Python | Standard deviation of list

Sometimes, while working with Mathematics, we can have a problem in which we intend to compute the standard deviation of a sample. This has many applications in competitive programming as well as school level projects. Let’s discuss certain ways in which this task can be performed. 
Method #1 : Using sum() + list comprehension This is a brute force shorthand to perform this particular task. We can approach this problem in sections, computing mean, variance and standard deviation as square root of variance. The sum() is key to compute mean and variance. List comprehension is used to extend the common functionality to each of element of list. 

The original list : [4, 5, 8, 9, 10]
Standard deviation of sample is : 2.3151673805580453

Time Complexity: O(n) where n is the number of elements in the list “test_list”. sum() + list comprehension performs n number of operations.
Auxiliary Space: O(1), constant extra space is required 

Method #2 : Using pstdev() This task can also be performed using inbuilt functionality of pstdev(). This function computes standard deviation of sample internally. 

The original list : [4, 5, 8, 9, 10]
Standard deviation of sample is : 2.3151673805580453

Method #3 : Using numpy library

Note: Install numpy module using command “pip install numpy”

Another approach to calculate the standard deviation of a list is by using the numpy library. The numpy library provides a function called std() which can be used to calculate the standard deviation of a list.

Output:

2.3151673805580453