Tokyo.R #97 Data Visualization

第97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。

Transcript

1. #97
   @kilometer00
   2022.03.19
   BeginneR Session
   -- Data Visualization --
   

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2. Who！？
   誰だ？
   

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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: むし社
   

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4. 宣伝!!（書籍の翻訳に参加しました。）
   

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5. BeginneR Session
   

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6. BeginneR
   

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7. Beginne
   R
   Advance
   d
   Hoxo_m
   If I have seen further it is by standing on the
   shoulders of Giants.
   -- Sir Isaac Newton, 1676
   

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8. Before After
   BeginneR Session
   BeginneR BeginneR
   

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9. "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
   

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10. George Boole
    1815 - 1864
    A Class-Room Introduc2on to Logic
    h7ps://niyamaklogic.wordpress.com/c
    ategory/laws-of-thoughts/
    Mathema;cian
    Philosopher
    &
    

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11. 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
    

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12. Programing
    

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13. Programing
    

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14. Programing
    Write
    Run
    Read
    Think
    Write
    Run
    Read
    Think
    Communicate
    Share
    

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15. Text Image
    Information
    Intention
    Data
    decode
    encode
    Data analysis
    feedback
    ≠
    

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16. Text
    Image
    First, A. Next, B.
    Then C. Finally D.
    time
    Intention
    encode
    "Frozen" structure
    A B C D 8me
    value
    α
    β
    

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17. σʔλ
    情報のうち意思伝達・解釈・処理に
    適した再利⽤可能なもの
    国際電気標準会議(International Electrotechnical Commission, IEC)による定義
    

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18. σʔλ
    情報のうち意思伝達・解釈・処理に
    適した再利⽤可能なもの
    ৘ใ 実存を符号化した表象
    

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19. σʔλ
    ৘ใͷ͏ͪҙࢥ఻ୡɾղऍɾॲཧʹ
    దͨ͠࠶ར༻Մೳͳ΋ͷ
    ৘ใ ࣮ଘΛූ߸Խͨ͠ද৅
    ࣮ଘ
    ؍࡯ͷ༗ແʹΑΒͣଘࡏ͍ͯ͠Δ
    ΋ͷͦͷ΋ͷ
    ࣸ૾ʢූ߸Խʣ
    

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20. ࣸ૾
    Ϧϯΰ
    ʢ࣮ଘʣ
    Ϧϯΰ
    ʢ৘ใʣ
    mapping
    

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21. ࣸ૾ (mapping)
    𝑓: 𝑋 → 𝑌
    𝑋 𝑌
    ͋Δ৘ใͷू߹ͷཁૉΛɺผͷ৘ใͷू߹ͷ
    ͨͩͭͷཁૉʹରԠ͚ͮΔϓϩηε
    

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22. ৘ใྔ
    ࣮ଘ
    ৘ใ
    σʔλ Ϧϯΰ
    ූ߸Խ
    

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23. ৘ใྔ
    ࣮ଘ
    ৘ใ
    σʔλ Ϧϯΰ
    ූ߸Խ
    ৘ใྔͷଛࣦ
    

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24. Ϧϯΰ
    ࣸ૾
    ϑϧʔπ
    ੺৭
    
    ը૾
    
    ࣮ଘ ৘ใ
    νϟωϧ
    mapping
    channel
    

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25. 𝑋
    𝑌
    𝑦!
    𝑥!
    𝑦"
    𝑥"
    𝑋 𝑌
    𝑥!
    𝑥"
    𝑦!
    𝑦"
    σʔλՄࢹԽ
    ࣸ૾
    mapping
    

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26. 𝑋
    𝑌
    𝑦!
    𝑥!
    𝑦"
    𝑥"
    𝑋 𝑌
    𝑥!
    𝑥"
    𝑦!
    𝑦"
    σʔλՄࢹԽ
    ࣸ૾
    mapping
    x axis, y axis, color, fill,
    shape, linetype, alpha…
    aesthetic channels
    ৹ඒతνϟωϧ
    

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27. 𝑋
    𝑌
    𝑦!
    𝑥!
    𝑦"
    𝑥"
    𝑋 𝑌
    𝑥!
    𝑥"
    𝑦!
    𝑦"
    σʔλՄࢹԽ
    ࣸ૾
    mapping
    x axis, y axis, color, fill,
    shape, linetype, alpha…
    aesthetic channels
    ৹ඒతνϟωϧ
    ggplot(data = my_data) +
    aes(x = X, y = Y)) +
    goem_point()
    HHQMPUʹΑΔ࡞ਤ
    

