操作Ndarray元素

1. 访问和删除和插入 ndarray 中的元素

1.1 访问ndarry元素

1.1.1 索引访问元素

import numpy as np
x = np.array([1, 2, 3, 4, 5])
print(x[0])
print(x[-1])

1
5

1.1.2 元素赋值

x[3] = 5
x[4] = 4
print(x)

[1 2 3 5 4]

1.1.3 二维数组

x = np.arange(1,10).reshape(3,3)
print(x)
print(x[1,1])
x[1,1] = 0
print(x[1,1])

[[1 2 3]
 [4 5 6]
 [7 8 9]]
5
0

1.2 删除ndarray元素

x = [1, 2, 3, 4, 5, 0]
y = np.arange(1,17).reshape(4,4)
print(x)
print(y)
a = np.delete(x,[0,4])
print(a)
b = np.delete(y, 0, axis = 0)
print(b)
b = np.delete(y, 3, axis = 1)
print(b)

[1, 2, 3, 4, 5, 0]
[[ 1  2  3  4]
 [ 5  6  7  8]
 [ 9 10 11 12]
 [13 14 15 16]]
[2 3 4 0]
[[ 5  6  7  8]
 [ 9 10 11 12]
 [13 14 15 16]]
[[ 1  2  3]
 [ 5  6  7]
 [ 9 10 11]
 [13 14 15]]

1.3 添加ndarray元素

1.3.1 append 方法

x = np.array([1, 2, 3, 4, 5])
y = np.arange(1,10).reshape(3,3)
print("Origin x is : \n{}\n".format(x))
print("Origin y is : \n{}\n".format(y))
a = np.append(x, [6, 7, 8])
print("After append x is:\n{}\n".format(a))
b = np.append(y,[ [10, 11, 12]], axis = 0)
print("After append y is:\n{}\n".format(b))
z = np.append(y, [[10],[11],[12]], axis = 1)
print("After append y is:\n{}\n".format(z))
#注 参数中的value向量的维数必须与目标向量的维数完全一致，否则会报错

Origin x is : 
[1 2 3 4 5]

Origin y is : 
[[1 2 3]
 [4 5 6]
 [7 8 9]]

After append x is:
[1 2 3 4 5 6 7 8]

After append y is:
[[ 1  2  3]
 [ 4  5  6]
 [ 7  8  9]
 [10 11 12]]

After append y is:
[[ 1  2  3 10]
 [ 4  5  6 11]
 [ 7  8  9 12]]

1.3.2 insert 方法

x = np.array([1, 2, 3, 4, 5])
y = np.arange(1,10).reshape(3,3)
print("Origin x is : \n{}\n".format(x))
print("Origin y is : \n{}\n".format(y))
a = np.insert(x, 3, [0, 1, 2])
print("After insert x is:\n{}\n".format(a))
b = np.insert(y, 1, [5, 6, 7], axis = 0)
print("After insert y is:\n{}\n".format(b))
b = np.insert(y, 1, [5,6,7], axis = 1)
print("After insert y is:\n{}\n".format(b))

Origin x is : 
[1 2 3 4 5]

Origin y is : 
[[1 2 3]
 [4 5 6]
 [7 8 9]]

After insert x is:
[1 2 3 0 1 2 4 5]

After insert y is:
[[1 2 3]
 [5 6 7]
 [4 5 6]
 [7 8 9]]

After insert y is:
[[1 5 2 3]
 [4 6 5 6]
 [7 7 8 9]]

1.3.3 vstack 和 hstack方法

x = np.array([1,2])
Y = np.array([[3,4],[5,6]])
print()
print('x = ', x)
print()
print('Y = \n', Y)
z = np.vstack((x,Y))
w = np.hstack((Y,x.reshape(2,1)))

print()
print('z = \n', z)
print()
print('w = \n', w)

x =  [1 2]

Y = 
 [[3 4]
 [5 6]]

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

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