# Geometric Mean in Python (Example)

This tutorial illustrates how to compute the geometric mean in Python programming.

The post consists of this information:

Let’s do this!

## Example Data & Add-On Libraries

I’ll use the data below as a basis for this Python tutorial:

my_list = [4, 3, 8, 7, 8, 4, 4, 1, 5] # Create example list print(my_list) # Print example list # [4, 3, 8, 7, 8, 4, 4, 1, 5] |

my_list = [4, 3, 8, 7, 8, 4, 4, 1, 5] # Create example list print(my_list) # Print example list # [4, 3, 8, 7, 8, 4, 4, 1, 5]

The previous output of the Python console shows that our example data is a list object containing nine integers.

## Example: Get Geometric Mean Using gmean() Function of SciPy Library

In this example, I’ll demonstrate how to calculate the geometric mean of a list in Python.

For this task, we first have to import the gmean function of the SciPy library:

from scipy.stats import gmean # Import gmean function of SciPy library |

from scipy.stats import gmean # Import gmean function of SciPy library

In the next step, we can apply the gmean function to our example list to get the geometric mean:

print(gmean(my_list)) # Apply gmean function # 4.226198741306655 |

print(gmean(my_list)) # Apply gmean function # 4.226198741306655

As you can see, the geometric mean of the numbers in our list is 4.22.

## Video & Further Resources

Have a look at the following video which I have published on my YouTube channel. In the video, I’m explaining the Python programming code of this tutorial in the Python programming language:

*The YouTube video will be added soon.*

Furthermore, you might want to read the related articles on this website.

- Calculate Mean in Python
- Harmonic Mean in Python
- Mean of Columns & Rows of pandas DataFrame
- Calculate Mean by Group in Python
- mean() Function of NumPy Library
- mean() Function of statistics Module in Python
- Introduction to Python

You have learned in this tutorial how to **find the geometric mean** in Python. Don’t hesitate to let me know in the comments below, in case you have any additional questions.