You are given a data set consisting of variables having more than 30% missing values? Let’s say, out of 50 variables, 8 variables have missing values higher than 30%. How will you deal with them?

by
  • Assign a unique category to the missing values, who knows the missing values might uncover some trend.
  • We can remove them blatantly.
  • Or, we can sensibly check their distribution with the target variable, and if found any pattern we’ll keep those missing values and assign them a new category while removing others.