This document discusses using Python and PyData tools for baseball analytics. It introduces Shinichi Nakagawa, a baseball analyst and Python expert. It explains common PyData tools like Grafana, Redash and Jupyter Notebook, and how they can be used to visualize and analyze baseball metrics and stats. It also discusses using Python and scraping to analyze run creation (RC) and run creation per 27 outs (RC27) stats to evaluate player and team performance.

1. Py “Baseball” Data
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MonotaRO TechTalk #4 2016/11/25
Shinichi Nakagawa(Baseball Analyst&Pythonista)

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• Shinichi Nakagawa(@shinyorke)
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4. PyCon JP 2016

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• Grafana
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21. Re:dash
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AWS(EC2)/GCE/Docker
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Mail Slack
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22. Re:dash
MLB Retrosheet
Metrics

23. Re:dash

24. Docker
VISASQ TECH BLOG Re:dash Docker for Mac
https://tech.visasq.com/redash-docker/

25. Jupyter
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27. Jupyter (Jupyter lab)
PyCon JP 2016
Jupyter notebook Jupyter lab

28. PyData
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45. RC(Run Created)
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46. RC
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48. RC
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※ DELTA http://1point02.jp/op/index.aspx

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http://www.daily.co.jp/tigers/2016/11/25/0009697275.shtml

63. • ?
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73. •
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74. &
Shinichi Nakagawa(Twitter/Facebook/visasQ:@shinyorke)