Find Mean of a List of Numpy Array in Python

Numpy is a very powerful python library for numerical data processing. It mostly takes in the data in form of arrays and applies various functions including statistical functions to get the result out of the array. In this article we will see how to get the mean value of a given array.

with mean

The mean function can take in an array and give the mathematical mean value of all the elements in it. So we design a for loop to keep track of the length of the input and go through each array calculating its mean.

Example

 Live Demo

import numpy as np

# GIven Array
Arrays_In = [np.array([11, 5, 41]),
         np.array([12, 13, 26]),
         np.array([56, 20, 51])]

# Resultihg Array
Arrays_res = []

# With np.mean()
for x in range(len(Arrays_In)):
   Arrays_res.append(np.mean(Arrays_In[x]))

# Result
print("The means of the arrays: \n",Arrays_res)

Output

Running the above code gives us the following result −

The means of the arrays:
[19.0, 17.0, 42.333333333333336]

with Average

It is a very similar approach as above except that we use the average function instead of mean function. It gives the exact same result.

Example

 Live Demo

import numpy as np

# GIven Array
Arrays_In = [np.array([11, 5, 41]),
         np.array([12, 13, 26]),
         np.array([56, 20, 51])]

# Resultihg Array
Arrays_res = []

# With np.average()
for x in range(len(Arrays_In)):
   Arrays_res.append(np.average(Arrays_In[x]))

# Result
print("The means of the arrays: \n",Arrays_res)

Output

Running the above code gives us the following result −

The means of the arrays:
[19.0, 17.0, 42.333333333333336]