Tokyo.R#89 Data visualization

第89回Tokyo.Rの初心者セッションでトークした際のスライドです。

1. #89 @kilometer00 2021.01.23 BeginneR Session -- Data Visualization --
2. Who！？ 誰だ？
3. Who！？ 名前： 三村 @kilometer 職業： ポスドク (こうがくはくし) 専⾨： ⾏動神経科学(霊⻑類) 脳イメージング 医療システム⼯学 R歴： ~ 10年ぐらい 流⾏: 直⽴⼆⾜歩⾏
4. 㲚⚥傴盈ס緾錌מ⹆ⱶ׊ױ׊גն 
   鞄㚞ꝧ㡎 "NB[PO־׼◀硜ך׀ױ׌
5. BeginneR Session
6. BeginneR
7. BeginneR Advanced Hoxo_m If I have seen further it is by standing on the shoulders of Giants. -- Sir Isaac Newton, 1676
8. Before A'er BeginneR Session BeginneR BeginneR
9. Why & How
10. "a" != "b" # is A in B? ブール演算⼦ Boolean Algebra [1] TRUE 1 %in% 10:100 # is A in B? [1] FALSE
11. George Boole 1815 - 1864 A Class-Room Introduction to Logic https://niyamaklogic.wordpress.com/c ategory/laws-of-thoughts/ Mathematician Philosopher &
12. ブール演算⼦ Boolean Algebra A == B A != B George Boole 1815 - 1864 A | B A & B A %in% B # equal to # not equal to # or # and # is A in B? wikipedia
13. 1JQF
    BMHFCSB X %>% f X %>% f(y) X %>% f %>% g X %>% f(y, .) f(X) f(X, y) g(f(X)) f(y, X) %>% {magrittr} 「dplyr再⼊⾨（基本編）」yutanihilation https://speakerdeck.com/yutannihilation/dplyrzai-ru-men-ji-ben-bian
14. ① ② ③ ④ lift take pour put Bring me milk from the kitchen!
15. ① lift Bring me milk from the kitchen! lift(Robot, glass, table) -> Robot' take ② take(Robot', fridge, milk) -> Robot''
16. Bring me milk from the kitchen! Robot' <- lift(Robot, glass, table) Robot'' <- take(Robot', fridge, milk) Robot''' <- pour(Robot'', milk, glass) result <- put(Robot''', glass, table) result <- Robot %>% lift(glass, table) %>% take(fridge, milk) %>% pour(milk, glass) %>% put(glass, table) by using pipe, # ① # ② # ③ # ④ # ① # ② # ③ # ④
17. Programing
18. Programing
19. Programing Write Run Read Think Write Run Read Think Communicate Share
20. Text Image Information Intention Data decode encode Data analysis feedback ≠
21. Text Image First, A. Next, B. Then C. Finally D. time Intention encode "Frozen" structure A B C D time value α β
22. &ODPEF "QQMF 3FBM "QQMF *OGPSNBUJPO %FDPEF
23. %JWFSHFODF 3FBM *OGP %BUB "QQMF
    
