Using the Cut2 Function in R Programming

Another function, cut2(), in the Hmsic library will help group the observations of your dataset. Here’s how.

I explained in an earlier post how the cut() function in R programming worked. Yet more than one version of that function is available. That second one, cut2(), is included in the Hmisc library. It provides more nuanced features in identifying bins among a vector of data. This post will explain some of the details so you can appreciate the options and be imaginative in how you categorize your data.

The cut2() function has vectors, cut points, the minimum number of observations in a group, a number of quartile groups, and some additional parameters.

One difference is the cutpoints for each bin. The “cutpoints” describe the start and end points of the bin groups.

In cut() you have a starting point, lower, and end point, upper. They appear as (lower, upper] which indicates the cutpoints for a bin range that excludes the lower number.

In cut2(), the bins have inclusive lower endpoints and exclude the upper endpoint. The bins in the data range appear as [lower, upper), with the exception that the last interval is completely inclusive — [lower, upper]. This means cut2() will by default ensure that…