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Sorting 2D Arrays | Commonly used NumPy Functions
Ultimate NumPy
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Зміст курсу

Ultimate NumPy

Ultimate NumPy

1. NumPy Basics
2. Indexing and Slicing
3. Commonly used NumPy Functions
4. Math with NumPy

book
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.

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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))
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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.

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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])
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Завдання
test

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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.

  1. 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.

  2. 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.

Switch to desktopПерейдіть на комп'ютер для реальної практикиПродовжуйте з того місця, де ви зупинились, використовуючи один з наведених нижче варіантів
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Секція 3. Розділ 2
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book
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))
copy

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])
copy
Завдання
test

Swipe to show code editor

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.

  1. 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.

  2. 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.

Switch to desktopПерейдіть на комп'ютер для реальної практикиПродовжуйте з того місця, де ви зупинились, використовуючи один з наведених нижче варіантів
Все було зрозуміло?

Як ми можемо покращити це?

Дякуємо за ваш відгук!

Секція 3. Розділ 2
Switch to desktopПерейдіть на комп'ютер для реальної практикиПродовжуйте з того місця, де ви зупинились, використовуючи один з наведених нижче варіантів
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