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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93
4
章
NumPy
の基礎：
配列とベクトル演算
NumPy
は「
Numerical Python
」、つまり「数的
Python
」くらいの意味で、
Python
での数値計算におけ
る最も重要な基本パッケージの
1
つです。科学技術計算向けの多くの
Python
パッケージが、データ交
換のためのいわば共通語として
NumPy
の配列オブジェクトを用いています。
NumPy
の特徴には次のようなものがあります。
●
高速な行列計算と柔軟なブロードキャストを提供する効率的な多次元配列である
ndarray
。
●
高速に動作し、呼び出しにループ記法を必要としない標準的な数学関数。
●
ディスクへの配列の読み書きに加え、メモリマップファイル機能を提供する入出力機能。
●
行列計算、乱数生成、フーリエ変換といった機能。
●
C
、
C++
、
Fortran
へのインタフェース。
NumPy
には
C
言語呼び出しの
API
があり、
NumPy
から
C
で書かれた外
部ライブラリへ容易にデー
タを渡すことができ、また外部ライブラリの計算結果を
NumPy
に戻して
ndarray
として扱うこともで
きます。この機能のおかげで、
Python
は
C
、
C++
、
Fortran
などで書かれた既存のコード資産へのラッ
パーとしての位置づけを獲得してきました。
NumPy
はこれら既存ライブラリを簡単に呼び出せる、動
的インタフェースとしての役割を担っています。
NumPy
はそれ自体が数理モデリングや何らかのデータ分析手法を提供するというわけではありませ
ん。しかし
NumPy
の配列、お
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