Description
Assignment Overview
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List and Tuples
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File manipulation
Assignment Background
Modern medicine has improved greatly over the past few centuries. From treating infections to building our immune system to combat diseases that our ancestors were defenseless against. However, these treatments are very expensive and unfortunately very few individuals can afford it. For this reason, Medicaid was signed into a law back in 1965 to help patients of low income households by covering some of the medication expenses. The Centers for Medicare & Medicaid Services have a record of its drug spending and utilization by their beneficiaries. This document records the annual total spending, prescriptions fill count, and unit count for each medication. The prescription fill count records how many medications were prescribed by a certified physician. The unit count indicates how many units for this medication were prescribed. Each prescription have certain units (number of pills, grams, milliliters or other units). For example, one prescription of Xanax can have 60 pills, i.e. 60 units. For more information, see the interactive dashboard (https://www.cms.gov/Research-Statistics-Data-and-Systems/Statistics-Trends-and-Reports/Information-on-Prescription-Drugs/2015Medicaid.html).
For this project, you are tasked to build an interface which will show the user some medications covered by Medicaid and how much the medications cost. You must read the file that we provide of Medicaid Drug Expending Data from 2011 to 2015 and store into a list of tuples for the program to extract and process the information. We want to display a table with the information of each medication for each year. Also, we want to plot two charts presenting the top 10 most prescribed medications and another for the top 10 most covered or money spent by Medicaid.
Project Specifications
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You must implement the following functions:
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open_file() prompts the user to enter a filename. The program will try to open a comma-separated value (csv) file. An error message should be shown if the file cannot be opened. This function will loop until it receives proper input and successfully opens the file. It returns a file pointer.
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read_data(fp) receives a file pointer of the data file. For this project, we are only interested in the following columns:
column 0: year (int) # convert year to an int
column 1: brand (string)
column 3: total (float) # total spending on that drug
column 4: prescriptions (int)
column 5: units (int)
In addition to these variables, you must compute two more values. In this function you need to compute the average cost per prescription as well as the average cost per unit. Only append the medications where they have defined numeric values for the total, prescriptions, and units.
This function returns a sorted list of tuples (we sort so we have a canonical ordering for
Mimir testing). Each tuple should include the following data in the this order:
(year, brand, total, prescriptions, units, avg_cost_prescription, avg_cost_units)
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get_year_list(year, data) This function receives the specified year (integer) and the list of tuples with the entire dataset, that is, the list returned by read_data. This function returns a sorted list of tuples with all the medications covered by Medicaid during the specified year.
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top_ten_list(column, year_list) Receives column index (integer) and a list of tuples containing all the medications covered for a specific year, i.e. data returned from the get_year_list function. This function returns two lists: (list1) containing the brand names of the top 10 and (list2) the values in the specified column for the top 10 tuples reverse order. 3 is for Medicaid coverage, 4 is for number of prescriptions. Note that column n is in index n-1 of the tuple, so you should adjust it. Hint: sort the whole list in reverse order, slice off the top ten, and then create the two lists to return as a tuple (list1,list2).
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display_table(year, year_list) This function displays the following information for each medication in a year (sorted by brand name, A-Z): brand name, number of prescriptions, average prescription cost, and the total spending per medication. Remember to use string formatting specified below to properly display the results. Divide the total spending by 1000 to make the output look nicer.
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main() This function is the main part of the program. You need to open the file and pass the file pointer to the read_data function. Then you need to prompt for a year to search in the data list and send it to the display_table function to output. Then you prompt whether you want to plot the top 10 medications in the data list. Hint: Make sure that the entered year exists in the data file (validate the input!)
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Requirements
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Use sorted() and itemgetter() functions. For the top 10 lists, sort the list of tuples from largest item first, if two tuples have the same value, sort by brand name. Hint: both top 10 functions will sort; in the example below, y is the index of the brand name.
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from operator import itemgetter
sorted_lst = sorted(num_list, key=itemgetter(x,y), reverse=True)
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For display_table, use the following formatting. To get commas in numbers place a comma immediately after the field width, e.g. {:10,d} or {:10,.2f}:
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The header should be centered on 80 spaces
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Medication Brand Name = 35 spaces, left justified
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Prescription = 15 spaces, right justified with comma between 3 digits
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Average Prescription Cost = 20 spaces, right justified, 2 decimal digits
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Total spending by Medicaid = 15 spaces, right justified, 2 decimal digits, with comma between 3 digits (this value is in thousands)
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plot_top_ten(x, y, title, xlabel, ylabel) You must use this provided function to plot the results. This function has 5 parameters: the list of medication brand names x, the list of numeric values y, the plot title, the x-axis title xlabel, and the y-axis title ylabel. Note that this function will be used to draw both plots, one for the most prescribed medications and the other for the highest prescription cost.
