blocks|key|3399566|text|内置的zip命令是这里的工作。它会做你想要的。|type|unstyled|depth|inlineStyleRanges|offset|length|style|CODE|entityRanges|data|3399567|arr1+=+[1,2,3,4]
arr2+=+[5,6,7,8]
list(zip(arr1,+arr2))
[(1,+5),+(2,+6),+(3,+7),+(4,+8)]|code-block|syntax|javascript|3399568|https://docs.python.org/3/library/functions.html#zip|3399569|entityMap|0|LINK|mutability|MUTABLE|url^0|3|3|0|0|0|1G|0|0^^$0|@$1|2|3|4|5|6|7|T|8|@$9|U|A|V|B|C]]|D|@]|E|$]]|$1|F|3|G|5|H|7|W|8|@]|D|@]|E|$I|J]]|$1|K|3|L|5|6|7|X|8|@]|D|@$9|Y|A|Z|1|10]]|E|$]]|$1|M|3|-4|5|6|7|11|8|@]|D|@]|E|$]]]|N|$O|$5|P|Q|R|E|$S|L]]]]

The built in <code>zip</code> command is the job for you here. It'll do exactly what you're asking.

<pre><code>arr1 = [1,2,3,4]
arr2 = [5,6,7,8]
list(zip(arr1, arr2))
[(1, 5), (2, 6), (3, 7), (4, 8)]
</code></pre>

<a href="https://docs.python.org/3/library/functions.html#zip" rel="nofollow noreferrer">https://docs.python.org/3/library/functions.html#zip</a>

blocks|key|3399645|text|IIUC，一种方法是使用numpy.vstack()，然后是transpose()|type|unstyled|depth|inlineStyleRanges|offset|length|style|CODE|entityRanges|data|3399646|import+numpy+as+np
arr1+=+np.array([1,+2,+3,+4])
arr2+=+np.array([5,+6,+7,+8])
print(np.vstack([arr1,+arr2]).transpose())
#array([[1,+5],
#+++++++[2,+6],
#+++++++[3,+7],
#+++++++[4,+8]])|code-block|syntax|javascript|3399647|也可以将zip的输出传递给array构造函数：|3399648|print(np.array(zip(arr1,+arr2)))
#array([[1,+5],
#+++++++[2,+6],
#+++++++[3,+7],
#+++++++[4,+8]])|3399649|entityMap|0|LINK|mutability|MUTABLE|url|https://docs.scipy.org/doc/numpy-1.14.0/reference/generated/numpy.vstack.html|1|https://docs.scipy.org/doc/numpy-1.14.0/reference/generated/numpy.ndarray.transpose.html^0|C|E|U|B|C|E|0|U|B|1|0|0|4|3|D|5|0|0^^$0|@$1|2|3|4|5|6|7|Y|8|@$9|Z|A|10|B|C]|$9|11|A|12|B|C]]|D|@$9|13|A|14|1|15]|$9|16|A|17|1|18]]|E|$]]|$1|F|3|G|5|H|7|19|8|@]|D|@]|E|$I|J]]|$1|K|3|L|5|6|7|1A|8|@$9|1B|A|1C|B|C]|$9|1D|A|1E|B|C]]|D|@]|E|$]]|$1|M|3|N|5|H|7|1F|8|@]|D|@]|E|$I|J]]|$1|O|3|-4|5|6|7|1G|8|@]|D|@]|E|$]]]|P|$Q|$5|R|S|T|E|$U|V]]|W|$5|R|S|T|E|$U|X]]]]

IIUC, one way is to use <a href="https://docs.scipy.org/doc/numpy-1.14.0/reference/generated/numpy.vstack.html" rel="nofollow noreferrer"><code>numpy.vstack()</code></a> followed by <a href="https://docs.scipy.org/doc/numpy-1.14.0/reference/generated/numpy.ndarray.transpose.html" rel="nofollow noreferrer"><code>transpose()</code></a>:

<pre><code>import numpy as np
arr1 = np.array([1, 2, 3, 4])
arr2 = np.array([5, 6, 7, 8])
print(np.vstack([arr1, arr2]).transpose())
#array([[1, 5],
# [2, 6],
# [3, 7],
# [4, 8]])
</code></pre>

Or you could pass the output of <code>zip</code> to the <code>array</code> constructor:

<pre><code>print(np.array(zip(arr1, arr2)))
#array([[1, 5],
# [2, 6],
# [3, 7],
# [4, 8]])
</code></pre>

blocks|key|3399697|text|你在找np.dstack|type|unstyled|depth|inlineStyleRanges|entityRanges|offset|length|data|3399698|按顺序深度排列的堆栈数组(沿第三轴)。|blockquote|3399699|np.dstack([arr1,+arr2])

array([[[1,+5],
++++++++[2,+6],
++++++++[3,+7],
++++++++[4,+8]]])|code-block|syntax|javascript|3399700|entityMap|0|LINK|mutability|MUTABLE|url|https://docs.scipy.org/doc/numpy-1.13.0/reference/generated/numpy.dstack.html^0|3|9|0|0|0|0^^$0|@$1|2|3|4|5|6|7|T|8|@]|9|@$A|U|B|V|1|W]]|C|$]]|$1|D|3|E|5|F|7|X|8|@]|9|@]|C|$]]|$1|G|3|H|5|I|7|Y|8|@]|9|@]|C|$J|K]]|$1|L|3|-4|5|6|7|Z|8|@]|9|@]|C|$]]]|M|$N|$5|O|P|Q|C|$R|S]]]]

You are looking for <a href="https://docs.scipy.org/doc/numpy-1.13.0/reference/generated/numpy.dstack.html" rel="nofollow noreferrer"><code>np.dstack</code></a>

<blockquote>
 Stack arrays in sequence depth wise (along third axis).
</blockquote>

<pre><code>np.dstack([arr1, arr2])

array([[[1, 5],
 [2, 6],
 [3, 7],
 [4, 8]]])
</code></pre>

I am trying to map 2 numpy arrays as [x, y] similar to what zip does for lists and tuples.

I have 2 numpy arrays as follows:

<pre><code>arr1 = [1, 2, 3, 4]
arr2 = [5, 6, 7, 8]
</code></pre>

I am looking for an <code>output as np.array([[[1, 5], [2, 6], [3, 7], [4, 8]]])</code>

I tried this but it maps every value and not with same indices. I can add more if conditions here but is there any other way to do so without adding any more if conditions.

<pre><code>res = [arr1, arr2] for a1 in arr1 for a2 in arr2]
</code></pre>

How can I map 2 numpy arrays with same indices

翻译质量差，导致语言生硬或混乱。

没有提供实际的解决方法或示例。

解答不清晰，无法理解或解决问题。

页面排版不美观，阅读体验差。

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我试图将2个numpy数组映射为x，y，类似于zip对列表和元组所做的操作。我有2个numpy数组如下：arr1 = [1, 2, 3, 4]arr2 = [5, 6, 7, 8]我在找output as np.array([[[1, 5], [2, 6], [3, 7], [4, 8]]])我试过这样做，但它映射每个...

问如何映射两个具有相同索引的numpy数组？
EN

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问如何映射两个具有相同索引的numpy数组？EN