I'm an educational researcher learning about machine learning so I can further explore my data beyond the usual statistics.
I currently have some assessment data but I am not sure how to appropriately handle features with 'no data'. For example, a school offers Subject A, B, C, D, E to students. All students are required to take Subject A and B. Subject C, D, E are optional. This means for Subject C, D, E, instead of a numerical 0-100 grade, it would show only as "-". This is not missing data per se. I can impute it but imputing it with the mean or median does not make much sense because some subjects may only have 5% of the students selecting it.
For Subject A and B, which are compulsory, sometimes students get sick, so a categorical value like 'MC' is recorded instead of a 0-100 numerical grade.
What are the appropriate/best practices to approach data in such scenarios?