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Read the file only once. Specifically, you read the file once in the read_data function and store the information in a list. For the rest of the program you get information from lists—you don’t go back and re-read the file.
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Want an extra challenge? Using list comprehension you can write the function get_year_list in one line that is readable.
Deliverables
The deliverable for this assignment is the following file:
proj07.py – the source code for your Python program
Be sure to use the specified file name and to submit it for grading via Mimir before the project deadline.
Read_data function test:
fp = open(“medicaid_spending_small.csv”,”r”)
read_data(fp)
returns:
[(2011, ‘Abilify’, 1715769087.0, 3007841, 98263157, 570.4321096095173,
17.460960337352077), (2011, ‘Adderall XR’, 376431028.8, 1613783, 55728012,
233.26000385429765, 6.7547901906136545), (2011, ‘Advair Diskus’, 578947345.1, 2462514, 150975222, 235.10418421986637, 3.8347176273733186), (2011, ‘Carbamazepine’, 11436846.03, 618588, 99627263, 18.48863222370948,
0.11479634876650179), (2011, ‘Clobetasol Propionate’, 10157350.16, 379057,
20788507, 26.796366140184723, 0.4886041195743398), (2011, ‘Flovent HFA’,
280559007.5, 1924032, 22347142, 145.81826471701095, 12.55458114062192),
(2011, ‘Humalog’, 128527266.2, 602919, 10883844, 213.17501389075483,
11.808995626912697), (2011, ‘Invega’, 283641529.9, 380435, 8945035,
745.5715954105168, 31.709381785538007), (2011, ‘Lantus’, 410789437.2, 2204518, 36172479, 186.33979727087734, 11.35640820193717), (2011, ‘Lyrica’, 208052625.3, 1080100, 75574568, 192.6234842144246, 2.752944949682015), (2011, ‘Methylphenidate ER’, 226032289.6, 1332576, 44673828, 169.6205616790337, 5.0596131945531955), (2011, ‘Morphine Sulfate’, 20089793.94, 576161, 31066801, 34.86836828594785, 0.6466643907108428), (2011, ‘Proair HFA’, 221936930.0, 4784692, 44759787, 46.384789240352355, 4.9584000477929), (2011, ‘Seroquel XR’, 371592404.1, 952900, 36177324, 389.9594963794732,
10.271417645484227), (2011, ‘Spiriva’, 215473653.8, 936931, 28940707,
229.97814545574863, 7.445348650259305), (2011, ‘Suboxone’, 318060139.8, 1198265, 48316821, 265.4338896654747, 6.582803529230534), (2011, ‘Symbicort’, 128740153.2, 621462, 6467805, 207.15691900711548, 19.904767258753164), (2011, ‘Truvada’, 457327611.8, 427891, 12715594, 1068.794650506788,
35.96588659562424), (2011, ‘Ventolin HFA’, 199072297.7, 4889379, 95528093,
40.715251916449915, 2.08391365773417), (2011, ‘Vyvanse’, 385235408.5,
2453085, 75585425, 157.04119853164485, 5.096689057447253), (2013, ‘Enbrel’,
255847098.5, 108123, 470496, 2366.259708850106, 543.7816655189417)]
Get_year_list function test:
fp = open(“medicaid_spending_small.csv”,”r”)
data = read_data(fp)
get_year_list(2011,data)
returns:
[(2011, ‘Abilify’, 1715769087.0, 3007841, 98263157, 570.4321096095173,
17.460960337352077), (2011, ‘Adderall XR’, 376431028.8, 1613783, 55728012,
233.26000385429765, 6.7547901906136545), (2011, ‘Advair Diskus’, 578947345.1, 2462514, 150975222, 235.10418421986637, 3.8347176273733186), (2011, ‘Carbamazepine’, 11436846.03, 618588, 99627263, 18.48863222370948,
0.11479634876650179), (2011, ‘Clobetasol Propionate’, 10157350.16, 379057,
20788507, 26.796366140184723, 0.4886041195743398), (2011, ‘Flovent HFA’,
280559007.5, 1924032, 22347142, 145.81826471701095, 12.55458114062192),
(2011, ‘Humalog’, 128527266.2, 602919, 10883844, 213.17501389075483,
11.808995626912697), (2011, ‘Invega’, 283641529.9, 380435, 8945035,
745.5715954105168, 31.709381785538007), (2011, ‘Lantus’, 410789437.2, 2204518, 36172479, 186.33979727087734, 11.35640820193717), (2011, ‘Lyrica’, 208052625.3, 1080100, 75574568, 192.6234842144246, 2.752944949682015), (2011, ‘Methylphenidate ER’, 226032289.6, 1332576, 44673828, 169.6205616790337, 5.0596131945531955), (2011, ‘Morphine Sulfate’, 20089793.94, 576161, 31066801, 34.86836828594785, 0.6466643907108428), (2011, ‘Proair HFA’,
