Pls do this also

Overview In this assignment, you are tasked to implement a smart applicants search program that can be used by the potential recruiters to find suitable applicants from the field of Computing & IT. The program will facilitate recruiters to filter, sort and save profiles by considering various factors such as area of specialization, country of the highest qualification, years of experience, expected salary, and qualification level. Assume that you have a dataset of the profiles extracted from a job search site. A sample of the profiles data is given below: profiles = ['Rose Winds!, 'Cloud Computing', 'USA', 6.5, 5000, 5, 'F'], ('Merry Brown', 'Cloud Computing', 'UK', 5, 7000, 5, 'F'], ('Lina Mesro, Cyber Security', 'Malaysia', 7, 6500, 4, 'F'], FAbdul Fazil', 'Big Data', 'Australia', 11, 8000, 4, 'M'], [Chris Janes', Big Data', 'Ireland', 7, 2500, 4, 'M'], ['Sireen May', Artificial Intelligence', 'Australia, 0, 4000, 4, 'F'], Mine Tims', 'Robotics', 'Australia', 0, 3500, 3, 'M'], ['Niki Rohdes', 'Artificial Intelligence', 'China', 9, 8500, 5, Fl] In the dataset above, "Rose Winds' is the applicant name, 'Cloud Computing' is the area of specialization, 'USA' is the country of the highest qualification, 6.5 is the years of experience, 5000 is the expected monthly salary, 5 is the level of qualification, and F' is the gender, i.e. Female. 'M' refers to the male gender. Levels of qualification: 5= PhD, 4 = Master, 3 = Bachelor degree (Highest to Lowest) Note: your functions and algorithms must be generic and not dependent on the specific data. For example, your program must be able to perform all the tasks when provided new data. Task 5: Sorting of Profiles (30 marks): You are required to design and implement an algorithm as a python program which can sort the profiles data by considering the sorting criterion provided from the application user. In your application user should be able to Sort by Full Name Alphabetically (A-2), Sort by Expected Salary (Low to High) or Sort by Years of Experience (High to Low). Note: Sorting by one criterion at a time is acceptable, but your algorithm should support all 3 sorting aspects. Your algorithm should not be fixed on the dataset of profiles as mentioned in this document. In other words, your program should work accurately whenever a new record is added to profiles. For example: Below are the results of Sort by Expected Salary (Low to High) profiles = [['Chris Janes', 'Big Data', 'Ireland', 7, 2500, 4, 'M'], [Jine Tims', 'Robotics', 'Australia', 0, 3500, 3, 'M'], ['Sireen May', 'Artificial Intelligence', 'Australia', 0, 4000, 4, 'F'], ['Rose Winds', 'Cloud Computing', 'USA', 6.5, 5000, 5, 'F'], ['Lina Mesro', 'Cyber Security', 'Malaysia', 7, 6500, 4, 'F'], ['Merry Brown', 'Cloud Computing', 'UK', 5, 7000, 5, 'F'], ['Abdul Fazil', 'Big Data', 'Australia', 11, 8000, 4, 'M'], ['Niki Rhdes', Artificial Intelligence' , 'China', 9, 8500, 5='F']] MI Marks allocation: 5. Correctness, completeness, quality of the code, effectiveness and results of the sorting. Sorting by name, expected salary and years of experience. (15 marks) 6. Discuss and justify your implementation technique/approach. (2 marks) 7. Analyse the Big-O complexity of your algorithm by measuring the complexity step-by- step in your program code. (10 marks) 8. Critically discuss the complexity of your algorithm, especially focusing on the growth rate with respect to the input size and efficiency of your algorithm. (3 marks) Note: Use of built-in functions from python libraries to implement this task is not permitted, and it will not contribute to marks. The theoretical discussion should be included in your python module as docstring or comments. 7. Analyse the Big-O complexity of your algorithm by measuring the complexity step-by- step in your program code. (10 marks) 8. Critically discuss the complexity of your algorithm, especially focusing on the growth rate with respect to the input size and efficiency of your algorithm