Python statistics mean() Function

The Pythonstatistics.mean() function calculates the mean of the given data set. Data set is passed as a parameter where this can be used to calculate the average of a given list.

Mean is commonly called as the average sum of the arithmetic mean that is divided by the number of data points.

If this function contains empty dataset then statisticsError will be raised.

Syntax

Following is the basic syntax of thestatistics.mean() function −

statistics.mean(data)

Parameters

Here, the data values can be used as any sequence, list or iterator.

Return Value

This function returns the arithmetic mean of data which can be a sequence or iterator.

Example 1

In the below example we are calculating the average of the given data usingstatistics.mean function.

import statisticsprint(statistics.mean([5, 10, 15, 20, 25]))print(statistics.mean([-11, 4.8, -2, 23]))

Output

The output obtained is as follows −

153.7

Example 2

Here, we are importing fractions to find the mean of the given data usingstatistics.mean() function.

import statisticsfrom fractions import Fraction as Fx = statistics.mean([F(3, 7), F(1, 21), F(5, 3), F(1, 3)])print(x)

Output

When we run the above code we will get the following output −

13/21

Example 3

Now, we are passing decimal values to find the mean of the given data usingstatistics.mean() function.

import statisticsfrom decimal import Decimal as Dx = statistics.mean([D("0.5"), D("0.75"), D("0.625"), D("0.375")])print(x)

Output

The result is obtained as follows −

0.5625

Example 4

If we don't pass any data point as a parameter to this function, then it will throwStatisticsError as shown in the below example.

import statistics# creating an empty population setpop = ()# will raise StatisticsErrorprint(statistics.pvariance(pop))

Output

While executing the above code we will get the following error −

Traceback (most recent call last):  File "/home/cg/root/50576/main.py", line 7, in <module>    print(statistics.pvariance(pop))  File "/usr/lib/python3.10/statistics.py", line 811, in pvariance    raise StatisticsError('pvariance requires at least one data point')statistics.StatisticsError: pvariance requires at least one data point