Upgrade to Pro — share decks privately, control downloads, hide ads and more …
Sign up for free

TokyoR#93

Avatar for soriente soriente
July 03, 2021
Technology
270
0

 TokyoR#93

TokyoR#93の初心者セッション可視化パートです。

Avatar for soriente

soriente

July 03, 2021

Other Decks in Technology

See All in Technology
目の前の楽しいが人生を変える - コミュニティの螺旋の歩き方と楽しむコツ / change your life
Avatar for soudai sone soudai
PRO
4
510
Microsoft 365 Copilot chat -tekoälypalvelun tietosuojaongelmat
Avatar for Harto Pönkä hponka
0
730
AIで仕事のやり方を変える
Avatar for Kentaro Matsumoto matsu7874
3
1.1k
omasushiというライブラリを作った
Avatar for polidog polidog
PRO
0
200
「重なり」は迎える側がつくる ― 人もAIエージェントも歓迎するプロダクトエンジニアリング ―
Avatar for Go Akazawa go0517go
PRO
0
280
Claude in Chrome 入門 / Introduction to Claude in Chrome
Avatar for yuta cielo1985
0
450
ASTを使って影響範囲を特定する
Avatar for Nealle nealle
0
170
AIエージェントの自己改善をどう設計するか / How to Design Self-Improvement for AI Agents
Avatar for 223 22mi
3
1.9k
AIで実装は速くなった。なのにプロダクトは速くならない。職能の壁を越えて価値のフローを設計する
Avatar for nwiizo nwiizo
8
7.9k
Reactの設計論
Avatar for uhyo uhyo
15
8.4k
DEFCON_CHV_CTF_Write-up.pdf
Avatar for bata_24 bata_24
0
140
AI時代、データエンジニアが一番おもろい
Avatar for ゲンシュン genshun9
0
160

Featured

See All Featured
Save Time (by Creating Custom Rails Generators)
Avatar for Garrett Dimon garrettdimon
PRO
32
4.7k
Digital Projects Gone Horribly Wrong (And the UX Pros Who Still Save the Day) - Dean Schuster
Avatar for UX Y'all uxyall
1
2.8k
Applied NLP in the Age of Generative AI
Avatar for Ines Montani inesmontani
PRO
4
2.4k
Measuring Dark Social's Impact On Conversion and Attribution
Avatar for Stephen Akadiri stephenakadiri
2
270
Product Roadmaps are Hard
Avatar for C. Todd Lombardo iamctodd
55
13k
Game over? The fight for quality and originality in the time of robots
Avatar for Wayne Barker wayneb77
1
270
The B2B funnel & how to create a winning content strategy
Avatar for Katarina Dahlin katarinadahlin
PRO
1
510
Music & Morning Musume
Avatar for Bryan Veloso bryan
47
7.4k
We Are The Robots
Avatar for Honza Javorek honzajavorek
0
360
The Success of Rails: Ensuring Growth for the Next 100 Years
Avatar for Eileen M. Uchitelle eileencodes
47
8.3k
Lessons Learnt from Crawling 1000+ Websites
Avatar for Charles Meaden charlesmeaden
PRO
1
1.6k
Discover your Explorer Soul
Avatar for Emna emna__ayadi
2
1.3k

Transcript

  1. 5PLZP3σʔλՄࢹԽ ॳ৺ऀηογϣϯ

  2. ࣗݾ঺հ w TPSJFOUF w ౎಺*5اۀۈ຿ w 3ྺ೥໨ ࡉ͘௕͘΍ͬͯ·͢ɻ  w

    ͱ͍ͬͯ΋࠷ۙ͸1ZUIPO͕ϝΠϯ w 1)1ॻ͍ͯͨ࣌ظ΋͋Γ·ͨ͠ɻ

  3. ՄࢹԽͱ͸ w จࣈͷ௨Γɺݟ͑ΔԽ͢Δɻ σʔλ෼ੳͷจ຺Ͱ͸ɺσʔλͷؔ܎ੑΛݟ͑ ΔԽ͢Δɻ  w ՄࢹԽΛ͚ͨͩ͠ͰΘ͔Δ͜ͱ΋ଟ͍ɻ w ՄࢹԽΛ͢ΔͱɺΘ͔Γ΍͍͢ɻ

