Contenido del Curso

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.

Tarea

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.

Cambia al escritorio para practicar en el mundo realContinúe desde donde se encuentra utilizando una de las siguientes opciones

¿Todo estuvo claro?

¡Gracias por tus comentarios!

Sección 3. Capítulo 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.

Tarea

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.

Cambia al escritorio para practicar en el mundo realContinúe desde donde se encuentra utilizando una de las siguientes opciones

¿Todo estuvo claro?

¡Gracias por tus comentarios!

Sección 3. Capítulo 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.

Tarea

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.

Cambia al escritorio para practicar en el mundo realContinúe desde donde se encuentra utilizando una de las siguientes opciones

¿Todo estuvo claro?

¡Gracias por tus comentarios!

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.

Tarea

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.

Cambia al escritorio para practicar en el mundo realContinúe desde donde se encuentra utilizando una de las siguientes opciones

Sección 3. Capítulo 2

Cambia al escritorio para practicar en el mundo realContinúe desde donde se encuentra utilizando una de las siguientes opciones