Missing value analysis

can you please help me to know, whether to drop the missing value or to impute the missing value using different imputation method. If variable is having more than 70% as missing value then imputing the missing value will cause model error, if dropping the missing value, then data-set will left with 30% data that also will cause the model error, so how to handle this situation?

Hi @rupakumari9892,

Welcome to the community! I would recommend you to check out this post: