Compute the mean, standard deviation, and variance of a given NumPy array

 In NumPy, we can compute the mean, standard deviation, and variance of a given array along the second axis by two approaches first is by using inbuilt functions and second is by the formulas of the mean, standard deviation, and variance.

Method 1: Using numpy.mean(), numpy.std(), numpy.var()

Output:

[0 1 2 3 4 5 6 7 8 9]

Mean: 4.5

std: 2.8722813232690143

variance: 8.25

Method 2: Using the formulas 

Output:

[0 1 2 3 4 5 6 7 8 9]

Mean: 4.5

std: 2.8722813232690143

variance: 8.25

Example: Comparing both inbuilt methods and formulas

Output:

[0 1 2 3 4]

Mean: 2.0 2.0

std: 1.4142135623730951 1.4142135623730951

variance: 2.0 2.0