In this shot, we will discuss how to use the **`statistics.geometric_mean()`** function in Python.

#     
## Introduction
The **`statistics`** module in Python is an extremely useful module that provides functions to calculate mathematical statistics of numeric data. 

The `statistics` module supports both `int` and `float` type numeric data. Some of the functions in the `statistics` module in Python include:
* `mean()`
* `median()`
* `mode()`
* `geometric_mean()`
* `harmonic_mean()`


## Geometric mean
The **geometric mean** is referred to as the $n^{th}$ root of the product of $n$ numbers. Say we have a set of numbers, $x_1, x_2, x_3$, … $x_n$. The geometric mean is defined as:

$\prod_{i=1}^n$$x_{i}^{n}$ = $\sqrt[n]{x_1x_2x_3}$ 

For example, let the list of numbers be 54, 24, 36. Their geometric mean is $\sqrt[3]{54.24.36}$ = 36.

## Code

Let's take a look at the code snippet below.




import statistics
data = [54, 24, 36]
result = statistics.geometric_mean(data)
print(result)

#      
## Explanation

* *In line 1,* we import the `statistics` module to call `geometric_mean()`.

* *In line 2,* we provide a list of data whose geometric mean needs to be found.

* *In line 3,* we compute the geometric mean of the provided numbers. 

* *In line 4,* we print the output, which is stored in `result`.


> Note:
>* **`Module_name.function_name`** is the syntax for calling any function inside a module.
>* The output is not exactly 36 and has some floating points. This is because of the computational style of a machine. We can overcome this by using the **`round()`** function.


The `statistics.geometric_mean()` function comes in handy when we want to compute the central tendency of datasets.



What is the statistics.geometric_mean() function in Python?

Use `statistics.geometric_mean()` to compute the n-th root of the product of n numbers in Python.