These are my slides for my RStudio::conf presentation on February 2, 2018. Recording of the talk will be available soon.

1. The Lesser Known
s of the Tidyverse
Emily Robinson
@robinson_es

2. About Me
- Data Analyst at Etsy
- R User for ~6 years
- Enjoy talking about:
• A/B Testing
• Building and finding Data
Science community
• R

3. Disclaimers

4. This talk represents my
own views, not those
of Etsy

5. It’s not Base R vs. Tidyverse

6. Talk Goals

7. 1. Keep you hip to the lingo

8. 2. Stop you from doing this ...

9. … by sharing useful functions

10. 3. Point you to resources

11. The Tidyverse

12. An opinionated collection of R packages
designed for data science that share an
underlying design philosophy, grammar,
and data structures

14. Tidyverse ?=

15. Tidyverse !=

16. Tibble

17. Tidyverse != Hadleyverse

18. Tidyverse != Hadleyverse
Many other contributors

20. Demo

22. Problem: it takes over the console
Step 1: print your dataset!

23. Prints only 10 rows and the columns that fit on the screen
Solution: as_tibble()

24. Problem: your NAs aren’t actually NAs
Step 2: examine your NAs

25. Solution: na_if() to replace certain values with NA

26. Problem: how I can I do this quickly?
+
Skimr
Solution: dplyr::select_if() + skimr::skim()
Step 3: examine your numeric columns

27. Problem: it has multiple answers in each row
Step 4: examine a single column

28. Solution: stringr::str_split() …

29. Solution: stringr::str_split() and tidyr::unnest()
+

30. Problem: it’s a mess
Step 5: make a scatterplot!

31. ggplot(WorkChallenges, aes(x = fct_reorder(question, perc_problem), y =
perc_problem)) + geom_point()
Solution: fct_reorder() to order one axis by the other

32. Problem: your scale is mis-ordered
Step 6: make a bar chart!

33. Solution: fct_relevel() to manually order your factor
ggplot(aes(x = fct_relevel(response, "Rarely", "Sometimes", "Often", "Most of
the time"))) + geom_bar()

34. Final step: do something cool and new!
Problem:

35. One solution: make a minimal reproducible example
+

36. Part 0 (optional): use tribble() to make a toy dataset

37. Part 1: Use reprex() to find any problems
Credit: Nick Tiernay, https://www.njtierney.com/post/2017/01/11/magic-reprex/

38. Part 2: Use reprex() to post your question or issue
Credit: Nick Tiernay, https://www.njtierney.com/post/2017/01/11/magic-reprex/

39. Review
stringr::str_split
tidyr::unnest
forcats::fct_reorder
forcats::fct_relevel
reprex::reprex
tibble::as_tibble
tibble::tribble
dplyr::na_if
dplyr::select_if
skimr::skim

40. Resources

41. R4ds.had.co.nz

42. #rstats Twitter

43. #rstats Twitter

44. Datacamp.com

45. Base R to Tidyverse Translation
www.significantdigits.org/2017/10/switching-from-base-r-to-tidyverse/

46. - Tidyverse.org
- community.rstudio.com/c/tidyverse
- https://www.rstudio.com/resources/cheatsheets/
- https://medium.com/@kierisi/r4ds-the-next-iteration-
d51e0a1b0b82
And much more!

47. Come for the stickers
and package names
…
Stay for the friendly
community and happy
workflow.
The
tidyverse

48. Thank You!
tiny.cc/rstudiotalk
robinsones.github.io
@robinson_es