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
TokyoR#93
Search
Sponsored
·
Ship Features Fearlessly
Turn features on and off without deploys. Used by thousands of Ruby developers.
→
soriente
July 03, 2021
Technology
270
0
Share
TokyoR#93
TokyoR#93の初心者セッション可視化パートです。
soriente
July 03, 2021
Other Decks in Technology
See All in Technology
こんなアーキテクチャ図はいやだ / Anti-pattern in AWS Architecture Diagrams
naospon
1
430
20年前の「OSS革命」に学ぶ AI時代の生存戦略
samakada
0
290
猫でもわかるKiro CLI(CDKコーディング編)
kentapapa
1
130
データを"持てない"環境でのアノテーション基盤設計
sansantech
PRO
1
100
ネットワーク運用を楽にするAWS DevOps Agent活用法!! / 20260421 Masaki Okuda
shift_evolve
PRO
2
190
自分のハンドルは自分で握れ! ― 自分のケイパビリティを増やし、メンバーのケイパビリティ獲得を支援する ― / Take the wheel yourself
takaking22
1
840
Revisiting [CLS] and Patch Token Interaction in Vision Transformers
yu4u
0
330
JEDAI in Osaka 2026イントロ
taka_aki
0
280
最初の一歩を踏み出せなかった私が、誰かの背中を押したいと思うようになるまで / give someone a push
mii3king
0
160
小説執筆のハーネスエンジニアリング
yoshitetsu
0
340
レビューしきれない?それは「全て人力でのレビュー」だからではないでしょうか
amixedcolor
0
290
ARIA Notifyについて
ryokatsuse
1
120
Featured
See All Featured
Leveraging LLMs for student feedback in introductory data science courses - posit::conf(2025)
minecr
1
230
Bridging the Design Gap: How Collaborative Modelling removes blockers to flow between stakeholders and teams @FastFlow conf
baasie
0
510
brightonSEO & MeasureFest 2025 - Christian Goodrich - Winning strategies for Black Friday CRO & PPC
cargoodrich
3
680
Efficient Content Optimization with Google Search Console & Apps Script
katarinadahlin
PRO
1
500
The SEO identity crisis: Don't let AI make you average
varn
0
440
Documentation Writing (for coders)
carmenintech
77
5.3k
Breaking role norms: Why Content Design is so much more than writing copy - Taylor Woolridge
uxyall
0
260
Balancing Empowerment & Direction
lara
6
1.1k
What does AI have to do with Human Rights?
axbom
PRO
1
2.1k
Java REST API Framework Comparison - PWX 2021
mraible
34
9.3k
Fantastic passwords and where to find them - at NoRuKo
philnash
52
3.6k
Future Trends and Review - Lecture 12 - Web Technologies (1019888BNR)
signer
PRO
0
3.5k
Transcript
5PLZP3σʔλՄࢹԽ ॳ৺ऀηογϣϯ
ࣗݾհ w TPSJFOUF w *5اۀۈ w 3ྺ ࡉͬͯ͘͘·͢ɻ w
