如何在python中组合两个二维数组？答案

【问题标题】：How to combine two 2D arrays in python?如何在python中组合两个二维数组？
【发布时间】：2020-04-05 23:35:59
【问题描述】：

如图所示如何组合两个二维数组？

sample_list = [np.array([1, 2, 3]), np.array([4, 5, 6)])]
sample_objects = [np.array([object_1, object_2, object_3]), np.array([object_4, object_5, object_6])]

result = [np.array([(1, object_1), (2, object_2), (3, object_3)]), np.array([(4, object_4), (5, object_5), (6, object_)])

【问题讨论】：

为什么要混合整数和object_n？坚持使用列表不是更简单吗？

标签： arrays python-3.x list numpy

【解决方案1】：

使用zip尝试以下操作：

result = [np.array(list(zip(sample_list[i], sample_objects[i]))) for i in range(len(sample_list))]

【讨论】：

【解决方案2】：

您的问题的纯列表版本：

In [121]: sample_list = [[1, 2, 3], [4, 5, 6]] 
     ...: sample_objects = [["object_1", "object_2", "object_3"], ["object_4", "object_5", "object_6"]]                                                                             
In [122]: sample_list                                                                          
Out[122]: [[1, 2, 3], [4, 5, 6]]
In [123]: sample_objects                                                                       
Out[123]: [['object_1', 'object_2', 'object_3'], ['object_4', 'object_5', 'object_6']]
In [124]: [list(zip(a,b)) for a,b in zip(sample_list, sample_objects)]                         
Out[124]: 
[[(1, 'object_1'), (2, 'object_2'), (3, 'object_3')],
 [(4, 'object_4'), (5, 'object_5'), (6, 'object_6')]]

将东西包装在np.array 中几乎不会增加问题。请注意，我必须用字符串替换您的 objects。

sample_objects，如果它确实包含“对象”同时是object dtype：

sample_objects = [np.array(["object_1", "object_2", "object_3"],object), 
    np.array(["object_4", "object_5", "object_6"],object)]

====

定义一个示例类

class MyObj:
    def __init__(self,n):
        self.n = n
    def __repr__(self):
        return f'object_{self.n}'

还有你的数组：

In [141]: sample_list = [np.array([1, 2, 3]), np.array([4, 5, 6])] 
     ...: sample_objects = [np.array([MyObj(n) for n in [1,2,3]]), np.array([MyObj(n) for n in 
     ...: [4,5,6]])]                                                                                      
In [142]: sample_list                                                                          
Out[142]: [array([1, 2, 3]), array([4, 5, 6])]
In [143]: sample_objects                                                                       
Out[143]: 
[array([object_1, object_2, object_3], dtype=object),
 array([object_4, object_5, object_6], dtype=object)]

以及组合它们的list zip方式：

In [153]: [np.array(list(zip(a,b))) for a,b in zip(sample_list, sample_objects)]               
Out[153]: 
[array([[1, object_1],
        [2, object_2],
        [3, object_3]], dtype=object), array([[4, object_4],
        [5, object_5],
        [6, object_6]], dtype=object)]

以及使用np.stack的变体：

In [154]: [np.stack((a,b), axis=1) for a,b in zip(sample_list, sample_objects)]                
Out[154]: 
[array([[1, object_1],
        [2, object_2],
        [3, object_3]], dtype=object), array([[4, object_4],
        [5, object_5],
        [6, object_6]], dtype=object)]

hstack 不会将它们交错：

array([1, 2, 3, object_1, object_2, object_3], dtype=object)

【讨论】：