A Survivor′s Guide to R (eBook)

Chapter 1: Getting Started
Things Your Statistics Class Probably Won't Teach You
Why R?
Statistical Modeling
A Few R Basics
Saving Your Work
R Packages
Help with R Help
Organization of this Book
Chapter 2: A Sample Session
Reviewing Your Data
Data Visualization
Hypothesis Testing for Fun and Profit
A Regression Model
A Nonlinear Model
Chapter 3: Object Types in R
R Objects And Their Names
How to Think about Data Objects in R
R Object Storage Modes
R Data Object Types
The Basic Data Objects: Vectors
The Basic Data Objects: Matrices and Their Indices
The Basic Data Objects: Data Frames
The Basic Data Objects: Lists
A Few Things about Working with Objects
Object Attributes
Objects and Environments
R Object Classes
The Pseudo Storage Modes
Date and Time as a Storage Modes
Factors
Coercing Storage Modes
The Curse of Number-Character-Factor Confusion
Conclusions
Chapter 4: Getting Your Data Into R
Entering Data
Creating Data
Importing Data
The Read Command: Overview
The Read Command: Reading from the Clipboard
The Read Command: Blank Delimited Tables
The Read Command: Comma Separated Values
The Read Command: Tab Separated Data
The Read Command: Fixed-Width Data
Importing Foreign File Types
Integrating SQL with R
Extracting Data from Complex Data Sources
Web Scraping
Dealing with Multi-Dimensional Data
Importing Problematic Characters
More Resources
Chapter 5: Reviewing and Summarizing Data
Summary Functions
Checking A Sample Of Your Data
Reviewing Data By Categories
Displaying Data With A Histogram
Displaying Data With A Scatter Plot
Scatter Plot Matrices
Chapter 6: Sorting and Selecting Data
Using Index Values to Select Data
Using Conditional Values for Selecting
Using Subset( ) with Variable or Row Names to Select Data
Splitting a Dataset into Groups
Splitting Up Continuous Numeric Data
Sorting And Ordering Data
Chapter 7: Transforming Data
Creating New Variables
Editing Data
Basic Math with R
R Functions
Math and Logical Functions in R
Truncation and Rounding Functions
The Apply( ) Family of Functions
Changing Variable Values Conditionally
Creating New Functions
Additional R Programming
Character Strings as Program Elements and Program Elements as Character Strings
Chapter 8: Text Operations
Some Useful Text Functions
Finding Things
Regular Expressions
Processing Raw Text Data
Scraping the Web for Fun And Profit
Chapter 9: Working With Date And Time DataDates in R
Dates in R
Formatting Dates for R
Working with POSIX Dates
Special Date Operations
Formatting Dates for Output
Time Series Data
Creating Moving Averages in Time-Series Data
Lagged Variables in Time-Series Data
Differencing Variables in Time-Series Data
The Limitations of ts Data
Chapter 10: Data Merging And Aggregation
Dataset Concatenation
Match Merging
Keyed Table Look-up Merging
Aggregating Data
Transposing and Rotating Datasets
Chapter 11: Dealing with Missing Data
Reading Data with Missing Values
Summarizing Missing Values
The Missing Values Functions
Recoding Missing Values
Missing Values And Regression Modeling
Visualizing Missing Data
Chapter 12: R Graphics I: The Built-in Plots
Scatter Plots
Pairs Plots
Line Plots
Box Plots
Histograms, Density Plots, and Bar Charts
Dot Charts
Pie Charts
Mosaic Plots
Conclusions
Chapter 13: R Graphics II: The Boring Stuff
The Graphics Device
Graphics Parameters
The Plot Layout
Graphic Coordinates in R
Overlaying Plots
Multiple Plots
Conclusions
Chapter 14: R Graphics III: The Fun Stuff--Text
Adding Text
Setting up a Font
Titles and Subtitles
Creating a Legend
Simple Axes and Axis Labels
Building More Complex Axes
Ad-hoc Text
Chapter 15: R Graphics IV: The Fun Stuff--Shapes
Doing Colors
Custom Points
Adding Lines
Shapes
Incorporating Images into Plots
A Final Word about Aesthetics
Chapter 16 from Here to Where?