Problem: Given a list of lists representing a data matrix with n rows and m columns. How to sum over the columns of this matrix? In this article, you’re going to learn different ways to accomplish this in Python.
Let’s ensure that you’re on the same page. Here’s a graphical representation of the list of lists and what you want to achieve:
Example: Given the following code.
# Your list of lists
data = [[1, 2, 3],
[4, 5, 6],
[7, 8, 9]]
# ... Algorithm here ...
print(res)
# OUTPUT: [12, 15, 18]Background: To learn more about list of lists, check out our reference article on the Finxter blog.
Next, you’ll learn three different methods to sum over the columns. Let’s get a quick overview of all three methods—click “Run” to execute the code and see what happens!
Table of Contents
Method 1: Sum 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 = [[1, 2, 3],
[4, 5, 6],
[7, 8, 9]]
# Method 1: Pure Python
res = [sum(x) for x in zip(*data)]
print(res)
# [12, 15, 18]Do you love Python one-liners? I do for sure—I’ve even written a whole book about it with San Francisco Publisher NoStarch. Click to check out the book in a new tab:
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: Sum with NumPy Library
You create a NumPy array out of the data and pass it to the np.sum() function.
data = [[1, 2, 3],
[4, 5, 6],
[7, 8, 9]]
# Method 2: NumPy
import numpy as np
a = np.array(data)
res = np.sum(a, axis=0)
print(res)
# [12 15 18]
The axis argument of the sum function defines along which axis you want to calculate the sum value. If you want to sum over columns, use axis=0. If you want to sum over rows, use axis=1. If you want to sum over all values, skip this argument.
Method 3: Sum() + 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 = [[1, 2, 3],
[4, 5, 6],
[7, 8, 9]]
# Method 3: Map()
res = map(sum, zip(*data))
print(list(res))
# [12, 15, 18]
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.
Related articles:
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While working as a researcher in distributed systems, Dr. Christian Mayer found his love for teaching computer science students.
To help students reach higher levels of Python success, he founded the programming education website Finxter.com. He’s author of the popular programming book Python One-Liners (NoStarch 2020), coauthor of the Coffee Break Python series of self-published books, computer science enthusiast, freelancer, and owner of one of the top 10 largest Python blogs worldwide.
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