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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226
10 章 Matplotlib を使ったデータの可視化
10.3.1
Matplotlib
の設定
Matplotlib
はさまざまな設定ができます（
http://bit.ly/1ZWSMKA
）。この設定は
matplotlibrc
ファイル（
http://bit.ly/1UTaxJ1
）で指定するか、ディクショナリのような
rcParams
変数で動的
に指定します。ここでは、プロット線の幅とデフォルトの色を変更します。
import matplotlib as mpl
mpl.rcParams['lines.linewidth'] = 2
mpl.rcParams['lines.color'] = 'r' #
赤
メインサイト（
http://bit.ly/21r1YHF
）に
matplotlibrc
ファイルのサンプルがあります。
rcParams
変数だけでなく、
gcf
（
get current figure
：現在の図の取得）メソッドを使って現在ア
クティブな図を取得して直接操作することもできます。
次の節からは現在の図のサイズを設定する簡単な例を紹介します。
10.3.2
図サイズの設定
プロットのデフォルトが見やすくなかったり、幅と高さの比率がおかしい場合には、サイズ
を変更したいでしょう。デフォルトでは、
Matplotlib
はプロットのサイズにインチを使います。
Matplotlib
で保存できる（大抵はベクターグラフィックスベースの）多くのバックエンドを考える
と当然の選択でしょう。ここでは、
pyplot
で
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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.