221936930.0, 4784692, 44759787, 46.384789240352355, 4.9584000477929), (2011, ‘Seroquel XR’, 371592404.1, 952900, 36177324, 389.9594963794732,
10.271417645484227), (2011, ‘Spiriva’, 215473653.8, 936931, 28940707,
229.97814545574863, 7.445348650259305), (2011, ‘Suboxone’, 318060139.8, 1198265, 48316821, 265.4338896654747, 6.582803529230534), (2011, ‘Symbicort’, 128740153.2, 621462, 6467805, 207.15691900711548, 19.904767258753164), (2011, ‘Truvada’, 457327611.8, 427891, 12715594, 1068.794650506788,
35.96588659562424), (2011, ‘Ventolin HFA’, 199072297.7, 4889379, 95528093,
40.715251916449915, 2.08391365773417), (2011, ‘Vyvanse’, 385235408.5,
2453085, 75585425, 157.04119853164485, 5.096689057447253)]
Top_ten_list function test:
fp = open(“medicaid_spending_small.csv”,”r”)
data = read_data(fp)
list_2011 = get_year_list(2011,data)
top_ten_list(3,list_2011)
returns:
[‘Abilify’, ‘Advair Diskus’, ‘Truvada’, ‘Lantus’, ‘Vyvanse’, ‘Adderall XR’, ‘Seroquel XR’, ‘Suboxone’, ‘Invega’, ‘Flovent HFA’]
[1715769087.0, 578947345.1, 457327611.8, 410789437.2, 385235408.5,
376431028.8, 371592404.1, 318060139.8, 283641529.9, 280559007.5]
Test Case 1:
Input a file name: medicaid_spending_small.csv Medicaid drug spending 2011 – 2015
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Enter a year to process (‘q’ to terminate): 2011 |
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Drug spending by Medicaid in 2011 |
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Medication |
Prescriptions |
Prescription Cost |
Total |
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Abilify |
3,007,841 |
570.43 |
1,715,769.09 |
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Adderall XR |
1,613,783 |
233.26 |
376,431.03 |
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Advair Diskus |
2,462,514 |
235.10 |
578,947.35 |
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Carbamazepine |
618,588 |
18.49 |
11,436.85 |
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Clobetasol Propionate |
379,057 |
26.80 |
10,157.35 |
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Flovent HFA |
1,924,032 |
145.82 |
280,559.01 |
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Humalog |
602,919 |
213.18 |
128,527.27 |
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Invega |
380,435 |
745.57 |
283,641.53 |
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Lantus |
2,204,518 |
186.34 |
410,789.44 |
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Lyrica |
1,080,100 |
192.62 |
208,052.63 |
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Methylphenidate ER |
1,332,576 |
169.62 |
226,032.29 |
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Morphine Sulfate |
576,161 |
34.87 |
20,089.79 |
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Proair HFA |
4,784,692 |
46.38 |
221,936.93 |
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Seroquel XR |
952,900 |
389.96 |
371,592.40 |
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Spiriva |
936,931 |
229.98 |
215,473.65 |
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Suboxone |
1,198,265 |
265.43 |
318,060.14 |
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Symbicort |
621,462 |
207.16 |
128,740.15 |
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Truvada |
427,891 |
1,068.79 |
457,327.61 |
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Ventolin HFA |
4,889,379 |
40.72 |
199,072.30 |
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Vyvanse |
2,453,085 |
157.04 |
385,235.41 |
Do you want to plot the top 10 values (yes/no)? no Enter a year to process (‘q’ to terminate): q
Test Case 2:
Input a file name: xxx
Unable to open the file. Please try again.
