I have a dataset of 1600 rows and 28 columns. Only one column is partially complete with 1300 records. The rest is NaN. I did a value count of this columns and it has 84 different categories that are nominal. What is the best way to impute this column. I need to convert these in numbers impute it and then convert back. I understand that One-Hot encoding does not work in this case because of the high cardinality.
What is the best way to approach this problem?