Graphing Data with R An Introduction

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Название:Graphing Data with R An Introduction

АвторJohn Jay Hilfiger

Издательство: O'Reilly Media

Год: 2015

Страниц: 336

Язык: English

Формат: azw3, pdf

Размер: 9 Mb; 16 Mb

It’s much easier to grasp complex data relationships with a graph than by scanning numbers in a spreadsheet. This introductory guide shows you how to use the R language to create a variety of useful graphs for visualizing and analyzing complex data for science, business, media, and many other fields. You’ll learn methods for...

highlighting important relationships and trends, reducing data to simpler forms, and emphasizing key numbers at a glance.

Anyone who wants to analyze data will find something useful here—even if you don’t have a background in mathematics, statistics, or computer programming. If you want to examine data related to your work, this book is the ideal way to start.

Get started with R by learning basic commands

Build single variable graphs, such as dot and pie charts, box plots, and histograms

Explore the relationship between two quantitative variables with scatter plots, high-density plots, and other techniques

Use scatterplot matrices, 3D plots, clustering, heat maps, and other graphs to visualize relationships among three or more variables

Getting Started with R

Chapter 1R Basics

Downloading the Software

Try Some Simple Tasks

User Interface

Installing a Package: A GUI Interface

Data Structures

Sample Datasets

The Working Directory

Putting Data into R

Sourcing a Script

User-Written Functions

A Taste of Things to Come

Chapter 2An Overview of R Graphics

Exporting a Graph

Exploratory Graphs and Presentation Graphs

Graphics Systems in R

Single-Variable Graphs

Chapter 3Strip Charts

A Simple Graph

Data Can Be Beautiful

Chapter 4Dot Charts

Basic Dot Chart

Exercise 4-1

Chapter 5Box Plots

The Box Plot

Nimrod Again

Making the Data Beautiful

Chapter 6Stem-and-Leaf Plots

Basic Stem-and-Leaf Plot

Exercise 6-1

Chapter 7Histograms

Simple Histograms

Histograms with a Second Variable

Chapter 8Kernel Density Plots

Density Estimation

The Cumulative Distribution Function

Chapter 9Bar Plots (Bar Charts)

Basic Bar Plot

Spine Plot

Bar Spacing and Orientation

Chapter 10Pie Charts

Ordinary Pie Chart

Fan Plot

Chapter 11Rug Plots

The Rug Plot

Exercise 11-1

Two-Variable Graphs

Chapter 12Scatter Plots and Line Charts

Basic Scatter Plots

Line Charts

Templates

Enhanced Scatter Plots

Chapter 13High-Density Plots

Working with Large Datasets

Chapter 14The Bland-Altman Plot

Assessing Measurement Reliability

Chapter 15QQ Plots

Comparing Sets of Numbers

Multivariable Graphs

Chapter 16Scatter plot Matrices and Corrgrams

Scatter plot Matrix

Corrgram

Generalized Pairs Matrix with Mixed Quantitative and Categorical Variables

Chapter 17Three-Dimensional Plots

3D Scatter plots

False Color Plots

Bubble Plots

Chapter 18Coplots (Conditioning Plots)

The Coplot

Exercise 18-1

Chapter 19Clustering: Dendrograms and Heat Maps

Clustering

Heat Maps

Chapter 20Mosaic Plots

Graphing Categorical Data

What Now?

Chapter 21Resources for Extending Your Knowledge of Things Graphical and R Fluency

R Graphics

General Principles of Graphics

Learning More About R

Statistics with R

Appendix References

Appendix R Colors

Appendix The R Commander Graphical User Interface

Appendix Packages Used/Referenced

Appendix Importing Data from Outside of R

Some Useful Internet Data Repositories

Importing Data of Various Types into R

Appendix Solutions to Chapter Exercises

Exercises 1-1 Through 1-4

Exercise 3-1

Exercise 3-2

Exercise 4-1

Exercise 4-2

Exercise 5-1

Exercise 5-2

Exercise 6-1

Exercise 6-2

Exercise 7-1

Exercise 8-1

Exercise 8-2

Exercise 9-1

Exercise 9-2

Exercise 10-1

Exercise 10-2

Exercise 11-1

Exercise 12-1

Exercise 12-2

Exercise 13-1

Exercise 14-1

Exercise 15-1

Exercise 15-2

Exercise 16-1

Exercise 17-1

Exercise 17-2

Exercise 18-1

Exercise 19-1

Exercise 19-2

Exercise 19-3

Exercise 20-1

Exercise 21-1

Appendix Troubleshooting: Why Doesn’t My Code Work?

Misspelling

Confusing Uppercase/Lowercase

Too Few (or Too Many) Parenthesis Signs

Forgetting to Load a Package

Forgetting to Install a Package

A Dataset in a Loaded Package Is Not Found

Leaving Out a Comma

Copy-and-Paste Error

Directory Problems—Cannot Load a Saved File

Missing File Extension

Do Not Assume That All Packages Use the Same Argument Abbreviations

Outdated Packages/Package Incompatibility

Appendix R Functions Introduced in This Book

Data Input/Output

Datasets

Graphical Functions 1—Creates Graph

Graphical Functions 2—Adds Features to Existing Graph

Miscellaneous

Packages

Statistics

User-Defined Functions and Scripts

Workspace and Directories

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