Working with names and expressions in your tidy eval code

on YouTube ↗16m

" summary

Shows how passing ... into dplyr lets a wrapper accept either column selections or column actions and demonstrates two concrete wrappers: a selection-based summary built on summarize_at that returns per-group summaries, and an action-based version using transmute/summarize_all that creates new vectors then summarizes them. Includes a real fix: when gathering results exclude grouping variables so grouped tables work. Works as described but requires careful choice between selection vs action semantics.

AI-written summary · about

" chapters (11)

1. 0:00Tidy eval in R
2. 1:33Why quoting matters
3. 2:39Selection vs action verbs
4. 4:50Selection helpers
5. 6:37Challenges in functions
6. 7:19Simplest functions
7. 8:23Selection with purrr
8. 10:32Selection to action
9. 11:58Grouped summaries
10. 13:32Best practices
11. 14:37Q&A

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