R Programming
1
Intro to R Bookdown
2
Introduction to R
2.1
R Markdown File
2.2
Learning objectives
2.3
Comments
2.4
Syntax
2.5
Creating variables
2.6
Printing Variables
3
Data types and data structures
3.1
Data Types
3.2
Atomic Classes
3.2.1
Numeric
3.2.2
Integer
3.2.3
Logical
3.2.4
Character
3.2.5
Missing Value
3.3
Arithmetic Operations
3.4
Logical operators
3.5
Exercise
3.6
Data Structures
3.7
Vectors
3.7.1
Numeric
3.7.2
Integer
3.7.3
Logical
3.7.4
Character
3.7.5
Vector attributes
3.8
Factors
3.9
Exercise
3.9.1
Built-in functions
3.9.2
Vector Operations
3.9.3
Recycling
3.9.4
Indexing and subsetting
3.10
Lists
3.10.1
Indexing and subsetting
3.10.2
Built-in functions
3.11
Matrices
3.11.1
Attributes
3.11.2
Built-in functions
3.12
Data frames
3.12.1
Indexing and sub-setting
3.13
Coercion
3.14
Hands on: Data types
4
Control Structures & Functions
4.1
Learning Objectives
4.2
Conditional Statements
4.3
For & While Loops
4.4
Functions
4.5
Installing packages
4.6
Detour || Seeking help
4.7
Exercise
4.7.1
5
Basic data manipulation
5.1
Reading/writing data
5.1.1
Text files
5.1.2
R objects
5.2
Exploring data frames
5.2.1
Adding columns and rows
5.2.2
Removing columns and rows
5.2.3
Applying filters
5.2.4
Editing specific elements
5.3
Hands-on: basic data manipulation
6
Advanced data manipulation
6.1
Manipulation with
dplyr
6.1.1
Introducing pipes
6.1.2
Using
select()
6.1.3
Using
filter()
6.1.4
Using
group_by()
6.1.5
Using
summarize()
6.1.6
Using
mutate()
6.1.7
Putting them all together
6.2
Hands-on advanced data manipulation
7
Generating visual outputs
7.1
Graphics with base R
7.2
Graphics with ggplot2
7.2.1
Some ggplot tricks
8
Real life application
9
Software development concepts
9.1
Good coding practices
9.1.1
Script structure
9.1.2
Functions
9.1.3
External packages
9.2
Debugging and troubleshooting
10
References
11
Solutions || Data Types
11.1
Atomic Classes
11.1.1
11.2
Vectors
11.3
Matrices
11.4
Lists
11.5
Data frames
11.6
Coercion
12
Solutions || Basic Data Manipulation
12.1
Writing data
12.2
Exploring data frames
13
Solutions || Adv. Data Manipulation
14
Solutions || Medical Data
14.1
Clinics included
14.1.1
Number of clinics
14.1.2
Number of valid tests
14.1.3
Testing trend over time
14.2
Number of positive tests
14.2.1
Number of positive tests in the first 100 days
14.2.2
Tests by age group
14.3
Processing times
14.4
Bonus - Viral load
15
Workshop Slides
Published with bookdown
Intro to R
10
References
Base R Cheat Sheet
Google’s R Style Guide
Mastering Software Development in R
R for reproducible statistical analysis
Medicaldata - covid testing dataset