sciPy stats.nanstd() function | Python

scipy.stats.nanstd(array, axis=0) function calculates the standard deviation by ignoring the Nan (not a number) values of the array elements along the specified axis of the array.

It’s formula –

Parameters :
array : Input array or object having the elements, including Nan values, to calculate the standard deviation.
axis : Axis along which the standard deviation is to be computed. By default axis = 0

Returns : Standard deviation of the array elements (ignoring the Nan values) based on the set parameters.

Code #1:

# standard deviation
import scipy
import numpy as np

arr1 = [1, 3, np.nan, 27]

print("standard deviation using nanstd :", scipy.nanstd(arr1))

print("standard deviation without handling nan value :", scipy.std(arr1))

Output :

standard deviation using nanstd : 11.813363431112899
standard deviation without handling nan value : nan

Code #2: With multi-dimensional data

# standard deviation
from scipy import std
from scipy import nanstd
import numpy as np

arr1 = [[1, 3, 27],
        [3, np.nan, 6],
        [np.nan, 6, 3],
        [3, 6, np.nan]]

print("standard deviation is :", std(arr1))
print("standard deviation handling nan :", nanstd(arr1))

# using axis = 0
print("\nstandard deviation is with default axis = 0 : \n",
      std(arr1, axis = 0))
print("\nstandard deviation handling nan with default axis = 0 : \n",
      nanstd(arr1, axis = 0))

# using axis = 1
print("\nstandard deviation is with default axis = 1 : \n",
      std(arr1, axis = 1))
print("\nstandard deviation handling nan with default axis = 1 : \n",
      nanstd(arr1, axis = 1))

Output :

standard deviation is : nan
standard deviation handling nan : 7.455216087651669

standard deviation is with default axis =0 : 
 [nan nan nan]

standard deviation handling nan with default axis =0 : 
 [ 0.94280904  1.41421356 10.67707825]

standard deviation is with default axis =1 : 
 [11.81336343         nan         nan         nan]

standard deviation handling nan with default axis =1 : 
 [11.81336343  1.5         1.5         1.5       ]