{"id":887,"date":"2024-02-23T13:14:03","date_gmt":"2024-02-23T13:14:03","guid":{"rendered":"https:\/\/learnpython.elegantwallp.com\/?p=887"},"modified":"2024-02-23T13:14:04","modified_gmt":"2024-02-23T13:14:04","slug":"numpy-array-indexing","status":"publish","type":"post","link":"https:\/\/learnpython.elegantwallp.com\/2024\/02\/23\/numpy-array-indexing\/","title":{"rendered":"NumPy\u00a0Array Indexing"},"content":{"rendered":"\n

Access Array Elements<\/h2>\n\n\n\n

Array indexing is the same as accessing an array element.<\/p>\n\n\n\n

You can access an array element by referring to its index number.<\/p>\n\n\n\n

The indexes in NumPy arrays start with 0, meaning that the first element has index 0, and the second has index 1 etc.<\/p>\n\n\n\n

ExampleGet your own Python Server<\/h3>\n\n\n\n

Get the first element from the following array:<\/p>\n\n\n\n

import\u00a0numpy\u00a0as\u00a0np

arr = np.array([1,\u00a02,\u00a03,\u00a04])

print(arr[0])<\/code><\/pre>\n\n\n\n
Example<\/h3>\n\n\n\n
Get the second element from the following array.<\/p>\n\n\n\n
import\u00a0numpy\u00a0as\u00a0np

arr = np.array([1,\u00a02,\u00a03,\u00a04])

print(arr[1])<\/code><\/pre>\n\n\n\n
Example<\/h3>\n\n\n\n
Get third and fourth elements from the following array and add them.<\/p>\n\n\n\n
import\u00a0numpy\u00a0as\u00a0np

arr = np.array([1,\u00a02,\u00a03,\u00a04])

print(arr[2] +\u00a0arr[3])<\/code><\/pre>\n\n\n\n
\n\n\n\n
\n\n\n\n
Access 2-D Arrays<\/h2>\n\n\n\n
To access elements from 2-D arrays we can use comma separated integers representing the dimension and the index of the element.<\/p>\n\n\n\n
Think of 2-D arrays like a table with rows and columns, where the dimension represents the row and the index represents the column.<\/p>\n\n\n\n
Example<\/h3>\n\n\n\n
Access the element on the first row, second column:<\/p>\n\n\n\n
import\u00a0numpy\u00a0as\u00a0np\n\narr = np.array([[1,2,3,4,5], [6,7,8,9,10]])\n\nprint('2nd element on 1st row: ', arr[0,\u00a01])\n\n<\/code><\/pre>\n\n\n\n
Example<\/h3>\n\n\n\n
Access the element on the 2nd row, 5th column:<\/p>\n\n\n\n
import numpy as np

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

print('5th element on 2nd row: ', arr[1, 4])<\/code><\/pre>\n\n\n\n
Try it Yourself \u00bb<\/a><\/p>\n\n\n\n
\n\n\n\n
Access 3-D Arrays<\/h2>\n\n\n\n
To access elements from 3-D arrays we can use comma separated integers representing the dimensions and the index of the element.<\/p>\n\n\n\n
Example<\/h3>\n\n\n\n
Access the third element of the second array of the first array:<\/p>\n\n\n\n
import numpy as np

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

print(arr[0, 1, 2])<\/code><\/pre>\n\n\n\n
Try it Yourself \u00bb<\/a><\/p>\n\n\n\n
Example Explained<\/h3>\n\n\n\n
arr[0, 1, 2]<\/code> prints the value 6<\/code>.<\/p>\n\n\n\n
And this is why:<\/p>\n\n\n\n
The first number represents the first dimension, which contains two arrays:
[[1, 2, 3], [4, 5, 6]]
and:
[[7, 8, 9], [10, 11, 12]]
Since we selected 0<\/code>, we are left with the first array:
[[1, 2, 3], [4, 5, 6]]<\/code><\/pre>\n\n\n\n
The second number represents the second dimension, which also contains two arrays:
[1, 2, 3]
and:
[4, 5, 6]
Since we selected 1<\/code>, we are left with the second array:
[4, 5, 6]<\/code><\/pre>\n\n\n\n
The third number represents the third dimension, which contains three values:
4
5
6
Since we selected 2<\/code>, we end up with the third value:
6<\/code><\/pre>\n\n\n\n
\n\n\n\n
Negative Indexing<\/h2>\n\n\n\n
Use negative indexing to access an array from the end.<\/p>\n\n\n\n
Example<\/h3>\n\n\n\n
Print the last element from the 2nd dim:<\/p>\n\n\n\n
import numpy as np

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

print('Last element from 2nd dim: ', arr[1, -1])<\/code><\/pre>\n\n\n\n
Try it Yourself \u00bb<\/a><\/p>\n\n\n\n
\n\n\n\n
Test Yourself With Exercises<\/h2>\n\n\n\n
Exercise:<\/h2>\n\n\n\n
Insert the correct syntax for printing the first item in the array.arr = np.array([1, 2, 3, 4, 5]) print(arr)<\/code><\/pre>\n","protected":false},"excerpt":{"rendered":"
Access Array Elements Array indexing is the same as accessing an array element. You can access an array element by referring to its index number. The indexes in NumPy arrays start with 0, meaning that the first element has index 0, and the second has index 1 etc. ExampleGet your own Python Server Get the […]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[93],"tags":[],"class_list":["post-887","post","type-post","status-publish","format-standard","hentry","category-numpy"],"_links":{"self":[{"href":"https:\/\/learnpython.elegantwallp.com\/wp-json\/wp\/v2\/posts\/887","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/learnpython.elegantwallp.com\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/learnpython.elegantwallp.com\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/learnpython.elegantwallp.com\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/learnpython.elegantwallp.com\/wp-json\/wp\/v2\/comments?post=887"}],"version-history":[{"count":1,"href":"https:\/\/learnpython.elegantwallp.com\/wp-json\/wp\/v2\/posts\/887\/revisions"}],"predecessor-version":[{"id":888,"href":"https:\/\/learnpython.elegantwallp.com\/wp-json\/wp\/v2\/posts\/887\/revisions\/888"}],"wp:attachment":[{"href":"https:\/\/learnpython.elegantwallp.com\/wp-json\/wp\/v2\/media?parent=887"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/learnpython.elegantwallp.com\/wp-json\/wp\/v2\/categories?post=887"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/learnpython.elegantwallp.com\/wp-json\/wp\/v2\/tags?post=887"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}