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
910
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
920
TokyoR#102_RMarkdown
kilometer
1
680
TokyoR#101_RegressionAnalysis
kilometer
0
510
Other Decks in Technology
See All in Technology
Tableau API連携の罠!?脱スプシを夢見たはずが、逆に依存を深めた話
cuebic9bic
3
210
生成AI時代におけるAI・機械学習技術を用いたプロダクト開発の深化と進化 #BetAIDay
layerx
PRO
1
1k
Rubyの国のPerlMonger
anatofuz
3
730
相互運用可能な学修歴クレデンシャルに向けた標準技術と国際動向
fujie
0
200
マルチモーダル基盤モデルに基づく動画と音の解析技術
lycorptech_jp
PRO
4
500
風が吹けばWHOISが使えなくなる~なぜWHOIS・RDAPはサーバー証明書のメール認証に使えなくなったのか~
orangemorishita
15
5.5k
JAWS AI/ML #30 AI コーディング IDE "Kiro" を触ってみよう
inariku
3
270
【CEDEC2025】現場を理解して実現!ゲーム開発を効率化するWebサービスの開発と、利用促進のための継続的な改善
cygames
PRO
0
720
マルチプロダクト×マルチテナントを支えるモジュラモノリスを中心としたアソビューのアーキテクチャ
disc99
0
290
【CEDEC2025】『ウマ娘 プリティーダービー』における映像制作のさらなる高品質化へ!~ 豊富な素材出力と制作フローの改善を実現するツールについて~
cygames
PRO
0
230
2時間で300+テーブルをデータ基盤に連携するためのAI活用 / FukuokaDataEngineer
sansan_randd
0
130
【新卒研修資料】数理最適化 / Mathematical Optimization
brainpadpr
25
11k
Featured
See All Featured
How To Stay Up To Date on Web Technology
chriscoyier
790
250k
Bootstrapping a Software Product
garrettdimon
PRO
307
110k
Build The Right Thing And Hit Your Dates
maggiecrowley
37
2.8k
Creating an realtime collaboration tool: Agile Flush - .NET Oxford
marcduiker
30
2.2k
The Straight Up "How To Draw Better" Workshop
denniskardys
235
140k
Reflections from 52 weeks, 52 projects
jeffersonlam
351
21k
StorybookのUI Testing Handbookを読んだ
zakiyama
30
6k
Designing Dashboards & Data Visualisations in Web Apps
destraynor
231
53k
Music & Morning Musume
bryan
46
6.7k
Fight the Zombie Pattern Library - RWD Summit 2016
marcelosomers
234
17k
Java REST API Framework Comparison - PWX 2021
mraible
32
8.8k
Performance Is Good for Brains [We Love Speed 2024]
tammyeverts
10
1k
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©