Upgrade to Pro — share decks privately, control downloads, hide ads and more …

Pandasによる競馬データの分析

1a4bb4b2da22fbbe6c16b0b19562b5a7?s=47 anonaka
July 06, 2017
Research
3
1.6k

 Pandasによる競馬データの分析

Pandasとmatplotlibを使って競馬の馬の走るスピードを分析をしてみました。結論は、ドメイン知識は重要ということです。:-)

1a4bb4b2da22fbbe6c16b0b19562b5a7?s=128

anonaka

July 06, 2017
Tweet

More Decks by anonaka

See All by anonaka
Introduction to the data analysis using python
1a4bb4b2da22fbbe6c16b0b19562b5a7?s=48 anonaka
0
690
Rubyで電話をかける
1a4bb4b2da22fbbe6c16b0b19562b5a7?s=48 anonaka
0
250
PyCon APAC 2017へ行こう！
1a4bb4b2da22fbbe6c16b0b19562b5a7?s=48 anonaka
0
610
PythonでSlack Bot
1a4bb4b2da22fbbe6c16b0b19562b5a7?s=48 anonaka
0
780

Other Decks in Research

See All in Research
第8回チャンピオンズミーティング・サジタリウス杯決勝集計 / Umamusume Sagittarius 2021 Final
9782dd351a8f1737d4ef02d839e821f9?s=48 kitachan_black
0
1.1k
GovTechとマーケットデザイン （東京大学野田講師）
E4a4f85037f5c40aaf7f95b1528b925a?s=48 daimoriwaki
0
140
Recent Findings on Density-Ratio Approaches in Machine Learning
Bb6c3fc8c577710c72d03aeb4fa56bf6?s=48 masakat0
0
230
データに基づくレヴィ流行語大賞2021
569640c367efbb9719e31fbfc4b6b147?s=48 levii
0
230
CompilerGym CGO 2022 Tutorial Part 2
0d2bf4a55ccf5ca212897c2c09e18c94?s=48 chriscummins
0
470
ヒトをめぐるデータサイエンスにおけるAIの最新動向.pdf
2b1653e7910b85a3c5348b609d52ad8c?s=48 tdailab
0
170
Iterative source steering を用いたオンライン補助関数型独立ベクトル分析に基づくブラインド音源分離 / Blind source separation using online auxiliary-function-based independent vector analysis with iterative source steering
Fba2bc6aeb14d00ab84710be1903da49?s=48 taishi
0
140
log4shell注意喚起
02335420aa18081affbcb8974de06429?s=48 connect24h
1
2.2k
SketchODE: Learning neural sketch representation in continuous time
27e6303669f854882d672f3cd3fcb796?s=48 dasayan05
0
120
第9回チャンピオンズミーティング・カプリコーン杯ラウンド2集計 / Umamusume Capricorn 2022 Round2
9782dd351a8f1737d4ef02d839e821f9?s=48 kitachan_black
0
1.6k
ECサイトにおけるデータ駆動型意思決定のための非線形テンソル因子分解を用いたVisual Analyticsシステムの検討
B0edf7a7acbd634903de0106b1743056?s=48 ae14watanabe
0
210
AI最新論文読み会2022年4月
874ff503a00697a857e198a0ebb8f55f?s=48 ailaboocu
0
330

Featured

See All Featured
The World Runs on Bad Software
20bfe76b3d6105641f879fe45cfc9272?s=48 bkeepers
PRO
56
5.2k
Building an army of robots
5f2da528927a2ec9ba4fec2069cbc958?s=48 kneath
299
40k
Java REST API Framework Comparison - PWX 2021
72a2082c6a4dd79ad68befb3db911616?s=48 mraible
PRO
11
4.6k
Building a Scalable Design System with Sketch
1177e050db6bafe62885362edf6e3537?s=48 lauravandoore
447
30k
A better future with KSS
5f2da528927a2ec9ba4fec2069cbc958?s=48 kneath
225
15k
ReactJS: Keep Simple. Everything can be a component!
Af6a12710770ad9a7cfd08c97efd40d3?s=48 pedronauck
655
120k
XXLCSS - How to scale CSS and keep your sanity
1b8ad785acdd1ce1c99914b1c2a4e10e?s=48 sugarenia
236
1M
Infographics Made Easy
282d599b414022eba5096510f675b6e2?s=48 chrislema
233
17k
Become a Pro
828ace851b606e1206900f26459f55ad?s=48 speakerdeck
PRO
3
780
Mobile First: as difficult as doing things right
0fe2973fa8d27d96547e43322341183a?s=48 swwweet
212
7.5k
Templates, Plugins, & Blocks: Oh My! Creating the theme that thinks of everything
E195ae45320d9202eaa01c9f1d31a416?s=48 marktimemedia
15
910
Scaling GitHub
78b475797a14c84799063c7cd073962f?s=48 holman
451
140k

