How to Average a List of Lists in Python?

Problem: You have a list of lists and you want to calculate the average of the different columns.

Example: Given the following list of lists with four rows and three columns.

data = [[0, 1, 0],
        [1, 1, 1],
        [0, 0, 0],
        [1, 1, 0]]

You want to have the average values of the three columns:

[average_col_1, average_col_2, average_col_3]

There are three methods that solve this problem. You can play with them in the interactive shell and read more details below:

Method 1: Average in Python (No Library)

A simple one-liner with list comprehension in combination with the zip() function on the unpacked list to transpose the list of lists does the job in Python.

data = [[0, 1, 0],
        [1, 1, 1],
        [0, 0, 0],
        [1, 1, 0]]


# Method 1: Pure Python
res = [sum(x) / len(x) for x in zip(*data)]
print(res)
# [0.5, 0.75, 0.25]

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You can visualize the code execution and memory objects of this code in the following tool (just click “Next” to see how one step of the code unfolds).

Method 2: Average with NumPy Library

You create a NumPy array out of the data and pass it to the np.average() function.

data = [[0, 1, 0],
        [1, 1, 1],
        [0, 0, 0],
        [1, 1, 0]]

# Method 2: NumPy
import numpy as np
a = np.array(data)
res = np.average(a, axis=0)
print(res)
# [0.5  0.75 0.25]

The axis argument of the average function defines along which axis you want to calculate the average value. If you want to average columns, define axis=0. If you want to average rows, define axis=1. If you want to average over all values, skip this argument.

Method 3: Mean Statistics Library + Map()

Just to show you another alternative, here’s one using the map() function and our zip(*data) trick to transpose the “matrix” data.

data = [[0, 1, 0],
        [1, 1, 1],
        [0, 0, 0],
        [1, 1, 0]]

# Method 3: Statistics + Map()
import statistics
res = map(statistics.mean, zip(*data))
print(list(res))
# [0.5, 0.75, 0.25]

The map(function, iterable) function applies function to each element in iterable. As an alternative, you can also use list comprehension as shown in method 1 in this tutorial. In fact, Guido van Rossum, the creator of Python and Python’s benevolent dictator for life (BDFL), prefers list comprehension over the map() function.

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