Numpy MaskedArray.average () Function | python

NumPy | Python Methods and Functions

numpy.MaskedArray.average() is used to return the weighted average of an array along a given axis.

Syntax: numpy.ma.average (arr, axis = None, weights = None, returned = False)

Parameters:

arr: [array_like] Input masked array whose data to be averaged. Masked entries are not taken into account in the computation.
axis: [int, optional] Axis along which to average arr. If None, averaging is done over the flattened array.
weights: [array_like, optional] The importance that each element has in the computation of the average. If weights = None, then all data in arr are assumed to have a weight equal to one. If weights is complex, the imaginary parts are ignored.
returned: [bool, optional] It indicates whether a tuple (result, sum of weights) should be returned as output (True), or just the result (False). Default is False.

Return: [scalar or MaskedArray] The average along the specified axis. When returned is True, return a tuple with the average as the first element and the sum of the weights as the second element.

Code # 1:

# Python program explaining
# numpy.MaskedArray.average () method

 
# import numy as a geek
# and the numpy.ma module as ma

import numpy as geek 

import numpy.ma as ma 

 
# create input array

in_arr = geek.array ([[ 1 , 2 ], [ 3 , - 1 ], [ 5 , - 3 ]])

print ( "Input array:" , in_arr) 

 
# Now we create a masked array.
# making an entry invalid.

mask_arr = ma.masked_array (in_arr, mask = [[[ 1 , ], [ 1 , 0 ], [ 0 , 0 ]]) 

print ( "Masked array:" , mask_arr) 

 
# apply MaskedArray.average
# methods of the masked array

out_arr = ma.average (mask_arr) 

print ( "normal average of masked array: " , out_arr) 

Output:

 Input array: [[1 2] [3 -1] [5 -3] ] Masked array: [[- 2] [- -1] [5 -3]] normal average of masked array: 0.75 

Code # 2:

# Python program explaining
# numpy.MaskedArray.average () method

 
# import numy as a geek
# and the numpy.ma module as ma

import numpy as geek 

import numpy.ma as ma 

 
# create input array

in_arr = geek.array ([[ 1 , ], [ 3 , - 1 ], [ 5 , - 3 ]])

print ( "Input array:" , in_arr) 

 
# We are now creating a masked array.
# invalidating the post.

mask_arr = ma.masked_array (in_arr, mask = [[ 1 , 0 ], [ 1 , 0 ], [ 0 , 0 ]]) 

print ( "Masked array:" , mask_arr) 

 
# apply MaskedArray.average
# masked array methods

out_arr = ma.average (mask_arr, weights = [[ 0 , 1 ], [ 0 , 2 ], [ 3 , 1 ]]) 

print ( "weighted average of masked array:" , out_arr) 

Output:

 Input array: [[1 2] [3 -1] [5 -3]] Masked array: [[- 2] [- -1] [5 -3]] weighted average of masked array: 1.7142857142857142 




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