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Calculate mean across dimension in a 2D array

Learn, how to calculate mean across dimension in a 2D array in Python? By Pranit Sharma Last updated : October 09, 2023

NumPy is an abbreviated form of Numerical Python. It is used for different types of scientific operations in python. Numpy is a vast library in python which is used for almost every kind of scientific or mathematical operation. It is itself an array which is a collection of various methods and functions for processing the arrays.

Mean

Mean is nothing but an average value of a series of a number. Mathematically, the mean can be calculated as:

Here, x̄ is the mean, ∑x is the summation of all the values and n is the total number of values/elements.

Problem statement

Suppose we have a series of numbers from 1 to 10, then the average of this series will be:

∑x = 1+2+3+4+5+6+7+8+9+10
∑x = 55
n = 10
x̄ = 55/10
x̄ = 5.5

Calculating mean across dimension in a 2D array

Numpy provides a method called arr.mean() which will take an argument called axis=1 or axis=0 to calculate mean across column or row respectively.

Let us understand with the help of an example,

Python program to calculate mean across dimension in a 2D array

# Import numpy
import numpy as np

# Creating an array
arr = np.array([[4, 10], [40, 21]])

# Display original array
print("Original Array:\n",arr,"\n")

# Calculating mean
res = arr.mean(axis=1)

# Display result
print("Result:\n",res,"\n")

Output

The output of the above program is:

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