CODE EXAMPLE FOR PYTHON

np.mean

import numpy as np

import numpy as np

array1D = np.array([1,2,3,4,5])

print(f'Axis = -1 --> {array1D.mean(axis=-1)}')
print(f'Axis = 0  --> {array1D.mean(axis=0)}')

#### Output ####
Axis = -1 --> 3.0
Axis = 0  --> 3.0


array2D = np.array([[14, 17, 12, 33, 44],  
                     [15, 6, 27, 8, 19], 
                     [23, 2, 54, 1, 4]] )

print(f'Axis = -1 {array2D.mean(axis=-1)}')
print(f'Axis = 0 {array2D.mean(axis=0)}')
print(f'Axis = 1 {array2D.mean(axis=1)}')

#### Output ####
Axis = -1 [24.  15.  16.8]
Axis = 0 [17.33333333  8.33333333 31.         14.         22.33333333]
Axis = 1 [24.  15.  16.8]

# Online Python compiler (interpreter) to run Python online.
# Write Python 3 code in this online editor and run it.
import numpy as np

array3D = np.array([[[1, 2, 3, 4, 5],  
                     [1, 2, 3, 4, 5], 
                     [1, 2, 3, 4, 5]],
                     [[1, 2, 3, 4, 5],  
                     [1, 2, 3, 4, 5], 
                     [1, 2, 3, 4, 5]]])

print(f'Axis = -1 --> {array3D.mean(axis=-1)}')
print(f'Axis = 0  --> {array3D.mean(axis=0)}')
print(f'Axis = 1  --> {array3D.mean(axis=1)}')
print(f'Axis = 2  --> {array3D.mean(axis=2)}')

#### Output ####
Axis = -1 --> [[3. 3. 3.]
              [3. 3. 3.]]
            
Axis = 0  --> [[1. 2. 3. 4. 5.]
               [1. 2. 3. 4. 5.]
               [1. 2. 3. 4. 5.]]
               
Axis = 1  --> [[1. 2. 3. 4. 5.]
              [1. 2. 3. 4. 5.]]
              
Axis = 2  --> [[3. 3. 3.]
              [3. 3. 3.]]