Upgrade to Pro
— share decks privately, control downloads, hide ads and more …
Speaker Deck
Features
Speaker Deck
PRO
Sign in
Sign up for free
Search
Search
Tokyo.R #97 Data Visualization
Search
kilometer
March 19, 2022
Technology
1
360
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。
kilometer
March 19, 2022
Tweet
Share
More Decks by kilometer
See All by kilometer
TokyoR#111_ANOVA
kilometer
2
920
TokyoR109.pdf
kilometer
1
500
TokyoR#108_NestedDataHandling
kilometer
0
860
TokyoR#107_R_GeoData
kilometer
0
460
SappoRo.R_roundrobin
kilometer
0
160
TokyoR#104_DataProcessing
kilometer
1
720
TokyoR#103_DataProcessing
kilometer
0
930
TokyoR#102_RMarkdown
kilometer
1
680
TokyoR#101_RegressionAnalysis
kilometer
0
510
Other Decks in Technology
See All in Technology
ABEMAにおける 生成AI活用の現在地 / The Current Status of Generative AI at ABEMA
dekatotoro
0
650
mruby(PicoRuby)で ファミコン音楽を奏でる
kishima
1
220
ソフトウェア エンジニアとしての 姿勢と心構え
recruitengineers
PRO
2
620
GitHub Copilot coding agent を推したい / AIDD Nagoya #1
tnir
2
4.5k
つくって納得、つかって実感! 大規模言語モデルことはじめ
recruitengineers
PRO
19
5k
開発と脆弱性と脆弱性診断についての話
su3158
1
1.1k
ECS モニタリング手法大整理
yendoooo
1
120
知られざるprops命名の慣習 アクション編
uhyo
10
2.4k
事業価値と Engineering
recruitengineers
PRO
1
190
サービスロボット最前線:ugoが挑むPhysical AI活用
kmatsuiugo
0
190
Webアクセシビリティ入門
recruitengineers
PRO
1
230
フルカイテン株式会社 エンジニア向け採用資料
fullkaiten
0
8.6k
Featured
See All Featured
Let's Do A Bunch of Simple Stuff to Make Websites Faster
chriscoyier
507
140k
What’s in a name? Adding method to the madness
productmarketing
PRO
23
3.6k
Visualizing Your Data: Incorporating Mongo into Loggly Infrastructure
mongodb
48
9.6k
Typedesign – Prime Four
hannesfritz
42
2.8k
Why Our Code Smells
bkeepers
PRO
338
57k
Statistics for Hackers
jakevdp
799
220k
Designing for Performance
lara
610
69k
Fantastic passwords and where to find them - at NoRuKo
philnash
51
3.4k
It's Worth the Effort
3n
187
28k
The MySQL Ecosystem @ GitHub 2015
samlambert
251
13k
The Cult of Friendly URLs
andyhume
79
6.5k
Building a Modern Day E-commerce SEO Strategy
aleyda
43
7.5k
Transcript
#97 @kilometer00 2022.03.19 BeginneR Session -- Data Visualization --
Who!? 誰だ?
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
宣伝!!(書籍の翻訳に参加しました。)
BeginneR Session
BeginneR
Beginne R Advance d Hoxo_m If I have seen further
it is by standing on the shoulders of Giants. -- Sir Isaac Newton, 1676
Before After BeginneR Session BeginneR BeginneR
"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
George Boole 1815 - 1864 A Class-Room Introduc2on to Logic
h7ps://niyamaklogic.wordpress.com/c ategory/laws-of-thoughts/ Mathema;cian Philosopher &
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
Programing
Programing
Programing Write Run Read Think Write Run Read Think Communicate
Share
Text Image Information Intention Data decode encode Data analysis feedback
≠
Text Image First, A. Next, B. Then C. Finally D.
