Summary

That’s all we have for this workshop. By now you should have a better understanding of how you can make your code more easily shared, reusable and tidy. In this workshow we have covered:

• Search for and install R packages
• Using R packages and their functions
• Writing your own functions
• Error handling in functions
• Write tidy code to work with tidy data with tidyverse

This has been only a brief introduction. You can learn more from these excellent free online resources:

• R for Data Science (2e) by Hadley Wickham, Mine Çetinkaya-Rundel and Garrett Grolemund. - this is a must-read book that really shows you how to do data science with R.

• ggplot2: Elegant Graphics for Data Analysis, by Hadley Wickham, Danielle Navarro, and Thomas Lin Pedersen - this is an excellent book that show how to use ggplot for drawing graphs.

• Advanced R, by Hadley Wickham - this book goes deeper into the R programming language.

• Text mining with R: A Tidy approach, by Julia Silge and David Robinson - this book shows how to use tidy principles to perform text mining and sentiment analysis.

• Statistical Inference via Data Science: A ModernDive into R and the Tidyverse, by Chester Ismay and Albert Y. Kim - this book teaches statistical techniques, using R and the Tidyverse.

• The R Graph Gallery - a large showcase of different ggplot graphs covering pretty every type of data visualisation you would want to perform. Examples with code! Find an example that matches the type of graph that you want to draw and then adapt that to your own data.

• Mastering Shiny, by Hadley Wickham - This book teaches you how to use Shiny to turn your Tidyverse R data analysis and visualisations into interactive web pages and dashboards that you can share with your collaborators.