ͱ͍ͬͯ࠷ۙ1ZUIPO͕ϝΠϯ w 1)1ॻ͍ͯͨ࣌ظ͋Γ·ͨ͠ɻ
ՄࢹԽͱ w จࣈͷ௨Γɺݟ͑ΔԽ͢Δɻ σʔλੳͷจ຺ͰɺσʔλͷؔੑΛݟ͑ ΔԽ͢Δɻ w ՄࢹԽΛ͚ͨͩ͠ͰΘ͔Δ͜ͱଟ͍ɻ w ՄࢹԽΛ͢ΔͱɺΘ͔Γ͍͢ɻ
w ՄࢹԽΛͨ͋͠ͱʹԿΒ͔ͷҙࢥܾఆΛߦ͏͜ͱ͕ଟ͍ɻ ੳऀ͕ࣗҙࢥ ܾఆ͢Δ͜ͱɺ୭͔ʹҙࢥܾఆͯ͠Β͏͜ͱ͋Δɻ
None
HHQMPUͷجຊ
HHQMPUͱ w ՄࢹԽͷͨΊͷϥΠϒϥϦ w UJEZWFSTFͷϥΠϒϥϦ܈ͷҰͭ w ʰ5IF(SBNNBSPG(SBQIJDTʱΛϕʔεʹ࡞ΒΕ͍ͯΔ ˠҰ؏ੑͷ͋Δจ๏Ͱ߹ཧతʹॻ͚Δʂ
ࠓճ͏σʔλQFOHVJOT JOTUBMMQBDLBHFT QBMNFSQFOHVJOT MJCSBSZ QBMNFSQFOHVJOT IFBE QFOHVJOT
TQFDJFT JTMBOE CJMM@MFOHUI@NN CJMM@EFQUI@NN fl JQQFS@MFOHUI@NN CPEZ@NBTT@H TFY ZFBS "EFMJF 5PSHFSTFO NBMF "EFMJF 5PSHFSTFO GFNBMF "EFMJF 5PSHFSTFO GFNBMF "EFMJF 5PSHFSTFO /" /" /" /" /" "EFMJF 5PSHFSTFO GFNBMF "EFMJF 5PSHFSTFO NBMF
QFOHVJOT
HHQMPUΠϯετʔϧಡΈࠐΈ JOTUBMMQBDLBHFT HHQMPU JOTUBMMQBDLBHFT UJEZWFSTF ͰՄ MJCSBSZ HHQMPU MJCSBSZ UJEZWFSTF
ͰՄ
ࠓճॻ͘άϥϑͷछྨ w ࢄਤ w άϥϑ w ંΕઢάϥϑ
ࠓճ͏σʔλQFOHVJOT JOTUBMMQBDLBHFT QBMNFSQFOHVJOT MJCSBSZ QBMNFSQFOHVJOT IFBE QFOHVJOT
TQFDJFT JTMBOE CJMM@MFOHUI@NN CJMM@EFQUI@NN fl JQQFS@MFOHUI@NN CPEZ@NBTT@H TFY ZFBS "EFMJF 5PSHFSTFO NBMF "EFMJF 5PSHFSTFO GFNBMF "EFMJF 5PSHFSTFO GFNBMF "EFMJF 5PSHFSTFO /" /" /" /" /" "EFMJF 5PSHFSTFO GFNBMF "EFMJF 5PSHFSTFO NBMF
ࠓճ͏σʔλQFOHVJOT JOTUBMMQBDLBHFT QBMNFSQFOHVJOT MJCSBSZ QBMNFSQFOHVJOT IFBE QFOHVJOT
TQFDJFT JTMBOE CJMM@MFOHUI@NN CJMM@EFQUI@NN fl JQQFS@MFOHUI@NN CPEZ@NBTT@H TFY ZFBS "EFMJF 5PSHFSTFO NBMF "EFMJF 5PSHFSTFO GFNBMF "EFMJF 5PSHFSTFO GFNBMF "EFMJF 5PSHFSTFO /" /" /" /" /" "EFMJF 5PSHFSTFO GFNBMF "EFMJF 5PSHFSTFO NBMF
ࢄਤ ॻ͖ํओʹ3ύλʔϯ > ggplot(penguins, aes(x = bill_length_mm, y = bill_depth_mm))
+ geom_point() > ggplot(penguins) + geom_point(aes(x = bill_length_mm, y = bill_depth_mm)) > ggplot() + geom_point( data = penguins, aes(x = bill_length_mm, y = bill_depth_mm) )
ࠓճॻ͘άϥϑͷछྨ w ࢄਤ w ંΕઢάϥϑ w άϥϑ
ࠓճ͏σʔλQFOHVJOT JOTUBMMQBDLBHFT QBMNFSQFOHVJOT MJCSBSZ QBMNFSQFOHVJOT IFBE QFOHVJOT
TQFDJFT JTMBOE CJMM@MFOHUI@NN CJMM@EFQUI@NN fl JQQFS@MFOHUI@NN CPEZ@NBTT@H TFY ZFBS "EFMJF 5PSHFSTFO NBMF "EFMJF 5PSHFSTFO GFNBMF "EFMJF 5PSHFSTFO GFNBMF "EFMJF 5PSHFSTFO /" /" /" /" /" "EFMJF 5PSHFSTFO GFNBMF "EFMJF 5PSHFSTFO NBMF
ࠓճ͏σʔλQFOHVJOT JOTUBMMQBDLBHFT QBMNFSQFOHVJOT MJCSBSZ QBMNFSQFOHVJOT IFBE QFOHVJOT
