August 2017
Intermediate to advanced
500 pages
12h 3m
Japanese
Content preview from PythonとJavaScriptではじめるデータビジュアライゼーション
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O’Reilly covers everything we've got, with content to help us build a world-class technology community, upgrade the capabilities and competencies of our teams, and improve overall team performance as well as their engagement.I wanted to learn C and C++, but it didn't click for me until I picked up an O'Reilly book. When I went on the O’Reilly platform, I was astonished to find all the books there, plus live events and sandboxes so you could play around with the technology.I’ve been on the O’Reilly platform for more than eight years. I use a couple of learning platforms, but I'm on O'Reilly more than anybody else. When you're there, you start learning. I'm never disappointed.I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.
272
11 章 pandas を使ったデータ探索
これは図
11-22
を作成し、女性受賞者の方が少数であることと分布が平坦であることを考慮し
ながらも、男性と女性の平均が近いことを示しています。女性の受賞者は、一般集団の女性よりも
比較的短命であるように見えます。■
図
11-23
に示すバイオリンプロットは、別の角度からデータを見ることができます。
sns.violinplot(df.gender, age_at_death)
■
11.5.3
時代に伴う寿命の延長
受賞者の出生日と没年齢に相関があるかどうかを調べ、歴史的な人口学的分析を少し行ってみま
しょう。
Seaborn
の
lmplot
の
1
つを使い、散布図と信頼区間を伴う直線フィッティングを提供し
ます（「
10.6
Seaborn
」を参照）。
男性
女性
図
11-22
受賞者の性別ごとの没年齢
女性 男性
性別
図
11-23
受賞者の性別ごとの没年齢
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