October 2017
Intermediate to advanced
480 pages
9h 49m
Japanese
Content preview from Rではじめるデータサイエンス
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5.3
変動
79
これまでの質問の多くは、例えば、ある変数が別の変数の振る舞いを説明するのではないかと、
変数間の関係を調べる契機となります。もう少し後で、これを取り上げます。
5.3.3
異常値
パターンに当てはまらないデータ点である外れ値は異常な値です。外れ値はデータ入力エラーの
こともあれば、重要な新しい科学のきっかけとなることもあります。データが多数あると、ヒストグ
ラムでは、外れ値に気付くこと自体が困難です。例えば、データセット
diamonds
の
y
変数の分布を
考えます。外れ値が存在する証拠は、
y
の軸が（表示されているデータに比べると）異常に長くとら
れていることだけです。
ggplot(diamonds) +
geom_histogram(mapping = aes(x = y), binwidth = 0.5)
非常に多数の観測が一部の区間にあり、観測数の少ない区間の高さが非常に低いので、目には見
えない（もっとも、0 の付近で目を凝らせば見つかるかもしれません）。異常値を見えやすくするには、
y
の軸の小さな値まで
coord_cartesian()
で拡大します。
ggplot(diamonds) +
geom_histogram(mapping = aes(x = y), binwidth = 0.5) +
coord_cartesian(ylim = c(0, 50))
80
5
章 探索的データ分析
（
x
軸について拡大するときのために、
coord_cartesian()
には引数
xlim() ...
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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.
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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.