Question

1. Perform the following tasks with NumPy arrays. All of them can be done (elegantly) in 1 to 3 lines.

(a) Create an 8 × 8 array with ones on all the edges and zeros everywhere else.

(b) Create an 8 × 8 array of integers with a checkerboard pattern of ones and zeros.

(c) Given the array c = np.arange(2, 50, 5), make all the numbers not divisible by 3 negative.

(d) Find the size, shape, mean, and standard deviation of the arrays you created in parts (a)–(c).

Answer 1

# do comment if any problem arises

# Code

a)

import numpy

#create numpy array of 1's

array_2d=numpy.ones([8,8],dtype='int')

#set all non edge elements to 0

array_2d[1:-1,1:-1]=0

#print 2d array

print(array_2d)

Output:

b)

import numpy

#create numpy array of 1's

array_2d=numpy.zeros([8,8],dtype='int')

#set every second block ie alternate block to 1

array_2d[::2,::2]=1

array_2d[1::2,1::2]=1

#print 2d array

print(array_2d)

Output:

3)

import numpy as np

c = np.arange(2, 50, 5)

#loop through all numbers

for i in range(len(c)):

    #if number is not divisible by 3 make it -ve

    if c[i]%3!=0:

        c[i] = -c[i]

print(c)

Output:

d)

for 1)

import numpy

#create numpy array of 1's

array_2d = numpy.ones([8, 8], dtype='int')

#set all non edge elements to 0

array_2d[1:-1, 1:-1] = 0

row,column=array_2d.shape

print(f'Size: {row*column}')

print(f'Shape: {row}x{column}')

print(f'Mean: {numpy.mean(array_2d)}')

print(f'Standard daviation: {round(numpy.std(array_2d),4)}')

Output:

2)

import numpy

#create numpy array of 1's

array_2d = numpy.zeros([8, 8], dtype='int')

#set every second block ie alternate block to 1

array_2d[::2, ::2] = 1

array_2d[1::2, 1::2] = 1

row,column=array_2d.shape

print(f'Size: {row*column}')

print(f'Shape: {row}x{column}')

print(f'Mean: {numpy.mean(array_2d)}')

print(f'Standard daviation: {round(numpy.std(array_2d),4)}')

Output:

3)

import numpy as np

c = np.arange(2, 50, 5)

#loop through all numbers

for i in range(len(c)):

    #if number is not divisible by 3 make it -ve

    if c[i] % 3 != 0:

        c[i] = -c[i]

print(c)

print(f'Size: {len(c)}')

print(f'Shape: {c.shape}')

print(f'Mean: {np.mean(c)}')

print(f'Standard daviation: {round(np.std(c),4)}')

Output: