在Python Numpy中沿着多维数组访问数据

NumPy（Numerical Python）是一个Python库，由多维数组和众多函数组成，可以对其进行各种数学和逻辑操作。NumPy还包括各种函数来进行线性代数操作和生成随机数。NumPy经常与SciPy和Matplotlib等软件包一起使用，用于技术计算。
一个n维（多维）数组有固定的大小，并且包含相同类型的项目。多维数组的内容可以根据需要通过使用索引和切分数组来访问和修改。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Integer Indexing来访问数据的元素。我们还可以执行Slicing来访问数据的子序列。
示例 1:

# 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:

# 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:

# 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]]