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

Q. Create the following NumPy arrays:

(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.

Answer: -

(a)
import numpy  as np
zeros = np.zeros((10,))
print (zeros)

(b)
vowels = np.array(list('aeiou'))
print (vowels)

(c)
ones =np.ones ((2,5),dtype=int)
print(ones )

(d)
myarray1  =np.array([[2.7,  -2,  -19],[0,  3.4,  99.9],[10.6,  0,  13]])
print (myarray1)

(e)

myarray2 = np.arange(4, 4 + 3 * 5 * 4, 4, dtype=float).reshape(3, 5)

np.arange(4, 4 + 3 * 5 * 4, 4, dtype=float) generates a 1-D array starting from 4, with a step size of 4, and a total of 3 * 5 = 15 elements. The dtype=float ensures that the array has a floating-point data type.

.reshape(3, 5) reshapes the 1-D array into a 2-D array with 3 rows and 5 columns.