Transcript

  1. 1BOEBTʹΑΔڝഅσʔλ෼ੳ גࣜձࣾ909;0 ໺த఩

  2. ࣗݾ঺հ w 909;0ΤόϯδΣϦετ w ۭඈͿ1ZUIPOϓϩάϥϚ

  3. 909;0 w ి࿩ɺ4.4ͷ8FC"1*Λఏڙ͍ͯ͠·͢ w ΦϑΟεͳ͠ w શһ͕ϦϞʔτϫʔΫ

  4. ಈػ w ͦͷੲɺڝഅ༧૝ͷ8FCαʔϏεΛͭͬͨ͘ w ͔͠͠ڝഅ͸ૉਓ w 1BOEBTͷ࿅श

  5. ڝഅσʔλ෼ੳ w +"37"/͔Βσʔλ͕औΕΔ w ༗ྉαʔϏε w ڝഅͷσʔλʔ͸ͦͦ͜͜஝ੵ͕͋Δ w ೥෼Ҏ্ͷ+3"ެࣜσʔλ

  6. ·ͣ͸അͷεϐʔυΛ

  7. None

  8. ԾઆΛཱͯΔ w ௕͘૸Ε͹ർΕΔͩΖ͏ w ̎࣍ଟ߲ࣜͰճؼ෼ੳ

  9. None

  10. ଞͷ೥΋ௐ΂ͯΈΔ

  11. None
  12. None

  13. Ͳ͏΍Βɺڑ཭͕৳ͼΔͱ଎౓͕ૣ͘ ͳΔͷ͸ීวత܏޲ͷΑ͏ͩ

  14. ڝഅυϝΠϯͷΤΩεύʔτʹॿ͚ΛٻΊΔ

  15. ΤΩεύʔτͷΞυόΠε w ͍Ζ͍Ζͳڝഅ৔ͷσʔλΛɺ·ͱΊͯൺ΂Δͷ͸ ཚ๫ w ௚ઢ΍ۂ͕Γ֯ͷ௕͞͸ΈΜͳҧ͏ɻࡔ΋͋ͬͨΓ ͢Δɻ

  16. ڝഅ৔͝ͱʹ෼ੳ ·ͣ͸౦ژڝഅ৔͔Β

  17. None

  18. Ծઆ͸ূ໌͞Εͨ

  19. શࠃͷڝഅ৔Λௐ΂Δ

  20. ͔͠͠ɺ൓ྫ͕ଓʑʜ

  21. None
  22. None

  23. ࣍܎਺ͷ͹Β͖ͭ   ਖ਼ͷϨʔε Լʹತ   ෛͷϨʔε ্ʹತ 

    

  24. ڝഅ৔ͷίʔεਤΛ ோΊͯΈΔ ʢ஗͗͢ʜʣ

  25. ౦ژڝഅ৔

  26. ژ౎ڝഅ৔

  27. ࡕਆڝഅ৔

  28. தࢁڝഅ৔

  29. –؏Ҫ ॣ (AlphaImpact։ൃऀ) τϥοΫͷछྨ ࣳɾμʔτɾো֐ ΍
 ڑ཭͕ҧ͑͹ผͷڝٕ

  30. ࣍܎਺͕ܭࢉͰ͖ͳ͍έʔε ৽ׁڝഅ৔ɹμʔτ

  31. ֶΜͩ͜ͱ w Ͳ͏΍Βഅ͸Nఔ౓Ͱ͸ർΕͳ͍Β͍͠ w υϝΠϯ஌ࣝ͸ॏཁ

  32. ࢀߟจݙ தҪӻ࢘ஶ *5ΤϯδχΞͷͨΊͷػցֶशཧ࿦ೖ໳ ٕज़ධ࿦ࣾ

  33. ࠓޙͷ՝୊ w ͍͔ʹͯ͠ճऩ཰Λ௒ʹ΋͍͔ͬͯ͘

  34. ͔͜͜Βઌ͸༗ྉձһ༷ݶఆ ͱͳΓ·͢ʢӕʣ

  35. None