The first thing I need to do is write the initial data set. Afetr this, I was made aware of a new person that I had to add to the lists using .append().

    names = ["Mohamed", "Sara", "Xia", "Paul", "Valentina", "Jide", "Aaron", "Emily", "Nikita", "Paul"]
    insurance_costs = [13262.0, 4816.0, 6839.0, 5054.0, 14724.0, 5360.0, 7640.0, 6072.0, 2750.0, 12064.0]

    ## Add a new person to the arrays
    names.append("Priscilla")
    insurance_costs.append(8320.0)
            

The next task in the project was to combine and sort the data, I combined the data in two ways as this allowed me to both sort in alphebetical order and also by cost. Sorting it in two ways would allow me to answer a multitude of questions depending on the insights I was searching for.

    ## Combine insurance cost and names into a list and sort
    # Sorted by cost
    medical_records_by_cost=(list(zip(insurance_costs, names)))
    medical_records_by_cost.sort()
    print(medical_records_by_cost)
    # Sorted by name
    medical_records_by_name = list(zip(names, insurance_costs))
    medical_records_by_name.sort()
    print(medical_records_by_name)
            

Next I was asked to find how much data we have in our sample. Given that the data I am working with is only small, to find the length would be easy enoguh to count. However as I am practising my python, I decided to use len also with a statement so it is clear what the number is representing when printed.

    ## Find out how many medical records we have
    num_medical_records = len(medical_records_by_cost)
    print("There are ", num_medical_records, " medical records.")
            

Next I was practising selecting a specific value in a data depending on the index. I chose to select the first medical record in the list sorted by name to see the details of that person.

    ## Select the first medical record
    first_medical_record = medical_records_by_name[0]
    print("Here is the first medical record: ", first_medical_record)
            

Then I practised my slicing of a list, I used this to find the most expensive, cheapest and also the middle 5 to practise different ways to use the index.

    ## Slice the list to find the cheapest three, the middle five and the most expensive three
    cheapest_three = medical_records_by_cost[:3]
    middle_five_records = medical_records_by_cost[2:7]
    priciest_three = medical_records_by_cost[-3:]
    print("Here are the three cheapest insurance costs in our medical records: ", cheapest_three)
    print("Here are the middle five insurance costs in our medical records: ", middle_five_records)
    print("Here are the three most expensive insurance costs in our medical records: ", priciest_three)
            

As you can see, I used a negative index to find the most expensive as the cost was sorting in ascending order.

Finally, I practised the .count() method. I used this to count how many instances of a specific name was in the data. First I tried to count in just medical_records_by_name, however after getting 0 as the answer, I realised you have to specify which index in the list to search or use the name data.

    ## Count how many Pauls are in the data
    occurrences_paul = names.count("Paul")
    print("There are ", occurrences_paul, " individuals with the name Paul in our medical records.")