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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9.1
Matplotlib API
の概要
293
fig = plt.figure()
ax = fig.add_subplot(1, 1, 1)
rect = plt.Rectangle((0.2, 0.75), 0.4, 0.15, color='k', alpha=0.3)
circ = plt.Circle((0.7, 0.2), 0.15, color='b', alpha=0.3)
pgon = plt.Polygon([[0.15, 0.15], [0.35, 0.4], [0.2, 0.6]],
color='g', alpha=0.5)
ax.add_patch(rect)
ax.add_patch(circ)
ax.add_patch(pgon)
図9-12 3つの異なるパッチから作成したデータ可視化結果
これまでに登場したようなさまざまな種類のプロットの実装を覗いてみれば、それらもパッチを組み
合わせて作られているのがわかるでしょう。
9.1.5
プロットのファイルへの保存
アクティブな図
＊
1
は
plt.savefig
を使ってファイルに保存できます。このメソッドは、
Figure
オブジェ
クトのインスタンスメソッド
savefig
と等価です。例えば、図を
SVG
で保存する場合は次のように入力
するだけです。
plt.savefig('figpath.svg')
ファイル形式はファイルの拡張子から推測されます。したがって、
.svg
でなく
.pdf
とした場合は、
PDF
が出力されるでしょう。出版用に画像 ...
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