Summary and conclusion

Day 4, B

Michael C Sachs

What did we learn?

Project organization

• Setting up your project structure
• Documentation and readme
• Working directories and file paths

Basic programming principles

• Data structures
• Loops and conditionals
• Functions, classes, generics

Working with data

• Tidying
• Reshaping
• Merging
• Dealing with dates and strings
• Visualization

Conclusion

Where to go from here?

1. Research project management and reproducibility
   • targets package
   • project templates
   • git and/or github
2. R package development
   • Great way to share code, data, and documentation
   • Packages for personal and internal use
3. High performance computing
   • Parallelization, using computing servers
   • Using C/C++ (or other languages) in R
4. Visualization and interactivity
   • shiny package
   • Dynamic documents and graphics
   • ggplot2 custom Geoms and Stats

How to get help?

• Keep learning on your own, remember that things change
• Use the linked resources to get some background
• CRAN task views, help files, vignettes
• Google “how do I do x in R”, or the exact error message
• Stackoverflow, Rstudio forums, R mailing lists

Feedback

Course feedback

1. What did you like about the course?
2. What did you dislike about the course?
3. Did you knowledge about R programming improve during the course?
4. Are there topics you wanted to be covered but were not?

Office hours

Last chance

To ask about R, or anything else

My office is 10.2.25

You can also use our consulting services – Look under “Statistical Advisory Services” on the Biostat homepage.