Course Content

Ultimate NumPy

Sorting 2D Arrays

Here is an example of sorting a 2D array:

As you can see, simply passing our 2D array to the sort() function sorts each 1D array along the axis 1 (which is the default option in a 2D array). Setting axis=0 sorts each 1D array along the axis 0 (every column). Setting axis=None returns a contiguous sorted 1D array of all the elements of the 2D array.

Let’s now have a look at the code for our example:


              12345678910
            
import numpy as np
array_2d = np.array([[2, 9, 3], [1, 6, 4], [5, 7, 8]])
# Sorting a 2D array along axis 1
print(np.sort(array_2d))
print('-' * 20)
# Sorting a 2D array along axis 0
print(np.sort(array_2d, axis=0))
print('-' * 20)
# Creating a 1D sorted array out of the elements of array_2d
print(np.sort(array_2d, axis=None))

Sorting 2D Arrays in Descending Order

When sorting 2D arrays in descending order along a given axis, you need to use two slices: one full slice ([:]) and another with a negative step ([::-1]). The position of the slice with the negative step should correspond to the axis along which you are sorting.

Note
When sorting along axis 0, you can use only a slice with a negative step, as it already indexes along this axis.

Here is an example:

Let’s now have a look at the code for our example:


              12345678910
            
import numpy as np
array_2d = np.array([[2, 9, 3], [1, 6, 4], [5, 7, 8]])
# Sorting a 2D array along axis 1 in descending order
print(np.sort(array_2d)[:, ::-1])
print('-' * 20)
# Sorting a 2D array along axis 0 in descending order
print(np.sort(array_2d, axis=0)[::-1])
print('-' * 20)
# Creating a 1D sorted array out of the elements of array_2d in descending order
print(np.sort(array_2d, axis=None)[::-1])

You can always use NumPy documentation for reference: numpy.sort, ndarray.sort.

Task

You have a 2D array named exam_scores containing the scores for each exam from a certain subject. Each column represents a specific subject, and each row represents an individual student. Thus, a specific row displays the scores of that student for each exam. Your task is the following:

Create a 2D NumPy array named top_scores_subject based on exam_scores where each column representing a certain subject should be sorted by scores in descending order:
- use the appropriate NumPy function for sorting;
- specify the correct array to sort as the first argument;
- specify the second keyword argument to sort every column;
- use the correct slices for descending order.
Create a 1D NumPy array named sorted_scores based on exam_scores which contains all scores sorted in ascending order:
- use the appropriate NumPy function for sorting;
- specify the correct array to sort as the first argument;
- specify the second keyword argument to create a contiguous sorted 1D array.

By doing so, we can easily see the highest score for each exam and the lowest scores out of all exams.

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

Everything was clear?

Thanks for your feedback!

Section 3. Chapter 2

Sorting 2D Arrays

Here is an example of sorting a 2D array:

Let’s now have a look at the code for our example:


              12345678910
            
import numpy as np
array_2d = np.array([[2, 9, 3], [1, 6, 4], [5, 7, 8]])
# Sorting a 2D array along axis 1
print(np.sort(array_2d))
print('-' * 20)
# Sorting a 2D array along axis 0
print(np.sort(array_2d, axis=0))
print('-' * 20)
# Creating a 1D sorted array out of the elements of array_2d
print(np.sort(array_2d, axis=None))

Sorting 2D Arrays in Descending Order

Note
When sorting along axis 0, you can use only a slice with a negative step, as it already indexes along this axis.

Here is an example:

Let’s now have a look at the code for our example:


              12345678910
            
import numpy as np
array_2d = np.array([[2, 9, 3], [1, 6, 4], [5, 7, 8]])
# Sorting a 2D array along axis 1 in descending order
print(np.sort(array_2d)[:, ::-1])
print('-' * 20)
# Sorting a 2D array along axis 0 in descending order
print(np.sort(array_2d, axis=0)[::-1])
print('-' * 20)
# Creating a 1D sorted array out of the elements of array_2d in descending order
print(np.sort(array_2d, axis=None)[::-1])

You can always use NumPy documentation for reference: numpy.sort, ndarray.sort.

Task

Create a 2D NumPy array named top_scores_subject based on exam_scores where each column representing a certain subject should be sorted by scores in descending order:
- use the appropriate NumPy function for sorting;
- specify the correct array to sort as the first argument;
- specify the second keyword argument to sort every column;
- use the correct slices for descending order.
Create a 1D NumPy array named sorted_scores based on exam_scores which contains all scores sorted in ascending order:
- use the appropriate NumPy function for sorting;
- specify the correct array to sort as the first argument;
- specify the second keyword argument to create a contiguous sorted 1D array.

