├── Programming Assignment 1 - Air Pollution ├── complete.R ├── corr.R ├── pollutantmean.R ├── rprog-data-specdata.zip ├── specdata │ ├── .Rhistory │ ├── 001.csv │ ├── 002.csv │ ├── 003.csv │ ├── 004.csv │ ├── 005.csv │ ├── 006.csv │ ├── 007.csv │ ├── 008.csv │ ├── 009.csv │ ├── 010.csv │ ├── 011.csv │ ├── 012.csv │ ├── 013.csv │ ├── 014.csv │ ├── 015.csv │ ├── 016.csv │ ├── 017.csv │ ├── 018.csv │ ├── 019.csv │ ├── 020.csv │ ├── 021.csv │ ├── 022.csv │ ├── 023.csv │ ├── 024.csv │ ├── 025.csv │ ├── 026.csv │ ├── 027.csv │ ├── 028.csv │ ├── 029.csv │ ├── 030.csv │ ├── 031.csv │ ├── 032.csv │ ├── 033.csv │ ├── 034.csv │ ├── 035.csv │ ├── 036.csv │ ├── 037.csv │ ├── 038.csv │ ├── 039.csv │ ├── 040.csv │ ├── 041.csv │ ├── 042.csv │ ├── 043.csv │ ├── 044.csv │ ├── 045.csv │ ├── 046.csv │ ├── 047.csv │ ├── 048.csv │ ├── 049.csv │ ├── 050.csv │ ├── 051.csv │ ├── 052.csv │ ├── 053.csv │ ├── 054.csv │ ├── 055.csv │ ├── 056.csv │ ├── 057.csv │ ├── 058.csv │ ├── 059.csv │ ├── 060.csv │ ├── 061.csv │ ├── 062.csv │ ├── 063.csv │ ├── 064.csv │ ├── 065.csv │ ├── 066.csv │ ├── 067.csv │ ├── 068.csv │ ├── 069.csv │ ├── 070.csv │ ├── 071.csv │ ├── 072.csv │ ├── 073.csv │ ├── 074.csv │ ├── 075.csv │ ├── 076.csv │ ├── 077.csv │ ├── 078.csv │ ├── 079.csv │ ├── 080.csv │ ├── 081.csv │ ├── 082.csv │ ├── 083.csv │ ├── 084.csv │ ├── 085.csv │ ├── 086.csv │ ├── 087.csv │ ├── 088.csv │ ├── 089.csv │ ├── 090.csv │ ├── 091.csv │ ├── 092.csv │ ├── 093.csv │ ├── 094.csv │ ├── 095.csv │ ├── 096.csv │ ├── 097.csv │ ├── 098.csv │ ├── 099.csv │ ├── 100.csv │ ├── 101.csv │ ├── 102.csv │ ├── 103.csv │ ├── 104.csv │ ├── 105.csv │ ├── 106.csv │ ├── 107.csv │ ├── 108.csv │ ├── 109.csv │ ├── 110.csv │ ├── 111.csv │ ├── 112.csv │ ├── 113.csv │ ├── 114.csv │ ├── 115.csv │ ├── 116.csv │ ├── 117.csv │ ├── 118.csv │ ├── 119.csv │ ├── 120.csv │ ├── 121.csv │ ├── 122.csv │ ├── 123.csv │ ├── 124.csv │ ├── 125.csv │ ├── 126.csv │ ├── 127.csv │ ├── 128.csv │ ├── 129.csv │ ├── 130.csv │ ├── 131.csv │ ├── 132.csv │ ├── 133.csv │ ├── 134.csv │ ├── 135.csv │ ├── 136.csv │ ├── 137.csv │ ├── 138.csv │ ├── 139.csv │ ├── 140.csv │ ├── 141.csv │ ├── 142.csv │ ├── 143.csv │ ├── 144.csv │ ├── 145.csv │ ├── 146.csv │ ├── 147.csv │ ├── 148.csv │ ├── 149.csv │ ├── 150.csv │ ├── 151.csv │ ├── 152.csv │ ├── 153.csv │ ├── 154.csv │ ├── 155.csv │ ├── 156.csv │ ├── 157.csv │ ├── 158.csv │ ├── 159.csv │ ├── 160.csv │ ├── 161.csv │ ├── 162.csv │ ├── 163.csv │ ├── 164.csv │ ├── 165.csv │ ├── 166.csv │ ├── 167.csv │ ├── 168.csv │ ├── 169.csv │ ├── 170.csv │ ├── 171.csv │ ├── 172.csv │ ├── 173.csv │ ├── 174.csv │ ├── 175.csv │ ├── 176.csv │ ├── 177.csv │ ├── 178.csv │ ├── 179.csv │ ├── 180.csv │ ├── 181.csv │ ├── 182.csv │ ├── 183.csv │ ├── 184.csv │ ├── 185.csv │ ├── 186.csv │ ├── 187.csv │ ├── 188.csv │ ├── 189.csv │ ├── 190.csv │ ├── 191.csv │ ├── 192.csv │ ├── 193.csv │ ├── 194.csv │ ├── 195.csv │ ├── 196.csv │ ├── 197.csv │ ├── 198.csv │ ├── 199.csv │ ├── 200.csv │ ├── 201.csv │ ├── 202.csv │ ├── 203.csv │ ├── 204.csv │ ├── 205.csv │ ├── 206.csv │ ├── 207.csv │ ├── 208.csv │ ├── 209.csv │ ├── 210.csv │ ├── 211.csv │ ├── 212.csv │ ├── 213.csv │ ├── 214.csv │ ├── 215.csv │ ├── 216.csv │ ├── 217.csv │ ├── 218.csv │ ├── 219.csv │ ├── 220.csv │ ├── 221.csv │ ├── 222.csv │ ├── 223.csv │ ├── 224.csv │ ├── 225.csv │ ├── 226.csv │ ├── 227.csv │ ├── 228.csv │ ├── 229.csv │ ├── 230.csv │ ├── 231.csv │ ├── 232.csv │ ├── 233.csv │ ├── 234.csv │ ├── 235.csv │ ├── 236.csv │ ├── 237.csv │ ├── 238.csv │ ├── 239.csv │ ├── 240.csv │ ├── 241.csv │ ├── 242.csv │ ├── 243.csv │ ├── 244.csv │ ├── 245.csv │ ├── 246.csv │ ├── 247.csv │ ├── 248.csv │ ├── 249.csv │ ├── 250.csv │ ├── 251.csv │ ├── 252.csv │ ├── 253.csv │ ├── 254.csv │ ├── 255.csv │ ├── 256.csv │ ├── 257.csv │ ├── 258.csv │ ├── 259.csv │ ├── 260.csv │ ├── 261.csv │ ├── 262.csv │ ├── 263.csv │ ├── 264.csv │ ├── 265.csv │ ├── 266.csv │ ├── 267.csv │ ├── 268.csv │ ├── 269.csv │ ├── 270.csv │ ├── 271.csv │ ├── 272.csv │ ├── 273.csv │ ├── 274.csv │ ├── 275.csv │ ├── 276.csv │ ├── 277.csv │ ├── 278.csv │ ├── 279.csv │ ├── 280.csv │ ├── 281.csv │ ├── 282.csv │ ├── 283.csv │ ├── 284.csv │ ├── 285.csv │ ├── 286.csv │ ├── 287.csv │ ├── 288.csv │ ├── 289.csv │ ├── 290.csv │ ├── 291.csv │ ├── 292.csv │ ├── 293.csv │ ├── 294.csv │ ├── 295.csv │ ├── 296.csv │ ├── 297.csv │ ├── 298.csv │ ├── 299.csv │ ├── 300.csv │ ├── 301.csv │ ├── 302.csv │ ├── 303.csv │ ├── 304.csv │ ├── 305.csv │ ├── 306.csv │ ├── 307.csv │ ├── 308.csv │ ├── 309.csv │ ├── 310.csv │ ├── 311.csv │ ├── 312.csv │ ├── 313.csv │ ├── 314.csv │ ├── 315.csv │ ├── 316.csv │ ├── 317.csv │ ├── 318.csv │ ├── 319.csv │ ├── 320.csv │ ├── 321.csv │ ├── 322.csv │ ├── 323.csv │ ├── 324.csv │ ├── 325.csv │ ├── 326.csv │ ├── 327.csv │ ├── 328.csv │ ├── 329.csv │ ├── 330.csv │ ├── 331.csv │ ├── 332.csv │ ├── complete.R │ ├── corr.R │ ├── pollutantmean.R │ └── submitscript1.R └── submitscript1.R ├── Programming Assignment 2 - Lexical Scoping ├── Here's how makeVector and cachemean work.html ├── Here's how makeVector and cachemean work_files │ ├── 1.jpg │ ├── 172.jpg │ ├── 204.min.js │ ├── AAizenman.jpg │ ├── FaceShot3.jpg │ ├── IMG_5048.jpg │ ├── MathJax.js │ ├── course.css │ ├── flexjoinLastChanceModal.html.js │ ├── ga.js │ ├── header(1).js │ ├── header.html.js │ ├── header.js │ ├── headshot.png │ ├── info │ ├── jdeines.jpg │ ├── logo │ ├── readme.js │ ├── require.js │ ├── routes.js │ ├── select2.css │ ├── sidebar(1).js │ ├── sidebar.html.js │ ├── sidebar.js │ ├── signatureTrackLastChanceModal.html.js │ ├── signature_track.js │ ├── spark.forum.hg.css │ ├── spark.main.css │ ├── student-page.html.js │ ├── student-page.js │ ├── university_logo │ ├── util.js │ └── widgets.js └── cachematrix.R ├── Programming Assignment 3 - Hospital Quality ├── Submit script │ └── rprog-scripts-submitscript3.R ├── best.R ├── rankall.R ├── rankhospital.R ├── rprog-data-ProgAssignment3-data.zip ├── rprog-data-ProgAssignment3-data │ ├── .Rhistory │ ├── Hospital_Revised_Flatfiles.pdf │ ├── best.R │ ├── hospital-data.csv │ ├── outcome-of-care-measures.csv │ ├── rankall.R │ ├── rankhospital.R │ └── submitscript3.R └── rprog-doc-ProgAssignment3.pdf ├── README.md └── swirl Programming Assignment ├── Assignment Details Coursera.html └── Assignment Details Coursera_files ├── 204.min.js ├── MathJax.js ├── course.css ├── flexjoinLastChanceModal.html.js ├── ga.js ├── header(1).js ├── header.html.js ├── header.js ├── jquery.js ├── loadOrRefreshMathJax.js ├── logo ├── readme.js ├── require.js ├── routes.js ├── sidebar(1).js ├── sidebar.html.js ├── sidebar.js ├── signatureTrackLastChanceModal.html.js ├── signature_track.js ├── spark.main.css ├── student-page.html.js ├── student-page.js ├── university_logo └── util.js /Programming Assignment 1 - Air Pollution/complete.R: -------------------------------------------------------------------------------- 1 | complete <- function(directory, id = 1:332) { 2 | ## 'directory' is a character vector of length 1 indicating 3 | ## the location of the CSV files 4 | 5 | ## 'id' is an integer vector indicating the monitor ID numbers 6 | ## to be used 7 | 8 | ## Return a data frame of the form: 9 | ## id nobs 10 | ## 1 117 11 | ## 2 1041 12 | ## ... 13 | ## where 'id' is the monitor ID number and 'nobs' is the 14 | ## number of complete cases 15 | 16 | filename <- vector(mode="character", length=length(id)) 17 | for(i in seq_along(id)) { 18 | x <- id[i] 19 | id_string <- toString(x) 20 | if (x >= 1 && x <= 9) { 21 | monitor <- paste("00", id_string, ".csv", sep="") 22 | } 23 | else if (x >= 10 && x <= 99) { 24 | id_string <- toString(x) 25 | monitor <- paste("0", id_string, ".csv", sep="") 26 | } 27 | else { 28 | id_string <- toString(x) 29 | monitor <- paste(id_string, ".csv", sep="") 30 | } 31 | filename[i] <- monitor 32 | #print(monitor) 33 | } 34 | 35 | #accumulator <- 0 36 | nobs <- vector(mode="integer", length=length(id)) 37 | for(i in seq(filename)) { 38 | airquality <- read.csv(filename[i]) 39 | good <- complete.cases(airquality) 40 | airquality <- airquality[good, ] 41 | nobs[i] <- nrow(airquality) 42 | #accumulator <- accumulator + sum(airquality[pollutant], na.rm = TRUE) 43 | } 44 | result = data.frame(id, nobs) 45 | result 46 | } -------------------------------------------------------------------------------- /Programming Assignment 1 - Air Pollution/corr.R: -------------------------------------------------------------------------------- 1 | corr <- function(directory, threshold = 0) { 2 | ## 'directory' is a character vector of length 1 indicating 3 | ## the location of the CSV files 4 | 5 | ## 'threshold' is a numeric vector of length 1 indicating the 6 | ## number of completely observed observations (on all 7 | ## variables) required to compute the correlation between 8 | ## nitrate and sulfate; the default is 0 9 | 10 | ## Return a numeric vector of correlations 11 | 12 | id = 1:332 13 | filename <- vector(mode="character", length=length(id)) 14 | for(i in seq_along(id)) { 15 | x <- id[i] 16 | id_string <- toString(x) 17 | if (x >= 1 && x <= 9) { 18 | monitor <- paste("00", id_string, ".csv", sep="") 19 | } 20 | else if (x >= 10 && x <= 99) { 21 | id_string <- toString(x) 22 | monitor <- paste("0", id_string, ".csv", sep="") 23 | } 24 | else { 25 | id_string <- toString(x) 26 | monitor <- paste(id_string, ".csv", sep="") 27 | } 28 | filename[i] <- monitor 29 | } 30 | #print(filename) 31 | 32 | #empty vector 33 | result <-vector(mode="numeric", length=0) 34 | for(i in seq(filename)) { 35 | airquality <- read.csv(filename[i]) 36 | good <- complete.cases(airquality) 37 | airquality <- airquality[good, ] 38 | if (nrow(airquality) > threshold) { 39 | # We need [[]] around pollutant instead of [] since airquality["sulfate"] 40 | # is a data.frame but we need a vector here. Hence, [[]]. Please note that using either 41 | #[[]] or [] gives the same results as the test cases 42 | correlation <- cor(airquality[["sulfate"]], airquality[["nitrate"]]) 43 | result <- append(result, correlation) 44 | #print(correlation) 45 | } 46 | } 47 | result 48 | } 49 | -------------------------------------------------------------------------------- /Programming Assignment 1 - Air Pollution/pollutantmean.R: -------------------------------------------------------------------------------- 1 | pollutantmean <- function(directory, pollutant, id = 1:332) { 2 | ## 'directory' is a character vector of length 1 indicating 3 | ## the location of the CSV files 4 | 5 | ## 'pollutant' is a character vector of length 1 indicating 6 | ## the name of the pollutant for which we will calculate the 7 | ## mean; either "sulfate" or "nitrate". 