## 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.

Missing the answer for (e),

ReplyDelete(e)

myarray2 =np.arange(4,61,4,float).reshape (3,5)

print (myarray2)

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