合并两个Numpy数组并删除重复项？ [英] Merge two numpy arrays and delete duplicates?

问题描述

我有一个numpy数组=

I have one numpy array =

[1,6,7,9,3,5]

和第二个numpy数组=

and a second numpy array =

[3,5,8,9,2]

我想合并这两个数组在一起：

I would like to merge these two arrays together:

[1,6,7,9,3,5,3,5,8,9,2]

，然后删除numpy数组中的重复项以获得：

and then remove the duplicates in the numpy array to get :

[1,6,7,9,3,5,8,2]

我想保留尽可能多的数组1并取出数组2中没有出现在数组1中的元素，然后追加这些元素。

I would like to keep as much of array one as possible and take out elements of array two, that don't appear in array one, and append these.

我不确定是否更有意义：

I am not sure if it makes more sense to:

1. 合并两个数组并删除重复项。
   或


2. 循环遍历数组2的元素，如果它们未出现在数组1中，则连接到数组1。

我尝试使用各种循环，但这些循环似乎主要用于列表，我也尝试使用 set（），但这订购 numpy 数组，我想保留随机订购单。

I have tried using various loops but these appear to work mostly for lists, I have also tried using set() but this orders the numpy array, I would like to keep the random order form.

推荐答案

要加入两个数组，只需使用 np.concatenate

To join the two arrays, you can simply use np.concatenate

在保留订单的同时删除重复项有些棘手，因为通常 np.unique 也可以排序，但是您可以使用 return_index 然后进行排序以解决此问题：

Removing duplicates while preserving order is a bit tricky, because normally np.unique also sorts, but you can use return_index then sort to get around this:

In [61]: x
Out[61]: array([1, 6, 7, 9, 3, 5])

In [62]: y
Out[62]: array([3, 5, 8, 9, 2])

In [63]: z = np.concatenate((x, y))

In [64]: z
Out[64]: array([1, 6, 7, 9, 3, 5, 3, 5, 8, 9, 2])

In [65]: _, i = np.unique(z, return_index=True)

In [66]: z[np.sort(i)]
Out[66]: array([1, 6, 7, 9, 3, 5, 8, 2])

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