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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304
9
章 プロットと可視化
図9-20 曜日と時間帯ごとのチップのパーセンテージ
デフォルトのカラーパレットやプロットの背景色、グリッド線の色など、
seaborn
はプロットの見た
目の美しさを自動的に変更することに気付いたでしょうか。
seaborn.set
を用いると、プロットの見た
目を別のものに変えることができます。
In [90]: sns.set(style="whitegrid")
9.2.3
ヒストグラムと密度プロット
ヒストグラムは棒グラフの一種で、値の頻度を離散データとして表示します。各データポイントは等
間隔に置かれた個々のビンに分けて入れられ、各ビンの中のデータポイントの数がプロットされます。
先ほどのチップのデータを用いて、シリーズの
plot.hist
メソッドで、先ほど計算した請求額に対する
チップの割合のヒストグラムを作りましょう（図9-21を参照）。
In [92]: tips['tip_pct'].plot.hist(bins=50)
9.2
pandas
と
seaborn
のプロット関数
305
図9-21 チップの割合のヒストグラム
関連するプロット形式として密度プロットがあります。これは、実際に観測されたデータを生み出し
たと推定される連続確率分布の計算から作られます。通常はこの ...
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