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28. ࣮ଘ
    ࣸ૾ʢ؍࡯ʣ
    σʔλ
    ࣸ૾ʢσʔλՄࢹԽʣ
    άϥϑ
    𝑋
    𝑌
    𝑦!
    𝑥!
    𝑦"
    𝑥"
    𝑋 𝑌
    𝑥!
    𝑥"
    𝑦!
    𝑦"
    EBUB
    mapping
    aesthetic channels
    ৹ඒతνϟωϧ
    σʔλՄࢹԽ
    

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29. ॳΊͯͷHHQMPU
    library(tidyverse)
    dat data.frame(tag = rep(c("a", "b"), each = 2),
    X = c(1, 3, 5, 7),
    Y = c(3, 9, 4, 2))
    ggplot() +
    geom_point(data = dat,
    mapping = aes(x = X, y = Y))
    

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30. ॳΊͯͷHHQMPU
    

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31. ॳΊͯͷHHQMPU
    library(tidyverse)
    dat data.frame(tag = rep(c("a", "b"), each = 2),
    X = c(1, 3, 5, 7),
    Y = c(3, 9, 4, 2))
    ggplot() +
    geom_point(data = dat,
    mapping = aes(x = X, y = Y))
    EBUBGSBNFͷࢦఆ
    BFT
    ؔ਺ͷதͰ৹ඒతཁૉͱͯ͠ม਺ͱνϟωϧͷରԠΛࢦఆ
    ඳը։࢝Λએݴ ه߸Ͱͭͳ͙
    BFT
    ؔ਺ͷҾ਺໊
    EBUͷม਺໊
    άϥϑͷछྨʹ߹ΘͤͨHFPN@
    ؔ਺Λ࢖༻
    

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32. library(tidyverse)
    dat data.frame(tag = rep(c("a", "b"), each = 2),
    X = c(1, 3, 5, 7),
    Y = c(3, 9, 4, 2))
    ggplot() +
    geom_point(data = dat,
    mapping = aes(x = X, y = Y)) +
    geom_path(data = dat,
    mapping = aes(x = X, y = Y))
    ॳΊ͔ͯΒ൪໨ͷHHQMPU
    

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33. ॳΊ͔ͯΒ൪໨ͷHHQMPU
    

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34. HHQMPUίʔυͷॻ͖ํͷ৭ʑ
    ggplot() +
    geom_point(data = dat,
    mapping = aes(x = X, y = Y)) +
    geom_path(data = dat,
    mapping = aes(x = X, y = Y))
    ggplot(data = dat,
    mapping = aes(x = X, y = Y)) +
    geom_point() +
    geom_path()
    ggplot(data = dat) +
    aes(x = X, y = Y) +
    geom_point() +
    geom_path()
    ڞ௨ͷࢦఆΛHHQMPU
    ؔ਺ͷதͰߦ͍ɺҎԼলུ͢Δ͜ͱ͕Մೳ
    NBQQJOHͷ৘ใ͕ॻ͔ΕͨBFT
    ؔ਺ΛHHQMPU
    ؔ਺ͷ֎ʹஔ͘͜ͱ΋Ͱ͖Δ
    

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35. HHQMPUίʔυͷॻ͖ํͷ৭ʑ
    ggplot() +
    geom_point(data = dat,
    mapping = aes(x = X, y = Y, color = tag)) +
    geom_path(data = dat,
    mapping = aes(x = X, y = Y))
    ggplot(data = dat) +
    aes(x = X, y = Y) + # 括り出すのは共通するものだけ
    geom_point(mapping = aes(color = tag)) +
    geom_path()
    ϙΠϯτͷ৭ͷNBQQJOHΛࢦఆ
    

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36. HHQMPUίʔυͷॻ͖ํͷ৭ʑ
    ggplot(data = dat) +
    aes(x = X, y = Y) +
    geom_point(aes(color = tag)) +
    geom_path()
    ggplot(data = dat) +
    aes(x = X, y = Y) +
    geom_path() +
    geom_point(aes(color = tag))
    ͋ͱ͔ΒͰॏͶͨཁૉ͕લ໘ʹඳը͞ΕΔ
    

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37. library(tidyverse)
    dat data.frame(tag = rep(c("a", "b"), each = 2),
    X = c(1, 3, 5, 7),
    Y = c(3, 9, 4, 2))
    g ggplot(data = dat) +
    aes(x = X, y = Y) +
    geom_path() +
    geom_point(mapping = aes(color = tag))
    HHQMPUը૾ͷอଘ
    ggsave(filename = "fig/demo01.png",
    plot = g,
    width = 4, height = 3, dpi = 150)
    

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38. library(tidyverse)
    dat data.frame(tag = rep(c("a", "b"), each = 2),
    X = c(1, 3, 5, 7),
    Y = c(3, 9, 4, 2))
    g ggplot(data = dat) +
    aes(x = X, y = Y) +
    geom_path() +
    geom_point(mapping = aes(color = tag))
    HHQMPUը૾ͷอଘ
    ggsave(filename = "fig/demo01.png",
    plot = g,
    width = 4, height = 3, dpi = 150)
    αΠζ͸σϑΥϧτͰ͸Πϯν୯ҐͰࢦఆ
    

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39. library(tidyverse)
    dat data.frame(tag = rep(c("a", "b"), each = 2),
    X = c(1, 3, 5, 7),
    Y = c(3, 9, 4, 2))
    g ggplot(data = dat) +
    aes(x = X, y = Y) +
    geom_path() +
    geom_point(mapping = aes(color = tag))
    HHQMPUը૾ͷอଘ
    ggsave(filename = "fig/demo01.png",
    plot = g,
    width = 10, height = 7.5, dpi = 150,
    units = "cm") # "cm", "mm", "in"を指定可能
    

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40. HFNP@
    ؔ਺܈ DGIUUQTXXXSTUVEJPDPNSFTPVSDFTDIFBUTIFFUT
    

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41. ෳ਺ͷܥྻΛඳը͢Δ
    > head(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
    ggplot(data = anscombe) +
    geom_point(aes(x = x1, y = y1)) +
    geom_point(aes(x = x2, y = y2), color = "Red") +
    geom_point(aes(x = x3, y = y3), color = "Blue") +
    geom_point(aes(x = x4, y = y4), color = "Green")
    ͜Ε·Ͱͷ஌ࣝͰؤுΔͱ͜͏ͳΔ
    

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42. HHQMPUʹΑΔσʔλՄࢹԽ
    ࣮ଘ
    ࣸ૾ʢ؍࡯ʣ
    σʔλ
    ࣸ૾ʢσʔλՄࢹԽʣ
    άϥϑ
    𝑋
    𝑌
    𝑦!
    𝑥!
    𝑦"
    𝑥"
    SBXEBUB
    写像
    aesthetic channels
    ৹ඒతνϟωϧ
    ՄࢹԽʹదͨ͠EBUBܗࣜ
    変形
    ਤͷͭͷ৹ඒతνϟωϧ͕
    σʔλͷͭͷม਺ʹରԠ͍ͯ͠Δ
    

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43. > head(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
    > head(anscombe_long)
    key x y
    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
    ggplot(data = anscombe_long) +
    aes(x = x, y = y, color = key) +
    geom_point()
    ৹ඒతνϟωϧ Y࣠ Z࣠ ৭
    ʹରԠ͢Δม਺ʹͳΔΑ͏มܗ
    ݟ௨͠ྑ͘γϯϓϧʹՄࢹԽͰ͖Δ
    

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44. > head(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
    > head(anscombe_long)
    key x y
    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
    ৹ඒతνϟωϧ Y࣠ Z࣠ ৭
    ʹରԠ͢Δม਺ʹͳΔΑ͏มܗ
    anscombe_long pivot_longer(data = anscombe,
    cols = everything(),
    names_to = c(".value",
    "key"),
    names_pattern = "(.)(.)")
    ԣ௕σʔλ
    ॎ௕σʔλ
    

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45. ggplot(data = anscombe_long) +
    aes(x = x, y = y, color = key) +
    geom_point()
    ggplot(data = anscombe_long) +
    aes(x = x, y = y, color = key) +
    geom_point() +
    facet_wrap(facets = . ~ key, nrow = 1)
    ਫ४ͰਤΛ෼ׂ͢Δ
    

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46. Wide Long
    Nested
    input output
    pivot_longer
    pivot_wider
    group_nest
    unnest
    ggplot
    visualization
    map
    output
    ggsave
    

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47. Enjoy!!
    KMT©
    

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