Using the UCI dataset here: http://archive.ics.uci.edu/ml/datasets/Congressional+Voting+Records
Each congressperson votes yay, nay or present (basically abstains) on 16 issues. My teacher wants us to treat missing values (vote present) as a third category. So I thought of making a new column for each vote. So columns for votes 1 to 16 are either 1 for yay or 0 for nay and no value or NaN for abstaining. Then the new 16 columns called abstention are either 1 if the corresponding vote column was a NaN or no value and 0 otherwise. We can use up to 3 items to find some associations.
Is the above correct method to create a third category? Then when I search associations using Python apyori or R, do I include 3 pairs of (vote, abstention)?