笔记6 6.array合并

import numpy as np

arr1 = np.array([1,2,3])
arr2 = np.array([4,5,6])
arr3 = np.vstack((arr1,arr2))  #合并
print(arr3)
print(arr3.shape)  #合并结果两行三列，垂直方向的合并

[[1 2 3]
 [4 5 6]]
(2, 3)

arr4 = np.hstack((arr1,arr2))   #水平合并
print(arr4)
print(arr4.shape)

[1 2 3 4 5 6]
(6,)

arrv = np.vstack((arr1,arr2,arr3))   #对多个矩阵进行合并
print(arrv)

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

arrh = np.hstack((arr1,arr2,arr4))  ##水平多个合并
print(arrh)

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

arr = np.concatenate((arr1,arr2,arr1))
print(arr)   #合并的另一种方法

[1 2 3 4 5 6 1 2 3]

arr = np.concatenate((arr3,arrv),axis = 0)   #0为垂直合并 合并的矩阵维度要相同
print(arr)

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

arr = np.concatenate((arr3,arr3),axis = 1)   #横向合并 维度相同，形状匹配

arr1.T
print(arr1.T)   ##一维的array不能转置

[1 2 3]

print(arr1.shape)

(3,)

arr1_1 = arr1[np.newaxis,:]   #将矩阵变为一个二维矩阵 横向变化
print(arr1_1)
print(arr1_1.shape)

[[1 2 3]]
(1, 3)

print(arr1_1.T)

[[1]
 [2]
 [3]]

arr1_3  =np.atleast_2d(arr1)   #最少为2维数据
print(arr1_3)
print(arr1_3.T)

[[1 2 3]]
[[1]
 [2]
 [3]]

arr1_2 = arr1[:,np.newaxis]   #将矩阵变为一个二维矩阵,纵向变化
print(arr1_2)
print(arr1_2.shape)

[[1]
 [2]
 [3]]
(3, 1)