# How to Use The Cut Function In R Programming

## Basic subset functions in R provide ways to categorize your data. Here is a simple function for identifying ranges that your data fits into.

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*Cut() *is an often overlooked R programming function that is used for creating subsets within a list of R programming object elements. The subsets are bins — a range that you set for convenience.

*Cut() *differs from the *slice()* function in the *dyplr* library. Slice subsets according to the observations, and can even insert functions that determine where the subsets should occur. With the *cut()* function, you are actually positioning and naming where the bins should occur without requiring a calculation — just the range of numbers you want.

As an example, I am taking the data set GT cars from the GT library, and inserting them into an object in R as a data frame. I plan on creating bins based on miles per gallon rating of the listed vehicles. Below is the dataset — I included a view of the set so you can see the mpg_c column from which the data will be created.

Now I will create objects based on this data frame object using the *cut()* function on the mpg_c column data, indicating which observations fall into categories of fuel efficiency.

Cut parameters include the actual object followed by a comma, and then “*breaks =* “. It is here that you add a list of where those breaks occur.

So for the GT cars example, I create an object called mileage, with breaks that divide the set into bins of miles per gallon — 0–15, 15–20, 20–25, and so forth. The code is shown below.

The created object (*mileage*) displays the observations according to the bin each observation falls within. Here is what it looks like when you run the mileage object.