     &ODPEJOH
24. "QQMF &ODPEF 'SVJU 3FE  JNBHF 3FBM *OGPSNBUJPO
25. "QQMF &ODPEF 'SVJU 3FE  JNBHF 3FBM *OGPSNBUJPO DIBOOFM
26. ⫝⥼ (mapping) !: # → % # % ֵ׾䗯㕔ס꥗⺬ס釐碛؅յ⮯ס䗯㕔ס꥗⺬ס גדחס釐碛מ㵚䑴טׄ׾وٞجت
27. ⫝⥼ (mapping) !"##$%& '"(" )!"&*
28. ! " #$ %$ #& %& ! " %$ %& #$ #& ⺎釱⴫ ⊂ ⫝⥼ mapping
29. ! " #$ %$ #& %& ! " %$ %& #$ #& ⺎釱⴫ ⊂ ⫝⥼ mapping x axis, y axis, color, fill, shape, linetype, alpha… aesthetic channels
30. "QQMF &ODPEF 'SVJU 3FE  JNBHF 3FBM *OGPSNBUJPO DIBOOFM
31. ! " #$ %$ #& %& ! " %$ %& #$ #& mapping x axis, y axis, color, fill, shape, linetype, alpha… aesthetic channels data ggplot2 package
32. ggplot2 # install.packages("tidyverse") library(tidyverse) dat <- data.frame(a = 1:3, b = 8:10) Attach package Simple example > dat a b 1 1 8 2 2 9 3 3 10
33. dat <- data.frame(a = 1:3, b = 8:10) ggplot(data = dat) + geom_point(mapping = aes(x = a, y = b)) ggplot2
34. dat <- data.frame(a = 1:3, b = 8:10) ggplot(data = dat) + geom_point(mapping = aes(x = a, y = b)) ! " #! $! #" $" ! " $! $" #! #" mapping x axis, y axis, color, fill, shape, linetype, alpha… aesthetic channels data ggplot2
35. dat <- data.frame(a = 1:3, b = 8:10) ggplot(data = dat) + geom_point(mapping = aes(x = a, y = b)) + geom_path(mapping = aes(x = a, y = b))
36. dat <- data.frame(a = 1:3, b = 8:10) ggplot(data = dat, mapping = aes(x = a, y = b)) + geom_point() + geom_path() inheritance
37. dat <- data.frame(a = 1:3, b = 8:10) ggplot(data = dat) + aes(x = a, y = b)) + geom_point() + geom_path()
38. dat <- data.frame(a = 1:3, b = 8:10) ggplot(data = dat) + aes(x = a, y = b)) + geom_point() + geom_path()
39. dat <- data.frame(a = 1:3, b = 8:10) g <- ggplot(data = dat) + aes(x = a, y = b)) + geom_point() g + geom_path()
40. Anscombe's quartet > anscombe x1 x2 x3 x4 y1 y2 y3 y4 1 10 10 10 8 8.04 9.14 7.46 6.58 2 8 8 8 8 6.95 8.14 6.77 5.76 3 13 13 13 8 7.58 8.74 12.74 7.71 4 9 9 9 8 8.81 8.77 7.11 8.84 5 11 11 11 8 8.33 9.26 7.81 8.47 6 14 14 14 8 9.96 8.10 8.84 7.04 7 6 6 6 8 7.24 6.13 6.08 5.25 8 4 4 4 19 4.26 3.10 5.39 12.50 9 12 12 12 8 10.84 9.13 8.15 5.56 10 7 7 7 8 4.82 7.26 6.42 7.91 11 5 5 5 8 5.68 4.74 5.73 6.89
41. ggplot(data = anscombe) + aes(x = x1, y = y1)) + geom_point() Anscombe's quartet
42. > anscombe x1 x2 x3 x4 y1 y2 y3 y4 1 10 10 10 8 8.04 9.14 7.46 6.58 2 8 8 8 8 6.95 8.14 6.77 5.76 3 13 13 13 8 7.58 8.74 12.74 7.71 4 9 9 9 8 8.81 8.77 7.11 8.84 5 11 11 11 8 8.33 9.26 7.81 8.47 6 14 14 14 8 9.96 8.10 8.84 7.04 7 6 6 6 8 7.24 6.13 6.08 5.25 8 4 4 4 19 4.26 3.10 5.39 12.50 9 12 12 12 8 10.84 9.13 8.15 5.56 10 7 7 7 8 4.82 7.26 6.42 7.91 11 5 5 5 8 5.68 4.74 5.73 6.89 x y mapping Anscombe's quartet
43. > anscombe x1 x2 x3 x4 y1 y2 y3 y4 1 10 10 10 8 8.04 9.14 7.46 6.58 2 8 8 8 8 6.95 8.14 6.77 5.76 3 13 13 13 8 7.58 8.74 12.74 7.71 4 9 9 9 8 8.81 8.77 7.11 8.84 5 11 11 11 8 8.33 9.26 7.81 8.47 6 14 14 14 8 9.96 8.10 8.84 7.04 7 6 6 6 8 7.24 6.13 6.08 5.25 8 4 4 4 19 4.26 3.10 5.39 12.50 9 12 12 12 8 10.84 9.13 8.15 5.56 10 7 7 7 8 4.82 7.26 6.42 7.91 11 5 5 5 8 5.68 4.74 5.73 6.89 a > anscombe_long # A tibble: 44 x 3 key x y <chr> <dbl> <dbl> 1 1 10 8.04 2 2 10 9.14 3 3 10 7.46 4 4 8 6.58 5 1 8 6.95 6 2 8 8.14 7 3 8 6.77 8 4 8 5.76 Wide form Long form
44. > anscombe x1 x2 x3 x4 y1 y2 y3 y4 1 10 10 10 8 8.04 9.14 7.46 6.58 2 8 8 8 8 6.95 8.14 6.77 5.76 3 13 13 13 8 7.58 8.74 12.74 7.71 anscombe_long <- pivot_longer(data = anscombe, cols = everything(), names_pattern = "(.)(.)", names_to = c(".value", "key")) Wide -> Long form
45. anscombe_long <- pivot_longer(data = anscombe, cols = everything(), names_pattern = "(.)(.)", names_to = c(".value", "key")) > anscombe_long # A tibble: 44 x 3 key x y <chr> <dbl> <dbl> 1 1 10 8.04 2 2 10 9.14 3 3 10 7.46 4 4 8 6.58 5 1 8 6.95 6 2 8 8.14 7 3 8 6.77 8 4 8 5.76 Anscombe's quartet
46. anscombe_long <- pivot_longer(data = anscombe, cols = everything(), names_pattern = "(.)(.)", names_to = c(".value", "key")) > anscombe_long # A tibble: 44 x 3 key x y <chr> <dbl> <dbl> 1 1 10 8.04 2 2 10 9.14 3 3 10 7.46 4 4 8 6.58 5 1 8 6.95 6 2 8 8.14 7 3 8 6.77 8 4 8 5.76 Anscombe's quartet g_anscomb <- ggplot(data = anscombe_long) + aes(x = x, y = y, color = key) + geom_point()
47. anscombe_long <- pivot_longer(data = anscombe, cols = everything(), names_pattern = "(.)(.)", names_to = c(".value", "key")) g_anscomb <- ggplot(data = anscombe_long)+ aes(x = x, y = y, color = key)+ geom_point() > anscombe_long # A tibble: 44 x 3 key x y <chr> <dbl> <dbl> 1 1 10 8.04 2 2 10 9.14 3 3 10 7.46 4 4 8 6.58 5 1 8 6.95 6 2 8 8.14 7 3 8 6.77 8 4 8 5.76 Anscombe's quartet
48. g_anscomb + facet_wrap( ~ key) Anscombe's quartet
49. g_anscomb + facet_wrap( ~ key) + theme(legend.position = "none") Anscombe's quartet
50. Wide Long Nested input output pivot_longer pivot_wider group_nest unnest ggplot visualization map output ggsave
51. Enjoy!! KMT©