R for Data Science: Chapter 4 (Workflow Basics); Chapter 5 (Data Transformation); Chapter 6 (Work-Flow Scripts); Chapter 7 (Exploratory Data Analysis); Chapter 8 (Workflow - Projects); Chapter 12 (Tibbles); Chapter 18 (Pipes); Chapter 12 (Vectors); Chapter 20 (Vectors); Chapter 21 (Iteration)
R for Finance: 3.2 (Stocks and Dividends); 3.3 (Exchange Traded Funds); 5.1 (Stock PNL); 5.4 (Returns)
Using R Studio Projects - a tutorial on how and why to use R Studio projects
Core Functions in tidyquant - the first in a series of well written vignette on how to get started with the tidyquant package. I recommend continuing with the vignettes if you’d like to learn more about this package.
R for Data Science: Chapter 12 (Tidy Data); Chapter 13 (Relational Data); Chapter 19 (Functions); Chapter 21 (Iteration)
A Tutorial on Using Functions in R! - a good introductory tutorial on functions.
Jenny Bryan Purr Tutorials - these are fairly in-depth, but the first two are good for becoming more familiar with vectors and lists.
R for Data Science: Chapter 3 (Data Visualization); Chapter 28 (R Graphics for Communication)
Visual Data Exploration - an excellent online tutorial on ggplot2; however, it’s quite long so expect it to take some time to work all the way through.
Advanced Plots with ggplot2 - a series of online articles that focus on individual plot types.
R for Finance: Chapter 2 (Options 101); Chapter 5 (Profit & Loss); Chapter 6 (Option Pricing)