1.使用array函数创建数组

import numpy as npndarray1 = np.array([1, 2, 3])array([1, 2, 3])ndarray2 = np.array(list('abcd'))array(['a', 'b', 'c', 'd'],      dtype='

2.zeros和zeros_like创建数组

用于创建数组，数组元素默认值是0. 注意:zeros_like函数只是根据传入的ndarray数组的shape来创建所有元素为0的数组，并不是拷贝源数组中的数据

ndarray1 = np.zeros(6)ndarray2 = np.zeros((2, 3))ndarray3 = np.zeros_like(ndarray2)  # 按照 ndarray2 的shape创建数组print("数组类型:")print('ndarray1:', type(ndarray1))print('ndarray2:', type(ndarray2))print('ndarray3:', type(ndarray3))print("数组元素类型:")print('ndarray1:', ndarray1.dtype)print('ndarray2:', ndarray2.dtype)print('ndarray3:', ndarray3.dtype)print("数组形状:")print('ndarray1:', ndarray1.shape)print('ndarray2:', ndarray2.shape)print('ndarray3:', ndarray3.shape)输出结果：数组类型:ndarray1: 
     
      ndarray2: 
      
       ndarray3: 
       
        数组元素类型:ndarray1: float64ndarray2: float64ndarray3: float64数组形状:ndarray1: (6,)ndarray2: (2, 3)ndarray3: (2, 3)
       
      
     

3.ones和ones_like创建数组

与zero类似

# 创建数组，元素默认值是0ndarray1 = np.ones(7)ndarray2 = np.ones((2, 3))# 修改元素的值ndarray2[0][1] = 4ndarray3 = np.ones_like(ndarray2)  # 按照 ndarray2 的shape创建数组# 打印数组元素类型print("数组类型:")print('ndarray1:', type(ndarray1))print('ndarray2:', type(ndarray2))print('ndarray3:', type(ndarray3))print("数组元素类型:")print('ndarray1:', ndarray1.dtype)print('ndarray2:', ndarray2.dtype)print('ndarray3:', ndarray3.dtype)print("数组形状:")print('ndarray1:', ndarray1.shape)print('ndarray2:', ndarray2.shape)print('ndarray3:', ndarray3.shape)输出结果：数组类型:ndarray1: 
     
      ndarray2: 
      
       ndarray3: 
       
        数组元素类型:ndarray1: float64ndarray2: float64ndarray3: float64数组形状:ndarray1: (7,)ndarray2: (2, 3)ndarray3: (2, 3)
       
      
     

4.empty和empty_like创建数组

用于创建空数组，空数据中的值并不为0,而是未初始化的随机值.

ndarray1 = np.empty(5)ndarray2 = np.empty((2, 3))ndarray3 = np.empty_like(ndarray1)# 打印数组元素类型print("数组类型:")print('ndarray1:', type(ndarray1))print('ndarray2:', type(ndarray2))print('ndarray3:', type(ndarray3))print("数组元素类型:")print('ndarray1:', ndarray1.dtype)print('ndarray2:', ndarray2.dtype)print('ndarray3:', ndarray3.dtype)print("数组形状:")print('ndarray1:', ndarray1.shape)print('ndarray2:', ndarray2.shape)print('ndarray3:', ndarray3.shape)输出结果：数组类型:ndarray1: 
     
      ndarray2: 
      
       ndarray3: 
       
        数组元素类型:ndarray1: float64ndarray2: float64ndarray3: float64数组形状:ndarray1: (5,)ndarray2: (2, 3)ndarray3: (5,)
       
      
     

5.arange函数创建数组

arange函数是python内置函数range函数的数组版本

ndarray1 = np.arange(10)print("ndarray1:",ndarray1)ndarray2 = np.arange(10, 20)print("ndarray2:",ndarray2)ndarray3 = np.arange(10, 20, 2)print("ndarray3:",ndarray3)输出结果：ndarray1: [0 1 2 3 4 5 6 7 8 9]ndarray2: [10 11 12 13 14 15 16 17 18 19]ndarray3: [10 12 14 16 18]

6.eye创建对角矩阵数组

该函数用于创建一个N*N的矩阵，对角线为1，其余为0.

ndarray1 = np.eye(3)ndarray1输出结果：array([[ 1.,  0.,  0.],       [ 0.,  1.,  0.],       [ 0.,  0.,  1.]])