Numpy：数组创建、数组基本属性

Numpy数组创建

import numpy as np
'''
numpy中的ndarray数组
'''

ary = np.array([1, 2, 3, 4, 5])
print(ary)
ary = ary * 10
print(ary)

'''
ndarray对象的创建
'''
# 创建二维数组
# np.array([[],[],...])
a = np.array([[1, 2, 3, 4], [5, 6, 7, 8]])
print(a)

# np.arange(起始值, 结束值, 步长（默认1）)
b = np.arange(1, 10, 1)
print(b)

# np.zeros(数组元素个数, dtype='数组元素类型')
c = np.zeros(10)
print(c, '; c.dtype:', c.dtype)

# np.ones(数组元素个数, dtype='数组元素类型')
d = np.ones(10, dtype='int64')
print(d, '; d.dtype:', d.dtype)

Numpy的ndarray对象属性：

数组的维度：array.shape

元素的类型：array.dtype

数组元素的个数：array.size

数组的索引（下标）:array[0]

'''
数组的基本属性
'''
a = np.array([[1, 2, 3], [4, 5, 6]])
print(a)

# 测试数组的基本属性
print('a.shape:', a.shape)
# a.shape = (6, )  # 此格式可将原数组结构变成1行6列的数据结构
# print(a, 'a.shape:', a.shape)
print('a.size:', a.size)
print('len(a):', len(a))

# 数组元素的索引
ary = np.arange(1, 28)
ary.shape = (3, 3, 3)   # 创建三维数组
print(ary, '; ary.shape:', ary.shape)

print('ary[0]:', ary[0])
print('ary[0][0]:', ary[0][0])
print('ary[0][0][0]:', ary[0][0][0])
print('ary[0,0,0]:', ary[0, 0, 0])

# 遍历三维数组
for i in range(ary.shape[0]):
    for j in range(ary.shape[1]):
        for k in range(ary.shape[2]):
            print(ary[i, j, k], end=' ')