Data Science Using R E-learning

Course Introduction
Introduction to Data Wrangling in R

The dplyr Library

Data Wrangling with dplyr
Exploring Data with dplyr
Filtering with dplyr
Piping with dplyr
Mutating Data with dplyr
Summarizing Data with dplyr
Selecting with dplyr
Combining Data Sets with dplyr
Set Operations with dplyr
Arranging with dplyr

The tidyr Library

Data Manipulation with tidyr
Gathering with tidyr
Separating with tidyr

Rectangular Data Extraction

Using readr
Using readxl

Practice: Using the dplyr Library

Exercise: Combine dplyr Verbs

Debugging

Course Introduction
Debugging with RStudio
Using Traceback
Debugging with Browser
Displaying Warnings and Messages
Implementing Handlers
Benchmarking in R

Defensive Programming in R

Methods of Defensive Programming
Turning Warnings into Errors
Programming with Asserts

Memory Management

Using pryr
Addressing Memory with pryr

Practice: Using Debugging

Exercise: Debug with Browser

Utility Functions in R

Course Introduction
Using substitute, quote, and deparse
Using ast
Using str
Lazy Evaluation in R
Using eval
Using paste Functions

Classes and Operators

Creating Reference Classes
Using class
Defining a Binary Operator
Simulating a Unary Operator

Code Translation

Using SQL to R Translation
Exporting HTML tables
Exporting a LaTeX document
Using list2env

C and C++ Integration

Connecting inline C++ to R
Calling External C++ with R
Using cfunction in R

Practice: Code Transformation

Exercise: Output an R Table as LaTeX

Library Tools

Course Introduction
Exploring the tidyverse Collection of Libraries
Manipulating Strings with the stringr Library
Using the forcats Library
Using the purrr Library

Web Application Tools

Creating a shiny Application
Rendering a Plot in shiny
Displaying a JavaScript DataTable

R Markdown

Using Markdown in R
Rendering HTML
Rendering LaTeX
Passing knitr Parameters
Referencing with bibtex

Practice: R Markdown Publishing

Exercise: Create and Publish from R Markdown