Pandas cut vs. qcut Explained Clearly (Finally)

Author(s): Bex T.

Originally published on Towards AI.

How to customarily bin data in Pandas
Photo by Karan Bhatia on Unsplash

“What the heck is this?”

That is the reaction beginners often get when they look at the output of some hard pandas function. It always baffles me how lots of tutorials and courses introduce such functions in a single sentence and move on to other topics in a heartbeat. Even if you read their documentation from top to bottom, it is gonna be more than a minute, guaranteed.

As a beginner, I was always so frustrated when I was in such situations. One time, while doing a nano degree at Udacity, I was learning about Matplotlib’s heatmaps. As you know, Matplotlib cannot create annotations for heatmaps automatically like Seaborn, so you had to create them by hand. To do that, you would useqcut or cut (which are the topic of this article) to bin your data into categories, and I was completely new to these functions.

The instructor, in a single sentence, briefly ‘explained’ the functions and a link to the documentation appeared on the screenU+1F926‍U+2642️. He even fast-forwarded through the parts where he was typing out the syntax.

Lately, I have been writing a little series explaining the hardest functions pandas in the hopes that other people won’t… Read the full blog for free on Medium.

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Published via Towards AI