    w ՄࢹԽΛͨ͋͠ͱʹԿΒ͔ͷҙࢥܾఆΛߦ͏͜ͱ͕ଟ͍ɻ ෼ੳऀࣗ਎͕ҙࢥ ܾఆ͢Δ͜ͱ΋ɺ୭͔ʹҙࢥܾఆͯ͠΋Β͏͜ͱ΋͋Δɻ
  4. None

  5. HHQMPUͷجຊ

  6. HHQMPUͱ͸ w ՄࢹԽͷͨΊͷϥΠϒϥϦ w UJEZWFSTFͷϥΠϒϥϦ܈ͷҰͭ w ʰ5IF(SBNNBSPG(SBQIJDTʱΛϕʔεʹ࡞ΒΕ͍ͯΔ 
 ˠҰ؏ੑͷ͋Δจ๏Ͱ߹ཧతʹॻ͚Δʂ

  7. ࠓճ࢖͏σʔλQFOHVJOT 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 

  8.  QFOHVJOT

  9. HHQMPUΠϯετʔϧಡΈࠐΈ JOTUBMMQBDLBHFT HHQMPU JOTUBMMQBDLBHFT UJEZWFSTF Ͱ΋Մ MJCSBSZ HHQMPU MJCSBSZ UJEZWFSTF

    Ͱ΋Մ

  10. ࠓճॻ͘άϥϑͷछྨ w ࢄ෍ਤ w ๮άϥϑ w ંΕઢάϥϑ

  11. ࠓճ࢖͏σʔλQFOHVJOT 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 

  12. ࠓճ࢖͏σʔλQFOHVJOT 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 

  13. ࢄ෍ਤ ॻ͖ํ͸ओʹ3ύλʔϯ > 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) )

  14. ࠓճॻ͘άϥϑͷछྨ w ࢄ෍ਤ w ંΕઢάϥϑ w ๮άϥϑ

  15. ࠓճ࢖͏σʔλQFOHVJOT 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 

  16. ࠓճ࢖͏σʔλQFOHVJOT 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 

  17. σʔλूܭ MJCBSBSZ EQMZS  QFOHVJOT@GPS@MJOFQFOHVJOT HSPVQ@CZ ZFBS  TVNNBSJTF NFBO@NBTTNFBO

    CPEZ@NBTT@H OBSN536&  QFOHVJOT@GPS@MJOF ZFBS NFBO@NBTT         

  18. ંΕઢάϥϑ ॻ͖ํ͸ओʹ3ύλʔϯ > 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) )

  19. ๮άϥϑ ॻ͖ํ͸3ύλʔϯ > 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") ҎԼͰ΋Մ > ggplot() + geom_bar( data = penguins, aes(x = year, y = body_mass_g), stat = "summary", fun = "mean" )

  20. ͦͷଞͷάϥϑ͸ɻɻɻ w άάΔ w ެࣜνʔτγʔτ 
 IUUQTHJUIVCDPNSTUVEJPDIFBUTIFFUTCMPCNBTUFSEBUB WJTVBMJ[BUJPOQEG w 4MBDLͷSXBLBMBOH࣭໰

  21. ͍͔ͭ͘άϥϑॻ͍ͯΈͯ w λΠτϧ͚͍ͭͨɻ w ͕࣠ؾʹͳΔɻ

  22. > ggplot() + geom_line( data = penguins_for_line, aes(x = year,

    y = mean_mass) ) + ggtitle("ંΕઢάϥϑ") + theme_gray(base_family = "HiraKakuPro-W3") λΠτϧઃఆ

  23. λΠτϧઃఆ > ggplot() + geom_line( data = penguins_for_line, aes(x =

    year, y = mean_mass) ) + ggtitle("ંΕઢάϥϑ") + theme_gray(base_family = "HiraKakuPro-W3")

  24. 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))

  25. Z࣠ > ggplot() + geom_line( data = penguins_for_line, aes(x =

    year, y = mean_mass) ) + ggtitle("ࢄ෍ਤ") + 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)

  26. ࢄ෍ਤ छྨʹΑͬͯ৭෼͚͍ͨ > ggplot() + geom_point( data = penguins, aes(x

    = bill_length_mm, y = bill_depth_mm, color = species) )

  27. ·ͱΊ w ՄࢹԽ͸͔ͳΓधཁͳύʔτ͕ͩɺ೉͍͠ɻ w άϥϑ͸HHQMPU ͱHFPN@YYY Λ࢖͏ͱॻ͘͜ͱ͕Ͱ͖Δɻ w ؔ਺͸ϓϥεͰͭͳ͙ɻ w

    ΍Γ͍ͨ͜ͱΛάάͬͯΈͯɺࢼͯ͠ΈͯɺΘ͔Βͳ͚Ε͹ɺ4MBDLͷSXBLBMBOHʹ࣭ͯ໰ͯ͠ Έ·͠ΐ͏ʂ

  28. &/+0: