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 Charts (and Pie Chart)
Search
Kenji Saito
PRO
December 10, 2023
Business
0
260
棒グラフ、帯グラフ(、円グラフ) / Bar Charts (and Pie Chart)
早稲田大学大学院経営管理研究科「企業データ分析」2023 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
December 10, 2023
Tweet
Share
More Decks by Kenji Saito
See All by Kenji Saito
スマートコントラクトデザイン / Smart Contract Design
ks91
PRO
0
5
FinTech 7-8 : Blockchain
ks91
PRO
0
70
スマートコントラクトプログラミング / Smart Contract Programming
ks91
PRO
0
19
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
51
FinTech 5-6 : The World of Apps
ks91
PRO
0
100
生成AI による論文執筆サポート・ワークショップ ─ サーベイ/リサーチクエスチョン編 / Workshop on AI-Assisted Paper Writing Support: Survey/Research Question Edition
ks91
PRO
0
81
ブロックチェーン概論とインストール大会 / Introduction to Blockchain and Installation Workshop
ks91
PRO
0
10
FinTech 3-4 : Internet Technology and Governance
ks91
PRO
0
83
民主主義と博愛(Humanitarianism) / Democracy and Humanitarianism
ks91
PRO
0
15
Other Decks in Business
See All in Business
フルカイテン株式会社 採用資料
fullkaiten
0
76k
Mercari Group Code of Conduct
mercari_inc
0
250
株式会社EventHub 会社紹介資料
eventhub
1
40k
Kyash TechTalk #8 Kyashにおけるクレジット事業部とは
sayueda
0
130
マネージャーの「責任」、サーバントリーダーの「精神」 スクラムマスターの「行動」
ichizin
2
120
メルカリグループ行動規範
mercari_inc
0
580
Gemini と NotebookLM を組み合わせて 目標設定の負荷を軽減する方法 / Goal setting with gemini and notebooklm
tbpgr
19
38k
社内請負スクラムから脱却する〜複雑性に適応するスクラムチームの作り方〜
yasuhirokimesawa
1
180
Guiding teams, and shaping a portfolio, using Wardley Maps & DDD at KanDDDinsky
marijn
0
100
MagicPodを使い倒すメドレーの活用術 / How to utilize of MagicPod
medley
1
200
TechnoKuRo LLC.
technokuro
0
400
テオリア・テクノロジーズ:About Us
theoriatec2024
2
40k
Featured
See All Featured
How Fast Is Fast Enough? [PerfNow 2025]
tammyeverts
2
94
JavaScript: Past, Present, and Future - NDC Porto 2020
reverentgeek
52
5.7k
Designing for Performance
lara
610
69k
Why Our Code Smells
bkeepers
PRO
340
57k
Building a Modern Day E-commerce SEO Strategy
aleyda
44
7.8k
Put a Button on it: Removing Barriers to Going Fast.
kastner
60
4k
Leading Effective Engineering Teams in the AI Era
addyosmani
7
650
Distributed Sagas: A Protocol for Coordinating Microservices
caitiem20
333
22k
Git: the NoSQL Database
bkeepers
PRO
431
66k
CSS Pre-Processors: Stylus, Less & Sass
bermonpainter
359
30k
The Psychology of Web Performance [Beyond Tellerrand 2023]
tammyeverts
49
3.1k
Understanding Cognitive Biases in Performance Measurement
bluesmoon
31
2.7k
Transcript
generated by Stable Diffusion XL v1.0 2023 6 ( )
(WBS) 2023 6 ( ) — 2023-12 – p.1/23
https://speakerdeck.com/ks91/collections/corporate-data-analysis-2023-winter 2023 6 ( ) — 2023-12 – 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 (12/21 ) / (2 ) OK / 2023 6 ( ) — 2023-12 – p.3/23
( ) ( ) 2023 6 ( ) — 2023-12
– p.4/23
(bar chart) y ( ) cda-demo “ .R” Git 1
2023 6 ( ) — 2023-12 – 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( . . . )’ : 2023 6 ( ) — 2023-12 – 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 2023 6 ( ) — 2023-12 – 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 ") : 2023 6 ( ) — 2023-12 – 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 2023 6 ( ) — 2023-12 – p.9/23
100% barplot 2023 6 ( ) — 2023-12 – 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 ") # 2023 6 ( ) — 2023-12 – 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 2023 6 ( ) — 2023-12 – p.12/23
Xᆅᇦ Yᆅᇦ A♫〇 B♫〇 C♫〇 D♫〇 ᆅᇦูࢩ࢙ ࢩ࢙ (%) 0
20 40 60 80 100 2023 6 ( ) — 2023-12 – p.13/23
( ) barplot(data, col=cm.colors(4), ylab=" (%)", legend.text=names(data1), main=" ") ‘horiz’
R ggplot2 2023 6 ( ) — 2023-12 – p.14/23
Xᆅᇦ Yᆅᇦ D♫〇 C♫〇 B♫〇 A♫〇 ᆅᇦูࢩ࢙ ࢩ࢙ (%) 0
20 40 60 80 100 2023 6 ( ) — 2023-12 – p.15/23
barplot(data, beside=T, col=cm.colors(4), ylab=" (%)", legend.text=names(data1), main=" ") ‘beside=T’ 2023
6 ( ) — 2023-12 – p.16/23
Xᆅᇦ Yᆅᇦ A♫〇 B♫〇 C♫〇 D♫〇 ᆅᇦูࢩ࢙ ࢩ࢙ (%) 0
10 20 30 40 50 2023 6 ( ) — 2023-12 – p.17/23
## ## col ## density density <- c(50, 25, 13,
7) barplot(data, beside=T, density=density, ylab=" (%)", legend.text=names(data1), main=" ") ‘density’ 2023 6 ( ) — 2023-12 – p.18/23
Xᆅᇦ Yᆅᇦ A♫〇 B♫〇 C♫〇 D♫〇 ᆅᇦูࢩ࢙ ࢩ࢙ (%) 0
10 20 30 40 50 2023 6 ( ) — 2023-12 – p.19/23
2023 6 ( ) — 2023-12 – p.20/23
pie(data1, col=cm.colors(4), main="X ") pie(data2, col=cm.colors(4), main="Y ") ‘pie( .
. . )’ 2023 6 ( ) — 2023-12 – 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 2023 6 ( ) — 2023-12 – p.22/23
2023 6 ( ) — 2023-12 – p.23/23