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
棒グラフ、帯グラフ(、円グラフ) / Bar chart, band chart (, pie...
Search
Kenji Saito
PRO
November 29, 2024
Technology
0
97
棒グラフ、帯グラフ(、円グラフ) / Bar chart, band chart (, pie chart)
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6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
FinTech 3-4 : Internet Technology and Governance
ks91
PRO
0
19
民主主義と博愛(Humanitarianism) / Democracy and Humanitarianism
ks91
PRO
0
1
ブロックチェーン概論 / Introduction to Blockchain
ks91
PRO
0
6
ブロックチェーンと分散ファイナンス概論 / Introduction to Blockchain and Decentralized Finance
ks91
PRO
0
47
Proof of Authenticity of General IoT Information with Tamper-Evident Sensors and Blockchain
ks91
PRO
0
5
FinTech 1-2 : Overview of FinTech
ks91
PRO
0
14
デジタルトランスフォーメーションと民主主義 / Digital Transformation and Democracy
ks91
PRO
0
19
We Never Took the Kobayashi Maru Test Until Now. What Do You Think of Our Solutions? — Journeys of the Mind Through a No-Win Game
ks91
PRO
0
24
思いつきが武器になる:研究というゲームを始めよう / Ideas Are Your Equipments : Let the Game of Research Begin!
ks91
PRO
0
79
Other Decks in Technology
See All in Technology
Trust as Infrastructure
bcantrill
0
340
KMP の Swift export
kokihirokawa
0
330
いま注目しているデータエンジニアリングの論点
ikkimiyazaki
0
600
データエンジニアがこの先生きのこるには...?
10xinc
0
450
KAGのLT会 #8 - 東京リージョンでGAしたAmazon Q in QuickSightを使って、報告用の資料を作ってみた
0air
0
210
許しとアジャイル
jnuank
1
130
GA technologiesでのAI-Readyの取り組み@DataOps Night
yuto16
0
270
研究開発部メンバーの働き⽅ / Sansan R&D Profile
sansan33
PRO
3
20k
社内お問い合わせBotの仕組みと学び
nish01
0
410
How to achieve interoperable digital identity across Asian countries
fujie
0
120
フルカイテン株式会社 エンジニア向け採用資料
fullkaiten
0
9.1k
動画データのポテンシャルを引き出す! Databricks と AI活用への奮闘記(現在進行形)
databricksjapan
0
150
Featured
See All Featured
実際に使うSQLの書き方 徹底解説 / pgcon21j-tutorial
soudai
PRO
188
55k
Distributed Sagas: A Protocol for Coordinating Microservices
caitiem20
333
22k
Done Done
chrislema
185
16k
Writing Fast Ruby
sferik
629
62k
"I'm Feeling Lucky" - Building Great Search Experiences for Today's Users (#IAC19)
danielanewman
229
22k
Faster Mobile Websites
deanohume
310
31k
Why Our Code Smells
bkeepers
PRO
339
57k
[RailsConf 2023] Rails as a piece of cake
palkan
57
5.9k
Designing Dashboards & Data Visualisations in Web Apps
destraynor
231
53k
The Invisible Side of Design
smashingmag
301
51k
Six Lessons from altMBA
skipperchong
28
4k
Evolution of real-time – Irina Nazarova, EuRuKo, 2024
irinanazarova
9
960
Transcript
Boxes and whiskers — generated by Stable Diffusion XL v1.0
2024 6 ( ) (WBS) 2024 6 ( ) — 2024-11 – p.1/23
https://speakerdeck.com/ks91/collections/corporate-data-analysis-2024-winter 2024 6 ( ) — 2024-11 – p.2/23
( 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 6 ( ) — 2024-11 – p.3/23
( ) ( ) 2024 6 ( ) — 2024-11
– p.4/23
(bar chart) y ( ) cda-demo “ .R” Git “
.R” 1 2024 6 ( ) — 2024-11 – p.5/23
“ .txt” 1 1 <- read.table(" .txt", header=T) 10 barplot(
1$ [1:10], names.arg=c(1:10), xlab=" ", ylab=" ", main=" 1 10 ") ‘barplot( . . . )’ : 2024 6 ( ) — 2024-11 – p.6/23
1 2 3 4 5 6 7 8 9 10
ฟᖍ␒ྕ1ࠥ10ࡢⱥㄒࡢヨ㦂⤖ᯝ ฟᖍ␒ྕ ᚓⅬ 0 20 40 60 80 2024 6 ( ) — 2024-11 – p.7/23
( 10 ) 1 2 ## t(table) table ## (matrix)
2 <- t( data.frame( = 1$ [1:10], = 1$ [1:10])) (‘beside=T’) barplot( , beside=T, names.arg=c(1:10), legend.text=T, ylim=c(0, 100), xlab=" ", ylab=" ", main=" 1 10 ") : 2024 6 ( ) — 2024-11 – p.8/23
1 2 3 4 5 6 7 8 9 10
ⱥㄒ ᩘᏛ ฟᖍ␒ྕ1ࠥ10ࡢⱥㄒ࣭ᩘᏛࡢヨ㦂⤖ᯝ ฟᖍ␒ྕ ᚓⅬ 0 20 40 60 80 100 2024 6 ( ) — 2024-11 – p.9/23
100% barplot 2024 6 ( ) — 2024-11 – p.10/23
A∼D ( 100%) X Y data1 <- c( "A "=51,
"B "=21, "C "=20, "D "=8) data2 <- c( "A "=33, "B "=35, "C "=20, "D "=12) data <- matrix(c(data1, data2), length(data1), 2) # 4 2 colnames(data) <- c("X ", "Y ") # 2024 6 ( ) — 2024-11 – p.11/23
barplot(data, horiz=T, col=cm.colors(4), xlab=" (%)", legend.text=names(data1), main=" ") ‘horiz’ (
F (False)) ‘col’ ‘cm.colors(4)’ cm ( ) 4 ‘legend.text=names(data1)’ data1 2024 6 ( ) — 2024-11 – p.12/23
Xᆅᇦ Yᆅᇦ A♫〇 B♫〇 C♫〇 D♫〇 ᆅᇦูࢩ࢙ ࢩ࢙ (%) 0
20 40 60 80 100 2024 6 ( ) — 2024-11 – p.13/23
( ) barplot(data, col=cm.colors(4), ylab=" (%)", legend.text=names(data1), main=" ") ‘horiz’
R ggplot2 2024 6 ( ) — 2024-11 – p.14/23
Xᆅᇦ Yᆅᇦ D♫〇 C♫〇 B♫〇 A♫〇 ᆅᇦูࢩ࢙ ࢩ࢙ (%) 0
20 40 60 80 100 2024 6 ( ) — 2024-11 – p.15/23
barplot(data, beside=T, col=cm.colors(4), ylab=" (%)", legend.text=names(data1), main=" ") ‘beside=T’ 2024
6 ( ) — 2024-11 – p.16/23
Xᆅᇦ Yᆅᇦ A♫〇 B♫〇 C♫〇 D♫〇 ᆅᇦูࢩ࢙ ࢩ࢙ (%) 0
10 20 30 40 50 2024 6 ( ) — 2024-11 – p.17/23
## ## col ## density density <- c(50, 25, 13,
7) barplot(data, beside=T, density=density, ylab=" (%)", legend.text=names(data1), main=" ") ‘density’ 2024 6 ( ) — 2024-11 – p.18/23
Xᆅᇦ Yᆅᇦ A♫〇 B♫〇 C♫〇 D♫〇 ᆅᇦูࢩ࢙ ࢩ࢙ (%) 0
10 20 30 40 50 2024 6 ( ) — 2024-11 – p.19/23
2024 6 ( ) — 2024-11 – p.20/23
pie(data1, col=cm.colors(4), main="X ") pie(data2, col=cm.colors(4), main="Y ") ‘pie( .
. . )’ 2024 6 ( ) — 2024-11 – p.21/23
A♫〇 B♫〇 C♫〇 D♫〇 Xᆅᇦ࡛ࡢࢩ࢙ A♫〇 B♫〇 C♫〇 D♫〇 Yᆅᇦ࡛ࡢࢩ࢙
X B C Y A B D % p.15 p.17 2024 6 ( ) — 2024-11 – p.22/23
2024 6 ( ) — 2024-11 – p.23/23