Data Cleaning Techniques - What to drop?
Check the percantege of missing values in each column. If it is high then you should remove this column, otherwise you are able to try to impute the missing values. For the latter you may replace them with the mean (median or mode etc) or try to predict them using the other known values. You should check if these are values are mising at random or not.