Part 1 For this assignment you will review data and them using the information, map ICD-9-CM to ICD-10-CM. You can find the data you need here. This data set has 1000 patients information including patient id, age, gender, race, admission date, diagnosis1 to 5. Your tasks: 1. Transfer the diagnosis information. In the results, each line contains one diagnosis only. For example, change the format of input file (patient_id, age, gender, race, admission_date, diagnosis1, diagnosis2, diagnosis3, diagnosis4, diagnosis5) into the following format of: patient_id, age, gender, race, admission_date, diagnosis1 patient_id, age, gender, race, admission_date, diagnosis2 patient_id, age, gender, race, admission_date, diagnosis3 patient_id, age, gender, race, admission_date, diagnosis4 patient_id, age, gender, race, admission_date, diagnosis5 2. Use the General Equivalence Mappings (GEMS) in order to map diagnosis 1-5 to their corresponding ICD-10-CM code. You could download the GEMS from https://www.cms.gov/medicare/coding/icd10/2018-icd-10-cm-and-gems.html. Icd-10-cm https://www.medicalbillingandcoding.org/icd-10-cm/ You must submit the python file or R file to me, that were used to do the mapping as well as the mapped file Part 2 The Clinical Classifications Software (CCS) is a tool for clustering patient diagnoses and procedures into a manageable number of clinically meaningful categories. It is developed at the Agency for Healthcare Research and Quality (AHRQ). CCS offers researchers the ability to group conditions and procedures without having to sort through thousands of codes. This “clinical grouper” makes it easier to quickly understand patterns of diagnoses and v procedures so that health plans, policy makers, and researchers can analyze costs, utilization, and outcomes associated with particular illnesses and procedures. Your tasks: 1. Map the diagnosis 1-5 from the CSV file to their corresponding CCS categories. 2. Please use the single-level diagnosis/procedures Appendix A – Clinical Classification Software – DIAGNOSES located at the link https://www.hcup-us.ahrq.gov/toolssoftware/ccs/AppendixASingleDX.txt and attached files in order to Map the diagnosis 1-5 from the CSV file to their corresponding CCS categories.