在Python Numpy 中沿多维数组访问数据

NumPy (Numerical Python) 是一个Python库，由多维数组和众多函数组成，用于对它们执行各种数学和逻辑运算。 NumPy 还包含执行线性代数运算和生成随机数的各种函数。 NumPy 通常与 SciPy 和 Matplotlib 等软件包一起用于技术计算。
n 维（多维）数组具有固定大小并包含相同类型的项。可以根据需要使用索引和切片数组来访问和修改多维数组的内容。为了访问数组的元素，我们需要首先导入库：

import numpy as np

我们可以使用整数索引来访问数据元素。我们还可以执行切片来访问数据的子序列。
示例 1：

Python3

# 1-dimensional array
array1D = np.array([1, 2, 3, 4, 5])
 
print(array1D)
 
# to access elements using positive
# index
print("\nusing positive index :" +str(array1D[0]))
print("using positive index :" +str(array1D[4]))
 
# negative indexing works in opposite
# direction
print("\nusing negative index :" +str(array1D[-5]))
print("using negative index :" +str(array1D[-1]))

输出 ：

[1 2 3 4 5]

using positive index :1
using positive index :5

using negative index :5
using negative index :1

示例 2：

Python3

# 2-dimensional array
array2D = np.array([[93,  95],
                    [84, 100],
                    [99,  87]])
 
print(array2D)
print("shape :" +str(array2D.shape))
 
print("\npositive indexing :" +str(array2D[1, 0]))
print("negative indexing :" +str(array2D[-2, 0]))
 
print("\nslicing using positive indices :" +str(array2D[0:3, 1]))
print("slicing using positive indices :" +str(array2D[:, 1]))
print("slicing using negative indices :" +str(array2D[:, -1]))

输出 ：

[[ 93  95]
 [ 84 100]
 [ 99  87]]
shape :(3, 2)

positive indexing :84
negative indexing :84

slicing using positive indices :[ 95 100  87]
slicing using positive indices :[ 95 100  87]
slicing using negative indices :[ 95 100  87]

示例 3：

Python3

# 3-dimensional array
array3D = np.array([[[ 0,  1,  2],
                     [ 3,  4,  5],
                     [ 6,  7,  8]],
  
                    [[ 9, 10, 11],
                     [12, 13, 14],
                     [15, 16, 17]],
 
                    [[18, 19, 20],
                     [21, 22, 23],
                     [24, 25, 26]]])
 
print(array3D)
print("shape :" +str(array3D.shape))
 
print("\naccessing element :" +str(array3D[0, 1, 0]))
print("accessing elements of a row and a column of an array:"
      +str(array3D[:, 1, 0]))
print("accessing sub part of an array :" +str(array3D[1]))

输出 ：

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

 [[ 9 10 11]
  [12 13 14]
  [15 16 17]]

 [[18 19 20]
  [21 22 23]
  [24 25 26]]]
shape :(3, 3, 3)
accessing element :3
accessing elements of a row and a column of an array:[ 3 12 21]
accessing sub part of an array :[[ 9 10 11]
 [12 13 14]
 [15 16 17]]