# Mean, Variance And Standard Deviation Of Values Of Numpy.ndarray With Example

## Overview:

• The mean() function of numpy.ndarray calculates and returns the mean value along a given axis.

• Based on the axis specified the mean value is calculated.

• If no axis is specified, all the values of the n-dimensional array is considered while calculating the mean value.

• numpy.ndarray also provides methods var(), std() methods that calculates the variance and standard deviation along any given axis of a ndarray object.

## Example:

 import numpy as np   # Create a 3 dimensional ndarray nd_array = np.array([[[5,5,5,5],                      [6,6,6,6],                      [7,7,7,7]],                       [[8,8,8,8],                      [9,9,9,9],                      [9,9,9,9]],                                         [[10,10,10,10],                      [11,11,11,11],                      [12,12,12,12]]]                  ) print("Input Array:") print(nd_array)   print("Shape of the array:") print(nd_array.shape)   print("Dimensions of the array:") print(nd_array.ndim)   print("Mean of a numpy.ndarray object - No axis specified:") print(nd_array.mean())   print("Mean of a numpy.ndarray object  - Along axis 0:") print(nd_array.mean(axis=0))   print("Mean of a numpy.ndarray object  - Along axis 1:") print(nd_array.mean(axis=1))   print("Mean of a numpy.ndarray object  - Along axis 2:") print(nd_array.mean(axis=2))   print("Variance of a numpy.ndarray object - No axis specified:") print(nd_array.var())   print("Variance of a numpy.ndarray object  - Along axis 0:") print(nd_array.var(axis=0))   print("Variance of a numpy.ndarray object  - Along axis 1:") print(nd_array.var(axis=1))   print("Variance of a numpy.ndarray object  - Along axis 2:") print(nd_array.var(axis=2))   print("Standard deviation of a numpy.ndarray object - No axis specified:") print(nd_array.std())   print("Standard deviation of a numpy.ndarray object - Along axis 0:") print(nd_array.std(axis=0))   print("Standard deviation of a numpy.ndarray object - Along axis 1:") print(nd_array.std(axis=1))   print("Standard deviation of a numpy.ndarray object - Along axis 2:") print(nd_array.std(axis=2))

## Output:

 Input Array: [[[ 5  5  5  5]   [ 6  6  6  6]   [ 7  7  7  7]]    [[ 8  8  8  8]   [ 9  9  9  9]   [ 9  9  9  9]]    [[10 10 10 10]   [11 11 11 11]   [12 12 12 12]]] Shape of the array: (3, 3, 4) Dimensions of the array: 3 Mean of a numpy.ndarray object - No axis specified: 8.55555555556 Mean of a numpy.ndarray object  - Along axis 0: [[ 7.66666667  7.66666667  7.66666667  7.66666667]  [ 8.66666667  8.66666667  8.66666667  8.66666667]  [ 9.33333333  9.33333333  9.33333333  9.33333333]] Mean of a numpy.ndarray object  - Along axis 1: [[  6.           6.           6.           6.        ]  [  8.66666667   8.66666667   8.66666667   8.66666667]  [ 11.          11.          11.          11.        ]] Mean of a numpy.ndarray object  - Along axis 2: [[  5.   6.   7.]  [  8.   9.   9.]  [ 10.  11.  12.]] Variance of a numpy.ndarray object - No axis specified: 4.69135802469 Variance of a numpy.ndarray object  - Along axis 0: [[ 4.22222222  4.22222222  4.22222222  4.22222222]  [ 4.22222222  4.22222222  4.22222222  4.22222222]  [ 4.22222222  4.22222222  4.22222222  4.22222222]] Variance of a numpy.ndarray object  - Along axis 1: [[ 0.66666667  0.66666667  0.66666667  0.66666667]  [ 0.22222222  0.22222222  0.22222222  0.22222222]  [ 0.66666667  0.66666667  0.66666667  0.66666667]] Variance of a numpy.ndarray object  - Along axis 2: [[ 0.  0.  0.]  [ 0.  0.  0.]  [ 0.  0.  0.]] Standard deviation of a numpy.ndarray object - No axis specified: 2.16595429885 Standard deviation of a numpy.ndarray object - Along axis 0: [[ 2.05480467  2.05480467  2.05480467  2.05480467]  [ 2.05480467  2.05480467  2.05480467  2.05480467]  [ 2.05480467  2.05480467  2.05480467  2.05480467]] Standard deviation of a numpy.ndarray object - Along axis 1: [[ 0.81649658  0.81649658  0.81649658  0.81649658]  [ 0.47140452  0.47140452  0.47140452  0.47140452]  [ 0.81649658  0.81649658  0.81649658  0.81649658]] Standard deviation of a numpy.ndarray object - Along axis 2: [[ 0.  0.  0.]  [ 0.  0.  0.]  [ 0.  0.  0.]]