Input a file name: test.csv
Unable to open the file. Please try again.
Input a file name: medicaid_spending.csv
Medicaid drug spending 2011 – 2015
Enter a year to process (‘q’ to terminate): year Invalid Year. Try Again!
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Enter a year to process (‘q’ to terminate): 2015 |
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Drug spending by Medicaid in 2015 |
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Medication |
Prescriptions |
Prescription Cost |
Total |
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Abilify |
2,074,321 |
978.44 |
2,029,596.06 |
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Adderall XR |
1,805,993 |
248.65 |
449,064.90 |
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Advair Diskus |
1,758,551 |
330.32 |
580,892.33 |
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Advate |
16,979 |
20,828.38 |
353,645.10 |
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Anucort-HC |
18,364 |
273.61 |
5,024.49 |
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Aripiprazole |
947,738 |
638.50 |
605,129.20 |
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Ativan |
7,168 |
734.32 |
5,263.61 |
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Atripla |
265,692 |
2,269.63 |
603,023.28 |
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Avastin |
144,610 |
1,297.06 |
187,568.41 |
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Carbamazepine |
585,130 |
64.50 |
37,741.07 |
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Clindamycin Phos-Benzoyl Perox |
10,413 |
630.46 |
6,564.98 |
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Clobetasol Propionate |
741,509 |
193.99 |
143,846.67 |
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Complera |
138,938 |
2,255.99 |
313,442.46 |
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Copaxone |
51,497 |
5,418.03 |
279,012.52 |
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Daraprim |
2,585 |
6,075.41 |
15,704.94 |
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Demerol |
48,806 |
100.42 |
4,900.98 |
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Econazole Nitrate |
218,702 |
211.28 |
46,206.96 |
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Enbrel |
136,508 |
3,204.75 |
437,474.12 |
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Epitol |
58,483 |
46.27 |
2,706.08 |
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Epzicom |
117,317 |
1,205.16 |
141,386.15 |
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Fentanyl Citrate |
474,760 |
116.52 |
55,317.74 |
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Flovent HFA |
2,264,825 |
194.88 |
441,361.06 |
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Gleevec |
20,001 |
9,528.69 |
190,583.27 |
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Glumetza |
7,873 |
2,048.88 |
16,130.82 |
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Granisetron HCl |
43,149 |
180.47 |
7,787.08 |
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H.P. Acthar |
3,278 |
44,101.85 |
144,565.87 |
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Harvoni |
78,467 |
27,720.64 |
2,175,155.84 |
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Herceptin |
53,136 |
3,290.87 |
174,863.75 |
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Humalog |
941,420 |
377.72 |
355,593.19 |
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Humira |
219,266 |
3,673.43 |
805,458.62 |
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Hydroxychloroquine Sulfate |
545,452 |
110.00 |
60,001.01 |
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Invega |
526,070 |
1,380.61 |
726,297.32 |
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Isentress |
188,181 |
1,229.77 |
231,419.27 |
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Semester SS18 |
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Lantus |
3,651,839 |
393.11 |
1,435,574.72 |
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Latuda |
