How Do I Efficiently Calculate the Mean of a List in Python?

Calculating the Mean of a List in Python

Determining the average of a list involves finding the arithmetic mean, which is the sum of all values divided by the number of values in the list. In Python, there are multiple approaches to achieving this.

Python 3.8

For the greatest numerical stability when working with floating-point values, Python 3.8 provides the statistics.fmean function. It handles floating-point imprecisions effectively, offering faster execution speeds.

Python 3.4

In Python versions 3.4 and higher, the statistics.mean function delivers numerical stability with floats. While not as fast as statistics.fmean, it is still suitable for calculating averages.

Example:

import statistics

xs = [15, 18, 2, 36, 12, 78, 5, 6, 9]

print(statistics.fmean(xs))  # Output: 20.11111111111111

Python 2

For Python 2 users, the following formula can be used to calculate the mean:

sum(xs) / float(len(xs))

In this case, it is crucial to cast len(xs) as a float to ensure that the division results in a floating-point number.

By applying the appropriate method based on your Python version and the nature of your data, you can effectively calculate the average of a list in Python.

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