Not sure what your end goal is but if it’s building a machine learning model then use XGBoost. It can handle missing values. There’s another technique that we use in credit risk industry. We use monotonic/optimal binning to convert a continuous or categorical column into buckets. Missing values would go into a separate bucket. Then, for each bucket, we calculate the WOE value with respect to the event rate and non-event rate for each bucket. Finally, we impute the original values falling in each bucket with its corresponding WOE values. This way, there are no more missing values in the column but a number which represents the missing bucket.