time Intention encode "Frozen" structure A B C D 8me value α β
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
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
σʔλ ใͷ͏ͪҙࢥୡɾղऍɾॲཧʹ దͨ͠࠶ར༻Մೳͳͷ ใ ࣮ଘΛූ߸Խͨ͠ද ࣮ଘ ؍ͷ༗ແʹΑΒͣଘࡏ͍ͯ͠Δ ͷͦͷͷ ࣸ૾ʢූ߸Խʣ
ࣸ૾ Ϧϯΰ ʢ࣮ଘʣ Ϧϯΰ ʢใʣ mapping
ࣸ૾ (mapping) 𝑓: 𝑋 → 𝑌 𝑋 𝑌 ͋Δใͷू߹ͷཁૉΛɺผͷใͷू߹ͷ ͨͩͭͷཁૉʹରԠ͚ͮΔϓϩηε
ใྔ ࣮ଘ ใ σʔλ Ϧϯΰ ූ߸Խ
ใྔ ࣮ଘ ใ σʔλ Ϧϯΰ ූ߸Խ ใྔͷଛࣦ
Ϧϯΰ ࣸ૾ ϑϧʔπ ৭ ը૾ ࣮ଘ ใ νϟωϧ mapping
channel
𝑋 𝑌 𝑦! 𝑥! 𝑦" 𝑥" 𝑋 𝑌 𝑥! 𝑥"
𝑦! 𝑦" σʔλՄࢹԽ ࣸ૾ mapping
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
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
࣮ଘ ࣸ૾ʢ؍ʣ σʔλ ࣸ૾ʢσʔλՄࢹԽʣ άϥϑ 𝑋 𝑌 𝑦! 𝑥! 𝑦"
𝑥" 𝑋 𝑌 𝑥! 𝑥" 𝑦! 𝑦" EBUB mapping aesthetic channels ৹ඒతνϟωϧ σʔλՄࢹԽ
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))
ॳΊͯͷHHQMPU
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 ؔͷதͰ৹ඒతཁૉͱͯ͠มͱνϟωϧͷରԠΛࢦఆ ඳը։࢝Λએݴ ه߸Ͱͭͳ͙ BFT ؔͷҾ໊ EBUͷม໊ άϥϑͷछྨʹ߹ΘͤͨHFPN@ ؔΛ༻
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)) ॳΊ͔ͯΒ൪ͷHHQMPU
ॳΊ͔ͯΒ൪ͷHHQMPU
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 NBQQJOHͷใ͕ॻ͔ΕͨBFT ؔΛHHQMPU ؔͷ֎ʹஔ͘͜ͱͰ͖Δ
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
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)) ͋ͱ͔Β ͰॏͶͨཁૉ͕લ໘ʹඳը͞ΕΔ
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)
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) αΠζσϑΥϧτͰΠϯν୯ҐͰࢦఆ
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
HFNP@ ؔ܈ DGIUUQTXXXSTUVEJPDPNSFTPVSDFTDIFBUTIFFUT
ෳ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·ͰͷࣝͰؤுΔͱ͜͏ͳΔ
HHQMPUʹΑΔσʔλՄࢹԽ ࣮ଘ ࣸ૾ʢ؍ʣ σʔλ ࣸ૾ʢσʔλՄࢹԽʣ άϥϑ 𝑋 𝑌 𝑦! 𝑥!
𝑦" 𝑥" SBXEBUB 写像 aesthetic channels ৹ඒతνϟωϧ ՄࢹԽʹదͨ͠EBUBܗࣜ 変形 ਤͷͭͷ৹ඒతνϟωϧ͕ σʔλͷͭͷมʹରԠ͍ͯ͠Δ
> 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 ʹରԠ͢ΔมʹͳΔΑ͏มܗ ݟ௨͠ྑ͘γϯϓϧʹՄࢹԽͰ͖Δ
> 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 ʹରԠ͢ΔมʹͳΔΑ͏มܗ anscombe_long <- pivot_longer(data = anscombe, cols = everything(), names_to = c(".value", "key"), names_pattern = "(.)(.)") ԣσʔλ ॎσʔλ
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) ਫ४ͰਤΛׂ͢Δ
Wide Long Nested input output pivot_longer pivot_wider group_nest unnest ggplot
visualization map output ggsave
Enjoy!! KMT©