Let’s see how to calculate arithmetic mean in Python.

The mean is a measure of central tendency that is calculated by adding all the values in a set and then dividing by the number of values. In Python, you can calculate the mean using the mean() function from the statistics module.

## How to calculate mean in Python?

To calculate arithmetic average we need to import statistics module.

Luckily there is dedicated function in statistics module to calculate arithmetic mean.

import statistics as s x = [1, 5, 7, 8, 43, 6] mean = s.mean(x) print("Mean equals: " + str(round(mean, 2))) s.mean(x)

## Other ways to calculate mean in Python

In addition to the mean() function from the statistics module, there are also a few other ways to calculate the mean in Python.

One way is to use the sum() and len() functions. The sum() function adds all the values in a list, and the len() function returns the number of values in a list. So, you can calculate the mean by dividing the sum of the values in a list by the number of values in the list.

numbers = [1, 5, 7, 8, 43, 6] mean = sum(numbers) / len(numbers) print("The mean is:", mean)

This code will print the same output as the previous code, which is 12.7.

Another way to calculate the mean in Python is to use the for loop. The for loop iterates over a list, and each time it iterates, it adds the current value to a variable. At the end of the loop, the variable will contain the sum of all the values in the list. You can then divide this sum by the number of values in the list to get the mean.

numbers = [1, 5, 7, 8, 43, 6] sum = 0 for number in numbers: sum += number mean = sum / len(numbers) print("The mean is:", mean)

This code will also print the same output as the previous code, which is 12.7.

Which method you use to calculate the mean in Python is up to you. The mean() function from the statistics module is the most concise way to do it, but the other methods are also valid.

## Applications of mean in Python

The mean is a very versatile measure of central tendency, and it can be used in a variety of applications in Python.

One common application of the mean is to calculate the average of a series of numbers. For example, you could use the mean to calculate the average temperature for a week, the average score on a test, or the average sales for a month.

The mean can also be used to compare two or more groups of data. For example, you could use the mean to compare the average income of men and women, the average test scores of students from different schools, or the average sales of different products.

In addition, the mean can be used to identify outliers in a dataset. An outlier is a data point that is significantly different from the rest of the data points in a dataset. Outliers can be caused by errors in data entry or by unusual circumstances. The mean can be used to identify outliers by calculating the distance between each data point and the mean. Data points that are far away from the mean are likely to be outliers.

The mean is a powerful tool that can be used to analyze data in Python. It is a versatile measure of central tendency that can be used in a variety of applications.