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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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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

by Wes McKinney, 瀬戸山 雅人, 小林 儀匡, 滝口 開資
July 2018
Intermediate to advanced
596 pages
13h 35m
Japanese
O'Reilly Japan, Inc.
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
102
4
章 
NumPy
の基礎:配列とベクトル演算
[ 4., 5., 6.]])
In [53]: arr * arr
Out[53]:
array([[ 1., 4., 9.],
[ 16., 25., 36.]])
In [54]: arr - arr
Out[54]:
array([[ 0., 0., 0.],
[ 0., 0., 0.]])
次にスカラーと
ndarray
との算術演算の場合、要素ごとにその加減乗除が計算されます。
In [55]: 1 / arr
Out[55]:
array([[ 1. , 0.5 , 0.3333],
[ 0.25 , 0.2 , 0.1667]])
In [56]: arr ** 0.5
Out[56]:
array([[ 1. , 1.4142, 1.7321],
[ 2. , 2.2361
, 2.4495]])
ndarray
間を比較したとき、その結果は同要素数の真偽値配列として戻されます。
In [57]: arr2 = np.array([[0., 4., 1.], [7., 2., 12.]])
In [58]: arr2
Out[58]:
array([[ 0., 4., 1.],
[ 7., 2., 12.]])
In [59]: arr2 > arr
Out[59]:
array([[False, True, False],
[ True, False, True]], dtype=bool)
サイズの異なる
ndarray
同士の演算はブロードキャストと呼ば
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Publisher Resources

ISBN: 9784873118451Other