Your company is looking for candidates for the new Data Scientist role and you will write code that helps the HR department find the right candidate.

You will create the following data sources from scratch:

• 15 text files, each containing the resume for one candidate. As expected, each resume contains, among many other data, the skills of the candidate. You can create the text files from scratch or copy them from ones found in the web. Use fictitious names. Each person should have their own set of resumes. No two people can have same (nor even similar) resumes submitted.
• One csv file called Candidates.csv that contains 3 header rows to be skipped, and has a list of 15 candidates, including the name of the candidate and the name of the text file containing his/her resume. This file does NOT contain a list of skills.
• 1 flat file (you should determine the type of file and/or format) that contains the job description. Your job description should contain a list of skills required.
• You should make sure your data has a few errors or omissions (missing data) that need to be corrected (later with Python)
• Your task is to create a Python script that:
  • reads the job description, and gathers the required skills
  • loops through the Candidates.csv file to identify candidates fit for the role (exact fit for skill matching, you are NOT required to use regular expressions, but you can, if you know how to use them)
  • creates a text file called ToInterview.csv that contains a list of the 5 most fit candidates in order of priority (the most fit first) with their most salient characteristics (you have to determine what they are). The candidates are prioritized based on how much their skills match the job description. Hint: this is a good case where the use of Python sets will help you.