数组操作

一、形状操作

import numpy as np

ary = np.array([[1,2,3],[4,5,6]])
print(ary)
print("-----------------------------------")
#shape修改的是原有的  
ary.shape = (3,2)
print(ary) #这里是直接对原有数组ary修改成三行两列的数组 
print("-----------------------------------")
#reshape返回一个新的数组
ary = ary.reshape(3,2)
print(ary)
print("------------------------------------")
#将多维变为一维数组
ary01 = ary.reshape((6,),order = 'F') #默认情况下参数order=‘C’以行为顺序展开，F（Fortran）意味以列展开
ary03 = ary.flatten(order = 'F')
print(ary01)
print(ary03)
print("-----------------------------------")
#拓展：数组的形状
t = np.arange(24)
print(t)
print(t.shape)
print("-----------------------------------")
#转换成二维
t1 = t.reshape(4,6)
print(t1)
print(t1.shape)
print("-----------------------------------")
#转换成三维
t2 = t.reshape(2,3,4)
print(t2)
print(t2.shape)

[[1 2 3]
 [4 5 6]]
-----------------------------------
[[1 2]
 [3 4]
 [5 6]]
-----------------------------------
[[1 2]
 [3 4]
 [5 6]]
------------------------------------
[1 3 5 2 4 6]
[1 3 5 2 4 6]
-----------------------------------
[ 0  1  2  3  4  5  6  7  8  9 10 11 12 13 14 15 16 17 18 19 20 21 22 23]
(24,)
-----------------------------------
[[ 0  1  2  3  4  5]
 [ 6  7  8  9 10 11]
 [12 13 14 15 16 17]
 [18 19 20 21 22 23]]
(4, 6)
-----------------------------------
[[[ 0  1  2  3]
  [ 4  5  6  7]
  [ 8  9 10 11]]
 [[12 13 14 15]
  [16 17 18 19]
  [20 21 22 23]]]
(2, 3, 4)

二、ndarray转换成为list

#ndarray.tolist将数组转成list
a = np.array([9,12,88,14,25])
lst_a = a.tolist()
print(lst_a)
type(lst_a)

[9, 12, 88, 14, 25]
list

三、ndarray数组索引/切片/循环操作

#跟列表索引切片类似 
#print(ary[start,end,step])
#一维数组的切片操作
ary04 = np.arange(1,10)
print(ary04)
print(ary04[3:7])
print(ary04[:7:2])
print(ary04[-7::-2])
print("-----------------------------------")
#多维数组的切片操作
#数组对象[页，行，列]，下标从0开始，到数组len-1结束
ary05 = np.arange(1,28).reshape(3,3,3)
print(ary05)
print("-----------------------------------")
#切出1页
print(ary05[1,:,:])
print("-----------------------------------")
#切出所有页的1行
print(ary05[:,1,:])
print("-----------------------------------")
#切出0页的1行1列
print(ary05[0,1,1])

[1 2 3 4 5 6 7 8 9]
[4 5 6 7]
[1 3 5 7]
[3 1]
-----------------------------------
[[[ 1  2  3]
  [ 4  5  6]
  [ 7  8  9]]
 [[10 11 12]
  [13 14 15]
  [16 17 18]]
 [[19 20 21]
  [22 23 24]
  [25 26 27]]]
-----------------------------------
[[10 11 12]
 [13 14 15]
 [16 17 18]]
-----------------------------------
[[ 4  5  6]
 [13 14 15]
 [22 23 24]]
-----------------------------------
[ 5 14]

#多维数组循环操作
ary06 = np.arange(16).reshape(4,4)
ary06
print(ary06.shape)
print(ary06.ndim)
#flat属性
for element01 in ary06.flat:        #方式一
    print(element01)
for element02 in np.nditer(ary06):  #方式二
    print(element02)

(4, 4)
2
0
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
0
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15