## Q. Using the arrays created in Question 4 above, Write NumPy commands for the following:

(a) A 1-D array called zeros having 10 elements and all the elements are set to zero.

(b) A 1-D array called vowels having the elements ‘a’, ‘e’, ‘i’, ‘o’ and ‘u’.

(c) A 2-D array called ones having 2 rows and 5 columns and all the elements are set to 1 and dtype as int.

(d) Use nested Python lists to create a 2-D array called myarray1 having 3 rows and 3 columns and store the following data: 2.7, -2, -190, 3.4, 99.910.6, 0, 13

(e) A 2-D array called myarray2 using arange() having 3 rows and 5 columns with start value = 4, step size 4 and dtype as float.

**a) Find the transpose of ones and myarray2.**

**b) Sort the array vowels in reverse.**

**c) Sort the array myarray1 such that it brings the lowest value of the column in the first row and so on.**

Answer :

**(a)**

ones = np.ones((2, 5), dtype=int) myarray2 = np.arange(4, 4 + 3 * 5 * 4, 4, dtype=float).reshape(3, 5) #transpose of ones ones_transpose = ones.T # transpose of myarray2 myarray2_transpose = np.transpose(myarray2) print("Transpose of ones:") print(ones_transpose) print("\nTranspose of myarray2:") print(myarray2_transpose)

Transpose of ones, we use the .T attribute to obtain ones_transpose.

Transpose of myarray2, we can use the np.transpose() function, passing myarray2 as the argument. The resulting transpose is stored in myarray2_transpose.

In NumPy, you can obtain the transpose of an array using either the .T attribute or the np.transpose() function.

**(b)**

To sort the array vowels in reverse order in NumPy, you can use the np.sort() function with the [::-1] indexing

import numpy as np vowels = np.array(['a', 'e', 'i', 'o', 'u']) # Sort the vowels array in reverse order vowels_reverse_sorted = np.sort(vowels)[::-1] print(vowels_reverse_sorted)

**(c)**

To sort the array myarray1 in a way that brings the lowest value of each column to the first row and so on, you can use the np.sort() function with the axis parameter set to 0.

myarray1 = np.array([[2.7, -2, -19], [0, 3.4, 99.9], [10.6, 0, 13]]) # Sort the array myarray1 column-wise sorted_array = np.sort(myarray1, axis=0) print(sorted_array)

To sort myarray1 column-wise, we use the np.sort() function and set the axis parameter to 0. This indicates that the sorting should be performed along each column.

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