715,975 |
881.91 |
631,424.75 |
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Lyrica |
1,356,527 |
370.87 |
503,093.90 |
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Mestinon |
7,268 |
1,070.04 |
7,777.04 |
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Methylphenidate ER |
3,576,101 |
195.86 |
700,422.21 |
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Morphine Sulfate |
662,978 |
62.43 |
41,389.73 |
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Naproxen Sodium |
370,485 |
27.33 |
10,126.81 |
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Neulasta |
75,594 |
3,729.84 |
281,953.81 |
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Norditropin Flexpro |
79,156 |
3,473.33 |
274,934.63 |
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Novoseven RT |
4,444 |
67,098.11 |
298,184.00 |
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Phenergan |
10,047 |
255.73 |
2,569.27 |
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Prezista |
265,823 |
1,259.27 |
334,742.62 |
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Proair HFA |
6,690,081 |
58.56 |
391,742.23 |
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Proctosol-HC |
146,493 |
49.12 |
7,195.57 |
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Pulmozyme |
66,738 |
3,356.32 |
223,994.30 |
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Quelicin |
29,416 |
223.57 |
6,576.41 |
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Remicade |
52,764 |
3,576.20 |
188,694.62 |
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Retin-A Micro |
1,667 |
1,953.85 |
3,257.07 |
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Revlimid |
14,475 |
9,954.78 |
144,095.51 |
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Reyataz |
178,383 |
1,303.60 |
232,540.89 |
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Sabril |
13,297 |
9,962.99 |
132,477.85 |
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Seroquel XR |
743,257 |
650.00 |
483,117.34 |
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Sovaldi |
27,228 |
22,713.59 |
618,445.60 |
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Spiriva |
1,255,363 |
324.15 |
406,925.46 |
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Stribild |
176,445 |
2,580.10 |
455,245.06 |
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Suboxone |
2,051,871 |
233.41 |
478,918.14 |
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Symbicort |
1,682,405 |
270.45 |
455,006.23 |
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Synagis |
100,034 |
2,338.19 |
233,898.45 |
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Tecfidera |
39,697 |
5,505.27 |
218,542.81 |
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Tivicay |
132,094 |
1,457.12 |
192,476.94 |
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Triumeq |
81,914 |
2,422.67 |
198,450.69 |
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Truvada |
527,386 |
1,396.28 |
736,377.75 |
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Ventolin HFA |
7,227,336 |
49.25 |
355,949.41 |
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Viekira Pak |
8,612 |
24,413.83 |
210,251.89 |
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Vyvanse |
3,496,935 |
223.81 |
782,651.74 |
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Xifaxan |
93,982 |
1,441.23 |
135,449.72 |
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Xolair |
55,631 |
2,501.20 |
139,144.34 |
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Do you want to plot the top 10 values (yes/no)? no |
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Enter a year to process (‘q’ to terminate): 2012 |
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Drug spending by Medicaid in 2012 |
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Medication |
Prescriptions |
Prescription Cost |
Total |
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Abilify |
2,934,565 |
642.71 |
1,886,082.01 |
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Adderall XR |
1,511,503 |
243.27 |
367,706.53 |
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Advair Diskus |
2,359,382 |
251.29 |
592,900.57 |
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Advate |
7,514 |
21,674.67 |
162,863.51 |
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Anucort-HC |
4,186 |
21.75 |
91.04 |
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Ativan |
19,385 |
147.53 |
2,859.96 |
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Atripla |
280,155 |
1,789.12 |
501,231.12 |
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Avastin |
93,763 |
1,506.96 |
141,296.63 |
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Carbamazepine |
617,133 |
17.96 |
11,084.27 |
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Clindamycin Phos-Benzoyl Perox |
3,149 |
149.21 |
469.86 |
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Clobetasol Propionate |
448,435 |
33.37 |
14,965.04 |
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Complera |
39,684 |
1,877.01 |
74,487.19 |
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Semester SS18 |
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Copaxone |
51,778 |
4,052.88 |
209,850.07 |
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Daraprim |
3,944 |
482.90 |
1,904.57 |
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Demerol |
64,621 |
24.61 |
1,590.54 |
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Econazole Nitrate |
170,593 |
23.28 |
3,971.12 |
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Enbrel |
104,737 |
2,120.79 |
222,125.19 |
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Epitol |
40,968 |
6.75 |
276.57 |
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Epzicom |
121,222 |
979.45 |
118,730.83 |
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Fentanyl Citrate |
285,140 |
55.18 |
15,733.57 |
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Flovent HFA |
2,071,046 |
148.45 |
307,448.30 |
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Gleevec |
16,077 |
5,910.02 |
95,015.38 |
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Glumetza |
6,226 |
371.46 |
2,312.70 |
|
Granisetron HCl |
37,292 |
63.47 |
2,367.08 |
|
H.P. Acthar |
1,303 |
44,059.63 |
57,409.70 |
|
Herceptin |
51,709 |
2,407.18 |
124,472.77 |
|
Humalog |
626,575 |
231.68 |
145,165.13 |
|
Humira |
114,272 |
2,323.64 |
265,527.47 |
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Hydroxychloroquine Sulfate |
348,418 |
13.86 |
4,827.38 |
|
Invega |
406,323 |
907.23 |
368,629.81 |
|
Isentress |
195,434 |
1,031.31 |
201,553.62 |
|
Lantus |
2,517,919 |
211.79 |
533,281.27 |
|
Latuda |
160,905 |
514.19 |
82,735.78 |
|
Lyrica |
1,019,589 |
211.20 |
215,339.53 |
|
Mestinon |
8,367 |
189.46 |
1,585.18 |
|
Methylphenidate ER |
2,932,089 |
168.52 |
494,115.10 |
|
Morphine Sulfate |
524,402 |
35.99 |
18,874.21 |
|
Naproxen Sodium |
340,547 |
10.55 |
3,594.08 |
|
Neulasta |
74,648 |
2,998.11 |
223,802.72 |
|
Norditropin Flexpro |
32,740 |
2,769.43 |
90,671.08 |
|
Novoseven RT |
3,804 |
56,437.66 |
214,688.85 |
|
Phenergan |
11,335 |
17.52 |
198.57 |
|
Prezista |
200,271 |
1,032.74 |
206,827.56 |
|
Proair HFA |
5,455,972 |
49.57 |
270,467.51 |
|
Proctosol-HC |
89,636 |
9.58 |
858.33 |
|
Pulmozyme |
63,223 |
2,595.71 |
164,108.80 |
|
Quelicin |
22,282 |
53.63 |
1,194.87 |
|
Remicade |
42,291 |
2,889.87 |
122,215.65 |
|
Retin-A Micro |
39,562 |
258.50 |
10,226.79 |
|
Revlimid |
9,249 |
8,498.63 |
78,603.81 |
|
Reyataz |
256,659 |
1,003.84 |
257,643.89 |
|
Sabril |
8,972 |
4,663.81 |
41,843.68 |
|
Seroquel XR |
887,711 |
460.66 |
408,935.89 |
|
Spiriva |
1,047,429 |
256.28 |
268,436.97 |
|
Stribild |
2,520 |
2,381.47 |
6,001.31 |
|
Suboxone |
1,407,720 |
278.23 |
391,667.33 |
|
Symbicort |
698,988 |
219.94 |
153,732.12 |
|
Synagis |
185,864 |
2,151.77 |
399,936.52 |
|
Truvada |
470,894 |
1,175.92 |
553,732.04 |
|
Ventolin HFA |
5,123,890 |
42.73 |
218,962.67 |
|
Vyvanse |
2,889,840 |
165.16 |
477,289.95 |
|
Xifaxan |
