How Can I Efficiently Calculate the Average of a List in Python?

Calculating the Average of a List in Python

Determining the arithmetic mean or average of a list is essential for statistical analysis. In Python, several methods are available for this operation. Here's a detailed exploration of each method:

• Python >= 3.8: statistics.fmean

  The statistics module provides numerical stability with floats, ensuring accurate results. It's the preferred method in Python 3.8 and later.

  import statistics
  xs = [15, 18, 2, 36, 12, 78, 5, 6, 9]
  statistics.fmean(xs)  # = 20.11111111111111

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• Python >= 3.4: statistics.mean

  While still providing numerical stability with floats, statistics.mean is slower than fmean. It remains a viable option for Python 3.4 and later.

  import statistics
  xs = [15, 18, 2, 36, 12, 78, 5, 6, 9]
  statistics.mean(xs)  # = 20.11111111111111

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• Earlier Python 3 Versions: sum(xs) / len(xs)

  This method computes the average using the sum of the elements divided by the length of the list. However, it can result in numerical instability with floats.

  xs = [15, 18, 2, 36, 12, 78, 5, 6, 9]
  sum(xs) / len(xs)  # = 20.11111111111111

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• Python 2:

  For Python 2, it's necessary to convert len to a float to obtain float division and prevent integer division:

  xs = [15, 18, 2, 36, 12, 78, 5, 6, 9]
  sum(xs) / float(len(xs))  # = 20.11111111111111

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By selecting the appropriate method based on your Python version, you can efficiently calculate the exact average of a list in Python.

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