Remove Rows in R with the Subset Command

Remove rows from datasets that you don’t need as an early transformation step to keep your datasets manageable. Here is an example of some code where I do that using an NHANES dataset as demonstration (which you can read about here).

If you watch the video, you will see that we downloaded the demographic dataset from NHANES. I imported that into R GUI and named the dataframe DG_a. We will remove rows from that dataframe and save it as DG_b.

The variable RIAGENDR means gender, and it’s coded 1 for men and 2 for women. Our aim was to remove all the men in the dataset – so we wanted to retain all the rows where RIAGENDR equals 2 (so we remove rows that are equal to 1). Here is the code.

You can post your code on GitHub so everyone can share.

nrow(DG_a)
DG_b <- subset(DG_a, RIAGENDR == 2)
nrow(DG_b)

As you can see in the code, we start by counting the number of rows in our dataframe DG_a using the nrow command. Then, we use the subset command, and set criteria for the value of the rows that should be retained in the resulting dataframe. That’s one way to remove rows in R. I named the resulting dataframe DG_b because that way, I can roll back to DG_a if anything goes wrong. Then, I count the final rows in DG_b to see how many there are left.

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Remove rows by criteria is a common ETL operation – and my blog post shows you how to do it using the subset command.

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