July 2018
Intermediate to advanced
596 pages
13h 35m
Japanese
Content preview from Pythonによるデータ分析入門 第2版 ―NumPy、pandasを使ったデータ処理
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454
14
章 データ分析の実例
title
Dumb & Dumber (1994) 1.321333
Blair Witch Project, The (1999) 1.316368
Natural Born Killers (1994) 1.307198
Tank Girl (1995) 1.277695
Rocky Horror Picture Show, The (1975) 1.260177
Eyes Wide Shut (1999) 1.259624
Evita (1996) 1.253631
Billy Madison (1995) 1.249970
Fea
r and Loathing in Las Vegas (1998) 1.246408
Bicentennial Man (1999) 1.245533
Name: rating, dtype: float64
このデータでは映画のジャンルがパイプ区切り（
|
）で与えられていることに気付いたでしょうか。も
しジャンルに関する分析をもっと進めたかったとしたら、もう少しデータの変形が必要となっていたで
しょう。
14.3
アメリカの赤ちゃんに名付けられた
名前リスト（
1880-2010
）
次に用いるデータ例は、アメリカ合衆国社会保障局（
Social Security Administration, SSA
）の提供す
る赤ちゃんの名前データです。
1880
年から現在まで、毎年継続して集計されています。このデータは
データ分析の入門によく用いられるもので
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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.Addison B.
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.Amir M.
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.