import numpy as np

number = np.arange(20)
print(number)

my_mean = np.mean(number)
print("mean is: ", my_mean)

my_var = np.var(number)
print("variance is: ", my_var)

stnd_dev = np.std(number)
print("standard deviation is: ", stnd_dev)

390d21071f07d19b050162ef4ee8bfa68fa54dde
<mask token>

<mask token>
print(number)
<mask token>
print('mean is: ', my_mean)
<mask token>
print('variance is: ', my_var)
<mask token>
print('standard deviation is: ', stnd_dev)

<mask token>
number = np.arange(20)
print(number)
my_mean = np.mean(number)
print('mean is: ', my_mean)
my_var = np.var(number)
print('variance is: ', my_var)
stnd_dev = np.std(number)
print('standard deviation is: ', stnd_dev)

import numpy as np
number = np.arange(20)
print(number)
my_mean = np.mean(number)
print('mean is: ', my_mean)
my_var = np.var(number)
print('variance is: ', my_var)
stnd_dev = np.std(number)
print('standard deviation is: ', stnd_dev)

import numpy as np

number = np.arange(20)
print(number)

my_mean = np.mean(number)
print("mean is: ", my_mean)

my_var = np.var(number)
print("variance is: ", my_var)

stnd_dev = np.std(number)
print("standard deviation is: ", stnd_dev)