By doing so, we can easily see the highest score for each exam and the lowest scores out of all exams.

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

Everything was clear?

Thanks for your feedback!

Section 3. Chapter 2

Sorting 2D Arrays

Here is an example of sorting a 2D array:

Let’s now have a look at the code for our example:


              12345678910
            
import numpy as np
array_2d = np.array([[2, 9, 3], [1, 6, 4], [5, 7, 8]])
# Sorting a 2D array along axis 1
print(np.sort(array_2d))
print('-' * 20)
# Sorting a 2D array along axis 0
print(np.sort(array_2d, axis=0))
print('-' * 20)
# Creating a 1D sorted array out of the elements of array_2d
print(np.sort(array_2d, axis=None))

Sorting 2D Arrays in Descending Order

Note
When sorting along axis 0, you can use only a slice with a negative step, as it already indexes along this axis.

Here is an example:

Let’s now have a look at the code for our example:


              12345678910
            
import numpy as np
array_2d = np.array([[2, 9, 3], [1, 6, 4], [5, 7, 8]])
# Sorting a 2D array along axis 1 in descending order
print(np.sort(array_2d)[:, ::-1])
print('-' * 20)
# Sorting a 2D array along axis 0 in descending order
print(np.sort(array_2d, axis=0)[::-1])
print('-' * 20)
# Creating a 1D sorted array out of the elements of array_2d in descending order
print(np.sort(array_2d, axis=None)[::-1])

You can always use NumPy documentation for reference: numpy.sort, ndarray.sort.

Task

Create a 2D NumPy array named top_scores_subject based on exam_scores where each column representing a certain subject should be sorted by scores in descending order:
- use the appropriate NumPy function for sorting;
- specify the correct array to sort as the first argument;
- specify the second keyword argument to sort every column;
- use the correct slices for descending order.
Create a 1D NumPy array named sorted_scores based on exam_scores which contains all scores sorted in ascending order:
- use the appropriate NumPy function for sorting;
- specify the correct array to sort as the first argument;
- specify the second keyword argument to create a contiguous sorted 1D array.

By doing so, we can easily see the highest score for each exam and the lowest scores out of all exams.

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

Everything was clear?

Thanks for your feedback!

Here is an example of sorting a 2D array:

Let’s now have a look at the code for our example:


              12345678910
            
import numpy as np
array_2d = np.array([[2, 9, 3], [1, 6, 4], [5, 7, 8]])
# Sorting a 2D array along axis 1
print(np.sort(array_2d))
print('-' * 20)
# Sorting a 2D array along axis 0
print(np.sort(array_2d, axis=0))
print('-' * 20)
# Creating a 1D sorted array out of the elements of array_2d
print(np.sort(array_2d, axis=None))

Sorting 2D Arrays in Descending Order

Note
When sorting along axis 0, you can use only a slice with a negative step, as it already indexes along this axis.

Here is an example:

Let’s now have a look at the code for our example:


              12345678910
            
import numpy as np
array_2d = np.array([[2, 9, 3], [1, 6, 4], [5, 7, 8]])
# Sorting a 2D array along axis 1 in descending order
print(np.sort(array_2d)[:, ::-1])
print('-' * 20)
# Sorting a 2D array along axis 0 in descending order
print(np.sort(array_2d, axis=0)[::-1])
print('-' * 20)
# Creating a 1D sorted array out of the elements of array_2d in descending order
print(np.sort(array_2d, axis=None)[::-1])

You can always use NumPy documentation for reference: numpy.sort, ndarray.sort.

Task

Create a 2D NumPy array named top_scores_subject based on exam_scores where each column representing a certain subject should be sorted by scores in descending order:
- use the appropriate NumPy function for sorting;
- specify the correct array to sort as the first argument;
- specify the second keyword argument to sort every column;
- use the correct slices for descending order.
Create a 1D NumPy array named sorted_scores based on exam_scores which contains all scores sorted in ascending order:
- use the appropriate NumPy function for sorting;
- specify the correct array to sort as the first argument;
- specify the second keyword argument to create a contiguous sorted 1D array.

By doing so, we can easily see the highest score for each exam and the lowest scores out of all exams.

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

Section 3. Chapter 2

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