Numpy array index slice

NumPy  Array index

Accessing array elements

Array index is the same as accessing array elements .

You can access an array element by referencing its index number .

NumPy The index in the array is in 0 start , This means that the index of the first element is 0, The index of the second element is 1, And so on .

example 1 Get the first element from the following array ：

import numpy as np

arr = np.array([1, 2, 3, 4])

print(arr[0])

Running results ：

1

example 2 Get the second element from the following array .

import numpy as np

arr = np.array([1, 2, 3, 4])

print(arr[1])

Running results ：

2

example 3 Get the third and fourth elements from the following array and add them .

import numpy as np

arr = np.array([1, 2, 3, 4])

print(arr[2] + arr[3])

Running results ：

7

visit 2-D Array

To access elements from a two-dimensional array , We can use comma separated integers to represent the dimension and index of elements .

Think of a two-dimensional array as a table containing rows and columns , Where rows represent dimensions , The index represents the column .

example : Access the elements on the first row and the second column ：

import numpy as np

arr = np.array([[1,2,3,4,5], [6,7,8,9,10]])

print(' The elements on the first row and the second column are : ', arr[0, 1])

Running results ：

 The elements on the first row and the second column are :  2

example 2： Access No. 2 Xing di 5 Elements in columns ：

import numpy as np

arr = np.array([[1,2,3,4,5], [6,7,8,9,10]])

print(' The first  2  Xing di  5  The elements in the column are : ', arr[1, 4])

Running results ：

 The first  2  Xing di  5  The elements in the column are :  10

visit 3-D Array

To access elements from a 3D array , We can use comma separated integers to represent the dimension and index of elements .

example 1 Access the third element of the second array of the first array ：

import numpy as np

arr = np.array([[[1, 2, 3], [4, 5, 6]], [[7, 8, 9], [10, 11, 12]]])

print(arr[0, 1, 2])

Running results ：

6

example

The first number represents the first dimension , It contains two arrays ：
[[1, 2, 3], [4, 5, 6]]
and ：
[[7, 8, 9], [10, 11, 12]]
Because we chose 0 , Represents that we have selected the array ：
[[1, 2, 3], [4, 5, 6]]

The second number represents the second dimension , It also contains two arrays ：
[1,2,3]
and ：
[4,5,6]
Because we chose 1, Represents that we selected the second array ：
[4,5,6]

The third number represents the third dimension , It contains three values ：
4
5
6
Because we chose 2 , We finally get the third value ：
6

Negative index

Use a negative index to access the array from the end .

example Print the second dim Last element of ：

import numpy as np

arr = np.array([[1,2,3,4,5], [6,7,8,9,10]])

print(' the second  dim  Last element of : ', arr[1, -1])

Running results ：

 the second  dim  Last element of :  10

NumPy  Array slice

Slice array

Python Slicing in means bringing elements from one given index to another .

We pass slices instead of indexes , As shown below ：.[start:end]

We can also define steps , As shown below ：.[start:end:step]

If we don't set start, Says from the 0 Start

If we don't set end, Indicates the length of the array

If we don't set step, The default is 1

example ： Index the elements from the following array 1 Slice to index 5：

import numpy as np

arr = np.array([1, 2, 3, 4, 5, 6, 7])

print(arr[1:5])

Running results ：

[2 3 4 5]

Be careful ： result Include Starting index , but barring End index .

example : Remove elements from the index 4 Slice to the end of the array ：

import numpy as np

arr = np.array([1, 2, 3, 4, 5, 6, 7])

print(arr[4:])

Running results ：

[5 6 7]

Example ： From start to index 4（ barring ） Slice elements ：

import numpy as np

arr = np.array([1, 2, 3, 4, 5, 6, 7])

print(arr[:4])

Running results ：

[1 2 3 4]

Negative slice

Use the minus operator to reference the index from the end ：

example : Index from the end 3 Cut to the index from the end 1：

import numpy as np

arr = np.array([1, 2, 3, 4, 5, 6, 7])

print(arr[-3:-1])

Running results ：

[5 6]

step step

Use step Determine the slice length ：

example ： Return from index 1 To the index 5 All other elements of ：

import numpy as np

arr = np.array([1, 2, 3, 4, 5, 6, 7])

print(arr[1:5:2])

Running results ：

[2 4]

Example Returns all odd elements from the entire array ：

import numpy as np

arr = np.array([1, 2, 3, 4, 5, 6, 7])

print(arr[::2])

Running results ：

[1 3 5 7]

2-D Array section

example Start with the second element , Remove elements from the index 1 Slice to index 4（ Not included ）：

import numpy as np

arr = np.array([[1, 2, 3, 4, 5], [6, 7, 8, 9, 10]])

print(arr[1, 1:4])

Running results ：

[7 8 9]

example Return the index from these two elements 2：

import numpy as np

arr = np.array([[1, 2, 3, 4, 5], [6, 7, 8, 9, 10]])

print(arr[0:2, 2])

Running results ：

[3 8]

Example ： From two elements , Slice indices 1 To the index 4（ Not included ）, This will return to a 2-D Array ：

import numpy as np

arr = np.array([[1, 2, 3, 4, 5], [6, 7, 8, 9, 10]])

print(arr[0:2, 1:4])

Running results ：

[[2 3 4]
 [7 8 9]]