1.浅拷贝
= 的赋值方式会带有关联性
比较 ‘ = ’赋值后的数是否一样
import numpy as np
a = np.arange(6)
print(a)
print('\n')
b = a
c = a
d = b
e = c
print(b)
print('\n')
print(c)
print('\n')
print(d)
print('\n')
print(e)
print('\n')
print(b is a)
print(c is b)
print(d is c)
print(e is d)
改变a中的一个数字看b、c、d、e会不会一起改变
import numpy as np
a = np.arange(6)
a[0] = 100
print(a)
print('\n')
b = a
c = a
d = b
e = c
print(b)
print('\n')
print(c)
print('\n')
print(d)
print('\n')
print(e)
print('\n')
print(b is a)
print(c is b)
print(d is c)
print(e is d)
由上面可知，“一改全改”，改变a的值，想要b、c、d、e的值也一起改变了，说明‘’=‘’赋值具有关联性
2.copy深拷贝
看代码，一看就懂。
import numpy as np
a = np.arange(6)
print(a)
print('\n')
b = a.copy()
a[2] = 1000
print(a)
print('\n') #b对a进行了深拷贝，当a的值改变时，b的值没有改变
print(b)