8 | 9 | ## 'id' is an integer vector indicating the monitor ID numbers 10 | ## to be used 11 | 12 | ## Return the mean of the pollutant across all monitors list 13 | ## in the 'id' vector (ignoring NA values) 14 | 15 | filename <- vector(mode="character", length=length(id)) 16 | for(i in seq_along(id)) { 17 | x <- id[i] 18 | id_string <- toString(x) 19 | if (x >= 1 && x <= 9) { 20 | monitor <- paste("00", id_string, ".csv", sep="") 21 | } 22 | else if (x >= 10 && x <= 99) { 23 | id_string <- toString(x) 24 | monitor <- paste("0", id_string, ".csv", sep="") 25 | } 26 | else { 27 | id_string <- toString(x) 28 | monitor <- paste(id_string, ".csv", sep="") 29 | } 30 | filename[i] <- monitor 31 | #print(monitor) 32 | } 33 | 34 | accumulator <- 0 35 | total <- 0 36 | for(i in filename) { 37 | airquality <- read.csv(i) 38 | good <- complete.cases(airquality[pollutant]) 39 | #good <- complete.cases(airquality[[pollutant]]) 40 | airquality <- airquality[good, ] 41 | total <- total + nrow(airquality) 42 | #accumulator <- accumulator + sum(airquality[pollutant], na.rm = TRUE) 43 | # We need [[]] around pollutant instead of [] since airquality[pollutant] 44 | # is a data.frame but we need a vector here. Please note that using either 45 | #[[]] or [] gives the same results as the test cases but only [[]] successfully 46 | #passes the submit() script 47 | accumulator <- accumulator + sum(airquality[[pollutant]], na.rm = TRUE) 48 | } 49 | accumulator/total 50 | } 51 | -------------------------------------------------------------------------------- /Programming Assignment 1 - Air Pollution/rprog-data-specdata.zip: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/muntasir2165/R-Programming-Assignments-1--2--and-3-/3dd6003062ddf6851a2baa06b04ed96e9eabfb60/Programming Assignment 1 - Air Pollution/rprog-data-specdata.zip -------------------------------------------------------------------------------- /Programming Assignment 1 - Air Pollution/specdata/040.csv: -------------------------------------------------------------------------------- 1 | "Date","sulfate","nitrate","ID" 2 | "2010-01-01",NA,NA,40 3 | "2010-01-02",0.653,6.6,40 4 | "2010-01-03",NA,NA,40 5 | "2010-01-04",NA,NA,40 6 | "2010-01-05",NA,NA,40 7 | "2010-01-06",NA,NA,40 8 | "2010-01-07",NA,NA,40 9 | "2010-01-08",1.13,6.86,40 10 | "2010-01-09",NA,NA,40 11 | "2010-01-10",NA,NA,40 12 | "2010-01-11",NA,NA,40 13 | "2010-01-12",NA,NA,40 14 | "2010-01-13",NA,NA,40 15 | "2010-01-14",0.488,3.93,40 16 | "2010-01-15",NA,NA,40 17 | "2010-01-16",NA,NA,40 18 | "2010-01-17",NA,NA,40 19 | "2010-01-18",NA,NA,40 20 | "2010-01-19",NA,NA,40 21 | "2010-01-20",0.243,1.88,40 22 | "2010-01-21",NA,NA,40 23 | "2010-01-22",NA,NA,40 24 | "2010-01-23",NA,NA,40 25 | "2010-01-24",NA,NA,40 26 | "2010-01-25",NA,NA,40 27 | "2010-01-26",0.615,3.34,40 28 | "2010-01-27",NA,NA,40 29 | "2010-01-28",NA,NA,40 30 | "2010-01-29",NA,NA,40 31 | "2010-01-30",NA,NA,40 32 | "2010-01-31",NA,NA,40 33 | "2010-02-01",0.511,1.91,40 34 | "2010-02-02",NA,NA,40 35 | "2010-02-03",NA,NA,40 36 | "2010-02-04",NA,NA,40 37 | "2010-02-05",NA,NA,40 38 | "2010-02-06",NA,NA,40 39 | "2010-02-07",2.11,4.56,40 40 | "2010-02-08",NA,NA,40 41 | "2010-02-09",NA,NA,40 42 | "2010-02-10",NA,NA,40 43 | "2010-02-11",NA,NA,40 44 | "2010-02-12",NA,NA,40 45 | "2010-02-13",0.403,0.283,40 46 | "2010-02-14",NA,NA,40 47 | "2010-02-15",NA,NA,40 48 | "2010-02-16",NA,NA,40 49 | "2010-02-17",1.22,2.88,40 50 | "2010-02-18",NA,NA,40 51 | "2010-02-19",NA,NA,40 52 | "2010-02-20",NA,NA,40 53 | "2010-02-21",NA,NA,40 54 | "2010-02-22",NA,NA,40 55 | "2010-02-23",NA,NA,40 56 | "2010-02-24",NA,NA,40 57 | "2010-02-25",0.787,2.84,40 58 | "2010-02-26",NA,NA,40 59 | "2010-02-27",NA,NA,40 60 | "2010-02-28",NA,NA,40 61 | "2010-03-01",NA,NA,40 62 | "2010-03-02",NA,NA,40 63 | "2010-03-03",0.815,3.81,40 64 | "2010-03-04",NA,NA,40 65 | "2010-03-05",NA,NA,40 66 | "2010-03-06",NA,NA,40 67 | "2010-03-07",NA,NA,40 68 | "2010-03-08",NA,NA,40 69 | "2010-03-09",1.12,0.688,40 70 | "2010-03-10",NA,NA,40 71 | "2010-03-11",NA,NA,40 72 | "2010-03-12",NA,NA,40 73 | "2010-03-13",NA,NA,40 74 | "2010-03-14",NA,NA,40 75 | "2010-03-15",3.27,6.5,40 76 | "2010-03-16",NA,NA,40 77 | "2010-03-17",NA,NA,40 78 | "2010-03-18",NA,NA,40 79 | "2010-03-19",NA,NA,40 80 | "2010-03-20",NA,NA,40 81 | "2010-03-21",0.573,0.321,40 82 | "2010-03-22",NA,NA,40 83 | "2010-03-23",NA,NA,40 84 | "2010-03-24",NA,NA,40 85 | "2010-03-25",NA,NA,40 86 | "2010-03-26",NA,NA,40 87 | "2010-03-27",0.543,0.345,40 88 | "2010-03-28",NA,NA,40 89 | "2010-03-29",NA,NA,40 90 | "2010-03-30",NA,NA,40 91 | "2010-03-31",NA,NA,40 92 | "2010-04-01",NA,NA,40 93 | "2010-04-02",0.372,0.255,40 94 | "2010-04-03",NA,NA,40 95 | "2010-04-04",NA,NA,40 96 | "2010-04-05",NA,NA,40 97 | "2010-04-06",NA,NA,40 98 | "2010-04-07",NA,NA,40 99 | "2010-04-08",0.727,0.623,40 100 | "2010-04-09",NA,NA,40 101 | "2010-04-10",NA,NA,40 102 | "2010-04-11",NA,NA,40 103 | "2010-04-12",NA,NA,40 104 | "2010-04-13",NA,NA,40 105 | "2010-04-14",0.809,0.296,40 106 | "2010-04-15",NA,NA,40 107 | "2010-04-16",NA,NA,40 108 | "2010-04-17",NA,NA,40 109 | "2010-04-18",NA,NA,40 110 | "2010-04-19",NA,NA,40 111 | "2010-04-20",3.04,3.04,40 112 | "2010-04-21",NA,NA,40 113 | "2010-04-22",NA,NA,40 114 | "2010-04-23",NA,NA,40 115 | "2010-04-24",NA,NA,40 116 | "2010-04-25",NA,NA,40 117 | "2010-04-26",NA,NA,40 118 | "2010-04-27",NA,NA,40 119 | "2010-04-28",NA,NA,40 120 | "2010-04-29",NA,NA,40 121 | "2010-04-30",NA,NA,40 122 | "2010-05-01",NA,NA,40 123 | "2010-05-02",NA,NA,40 124 | "2010-05-03",NA,NA,40 125 | "2010-05-04",NA,NA,40 126 | "2010-05-05",0.899,0.75,40 127 | "2010-05-06",NA,NA,40 128 | "2010-05-07",NA,NA,40 129 | "2010-05-08",0.692,1.54,40 130 | "2010-05-09",NA,NA,40 131 | "2010-05-10",NA,NA,40 132 | "2010-05-11",NA,NA,40 133 | "2010-05-12",NA,NA,40 134 | "2010-05-13",NA,NA,40 135 | "2010-05-14",NA,NA,40 136 | "2010-05-15",NA,NA,40 137 | "2010-05-16",NA,NA,40 138 | "2010-05-17",NA,NA,40 139 | "2010-05-18",NA,NA,40 140 | "2010-05-19",NA,NA,40 141 | "2010-05-20",NA,NA,40 142 | "2010-05-21",NA,NA,40 143 | "2010-05-22",NA,NA,40 144 | "2010-05-23",NA,NA,40 145 | 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-------------------------------------------------------------------------------- /Programming Assignment 1 - Air Pollution/specdata/118.csv: -------------------------------------------------------------------------------- 1 | "Date","sulfate","nitrate","ID" 2 | "2001-01-01",NA,NA,118 3 | "2001-01-02",NA,NA,118 4 | "2001-01-03",NA,NA,118 5 | "2001-01-04",NA,NA,118 6 | "2001-01-05",NA,NA,118 7 | "2001-01-06",NA,NA,118 8 | "2001-01-07",NA,NA,118 9 | "2001-01-08",NA,NA,118 10 | "2001-01-09",NA,NA,118 11 | "2001-01-10",NA,NA,118 12 | "2001-01-11",NA,NA,118 13 | "2001-01-12",NA,NA,118 14 | "2001-01-13",NA,NA,118 15 | "2001-01-14",NA,NA,118 16 | "2001-01-15",NA,NA,118 17 | "2001-01-16",NA,NA,118 18 | "2001-01-17",NA,NA,118 19 | "2001-01-18",NA,NA,118 20 | "2001-01-19",NA,NA,118 21 | "2001-01-20",NA,NA,118 22 | "2001-01-21",NA,NA,118 23 | "2001-01-22",NA,NA,118 24 | "2001-01-23",NA,NA,118 25 | "2001-01-24",NA,NA,118 26 | "2001-01-25",NA,NA,118 27 | "2001-01-26",NA,NA,118 28 | 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Assignment 1 - Air Pollution/specdata/162.csv: -------------------------------------------------------------------------------- 1 | "Date","sulfate","nitrate","ID" 2 | "2010-01-01",NA,NA,162 3 | "2010-01-02",NA,NA,162 4 | "2010-01-03",NA,NA,162 5 | "2010-01-04",NA,NA,162 6 | "2010-01-05",NA,NA,162 7 | "2010-01-06",NA,NA,162 8 | "2010-01-07",NA,NA,162 9 | "2010-01-08",NA,NA,162 10 | "2010-01-09",NA,NA,162 11 | "2010-01-10",NA,NA,162 12 | "2010-01-11",NA,NA,162 13 | "2010-01-12",NA,NA,162 14 | "2010-01-13",NA,NA,162 15 | "2010-01-14",NA,NA,162 16 | "2010-01-15",NA,NA,162 17 | "2010-01-16",NA,NA,162 18 | "2010-01-17",NA,NA,162 19 | "2010-01-18",NA,NA,162 20 | "2010-01-19",NA,NA,162 21 | "2010-01-20",NA,NA,162 22 | "2010-01-21",NA,NA,162 23 | "2010-01-22",NA,NA,162 24 | "2010-01-23",NA,NA,162 25 | "2010-01-24",NA,NA,162 26 | "2010-01-25",NA,NA,162 27 | "2010-01-26",NA,NA,162 28 | "2010-01-27",NA,NA,162 29 | "2010-01-28",NA,NA,162 30 | "2010-01-29",NA,NA,162 31 | "2010-01-30",NA,NA,162 32 | 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"2001-11-05",NA,NA,251 311 | "2001-11-06",NA,NA,251 312 | "2001-11-07",NA,NA,251 313 | "2001-11-08",NA,NA,251 314 | "2001-11-09",NA,NA,251 315 | "2001-11-10",NA,NA,251 316 | "2001-11-11",NA,NA,251 