemes 151

Creating curves for each factor level 152

Creating histograms 154

Creating bar charts 156

Creating a stacked bar chart 158

Creating a grouped bar chart 160

Creating a faceted bar chart 161

Creating boxplots 162

Labeling points with text 164

Mapping color to text 166

Including regression lines 168

Summary 171

Index 173

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