numpy数组连接:"ValueError:所有输入数组必须具有相同数量的维数" [英] numpy array concatenate: "ValueError: all the input arrays must have same number of dimensions"

问题描述

如何串联这些numpy数组?

第一个np.array具有形状(5,4)

[[  6487    400 489580      0]
 [  6488    401 492994      0]
 [  6491    408 489247      0]
 [  6491    408 489247      0]
 [  6492    402 499013      0]]

秒np.array，形状为(1,5)

[  16.   15.   12.  12.  17. ]

最终结果应为

[[  6487    400    489580    0   16]
 [  6488    401    492994    0   15]
 [  6491    408    489247    0   12]
 [  6491    408    489247    0   12]
 [  6492    402    499013    0   17]]

我尝试了np.concatenate([array1, array2]) 但我收到此错误

I tried np.concatenate([array1, array2]) but i get this error

ValueError: all the input arrays must have same number of dimensions

我在做什么错了?

推荐答案

要使用np.concatenate，我们需要将第二个数组扩展为2D，然后沿着axis=1-

To use np.concatenate, we need to extend the second array to 2D and then concatenate along axis=1 -

np.concatenate((a,b[:,None]),axis=1)

或者，我们可以使用np.column_stack来解决它-

Alternatively, we can use np.column_stack that takes care of it -

np.column_stack((a,b))

样品运行-

In [84]: a
Out[84]: 
array([[54, 30, 55, 12],
       [64, 94, 50, 72],
       [67, 31, 56, 43],
       [26, 58, 35, 14],
       [97, 76, 84, 52]])

In [85]: b
Out[85]: array([56, 70, 43, 19, 16])

In [86]: np.concatenate((a,b[:,None]),axis=1)
Out[86]: 
array([[54, 30, 55, 12, 56],
       [64, 94, 50, 72, 70],
       [67, 31, 56, 43, 43],
       [26, 58, 35, 14, 19],
       [97, 76, 84, 52, 16]])

如果b的形状是(1,)的dtype=object数组dtype=object，则很可能所有数据都包含在其中的唯一元素中，我们需要展平，然后再进行连接.为此，我们也可以在其上使用np.concatenate.这是运行示例以阐明要点-

If b is such that its a 1D array of dtype=object with a shape of (1,), most probably all of the data is contained in the only element in it, we need to flatten it out before concatenating. For that purpose, we can use np.concatenate on it too. Here's a sample run to make the point clear -

In [118]: a
Out[118]: 
array([[54, 30, 55, 12],
       [64, 94, 50, 72],
       [67, 31, 56, 43],
       [26, 58, 35, 14],
       [97, 76, 84, 52]])

In [119]: b
Out[119]: array([array([30, 41, 76, 13, 69])], dtype=object)

In [120]: b.shape
Out[120]: (1,)

In [121]: np.concatenate((a,np.concatenate(b)[:,None]),axis=1)
Out[121]: 
array([[54, 30, 55, 12, 30],
       [64, 94, 50, 72, 41],
       [67, 31, 56, 43, 76],
       [26, 58, 35, 14, 13],
       [97, 76, 84, 52, 69]])

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