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!
Method 1: Sum in Python (No Library)
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]
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
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]
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 = [[1, 2, 3], [4, 5, 6], [7, 8, 9]] # Method 3: Map() res = map(sum, zip(*data)) print(list(res)) # [12, 15, 18]
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
Where to Go From Here?
Enough theory, let’s get some practice!
To become successful in coding, you need to get out there and solve real problems for real people. That’s how you can become a six-figure earner easily. And that’s how you polish the skills you really need in practice. After all, what’s the use of learning theory that nobody ever needs?
Practice projects is how you sharpen your saw in coding!
Do you want to become a code master by focusing on practical code projects that actually earn you money and solve problems for people?
Then become a Python freelance developer! It’s the best way of approaching the task of improving your Python skills—even if you are a complete beginner.
Join my free webinar “How to Build Your High-Income Skill Python” and watch how I grew my coding business online and how you can, too—from the comfort of your own home.
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.
His passions are writing, reading, and coding. But his greatest passion is to serve aspiring coders through Finxter and help them to boost their skills. You can join his free email academy here.