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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284
9
章 プロットと可視化
図9-5 サブプロット間にスペースを入れないデータ可視化結果
軸のラベルが重なっているのに気付くでしょう。
Matplotlib
はラベルが重なっているかどうかを
チェックしないので、このようなケースでは、自分で目盛りの位置とラベルを明示的に指定して修正す
る必要があります（指定方法はこの後の節で取り上げます）。
9.1.2
色、マーカー、線種
Matplotlib
の主要な
plot
関数には
X
座標と
Y
座標の配列を引数として渡しますが、さらにオプション
で、色や線種を指定する、文字列を用いた簡略表記も指定できます。例えば、緑色の破線で
x
と
y
をプ
ロットするには、次のように実行します。
ax.plot(x, y, 'g--')
このような、文字列で色や線種を指定する方法は、利便性のために与えられているものです。実際
問題として、プログラムでプロットを作成する場合であれば、望みの線種でプロットを作成するために、
文字列を結
合処理しなければいけないのは嬉しくありません。先ほどのプロットは、もっと明示的に、
次のように書けます。
ax.plot(x, y, linestyle='--', color='g')
たくさんのよく使われる色に簡略表記が用意されていますが、
16
進数カラーコード（例えば
'#CECECE'
）を指定すれば、スペクトル上のどんな色も使えます。線種の完全な一覧については、
plot
9.1
Matplotlib API
の概要
285
の
docstring
で参照できます（
IPython ...
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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.