52,056 |
1,065.21 |
55,450.67 |
|
Xolair |
36,764 |
2,167.00 |
79,667.51 |
Do you want to plot the top 10 values (yes/no)? no Enter a year to process (‘q’ to terminate): q
Test Case 3 – Plot Test (Not on Mimir):
Input a file name: medicaid_spending.csv
Medicaid drug spending 2011 – 2015
|
Enter a year to process (‘q’ to terminate): 2013 |
|||
|
Drug spending by Medicaid in 2013 |
|||
|
Medication |
Prescriptions |
Prescription Cost |
Total |
|
Abilify |
2,749,155 |
731.64 |
2,011,387.68 |
|
Adderall XR |
1,519,701 |
248.41 |
377,512.24 |
|
Advair Diskus |
2,077,435 |
279.31 |
580,242.45 |
|
Advate |
15,337 |
17,737.43 |
272,038.97 |
|
Anucort-HC |
4,543 |
28.94 |
131.48 |
|
Ativan |
10,861 |
140.91 |
1,530.45 |
|
Atripla |
258,157 |
1,915.29 |
494,445.97 |
|
Avastin |
103,654 |
1,399.94 |
145,109.44 |
|
Carbamazepine |
584,314 |
17.67 |
10,324.83 |
|
Clindamycin Phos-Benzoyl Perox |
11,159 |
144.24 |
1,609.57 |
|
Clobetasol Propionate |
459,091 |
32.34 |
14,849.21 |
|
Complera |
73,381 |
1,959.14 |
143,763.70 |
|
Copaxone |
47,909 |
4,582.08 |
219,523.00 |
|
Daraprim |
3,466 |
579.98 |
2,010.21 |
|
Demerol |
57,556 |
55.21 |
3,177.66 |
|
Econazole Nitrate |
150,475 |
22.02 |
3,312.83 |
|
Enbrel |
108,123 |
2,366.26 |
255,847.10 |
|
Epitol |
45,149 |
6.59 |
297.40 |
|
Epzicom |
118,963 |
1,032.01 |
122,771.48 |
|
Fentanyl Citrate |
307,787 |
82.84 |
25,496.16 |
|
Flovent HFA |
2,065,708 |
161.34 |
333,273.79 |
|
Gleevec |
16,455 |
6,588.75 |
108,417.85 |
|
Glumetza |
1,345 |
374.93 |
504.28 |
|
Granisetron HCl |
41,572 |
56.14 |
2,333.64 |
|
H.P. Acthar |
2,021 |
41,533.21 |
83,938.62 |
|
Herceptin |
53,608 |
2,620.58 |
140,483.85 |
|
Humalog |
626,112 |
260.70 |
163,225.00 |
|
Humira |
127,339 |
2,613.33 |
332,779.41 |
|
Hydroxychloroquine Sulfate |
373,650 |
12.61 |
4,711.37 |
|
Invega |
423,737 |
1,038.37 |
439,996.34 |
|
Isentress |
204,795 |
1,070.59 |
219,251.61 |
|
Lantus |
2,690,587 |
252.86 |
680,347.46 |
|
Latuda |
250,199 |
626.14 |
156,660.75 |
|
Lyrica |
1,002,207 |
246.66 |
247,204.86 |
|
Mestinon |
8,592 |
217.22 |
1,866.40 |
|
Methylphenidate ER |
3,456,299 |
167.39 |
578,534.69 |
|
Morphine Sulfate |
518,903 |
54.14 |
28,093.10 |
|
Naproxen Sodium |
319,877 |
9.79 |
3,132.20 |
|
Neulasta |
72,410 |
3,107.82 |
225,037.00 |
|
Norditropin Flexpro |
40,357 |
2,970.33 |
119,873.51 |
|
Novoseven RT |
3,447 |
63,685.57 |
219,524.14 |
|
Phenergan |
9,770 |
20.86 |
203.82 |
|
Prezista |
223,170 |
1,092.12 |
243,728.80 |
|
Proair HFA |
5,404,529 |
52.91 |
285,949.65 |
|
Proctosol-HC |
87,127 |
11.49 |
1,001.15 |
|
Semester SS18 |
|||
|
Pulmozyme |
64,509 |
2,764.88 |
178,359.67 |
|
Quelicin |
22,785 |
68.93 |
1,570.62 |
|
Remicade |
42,768 |
3,022.90 |
129,283.31 |
|
Retin-A Micro |
25,081 |
417.39 |
10,468.57 |
|
Revlimid |
10,670 |
8,842.62 |
94,350.72 |
|
Reyataz |
228,462 |
1,100.65 |
251,457.68 |
|
Sabril |
10,120 |
6,306.84 |
63,825.23 |
|
Seroquel XR |
751,376 |
551.57 |
414,436.25 |
|
Sovaldi |
144 |
28,167.67 |
4,056.14 |
|
Spiriva |
1,089,524 |
278.01 |
302,903.95 |
|
Stribild |
38,611 |
2,384.84 |
92,080.87 |
|
Suboxone |
1,426,840 |
256.97 |
366,652.84 |
|
Symbicort |
858,102 |
234.30 |
201,057.26 |
|
Synagis |
174,691 |
2,215.36 |
387,004.17 |
|
Tecfidera |
7,213 |
4,534.59 |
32,708.03 |
|
Tivicay |
2,908 |
1,322.77 |
3,846.61 |
|
Truvada |
423,082 |
1,234.59 |
522,333.51 |
|
Ventolin HFA |
5,331,556 |
43.73 |
233,146.29 |
|
Vyvanse |
3,078,059 |
181.69 |
559,256.43 |
|
Xifaxan |
60,711 |
1,141.70 |
69,313.95 |
|
Xolair |
38,655 |
2,306.19 |
89,145.79 |
Do you want to plot the top 10 values (yes/no)? yes
Enter a year to process (‘q’ to terminate): q
Grading Rubrics
General Requirements:
__0__ (5 pts) Coding Standard 1-9
(descriptive comments, function headers, etc…)
Implementation:
__0__ (7 pts) read_data function test
__0__ (7 pts) get_year_list function test
__0__ (7 pts) top_ten_list function test
__0__ (6 pts) Pass Test1
__0__ (6 pts) Pass Test2
__0__ (6 pts) Pass Test3 (Plot Test)
__0__ (6 pts) Pass Test4 (Blind Test)
