Week 4 Readings

mutate(), across(), summarize(), group_by(), ggplot: faceting, scales

Required

• Data Transformation (3.1-3.3) from R for Data Science
• group_by() Data Transformation (3.5-3.6) from R for Data Science (2e)
  • The 1st edition’s Section 5.6 on Grouped summaries with summarise() is more detailed (wordier) and worth looking at as well.
  • The 1st edition also has Section 5.7 on Grouped mutates (and filters) that I did not see in the 2nd edition. Please let me know if you find this content in the 2nd edition!
• Aggregating data with summarize and map - we will cover map() and rowwise() later, but summarize and mutate with across are described here. You may want to re-visit this when we get to purrr.
• ggplot2: Elegant Graphics for Data Analysis, Scales & Guides
• R for Data Science: Factors - we will continue to work with factors in the next few classes with forcats examples like provided here.

Optional

• Tidyverse style guide
• Advanced R: style guide
• across(): This column-wise operations vignette will be useful for the next couple classes.