In the section below, you’ll see 3 ways to calculate the Geometric Mean in Python.

For each of the methods to be reviewed, the goal is to derive the Geometric Mean, given the following values:

**8, 16, 22, 12, 41**

### Method 1: Simple Calculations to get the Geometric Mean

To start, you can use the following calculations to get the Geometric Mean:

multiply_values = 8*16*22*12*41 n = 5 geometric_mean = multiply_values**(1/n) print("The Geometric Mean is: " + str(geometric_mean))

Where:

**multiply_values**represents the multiplication of all the values in the dataset**n****geometric_mean****= multiply_values**(1/n)**is the actual calculation to derive the geometric mean

Run the code in Python, and you’ll get the following result: **16.9168**

### Method 2: Using a List to Derive the Geometric Mean in Python

Alternatively, you can place all the values in a *List,* where each value should be separated by a comma:

values = [8, 16, 22, 12, 41] n = len(values) multiply = 1 for i in values: multiply = multiply * i geometric_mean = multiply**(1/n) print("The Geometric Mean is: " + str(geometric_mean))

Once you run the code in Python, you’ll get the same result: **16.9168**

### Method 3: Using Pandas and Scipy

You could also use the Pandas and Scipy packages to obtain the Geometric Mean:

import pandas as pd from scipy.stats.mstats import gmean data = {"values": [8, 16, 22, 12, 41]} df = pd.DataFrame(data) geometric_mean = gmean(df.loc[:,"values"]) print("The Geometric Mean is: " + str(geometric_mean))

As before, you’ll get the same Geometric Mean: **16.9168**