Find average of a list in python

Python | Find Mean of a List of Numpy Array

Last Updated : 14 Mar, 2019

Given a list of Numpy array, the task is to find mean of every numpy array. Let's see a few methods we can do the task. Method #1: Using np.mean()

Python3 1==

# Python code to find mean of every numpy array in list

# Importing module
import numpy as np

# List Initialization
Input = [np.array([1, 2, 3]),
         np.array([4, 5, 6]),
         np.array([7, 8, 9])]

# Output list initialization
Output = []

# using np.mean()
for i in range(len(Input)):
   Output.append(np.mean(Input[i]))

# Printing output
print(Output)

Output:

[2.0, 5.0, 8.0]

Method #2: Using np.average()

Python3 1==

# Python code to find mean of 
# every numpy array in list

# Importing module
import numpy as np

# List Initialization
Input = [np.array([11, 12, 13]),
         np.array([14, 15, 16]),
         np.array([17, 18, 19])]

# Output list initialization
Output = []

# using np.mean()
for i in range(len(Input)):
   Output.append(np.average(Input[i]))

# Printing output
print(Output)

Output:

[12.0, 15.0, 18.0]

Find average of a list in python

everythingispossible

Improve

Article Tags :

Practice Tags :

python

Similar Reads

Find the memory size of a NumPy array

In this post, we will see how to find the memory size of a NumPy array. So for finding the memory size of a NumPy array we are using following methods: Using size and itemsize attributes of NumPy array size: This attribute gives the number of elements present in the NumPy array. itemsize: This attri

Find average of a list in python

We are given a list of numbers and the task is to find the average (or mean) value of its elements. For example, if we have a list nums = [10, 20, 30, 40], the sum of the elements is 10 + 20 + 30 + 40, which equals 100. The number of elements in the list is 4. So, the average is calculated as 100 /

Describe a NumPy Array in Python

NumPy is a Python library used for numerical computing. It offers robust multidimensional arrays as a Python object along with a variety of mathematical functions. In this article, we will go through all the essential NumPy functions used in the descriptive analysis of an array. Let's start by initi

NumPy Array in Python

NumPy (Numerical Python) is a powerful library for numerical computations in Python. It is commonly referred to multidimensional container that holds the same data type. It is the core data structure of the NumPy library and is optimized for numerical and scientific computation in Python. Table of C

Python Lists VS Numpy Arrays

Here, we will understand the difference between Python List and Python Numpy array. What is a Numpy array?NumPy is the fundamental package for scientific computing in Python. Numpy arrays facilitate advanced mathematical and other types of operations on large numbers of data. Typically, such operati

numpy.mean() in Python

numpy.mean(arr, axis = None) : Compute the arithmetic mean (average) of the given data (array elements) along the specified axis. Parameters : arr : [array_like]input array. axis : [int or tuples of int]axis along which we want to calculate the arithmetic mean. Otherwise, it will consider arr to be

Convert Python List to numpy Arrays

NumPy arrays are more efficient than Python lists, especially for numerical operations on large datasets. NumPy provides two methods for converting a list into an array using numpy.array() and numpy.asarray(). In this article, we'll explore these two methods with examples for converting a list into

Find Average of a Number Digits in Python

AIn this article, we will see how to find the average of the digits of a number in Python. Examples: Input: N = 642 Output: 4.0 Explanation: (6+4+2)/3 = 12/3 = 4.0 Input: N = 3504 Output: 3.0 Explanation: (3+5+0+4)/4 = 12/4 = 3.0Calculate the average of a number of digits in python if the number is

How to normalize an array in NumPy in Python?

In this article, we are going to discuss how to normalize 1D and 2D arrays in Python using NumPy. Normalization refers to scaling values of an array to the desired range.Â Normalization of 1D-Array Suppose, we have an array = [1,2,3] and to normalize it in range [0,1] means that it will convert arra

numpy.median() in Python

numpy.median(arr, axis = None) : Compute the median of the given data (array elements) along the specified axis. How to calculate median? Given data points. Arrange them in ascending order Median = middle term if total no. of terms are odd. Median = Average of the terms in the middle (if total no. o