Data Carpentry with Tidyverse

Meetup Algoritma X Machine Learning ID X Komunitas R Indonesia

Transcript

2. • Sensory Scientist @ Sensolution.ID • Trainer @ R-Academy Telkom University and The Datanomics Institute (TDI) • Initiator of Komunitas R Indonesia • Pkgs: sensehubr, nusandata, bandungjuara, prakiraan, etc • Shinyapps: sensehub, thermostats, aquastats, bcrp, bandungjuara, etc aswansyahputra @aswansyahputra_
3. R Indonesia R Indonesia www.r-indonesia.id Komunitas t.me/GNURIndonesia @r_indonesia_ indo-r www.r-indonesia.id
4. R Indonesia www.r-indonesia.id
5. Know your neighbour! • Who are you? • What you do with data? • How would you describe your experience with R?
6. Artwork by @allison_horst
7. Artwork by @allison_horst
8. Data Carpentry?
9. It’s so relatable, is it not?
12. “ Do not underestimate DATA PREPROCESSING
13. is not a single process but a thousand of little skills and techniques “ - David Minmo
14. Artwork by @allison_horst The tidyverse is an opinionated collection of R packages designed for data science. All packages share an underlying design philosophy, grammar, and data structures.
15. Program Import Tidy Transform Visualise Model Communicate Understand
16. Program Import Tidy Transform Visualise Model Communicate Understand
17. Artwork by @allison_horst tidyr
18. Artwork by @allison_horst dplyr
19. dplyr basic functions: • filter() selects rows based on their values • mutate() creates new variables • select() picks columns by name • summarise() calculates summary statistics • arrange() sorts the rows dplyr basic functions: • filter() selects rows based on their values • mutate() creates new variables • select() picks columns by name • summarise() calculates summary statistics • arrange() sorts the rows Credits to Michael Toth tidyr basic functions: • gather() wide-format >> long-format • spread() long-format >> wide-format • fill() fills value based on previous entry • complete() turns implicit missing values into explicit tidyr basic functions: • gather() wide-format >> long-format • spread() long-format >> wide-format • fill() fills value based on previous entry • complete() turns implicit missing values into explicit Operators: • ! (not) • I (or) • & (and) • ==, != • <, <=, >, >= • %in% • is.na() Operators: • ! (not) • I (or) • & (and) • ==, != • <, <=, >, >= • %in% • is.na()
20. How can I chain?
22. 1. diputar 2. dijilat 3. dicelupin 4. dimakan :D
23. 1. putar(apa) 2. jilat(apa, berapa_kali) 3. celup(apa, ke) 4. makan(apa, output)
24. a > oreo_putar ← putar(apa = “oreo”) > oreo_jilat ← jilat(apa = oreo_putar, berapa_kali = 2) > oreo_celup ← celup(apa = oreo_jilat, ke = “susu”) > makan(apa = oreo_celup, output = “kenyang.perut”)
25. > oreo_putar ← putar(apa = “oreo”) > oreo_jilat ← jilat(apa = oreo_putar, berapa_kali = 2) > oreo_celup ← celup(apa = oreo_jilat, ke = “susu”) > makan(apa = oreo_celup, output = “kenyang.perut”) a
26. > makan( celup( jilat( putar(apa = “oreo”), berapa_kali = 2 ), ke = “susu” ), output = “kenyang.perut” ) b
27. function(arg1, arg2, arg3,...) arg1 %>% function(arg2, arg3,...) function(arg1, arg2, arg3,...) arg2 %>% function(arg1, arg2=.,arg3,...) magrittr
28. > putar(apa = “oreo”) %>% jilat(berapa_kali = 2) %>% celup(ke = “susu”) %>% makan(output = “kenyang.perut”) c
29. What to do today?
31. www.onepiece.fandom.com www.onepiece.fandom.com
32. Let’s get started! • Let’s write R scripts together! • I will demonstrate and explain the use of each code • Access this presesentation at: s.id/data-carpentry- with-tidyverse
39. s.id/yt_aswansyahputra s.id/yt_aswansyahputra
40. Thanks! aswansyahputra@sensolution.id www.aswansyahputra.com speakerdeck.com/ aswansyahputra R Indonesia www.r-indonesia.id