scipy.stats.nanmean(array, axis=0) function calculates the arithmetic mean 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 arithmetic mean.
axis : Axis along which the mean is to be computed. By default axis = 0.Returns : Arithmetic mean of the array elements (ignoring the Nan values) based on the set parameters.
Code #1:
# Arithmetic Mean import scipy import numpy as np arr1 = [1, 3, np.nan, 27] print("Arithmetic Mean using nanmean :", scipy.nanmean(arr1)) print("Arithmetic Mean without handling nan value :", scipy.mean(arr1)) |
Output :
Arithmetic Mean using nanmean : 10.333333333333334 Arithmetic Mean without handling nan value : nan
Code #2: With multi-dimensional data
# Arithmetic Mean from scipy import mean from scipy import nanmean import numpy as np arr1 = [[1, 3, 27], [3, np.nan, 6], [np.nan, 6, 3], [3, 6, np.nan]] print("Arithmetic Mean is :", mean(arr1)) print("Arithmetic Mean handling nan :", nanmean(arr1)) # using axis = 0 print("\nArithmetic Mean is with default axis = 0 : \n", mean(arr1, axis = 0)) print("\nArithmetic Mean handling nan with default axis = 0 : \n", nanmean(arr1, axis = 0)) # using axis = 1 print("\nArithmetic Mean is with default axis = 1 : \n", mean(arr1, axis = 1)) print("\nArithmetic Mean handling nan with default axis = 1 : \n", nanmean(arr1, axis = 1)) |
Output :
Arithmetic Mean is : nan Arithmetic Mean handling nan : 6.444444444444445 Arithmetic Mean is with default axis =0 : [nan nan nan] Arithmetic Mean handling nan with default axis =0 : [ 2.33333333 5. 12. ] Arithmetic Mean is with default axis =1 : [10.33333333 nan nan nan] Arithmetic Mean handling nan with default axis =1 : [10.33333333 4.5 4.5 4.5 ]
