Calculating the average of a list of numbers is a common task in various programming scenarios, including data analysis, graph plotting, and estimation. In this tutorial, we will be learning how to take the average of a list in **Python**.

Python is a powerful and easy-to-learn programming language, which makes it an excellent choice for this task.

### Step 1: Create a List of Numbers

First, let’s create a list of numbers that we want to find the average of. In this example, we will create a simple list of integers called `numbers`

.

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numbers = [1, 2, 3, 4, 5] |

### Step 2: Use the built-in sum() and len() functions in Python

Python has built-in functions `sum()`

and `len()`

which can be used to calculate the sum and length of a list, respectively. You can find the average by dividing the sum by the length of the list as follows:

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average = sum(numbers) / len(numbers) print(average) |

The `sum(numbers)`

function returns the total sum of all the elements in the list, while the `len(numbers)`

function returns the length of the list (i.e., the number of elements). By dividing these two values, we get the average.

### Step 3: Alternative method using the statistics module

Python comes with a built-in module called **statistics** that provides various statistical functions like mean, median, mode, and more. One such function is `mean()`

, which directly calculates the average of any iterable. Here is how to use it:

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

Here, the `statistics.mean()`

function calculates the average and returns the result.

## Full Code

Here is the complete code for both methods:

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import statistics numbers = [1, 2, 3, 4, 5] average = sum(numbers) / len(numbers) print(average) numbers = [1, 2, 3, 4, 5] average = statistics.mean(numbers) print(average) |

## Output:

3.0 3

## Conclusion

In this tutorial, we learned how to calculate the average of a list in Python using two different methods. The first method uses built-in Python functions `sum()`

and `len()`

. The second method uses the `statistics.mean()`

function from the built-in statistics module. Both methods produce the desired result, and you can choose the one that best fits your requirements.