Sorting 2D Arrays

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.


              12345678
            
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))
# Sorting a 2D array along axis 0
print(np.sort(array_2d, axis=0))
# 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.


              12345678
            
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])
# Sorting a 2D array along axis 0 in descending order
print(np.sort(array_2d, axis=0)[::-1])
# Creating a 1D sorted array out of the elements of array_2d in descending order
print(np.sort(array_2d, axis=None)[::-1])

Tarefa

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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.

Create a 2D NumPy array named top_scores_subject based on exam_scores where each column, representing a certain subject, is sorted by scores in descending order.
Create a 1D NumPy array named sorted_scores based on exam_scores, containing all scores sorted in ascending order.

By doing this, you can easily identify the highest scores for each exam and the lowest scores across all exams.

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Tudo estava claro?

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Seção 3. Capítulo 2

Sorting 2D Arrays

Setting axis=None returns a contiguous sorted 1D array of all the elements of the 2D array.


              12345678
            
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))
# Sorting a 2D array along axis 0
print(np.sort(array_2d, axis=0))
# 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.


              12345678
            
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])
# Sorting a 2D array along axis 0 in descending order
print(np.sort(array_2d, axis=0)[::-1])
# Creating a 1D sorted array out of the elements of array_2d in descending order
print(np.sort(array_2d, axis=None)[::-1])

Tarefa

Swipe to show code editor

Create a 2D NumPy array named top_scores_subject based on exam_scores where each column, representing a certain subject, is sorted by scores in descending order.
Create a 1D NumPy array named sorted_scores based on exam_scores, containing all scores sorted in ascending order.

By doing this, you can easily identify the highest scores for each exam and the lowest scores across all exams.

Mude para o desktop para praticar no mundo realContinue de onde você está usando uma das opções abaixo

Tudo estava claro?

Obrigado pelo seu feedback!

Seção 3. Capítulo 2

Mude para o desktop para praticar no mundo realContinue de onde você está usando uma das opções abaixo