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# NY R Conference talk

My talk in April 2018 at the NY R Conference on the Lesser Known Stars of the Tidyverse.

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### NY R Conference talk

1. 1. The Lesser Known s of the Tidyverse Emily Robinson @robinson_es
2. 2. About Me ➔ R User ~ 6 years ➔ Data Scientist at DataCamp ➔ Enjoy talking about: ◆ A/B testing ◆ Building and finding data science community ◆ R
3. 3. Talk Goals
4. 4. 1. Keep you hip to the lingo
5. 5. 2. Stop you from doing this ….
6. 6. …. by sharing useful functions
7. 7. 3. Point you to resources
8. 8. The Tidyverse
9. 9. Coherent system of packages for data manipulation, exploration, and visualization that share a common design philosophy
10. 10. Tidyverse = ?
11. 11. Tidyverse = !
13. 13. Tidyverse != Hadleyverse Many other contributors
14. 14. Demo
15. 15. Some steps of a data analysis workflow ➔ View dataset in console ➔ Inspect missing values ➔ Examine some columns ➔ Make a plot ➔ Do something cool and new!
16. 16. Problem: it takes over the console Step 1: print your dataset!
17. 17. Prints only 10 rows and the columns that fit on the screen Solution: as_tibble()
18. 18. Problem: how do you do this for every column? Step 2: examine your NAs
19. 19. Problem: missing values aren’t actually NA Answer: purrr::map_df() to “map” function over each column
20. 20. Solution: na_if() to replace certain values with NA
21. 21. Problem: how I can I do this quickly? + Skimr Solution: dplyr::select_if() + skimr::skim() Step 3: examine your numeric columns
22. 22. Problem: it has multiple answers in each row Step 4: examine a single column
23. 23. Solution: stringr::str_split() …
24. 24. Solution: stringr::str_split() and tidyr::unnest() +
25. 25. Problem: it’s a mess Step 5: make a plot!
26. 26. Solution: coord_flip … But they’re not ordered
27. 27. + forcats::fct_reorder
28. 28. Final step: do something cool and new! Problem:
29. 29. One solution: make a minimal reproducible example +
30. 30. Part 0 (optional): use tribble() to make a toy dataset
31. 31. Part 1: Use reprex() to find any problems Credit: Nick Tiernay, https://www.njtierney.com/post/2017/01/11/magic-reprex/
32. 32. Part 2: Use reprex() to post your question or issue Credit: Nick Tiernay, https://www.njtierney.com/post/2017/01/11/magic-reprex/
33. 33. Review stringr::str_split tidyr::unnest coord_flip() forcats::fct_reorder tibble::tribble reprex::reprex tibble::as_tibble purrr:map_df dplyr::na_if dplyr::select_if skimr::skim
34. 34. Resources
38. 38. Rstudio.com/resources/cheatsheets
39. 39. DataCamp.com
40. 40. Learn | https://datacamp.com/courses
41. 41. Conclusion
42. 42. The tidyverse Come for the stickers and package names … Stay for the friendly community and happy workflow
43. 43. Thank you! tiny.cc/nyrtalk hookedondata.org @robinson_es

My talk in April 2018 at the NY R Conference on the Lesser Known Stars of the Tidyverse.

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