有效地将一个元素附加到大型 numpy 数组中的每个列表 [英] Efficiently append an element to each of the lists in a large numpy array

问题描述

我有一个非常大的 numpy 列表数组，我想向每个数组附加一个元素.为了性能，我想避免使用循环.

I have a really large numpy of array of lists, and I want to append an element to each of the arrays. I want to avoid using a loop for the sake of performance.

以下语法不起作用.

a=np.array([[],[1],[0,1]])

[j.append(3) for j in a]

这个例子的预期结果是

np.array([[3],[1,3],[0,1,3]) 

但是我得到了

[None, None, None]

有什么线索吗?

推荐答案

list.append() 返回 None，所以你只是看到了 3 个追加操作每个都返回 None.

list.append() returns None, so you're just seeing that the 3 append operations each returned None.

但是，如果您打印 a 的内容，您会发现追加成功.

However, if you print the contents of a you'll find that the appends were successful.

a=np.array([[],[1],[0,1]])
[j.append(3) for j in a]
print(a)
# prints "[list([3]) list([1, 3]) list([0, 1, 3])]"

我不建议为任何事情使用 numpy 列表数组，但也许您有一些特殊的用例，这是有意义的.我建议问一个单独的问题，看看使用 numpy 列表数组的原因

I wouldn't recommend using a numpy array of lists for anything, but maybe you have some special use case where this makes sense. I suggest asking a separate quesiton that looks at the reasoning for using a numpy array of lists

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