[Solved] CSE231-Project 7-List and Tuples and File manipulation

Project 07.

Assignment Overview

• List and Tuples
• 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/StatisticsTrends-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

1. You must implement the following functions:
2. open_file() prompts the user to enter a filename. The program will try to open a commaseparated 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.
3. 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)

1. 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.
2. 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).
3. 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.
4. 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!)
5. Requirements
6. Use sorted() and itemgetter() 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.

from operator import itemgetter

sorted_lst = sorted(num_list, key=itemgetter(x,y), reverse=True)

1. 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}:
   1. The header should be centered on 80 spaces
   2. Medication Brand Name = 35 spaces, left justified

• Prescription = 15 spaces, right justified with comma between 3 digits

1. Average Prescription Cost = 20 spaces, right justified, 2 decimal digits
2. Total spending by Medicaid = 15 spaces, right justified, 2 decimal digits, with comma between 3 digits (this value is in thousands)
3. 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.

1. 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.

1. 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

Enter a year to process (‘q’ to terminate): 2011

Drug spending by Medicaid in 2011

Medication Prescriptions Prescription Cost Total

Abilify 3,007,841 570.43 1,715,769.09

Adderall XR 1,613,783 233.26 376,431.03

Advair Diskus 2,462,514 235.10 578,947.35

Carbamazepine 618,588 18.49 11,436.85

Clobetasol Propionate 379,057 26.80 10,157.35

Flovent HFA 1,924,032 145.82 280,559.01

Humalog 602,919 213.18 128,527.27

Invega 380,435 745.57 283,641.53

Lantus 2,204,518 186.34 410,789.44

Lyrica 1,080,100 192.62 208,052.63

Methylphenidate ER 1,332,576 169.62 226,032.29

Morphine Sulfate 576,161 34.87 20,089.79

Proair HFA 4,784,692 46.38 221,936.93

Seroquel XR 952,900 389.96 371,592.40

Spiriva 936,931 229.98 215,473.65

Suboxone 1,198,265 265.43 318,060.14 Symbicort 621,462 207.16 128,740.15

Truvada 427,891 1,068.79 457,327.61

Ventolin HFA 4,889,379 40.72 199,072.30 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!

Enter a year to process (‘q’ to terminate): 2015

Drug spending by Medicaid in 2015

Medication Prescriptions Prescription Cost Total

Abilify 2,074,321 978.44 2,029,596.06

Adderall XR 1,805,993 248.65 449,064.90

Advair Diskus 1,758,551 330.32 580,892.33

Advate 16,979 20,828.38 353,645.10

Anucort-HC 18,364 273.61 5,024.49

Aripiprazole 947,738 638.50 605,129.20

Ativan 7,168 734.32 5,263.61

Atripla 265,692 2,269.63 603,023.28

Avastin 144,610 1,297.06 187,568.41

Carbamazepine 585,130 64.50 37,741.07

Clindamycin Phos-Benzoyl Perox 10,413 630.46 6,564.98

Clobetasol Propionate 741,509 193.99 143,846.67

Complera 138,938 2,255.99 313,442.46

Copaxone 51,497 5,418.03 279,012.52

Daraprim 2,585 6,075.41 15,704.94

Demerol 48,806 100.42 4,900.98

Econazole Nitrate 218,702 211.28 46,206.96

Enbrel 136,508 3,204.75 437,474.12

Epitol 58,483 46.27 2,706.08

Epzicom 117,317 1,205.16 141,386.15

Fentanyl Citrate 474,760 116.52 55,317.74

Flovent HFA 2,264,825 194.88 441,361.06

Gleevec 20,001 9,528.69 190,583.27

Glumetza 7,873 2,048.88 16,130.82

Granisetron HCl 43,149 180.47 7,787.08

H.P. Acthar 3,278 44,101.85 144,565.87 Harvoni 78,467 27,720.64 2,175,155.84

Herceptin 53,136 3,290.87 174,863.75

Humalog 941,420 377.72 355,593.19

Humira 219,266 3,673.43 805,458.62

Hydroxychloroquine Sulfate 545,452 110.00 60,001.01

Invega 526,070 1,380.61 726,297.32

Isentress 188,181 1,229.77 231,419.27 Lantus 3,651,839 393.11 1,435,574.72

Latuda 715,975 881.91 631,424.75

Lyrica 1,356,527 370.87 503,093.90

Mestinon 7,268 1,070.04 7,777.04

Methylphenidate ER 3,576,101 195.86 700,422.21

Morphine Sulfate 662,978 62.43 41,389.73

Naproxen Sodium 370,485 27.33 10,126.81

Neulasta 75,594 3,729.84 281,953.81

Norditropin Flexpro 79,156 3,473.33 274,934.63

Novoseven RT 4,444 67,098.11 298,184.00

Phenergan 10,047 255.73 2,569.27

Prezista 265,823 1,259.27 334,742.62

Proair HFA 6,690,081 58.56 391,742.23

Proctosol-HC 146,493 49.12 7,195.57

Pulmozyme 66,738 3,356.32 223,994.30

Quelicin 29,416 223.57 6,576.41

Remicade 52,764 3,576.20 188,694.62 Retin-A Micro 1,667 1,953.85 3,257.07

Revlimid 14,475 9,954.78 144,095.51

Reyataz 178,383 1,303.60 232,540.89

Sabril 13,297 9,962.99 132,477.85 Seroquel XR 743,257 650.00 483,117.34

Sovaldi 27,228 22,713.59 618,445.60

Spiriva 1,255,363 324.15 406,925.46

Stribild 176,445 2,580.10 455,245.06

Suboxone 2,051,871 233.41 478,918.14

Symbicort 1,682,405 270.45 455,006.23

Synagis 100,034 2,338.19 233,898.45

Tecfidera 39,697 5,505.27 218,542.81

Tivicay 132,094 1,457.12 192,476.94

Triumeq 81,914 2,422.67 198,450.69

Truvada 527,386 1,396.28 736,377.75 Ventolin HFA 7,227,336 49.25 355,949.41

Viekira Pak 8,612 24,413.83 210,251.89

Vyvanse 3,496,935 223.81 782,651.74

Xifaxan 93,982 1,441.23 135,449.72 Xolair 55,631 2,501.20 139,144.34

Do you want to plot the top 10 values (yes/no)? no

Enter a year to process (‘q’ to terminate): 2012

Drug spending by Medicaid in 2012

Medication Prescriptions Prescription Cost Total

Abilify 2,934,565 642.71 1,886,082.01

Adderall XR 1,511,503 243.27 367,706.53

Advair Diskus 2,359,382 251.29 592,900.57

Advate 7,514 21,674.67 162,863.51 Anucort-HC 4,186 21.75 91.04

Ativan 19,385 147.53 2,859.96

Atripla 280,155 1,789.12 501,231.12

Avastin 93,763 1,506.96 141,296.63

Carbamazepine 617,133 17.96 11,084.27

Clindamycin Phos-Benzoyl Perox 3,149 149.21 469.86

Clobetasol Propionate 448,435 33.37 14,965.04

Complera 39,684 1,877.01 74,487.19 Copaxone 51,778 4,052.88 209,850.07

Daraprim 3,944 482.90 1,904.57

Demerol 64,621 24.61 1,590.54 Econazole Nitrate 170,593 23.28 3,971.12

Enbrel 104,737 2,120.79 222,125.19

Epitol 40,968 6.75 276.57

Epzicom 121,222 979.45 118,730.83

Fentanyl Citrate 285,140 55.18 15,733.57

Flovent HFA 2,071,046 148.45 307,448.30

Gleevec 16,077 5,910.02 95,015.38

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

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 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