SECUREWHEELS CASE STUDY SecureWheels The next 4 questions are based on this case study below. Jeremy Yashimoto is a data scientist working at SecureWheels, an insurance company headquartered in Boston that specializes in car insurance. Jeremy is working on a variety of projects that will inform marketing and the application process for a new insurance product for motorcycles.   They have been offering the insurance for 6 months and have collected the following data points: Variable Description Sample Value customer_id Unique customer number c15034 origination_date Date when customer was approved for the policy 2025-10-23 customer_age Current age of customer 32 number_of_policies Total number of other policies at SecureWheels  2 monthly_payment Monthly policy premium (payment)  450 number_of_claims Number of insurance claims on the policy since origination 1 motorcycle_type Street/Touring/Dirt/Sport/Scooter Street number_of_citations_5_years Number of police citations in the last 5 years in any vehicle 2 customer_survey_sentiment Positive/Neutral/Negative Neutral SecureWheels has launched a new motorcycle insurance product and collected raw customer data during the first six months. Jeremy, a data scientist, notices inconsistent formatting across payment values and dates when preparing the dataset for modeling. Which transformation tasks best prepare the data?