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
さまざまなグラフ描画(1) / Various graphical representatio...
Search
Kenji Saito
PRO
November 29, 2024
Technology
0
74
さまざまなグラフ描画(1) / Various graphical representations (1)
早稲田大学大学院経営管理研究科「企業データ分析」2024 冬のオンデマンド教材 第7回で使用したスライドです。
Kenji Saito
PRO
November 29, 2024
Tweet
Share
More Decks by Kenji Saito
See All by Kenji Saito
生成AI による論文執筆サポート・ワークショップ データ分析/論文ドラフト編 / Generative AI-Assisted Paper Writing Support Workshop: Data Analysis and Drafting Edition
ks91
PRO
0
28
生成AI による論文執筆サポート・ワークショップ コーディング・エージェントのインストール編 / Generative AI-Assisted Academic Writing Support Workshop: Installing the Coding Agents
ks91
PRO
0
7
FinTech 9-10 : Smart Contracts and Decentralized Finance
ks91
PRO
0
49
AI とデジタルトランスフォーメーション / AI and Digital Transformation
ks91
PRO
0
6
スマートコントラクトデザイン / Smart Contract Design
ks91
PRO
0
10
FinTech 7-8 : Blockchain
ks91
PRO
0
99
スマートコントラクトプログラミング / Smart Contract Programming
ks91
PRO
0
21
AI が研究する時代に、人はどう育つのか? — GAMER PAT にみる "シリアスゲームとしての知的訓練" / In an era where AI conducts research, how will humans develop? — "Intellectual Training as a Serious Game" Seen in GAMER PAT
ks91
PRO
0
69
FinTech 5-6 : The World of Apps
ks91
PRO
0
110
Other Decks in Technology
See All in Technology
Gov-JAWS4回_某団体でのAmazon Bedrock活用検証で見えた“使う側”の課題精度よりもリテラシー
takuma818t
0
120
今から間に合う re:Invent 準備グッズと現地の地図、その他ラスベガスを周る際の Tips/reinvent-preparation-guide
emiki
1
290
Databricks Free Editionで始めるMLflow
taka_aki
0
800
Copilotの精度を上げる!カスタムプロンプト入門.pdf
ismk
9
1.8k
AIの個性を理解し、指揮する
shoota
3
640
初海外がre:Inventだった人間の感じたこと
tommy0124
1
200
re:Inventに行きたい いつか行きたい 行けるようにできることは?
yama3133
0
100
データとAIで明らかになる、私たちの課題 ~Snowflake MCP,Salesforce MCPに触れて~ / Data and AI Insights
kaonavi
0
340
決済システムの信頼性を支える技術と運用の実践
ykagano
0
120
仕様駆動開発を実現する上流工程におけるAIエージェント活用
sergicalsix
12
6k
QAEが生成AIと越える、ソフトウェア開発の境界線
rinchsan
0
400
20251102 WordCamp Kansai 2025
chiilog
1
570
Featured
See All Featured
Designing for Performance
lara
610
69k
Distributed Sagas: A Protocol for Coordinating Microservices
caitiem20
333
22k
Building a Scalable Design System with Sketch
lauravandoore
463
33k
Building Better People: How to give real-time feedback that sticks.
wjessup
370
20k
Creating an realtime collaboration tool: Agile Flush - .NET Oxford
marcduiker
34
2.3k
YesSQL, Process and Tooling at Scale
rocio
174
15k
Typedesign – Prime Four
hannesfritz
42
2.9k
Designing Experiences People Love
moore
142
24k
Building Applications with DynamoDB
mza
96
6.7k
Side Projects
sachag
455
43k
GraphQLの誤解/rethinking-graphql
sonatard
73
11k
Put a Button on it: Removing Barriers to Going Fast.
