如何在Python中垂直连接两个数组？ [重复]

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concatenate two one-dimensional to two columns array 1 answer
连接两个一维到两列的数组1个答案

I want to concatenate two arrays vertically in Python using the NumPy package:

我想使用NumPy包在Python中垂直连接两个数组：

a = array([1,2,3,4])
b = array([5,6,7,8])

I want something like this:

我想要这样的东西：

c = array([[1,2,3,4],[5,6,7,8]])

How we can do that using the concatenate function? I checked these two functions but the results are the same:

我们如何使用连接函数来做到这一点？我检查了这两个函数但结果是一样的：

c = concatenate((a,b),axis=0)
# or
c = concatenate((a,b),axis=1)

We have this in both of these functions:

我们在以下两个功能中都有这个：

c = array([1,2,3,4,5,6,7,8])

4 个解决方案

#1

The problem is that both a and b are 1D arrays and so there's only one axis to join them on.

问题是a和b都是1D数组，因此只有一个轴可以连接它们。

Instead, you can use vstack (v for vertical):

相反，您可以使用vstack（v表示垂直）：

>>> np.vstack((a,b))
array([[1, 2, 3, 4],
       [5, 6, 7, 8]])

Also, row_stack is an alias of the vstack function:

另外，row_stack是vstack函数的别名：

>>> np.row_stack((a,b))
array([[1, 2, 3, 4],
       [5, 6, 7, 8]])

It's also worth noting that multiple arrays of the same length can be stacked at once. For instance, np.vstack((a,b,x,y)) would have four rows.

值得注意的是，可以同时堆叠相同长度的多个阵列。例如，np.vstack（（a，b，x，y））将有四行。

Under the hood, vstack works by making sure that each array has at least two dimensions (using atleast_2D) and then calling concatenate to join these arrays on the first axis (axis=0).

在引擎盖下，vstack通过确保每个数组至少具有两个维度（使用atleast_2D）然后调用concatenate以在第一个轴（轴= 0）上连接这些数组来工作。

#2

Maybe it's not a good solution, but it's simple way to makes your code works, just add reshape:

也许它不是一个好的解决方案，但它是使代码工作的简单方法，只需添加重塑：

a = array([1,2,3,4])
b = array([5,6,7,8])

c = concatenate((a,b),axis=0).reshape((2,4))

print c

out:

出：

[[1 2 3 4]
 [5 6 7 8]]

In general if you have more than 2 arrays with the same length:

通常，如果您有两个以上具有相同长度的数组：

reshape((number_of_arrays, length_of_array))

#3

To use concatenate, you need to make a and b 2D arrays instead of 1D, as in

要使用连接，您需要制作a和b 2D数组而不是1D，如

c = concatenate((atleast_2d(a), atleast_2d(b)))

Alternatively, you can simply do

或者，你可以做到

c = array((a,b))

#4

Use np.vstack:

使用np.vstack：

In [4]:

import numpy as np
a = np.array([1,2,3,4])
b = np.array([5,6,7,8])
c = np.vstack((a,b))
c
Out[4]:
array([[1, 2, 3, 4],
       [5, 6, 7, 8]])

In [5]:

d = np.array ([[1,2,3,4],[5,6,7,8]])
d

Out[5]:
array([[1, 2, 3, 4],
       [5, 6, 7, 8]])
In [6]:

np.equal(c,d)
Out[6]:
array([[ True,  True,  True,  True],
       [ True,  True,  True,  True]], dtype=bool)

#1