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 reflects the number of items in the dataset. Here we have 5 items
- 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