kastner
60
4.1k
Transcript
Boxes and whiskers — generated by Stable Diffusion XL v1.0
2024 7 (1) (WBS) 2024 7 (1) — 2024-11 – p.1/18
https://speakerdeck.com/ks91/collections/corporate-data-analysis-2024-winter 2024 7 (1) — 2024-11 – p.2/18
( 20 ) 1 • 2 R • 3 •
4 • 5 • 6 ( ) • 7 (1) • 8 (2) 9 R ( ) (1) 10 R ( ) (2) 11 R ( ) (1) 12 R ( ) (2) 13 GPT-4 14 GPT-4 15 ( ) LaTeX Overleaf 8 (12/16 ) / (2 ) OK / 2024 7 (1) — 2024-11 – p.3/18
( ) ( ) 2024 7 (1) — 2024-11 –
p.4/18
(line chart) x y cda-demo “ -1.R” Git “ -1.R”
1 2024 7 (1) — 2024-11 – p.5/18
“ .txt” 1 1 <- read.table(" .txt", header=T) A 4
plot( 1$ , 1$A , type="o", pch=0, ylim=c(40, 80), xaxp=c(1,4,3), ylab=" ", xlab=" ", main="A ") ‘type="o"’ ‘pch=0’ ‘xaxp=c(1,4,3)’ x 1 4 3 1.5 2024 7 (1) — 2024-11 – p.6/18
1 2 3 4 40 50 60 70 80 A⤌ࡢᖹᆒⅬࡢ᥎⛣
ᶍヨᅇ ᖹᆒⅬ 2024 7 (1) — 2024-11 – p.7/18
plot ( ) type ( ) : "p" ( )
"l" ( ) "o" ( ) "h" ( ) cf. https://r-charts.com/base-r/line-types/ (Line plot types) pch (plotting character)( ) : 0 ( ) 1 (◦) 2 (△) 3 (+) 4 (×) cf. https://r-charts.com/base-r/pch-symbols/ lty (line type)( ) : 1 ( ) 2 ( ) 3 ( ) cf. https://r-charts.com/base-r/line-types/ (Line types) lwd (line width)( ) 2024 7 (1) — 2024-11 – p.8/18
(1/2) A B plot( 1$ , 1$A , type="o", lty=1,
pch=1, col=1, ylim=c(40, 80), xaxp=c(1,4,3), ylab=" ", xlab=" ", main="A,B,C,D ") par(new=T) plot( 1$ , 1$B , type="o", lty=2, pch=2, col=2, ylim=c(40, 80), xaxp=c(1,4,3), axes=F, ann=F) ‘par(new=T)’ ( ) B plot ‘axes=F’ ‘ann=F’ ‘ylim’ ‘xaxp’ ‘lty’ ‘pch’ ‘col’ 2024 7 (1) — 2024-11 – p.9/18
(2/2) C D par(new=T) plot( 1$ , 1$C , type="o",
lty=3, pch=3, col=3, ylim=c(40, 80), xaxp=c(1,4,3), axes=F, ann=F) par(new=T) plot( 1$ , 1$D , type="o", lty=4, pch=4, col=4, ylim=c(40, 80), xaxp=c(1,4,3), axes=F, ann=F) legend("topleft", legend=names( 1)[2:5], lty=1:4, pch=1:4, col=1:4) ‘legend(. . .)’ ( top-left) 2024 7 (1) — 2024-11 – p.10/18
1 2 3 4 40 50 60 70 80 A,B,C,D⤌ࡢᖹᆒⅬࡢ᥎⛣
ᶍヨᅇ ᖹᆒⅬ A⤌ B⤌ C⤌ D⤌ 2024 7 (1) — 2024-11 – p.11/18
(radar chart) n n 0 n n 2024 7 (1)
— 2024-11 – p.12/18
(1/2) AI(GPT-4) install.packages("fmsb") library("fmsb") 2 <- read.table(" .txt", header=T) maxmin
<- data.frame( =c(7,0), =c(7,0), =c(7,0), =c(7,0), =c(7,0)) fmsb ( ) maxmin 2024 7 (1) — 2024-11 – p.13/18
(2/2) data <- rbind(maxmin, 2) radarchart(data, seg=7, centerzero=T, title="GPT-4 ")
legend("topleft", legend=c(" ", " "), lty=1:2, pch=16, col=c("black", "red")) ‘rbind(. . .)’ ‘radarchart(. . .)’ 2 3 ( 1∼ ) ‘seg=7’ 7 ‘centerzero=T’ 0 2024 7 (1) — 2024-11 – p.14/18
GPT-4 ࡼࡿே㛫ࡢᛶ᱁ࡢᨃែ ༠ㄪᛶ ㄔᐇᛶ እྥᛶ ᚰ㓄ᛶ 㛤ᨺᛶ ᨃែࡢᑐ㇟ ᨃែࡢ⤖ᯝ 2024
7 (1) — 2024-11 – p.15/18
2 barplot(as.matrix( 2), beside=T, ylim=c(0, 7), yaxp=c(1,7,6), col=c("black", "red"), density=c(25,
50), legend.text=c(" ", " "), args.legend=list(x="topleft"), main="GPT-4 ") ‘as.matrix(. . .)’ ( ) ‘args.legend’ 2024 7 (1) — 2024-11 – p.16/18
༠ㄪᛶ እྥᛶ 㛤ᨺᛶ ᨃែࡢᑐ㇟ ᨃែࡢ⤖ᯝ GPT-4 ࡼࡿே㛫ࡢᛶ᱁ࡢᨃែ 1 2 3
4 5 6 7 ㄔᐇᛶ ᚰ㓄ᛶ 2024 7 (1) — 2024-11 – p.17/18
2024 7 (1) — 2024-11 – p.18/18