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11  Continued learning

11.1 Free online books:

11.1.1 Beginner

• R for Data Science: Excellent open and online resource for using R for data analysis and data science.
• Fundamentals of Data Visualization: Excellent online resource for using ggplot2 and R graphics. The book mostly focuses on concepts and theory of how to visualize, rather than the practicalities (i.e. no coding involved).
• ModernDive: Statistical Inference via Data Science: Great book on using statistics and data science methods in R.
• Happy Git and GitHub for the useR (highly recommended): Specifically useful is the chapter on Daily Workflows using Git.
• Data Visualization: A practical introduction: A book that goes into practical as well as conceptual detail on how and why to make certain graphs, given your data.
• Course material for a statistics class: Excellent course material for teaching statistics and R.
• ModernDive: Statistical Inference via Data Science: Great book on using statistics and data science methods in R

11.1.2 Intermediate and above

• Efficient R Programming: Excellent book on being efficient when writing R code.
• Advanced R: Detailed book on advanced features of R.
• R Packages: Learn how to create R Packages from the basics.
• R Programming for Data Science: Great overview of using R for Data Science, with more of a focus on the programming side of things

11.2 Quick references:

• RStudio cheatsheets: Multiple, high-quality cheatsheets you can print off to use as a handy reference.
• Tidyverse style guide: To learn about how to write well-styled code in R.
• Tidyverse design philosophy of writing code

11.3 Articles:

• Good enough practicies in scientific computing: An article listing and describing some practices to use when writing code.
• Best practices in scientific computing.
• Case study of reproducible methodds in Bioinformatics: [@Kim2018a].

11.4 General sites:

• Organizing R Source Code.
• Hands-on tutorial for learning Git, in a web-based terminal.
• Simpler, first-steps guide to using Git.
• RStudio tutorial on using R Markdown.
• Markdown syntax guide.
• Pandoc Markdown Manual (R Markdown uses Pandoc).
• Adding citations in R Markdown.
• Case studies and lessons for doing reproducibility

11.5 Interactive sites or resources for hands-on learning:

• Interactive tutorials for using R, within R.
• RStudio’s Learning Primers.

11.6 Videos:

• Video on using Git in RStudio.

11.7 Getting help:

• StackOverflow for tidyr.
• StackOverflow for dplyr.
• StackOverflow for ggplot2.
• Tip: Combine auto-completion with :: to find new functions and documentation on the functions (e.g. try typing base:: and then hitting Tab to show a list of all functions found in base R).