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by Kun Ren
Learning R Programming
Learning R Programming
Learning R Programming
Credits
About the Author
About the Reviewer
www.PacktPub.com
Why subscribe?
Preface
What this book covers
What you need for this book
Who this book is for
Conventions
Reader feedback
Customer support
Downloading the example code
Errata
Piracy
Questions
1. Quick Start
Introducing R
R as a programming language
R as a computing environment
R as a community
R as an ecosystem
The need for R
Installing R
RStudio
RStudio's user interface
The console
The editor
The Environment pane
The History pane
The File pane
The Plots pane
The Packages pane
The Help pane
The Viewer pane
RStudio Server
A quick example
Summary
2. Basic Objects
Vector
Numeric vector
Logical vector
Character vector
Subsetting vectors
Named vectors
Extracting an element
Telling the class of vectors
Converting vectors
Arithmetic operators for numeric vectors
Matrix
Creating a matrix
Naming rows and columns
Subsetting a matrix
Using matrix operators
Array
Creating an array
Subsetting an array
Lists
Creating a list
Extracting an element from a list
Subsetting a list
Named lists
Setting values
Other functions
Data frames
Creating a data frame
Naming rows and columns
Subsetting a data frame
Subsetting a data frame as a list
Subsetting a data frame as a matrix
Filtering data
Setting values
Setting values as a list
Setting values as a matrix
Factors
Useful functions for data frames
Loading and writing data on disk
Functions
Creating a function
Calling a function
Dynamic typing
Generalizing a function
Default value for function arguments
Summary
3. Managing Your Workspace
R's working directory
Creating an R project in RStudio
Comparing absolute and relative paths
Managing project files
Inspecting the environment
Inspecting existing symbols
Viewing the structure of an object
Removing symbols
Modifying global options
Modifying the number of digits to print
Modifying the warning level
Managing the library of packages
Getting to know a package
Installing packages from CRAN
Updating packages from CRAN
Installing packages from online repositories
Using package functions
Masking and name conflicts
Checking whether a package is installed
Summary
4. Basic Expressions
Assignment expressions
Alternative assignment operators
Using backticks with non-standard names
Conditional expressions
Using if as a statement
Using if as an expression
Using if with vectors
Using vectorized if: ifelse
Using switch to branch values
Loop expressions
Using the for loop
Managing the flow of a for loop
Creating nested for loops
Using the while loop
Summary
5. Working with Basic Objects
Using object functions
Testing object types
Accessing object classes and types
Accessing data dimensions
Getting data dimensions
Reshaping data structures
Iterating over one dimension
Using logical functions
Logical operators
Logical functions
Aggregating logical vectors
Asking which elements are TRUE
Dealing with missing values
Logical coercion
Using math functions
Basic functions
Number rounding functions
Trigonometric functions
Hyperbolic functions
Extreme functions
Applying numeric methods
Root finding
Calculus
Derivatives
Integration
Using statistical functions
Sampling from a vector
Working with random distributions
Computing summary statistics
Computing covariance and correlation matrix
Using apply-family functions
lapply
sapply
vapply
mapply
apply
Summary
6. Working with Strings
Getting started with strings
Printing texts
Concatenating strings
Transforming texts
Changing cases
Counting characters
Trimming leading and trailing whitespaces
Substring
Splitting texts
Formatting texts
Using Python string functions in R
Formatting date/time
Parsing text as date/time
Formatting date/time to strings
Using regular expressions
Finding a string pattern
Using groups to extract the data
Reading data in customizable ways
Summary
7. Working with Data
Reading and writing data
Reading and writing text-format data in a file
Importing data via RStudio IDE
Importing data using built-in functions
Importing data using the readr package
Writing a data frame to a file
Reading and writing Excel worksheets
Reading and writing native data files
Reading and writing a single object in native format
Saving and restoring the working environment
Loading built-in datasets
Visualizing data
Creating scatter plots
Customizing chart elements
Customizing point styles
Customizing point colors
Creating line plots
Customizing line type and width
Plotting lines in multiple periods
Plotting lines with points
Plotting a multi-series chart with a legend
Creating bar charts
Creating pie charts
Creating histogram and density plots
Creating box plots
Analyzing data
Fitting a linear model
Fitting a regression tree
Summary
8. Inside R
Understanding lazy evaluation
Understanding the copy-on-modify mechanism
Modifying objects outside a function
Understanding lexical scoping
Understanding how an environment works
Knowing the environment object
Creating and chaining environments
Accessing an environment
Chaining environments
Using environments for reference semantics
Knowing the built-in environments
Understanding environments associated with a function
Summary
9. Metaprogramming
Understanding functional programming
Creating and using closures
Creating a simple closure
Making specialized functions
Fitting normal distribution with maximal likelihood estimation
Using higher-order functions
Creating aliases for functions
Using functions as variables
Passing functions as arguments
Computing on language
Capturing and modifying expressions
Capturing expressions as language objects
Modifying expressions
Capturing expressions of function arguments
Constructing function calls
Evaluating expressions
Understanding non-standard evaluation
Implementing quick subsetting using non-standard evaluation
Understanding dynamic scoping
Using formulas to capture expression and environment
Implementing subset with metaprogramming
Summary
10. Object-Oriented Programming
Introducing object-oriented programming
Understanding classes and methods
Understanding inheritance
Working with the S3 object system
Understanding generic functions and method dispatch
Working with built-in classes and methods
Defining generic functions for existing classes
Creating objects of new classes
Using list as the underlying data structure
Using an atomic vector as the underlying data structure
Understanding S3 inheritance
Working with S4
Defining S4 classes
Understanding S4 inheritance
Defining S4 generic functions
Understanding multiple dispatch
Working with the reference class
Working with R6
Summary
11. Working with Databases
Working with relational databases
Creating a SQLite database
Writing multiple tables to a database
Appending data to a table
Accessing tables and table fields
Learning SQL to query relational databases
Fetching query results chunk by chunk
Using transactions for consistency
Storing data in files to a database
Working with NoSQL databases
Working with MongoDB
Querying data from MongoDB
Creating and removing indexes
Using Redis
Accessing Redis from R
Setting and getting values from the Redis server
Summary
12. Data Manipulation
Using built-in functions to manipulate data frames
Using built-in functions to manipulate data frames
Reshaping data frames using reshape2
Using SQL to query data frames via the sqldf package
Using data.table to manipulate data
Using key to access rows
Summarizing data by groups
Reshaping data.table
Using in-place set functions
Understanding dynamic scoping of data.table
Using dplyr pipelines to manipulate data frames
Using rlist to work with nested data structures
Summary
13. High-Performance Computing
Understanding code performance issues
Measuring code performance
Profiling code
Profiling code with Rprof
Profiling code with profvis
Understanding why code can be slow
Boosting code performance
Using built-in functions
Using vectorization
Using byte-code compiler
Using Intel MKL-powered R distribution
Using parallel computing
Using parallel computing on Windows
Using parallel computing on Linux and MacOS
Using Rcpp
OpenMP
RcppParallel
Summary
14. Web Scraping
Looking inside web pages
Extracting data from web pages using CSS selectors
Learning XPath selectors
Analysing HTML code and extracting data
Summary
15. Boosting Productivity
Writing R Markdown documents
Getting to know markdown
Integrating R into Markdown
Embedding tables and charts
Embedding tables
Embedding charts and diagrams
Embedding interactive plots
Creating interactive apps
Creating a shiny app
Using shinydashboard
Summary
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