python中的数组和列表

####转自:模式识别实验室主任 

 

#环境win64+anaconda+python3.6

list & array

（1）list不具有array的全部属性（如维度、转置等）

代码1：

 
#eg1_1
 
import numpy as np
 
a = np.array([[1,2,0,1],[1,6,9,55],[7,8,9,5]])#a为数组
 
print(a.T)
 
 
 
#Result：
 
[[ 1  1  7]
 
 [ 2  6  8]
 
 [ 0  9  9]
 
 [ 1 55  5]]
 
 
 
#eg1_2
 
a = [[1,2,0,1],[1,6,9,55],[7,8,9,5]] #a为列表
 
print(a.T)
 
 
 
#Result：
 
'list' object has no attribute 'T'

代码2:

 

#eg1_3
 
import numpy as np
 
a=np.array([[1,2,3],[1,1,4],[1,5,1]])
 
print(a.shape)
 
 
 
#Result：
 
(3, 3)
 
 
 
#eg1_4
 
a=[[1,2,3],[1,1,4],[1,5,1]]
 
print(a.shape)
 
 
 
#Result
 
'list' object has no attribute 'shape'

（顺带一提，如何把一个数组转化为列向量：↓）

 
import numpy as np
 
a=np.array([[1,2,3],[1,1,4],[1,5,1]])
 
a=a.reshape(-1,1)
 
print(a)
 
 
 
#Result:
 
[[1]
 
[2]
 
[3]
 
[1]
 
[1]
 
[4]
 
[1]
 
[5]
 
[1]]

（2）a[:m]的含义，a可以是列表或者数组，但是无论是哪种情况，a[:0]为空

 

#eg2_1
import numpy as np
a=np.array([[4,1,2],
[7,4,10],
[12,17,88]])
#a=np.array([(4,1,2),
# (7,4,10),
# (12,17,88)]) 这两个a中[和(不一样，其实它们完全一样
print(a[:0])
print(a[:1])
print(a[:2])
#Result:
[]
[[4 1 2]]
[[ 4 1 2]
[ 7 4 10]]
#eg2_1
a=[(4,1,2),(7,4,10),(12,17,88)]
print(a[:0])
print(a[:1])
print(a[:2])
#Result:
[]
[(4, 1, 2)]
[(4, 1, 2), (7, 4, 10)]

（3）array和list关于“==”的计算

 
#eg3_1
 
import numpy as np
 
a=np.array(['dog','cat','car'])
 
b=np.array(['dog','cat','trunk'])
 
acc = (np.mean(a == b))
 
print(acc)
 
 
 
#Result
 
0.6666666666666666
 
 
 
#eg3_2
 
import numpy as np
 
a=['dog','cat','car']
 
b=['dog','cat','trunk']
 
acc = (np.mean(a == b))
 
print(acc)
 
 
 
#Result
 
0.0

（4）array和list关于“*”的计算

 

from numpy import *
 
#a为数组
 
a=array([[1,2,3],
 
[4,5,6]])
 
b=4*a
 
print(b)
 
 
 
[[ 4 8 12]
 
[16 20 24]]
 
 
 
 
 
from numpy import *
 
#a为列表
 
a=([[1,2,3],
 
[4,5,6]])
 
b=4*a
 
print(b)
 
 
 
[[1, 2, 3], [4, 5, 6], [1, 2, 3], [4, 5, 6], [1, 2, 3], [4, 5, 6], [1, 2, 3], [4, 5, 6]]