June 2024
Intermediate to advanced
200 pages
4h 46m
Japanese
Content preview from Python2年生 データ分析のしくみ 第2版 体験してわかる！会話でまなべる！
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Chapter
5
160
matplotlibの「データフレーム.plot.hist(bins=bins)」命令を使うと、ヒストグラムを表示
できましたが、
seabornの「sns.histplot（データフレーム, kde=True）」 命令を使うと、カー
ネル密度推定（データがどのように分布しているかを直感的に表現した曲線）を描けます。
この後者のグラフに「もしこのデータが正規分布だったとしたら、どんな曲線になるだろ
う」という曲線を重ね合わせて表示させれば、データがどれだけ正規分布に近いかを調べ
ることができます。
18
LESSON
データを正規分布と比べて、自然なばらつきかを確認してみましょう。
このデータは
自然な ば ら つ き？
いや〜、標準偏差は、便利便利！ もう、何でもこいだね。
あ、そっか。形が違ってたら、使えないもんね。
じゃあ、どうすればいいの。
方法はいろいろあるけど、まずはグラフを使って確認してみよう。
ただし、これを使うには「前提」がある。それは「データが正規分布になっ
ている」ということだ。
入手したデータが「正規分布じゃない現象」かもしれないし、「データ
数が少なくて正規分布にならない」かもしれない。
161
このデータは自然なばらつき？
LESSON
18
• 必要なライブラリ：pandas ...
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