TQFDJFT JTMBOE CJMM@MFOHUI@NN CJMM@EFQUI@NN fl JQQFS@MFOHUI@NN CPEZ@NBTT@H TFY ZFBS "EFMJF 5PSHFSTFO NBMF "EFMJF 5PSHFSTFO GFNBMF "EFMJF 5PSHFSTFO GFNBMF "EFMJF 5PSHFSTFO /" /" /" /" /" "EFMJF 5PSHFSTFO GFNBMF "EFMJF 5PSHFSTFO NBMF
σʔλूܭ MJCBSBSZ EQMZS QFOHVJOT@GPS@MJOFQFOHVJOT HSPVQ@CZ ZFBS TVNNBSJTF NFBO@NBTTNFBO
CPEZ@NBTT@H OBSN536& QFOHVJOT@GPS@MJOF ZFBS NFBO@NBTT
ંΕઢάϥϑ ॻ͖ํओʹ3ύλʔϯ > ggplot(penguins_for_line, aes(x = year, y = mean_mass))
+ geom_line() > penguins_for_line %>% ggplot() + geom_line(aes(x = year, y = mean_mass)) > ggplot(penguins_for_line) + geom_line(aes(x = year, y = mean_mass)) > ggplot() + geom_line( data = penguins_for_line, aes(x = year, y = mean_mass) )
άϥϑ ॻ͖ํ3ύλʔϯ > ggplot(penguins_for_line, aes(x = year, y = mean_mass))
+ geom_bar(stat = "identity") > ggplot(penguins_for_line) + geom_bar(aes(x = year, y = mean_mass), stat = "identity") > ggplot() + geom_bar( data = penguins_for_line, aes(x = year, y = mean_mass), stat = "identity") ҎԼͰՄ > ggplot() + geom_bar( data = penguins, aes(x = year, y = body_mass_g), stat = "summary", fun = "mean" )
ͦͷଞͷάϥϑɻɻɻ w άάΔ w ެࣜνʔτγʔτ IUUQTHJUIVCDPNSTUVEJPDIFBUTIFFUTCMPCNBTUFSEBUB WJTVBMJ[BUJPOQEG w 4MBDLͷSXBLBMBOH࣭
͍͔ͭ͘άϥϑॻ͍ͯΈͯ w λΠτϧ͚͍ͭͨɻ w ͕࣠ؾʹͳΔɻ
> ggplot() + geom_line( data = penguins_for_line, aes(x = year,
y = mean_mass) ) + ggtitle("ંΕઢάϥϑ") + theme_gray(base_family = "HiraKakuPro-W3") λΠτϧઃఆ
λΠτϧઃఆ > ggplot() + geom_line( data = penguins_for_line, aes(x =
year, y = mean_mass) ) + ggtitle("ંΕઢάϥϑ") + theme_gray(base_family = "HiraKakuPro-W3")
Y࣠ > ggplot() + geom_line( data = penguins_for_line, aes(x =
year, y = mean_mass)) + ggtitle("ંΕઢάϥϑ") + theme_gray(base_family = "HiraKakuPro-W3") + scale_x_continuous(breaks=seq(2007,2009,1))
Z࣠ > ggplot() + geom_line( data = penguins_for_line, aes(x =
year, y = mean_mass) ) + ggtitle("ࢄਤ") + theme_gray(base_family = "HiraKakuPro-W3") + scale_x_continuous( breaks = seq( min(penguins_for_line$year), max(penguins_for_line$year), 1 ) ) + ylim(0, 4300)
ࢄਤ छྨʹΑͬͯ৭͚͍ͨ > ggplot() + geom_point( data = penguins, aes(x
= bill_length_mm, y = bill_depth_mm, color = species) )
·ͱΊ w ՄࢹԽ͔ͳΓधཁͳύʔτ͕ͩɺ͍͠ɻ w άϥϑHHQMPU ͱHFPN@YYY Λ͏ͱॻ͘͜ͱ͕Ͱ͖Δɻ w ؔϓϥεͰͭͳ͙ɻ w
Γ͍ͨ͜ͱΛάάͬͯΈͯɺࢼͯ͠ΈͯɺΘ͔Βͳ͚Εɺ4MBDLͷSXBLBMBOHʹ࣭ͯͯ͠ Έ·͠ΐ͏ʂ
&/+0: