A data scientist is dealing with a feature databricks video

Full Certification Question

A data scientist is dealing with a feature set having the following schema: customer_id STRING , spend DOUBLE , units INTEGER , happiness_tier STRING In this set, the customer_id column is the primary key. Each column in the feature set has some missing values. The scientist aims to replace these missing values by imputing a common value for each feature. Which columns from the feature set should be imputed using the most common value of the column?