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

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

Introduction

Statistics is a very useful module in Python that provides functions to calculate mathematical statistics of numeric data.

Statistics 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()

Harmonic mean

To calculate the harmonic mean, we first find the sum of the reciprocals of all the observations, and then divide the total number of observations by that sum.

If a list of numbers contains a,b,c, then:

Harmonic mean = 31/a+1/b+1/c\frac{3}{1/a + 1/b + 1/c}

For example, let the list of numbers be 1, 4, and 4. Their harmonic mean is:

31/a+1/b+1/c\frac{3}{1/a + 1/b + 1/c} = 31.5\frac{3}{1.5} = 2

Code

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

import statistics
data = [1, 4, 4]
result = statistics.harmonic_mean(data)
print(result)

Explanation

  • In line 1, we import the statistics module to call harmonic_mean().

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

  • In line 3, we compute the harmonic mean of the provided numbers.

  • In line 4, we print the output that is stored in the result.

Note:

  • Module_name.function_name is the syntax for calling any function inside a module.

The statistics.harmonic_mean() function comes in handy when we want to compute the central location of the dataset.

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