# Python mean function of statistics

## How do you use mean in Python?

Here’s an example:

```
import statistics
numbers = [1, 2, 3, 4, 5]
mean = statistics.mean(numbers)
print(mean)
```

This will output: `3.0`

.

If you don’t have the statistics module available, you can also manually calculate the mean by summing up the numbers and dividing by the count of the numbers.

Here’s an example:

```
numbers = [1, 2, 3, 4, 5]
mean = sum(numbers) / len(numbers)
print(mean)
```

This will also output: `3.0`

.

In this example, we first created a list of numbers `[1, 2, 3, 4, 5]`

, and then calculated the mean by using either the `statistics.mean`

method or by manually summing up the numbers and dividing by the length of the list.

## where do use python mean function in real time

The mean is a commonly used statistical measure that has many real-world applications. Here are a few examples:

Data analysis: In data analysis, mean is often used to summarize a set of numbers and describe their central tendency. For example, you can calculate the mean of a set of sales data to get an idea of the average sales for a particular product.

Budgeting: In budgeting, mean is often used to calculate the average income or expenses for a given time period. This information can be used to make informed financial decisions.

Quality control: In quality control, mean is often used to monitor the performance of a process. For example, you can calculate the mean of a set of measurements to ensure that a process is producing consistent results.

Education: In education, mean is often used to calculate the average grade of a student. This information can be used to evaluate student performance and make decisions about grades, scholarships, and admission to programs.

Finance: In finance, mean is used in many areas such as calculating the average return on investment, or to determine the average stock price for a particular company.

These are just a few examples, but the mean is a versatile measure that can be used in a wide range of fields and applications.