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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244
10 章 Matplotlib を使ったデータの可視化
pal = dict(Female='red', Male='blue')
g = sns.FacetGrid(tips, col="smoker", row="time", #
❶
hue="sex", hue_kws={"marker": ["D", "s"]},
palette=pal, size=4, aspect=1, )
g.map(sns.regplot, "total_bill", "tip", alpha=.4)
g.add_legend();
❶ 時間についての行を加えて、チップの額を昼食と夕食で区別する。
図
10-16
は、女性と男性の色分け（
hue
）グループでの線形回帰モデルフィットと信頼区間を作
成する
4
つの
regplot
を示しています。プロットのタイトルは使用しているデータのサブセット
を示します。各行は同じ時間と喫煙状態です。■
例
10-12
で説明した
lmplot
を使って同じ効果を追加できます。
lmplot
は、
FacetGrid
と
regplot
の機能があります。次のコードは図
10-16
を作成します。
pal = dict(Female='red', Male='blue')
sns.lmplot(x="total_bill", y="tip", hue="sex",\
markers=["D", "s"], #
❶
col="smoker", row="time", data=tips, palette=pal, ...
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