Here is the program:

# Programmer: Johnny L. Hopkins

# Date: April 20, 2021

# mean.py: Computing the aritmetic mean without using libraries

# We will use matplotlib for basic visualizations based on the mean

import matplotlib.pyplot as plt

# We need sample data to calculate the mean

# We do this by declaring a new list

list_values = {80, 75, 93, 88, 99, 100, 80}

# We will now build the equation for the mean by using

# sum(), which takes the iterables in our list and sum over the

# elements. To count the elements we will use len(). We can combine

# the sum() and len() to build the equation for the mean. We declare a

# new variable to store the value of the mean.

values_mean = sum(list_values) / len(list_values)

# We now will print out the mean to the standard output:

print("The mean is: ", values_mean)

# Finally, we will graph a histogram to see the distribution of values

# To output the histogram, we have to specify the list as the values

# to be graphed. If we don't specify a variable, an error is returned to

# standard output

plt.hist(list_values, density = 1)

plt.show()

Here is the output:

Windows PowerShell

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PS C:\Users\hopki> & python c:/Users/hopki/OneDrive/Documents/mean.py

The mean is: 89.16666666666667

PS C:\Users\hopki>

This comes directly from Visual Studio Code.

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