Qcut - Tag - 300.Wattshttps://300watts.me/tags/qcut/Qcut - Tag - 300.WattsHugo -- gohugo.ioenmorristai01@gmail.com (Morris)morristai01@gmail.com (Morris)This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.Sat, 05 Aug 2017 11:46:56 +0800Pandas cut and qcut Functionshttps://300watts.me/posts/pandas-cut-and-qcut-functions/Sat, 05 Aug 2017 11:46:56 +0800Morrishttps://300watts.me/posts/pandas-cut-and-qcut-functions/When we have continuous numerical values, we can discretize them using cut and qcut. The cut function bins values by numeric intervals, while qcut bins them by quantiles. In other words, cut produces bins of equal length, while qcut produces bins of equal size.

Suppose we have the ages of a group of people:
ages = [20, 22, 25, 27, 21, 23, 37, 31, 61, 45, 41, 32, 101]
If we want to discretize this list into “18 to 25”, “25 to 35”, “35 to 60”, and “60 and above”, we can use the cut function:

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