scipy.stats.moment(array, axis=0) function calculates the nth moment about the mean for a sample i.e. array elements along the specified axis of the array (list in python).
Its formula –
Parameters :
array : Input array or object having the elements to calculate the moment.
axis : Axis along which the moment is to be computed. By default axis = 0.
moment : Order of central moment that is returned.Returns : n-th central moment of the array elements based on the set parameters.
Code #1:
# Moment from scipy import stats import numpy as np arr1 = np.array([[1, 31, 27, 13, 21, 9], [8, 12, 8, 4, 7, 10]]) print("Oth moment : \n", stats.moment(arr1, moment = 0)) |
Output :
Oth moment : [1. 1. 1. 1. 1. 1.]
Code #2: With multi-dimensional data
# Moment from scipy import stats import numpy as np arr1 = [[1, 3, 27], [3, 4, 6], [7, 6, 3], [3, 6, 8]] print("Oth moment : \n", stats.moment(arr1, moment = 0)) print("\n6th moment : \n", stats.moment(arr1, moment = 6)) print("\n9th moment : \n", stats.moment(arr1, moment = 9, axis = None)) print("\n12th moment : \n", stats.moment(arr1, moment = 12, axis = 1)) print("\n10th moment : \n", stats.moment(arr1, moment = 10, axis = 1)) |
Output :
Oth moment : [1. 1. 1.] 6th moment : [5.20609375e+02 9.13256836e+00 4.26392850e+06] 9th moment : 55265909588.26437 12th moment : [1.53284936e+14 1.63654317e+02 8.83474172e+03 5.17842143e+04] 10th moment : [5.53094361e+11 6.10464868e+01 1.64971407e+03 7.65588508e+03]
