Course Content

NumPy in a Nutshell

1. Getting Started with NumPy

What is NumPy?Function array()Basic Array Creation Quiz

2. Dimensions in Arrays

1-D Arrays Mathematical Operations with 1-D Arrays 2-D Arrays 3-D Arrays Multidimensional Arrays Quiz

3. Indexing and Slicing

Access Array Elements Match Math Operations Access 2-D and 3-D Arrays Match the Slicing Negative Indexing Match the Indices Get One Dimensional Array Using Slice and Only Positive Indexes Get One Dimensional Array Using Only Negative Indexes

4. Important Functions

Reshaping Flattening Joining Sorting Arrays Copying Arrays

Sorting Arrays

Now, let's dive into sorting arrays. Sorting an array involves arranging its elements in a specific order, whether it's ascending, descending, or some other sequence.

Let's try to sort the array:


              123456
            
import numpy as np

array = np.array([3, -4, 6, 0, 12, 499, -123])

print('unsorted array', array)
print('sorted array', np.sort(array))

Note
The sort() function returns a copy of the array, while the original array remains unchanged.

Let's try to sort a 2-D array:


              12345
            
import numpy as np

array = np.array([[-2, 4, -12, -434, 62], [1, 4, 7, 93, 75]])
print('Unsorted array', array)
print('Sorted array', np.sort(array))

Task

You have the following array: [15, -2, 33, 47, -55, 16, 0, 834]. Your task is to sort it.

Task

You have the following array: [15, -2, 33, 47, -55, 16, 0, 834]. Your task is to sort it.

Switch to desktop for real-world practiceContinue from where you are using one of the options below

Everything was clear?

Section 4. Chapter 4

Sorting Arrays

Now, let's dive into sorting arrays. Sorting an array involves arranging its elements in a specific order, whether it's ascending, descending, or some other sequence.

Let's try to sort the array:


              123456
            
import numpy as np

array = np.array([3, -4, 6, 0, 12, 499, -123])

print('unsorted array', array)
print('sorted array', np.sort(array))

Note
The sort() function returns a copy of the array, while the original array remains unchanged.

Let's try to sort a 2-D array:


              12345
            
import numpy as np

array = np.array([[-2, 4, -12, -434, 62], [1, 4, 7, 93, 75]])
print('Unsorted array', array)
print('Sorted array', np.sort(array))

Task

You have the following array: [15, -2, 33, 47, -55, 16, 0, 834]. Your task is to sort it.

Task

You have the following array: [15, -2, 33, 47, -55, 16, 0, 834]. Your task is to sort it.

Switch to desktop for real-world practiceContinue from where you are using one of the options below

Everything was clear?

Section 4. Chapter 4

Sorting Arrays

Now, let's dive into sorting arrays. Sorting an array involves arranging its elements in a specific order, whether it's ascending, descending, or some other sequence.

Let's try to sort the array:


              123456
            
import numpy as np

array = np.array([3, -4, 6, 0, 12, 499, -123])

print('unsorted array', array)
print('sorted array', np.sort(array))

Note
The sort() function returns a copy of the array, while the original array remains unchanged.

Let's try to sort a 2-D array:


              12345
            
import numpy as np

array = np.array([[-2, 4, -12, -434, 62], [1, 4, 7, 93, 75]])
print('Unsorted array', array)
print('Sorted array', np.sort(array))

Task

You have the following array: [15, -2, 33, 47, -55, 16, 0, 834]. Your task is to sort it.

Task

You have the following array: [15, -2, 33, 47, -55, 16, 0, 834]. Your task is to sort it.

Switch to desktop for real-world practiceContinue from where you are using one of the options below

Everything was clear?

Now, let's dive into sorting arrays. Sorting an array involves arranging its elements in a specific order, whether it's ascending, descending, or some other sequence.

Let's try to sort the array:


              123456
            
import numpy as np

array = np.array([3, -4, 6, 0, 12, 499, -123])

print('unsorted array', array)
print('sorted array', np.sort(array))

Note
The sort() function returns a copy of the array, while the original array remains unchanged.

Let's try to sort a 2-D array:


              12345
            
import numpy as np

array = np.array([[-2, 4, -12, -434, 62], [1, 4, 7, 93, 75]])
print('Unsorted array', array)
print('Sorted array', np.sort(array))

Task

You have the following array: [15, -2, 33, 47, -55, 16, 0, 834]. Your task is to sort it.

Switch to desktop for real-world practiceContinue from where you are using one of the options below

Section 4. Chapter 4

Switch to desktop for real-world practiceContinue from where you are using one of the options below