317 | "2001-11-12",NA,NA,251 318 | "2001-11-13",NA,NA,251 319 | "2001-11-14",NA,NA,251 320 | "2001-11-15",NA,NA,251 321 | "2001-11-16",NA,NA,251 322 | "2001-11-17",NA,NA,251 323 | "2001-11-18",NA,NA,251 324 | "2001-11-19",NA,NA,251 325 | "2001-11-20",NA,NA,251 326 | "2001-11-21",NA,NA,251 327 | "2001-11-22",NA,NA,251 328 | "2001-11-23",NA,NA,251 329 | "2001-11-24",NA,NA,251 330 | "2001-11-25",NA,NA,251 331 | "2001-11-26",NA,NA,251 332 | "2001-11-27",NA,NA,251 333 | "2001-11-28",NA,NA,251 334 | "2001-11-29",NA,NA,251 335 | "2001-11-30",NA,NA,251 336 | "2001-12-01",NA,NA,251 337 | "2001-12-02",NA,NA,251 338 | "2001-12-03",NA,NA,251 339 | "2001-12-04",NA,NA,251 340 | "2001-12-05",NA,NA,251 341 | "2001-12-06",NA,NA,251 342 | "2001-12-07",NA,NA,251 343 | "2001-12-08",NA,NA,251 344 | "2001-12-09",NA,NA,251 345 | "2001-12-10",NA,NA,251 346 | "2001-12-11",NA,NA,251 347 | "2001-12-12",NA,NA,251 348 | "2001-12-13",NA,NA,251 349 | "2001-12-14",NA,NA,251 350 | "2001-12-15",NA,NA,251 351 | "2001-12-16",NA,NA,251 352 | "2001-12-17",NA,NA,251 353 | "2001-12-18",NA,NA,251 354 | "2001-12-19",NA,NA,251 355 | "2001-12-20",NA,NA,251 356 | "2001-12-21",NA,NA,251 357 | "2001-12-22",NA,NA,251 358 | "2001-12-23",NA,NA,251 359 | "2001-12-24",NA,NA,251 360 | "2001-12-25",NA,NA,251 361 | "2001-12-26",NA,NA,251 362 | "2001-12-27",NA,NA,251 363 | "2001-12-28",NA,NA,251 364 | "2001-12-29",NA,NA,251 365 | "2001-12-30",NA,NA,251 366 | "2001-12-31",NA,NA,251 367 | -------------------------------------------------------------------------------- /Programming Assignment 1 - Air Pollution/specdata/complete.R: -------------------------------------------------------------------------------- 1 | complete <- function(directory, id = 1:332) { 2 | ## 'directory' is a character vector of length 1 indicating 3 | ## the location of the CSV files 4 | 5 | ## 'id' is an integer vector indicating the monitor ID numbers 6 | ## to be used 7 | 8 | ## Return a data frame of the form: 9 | ## id nobs 10 | ## 1 117 11 | ## 2 1041 12 | ## ... 13 | ## where 'id' is the monitor ID number and 'nobs' is the 14 | ## number of complete cases 15 | 16 | filename <- vector(mode="character", length=length(id)) 17 | for(i in seq_along(id)) { 18 | x <- id[i] 19 | id_string <- toString(x) 20 | if (x >= 1 && x <= 9) { 21 | monitor <- paste("00", id_string, ".csv", sep="") 22 | } 23 | else if (x >= 10 && x <= 99) { 24 | id_string <- toString(x) 25 | monitor <- paste("0", id_string, ".csv", sep="") 26 | } 27 | else { 28 | id_string <- toString(x) 29 | monitor <- paste(id_string, ".csv", sep="") 30 | } 31 | filename[i] <- monitor 32 | #print(monitor) 33 | } 34 | 35 | #accumulator <- 0 36 | nobs <- vector(mode="integer", length=length(id)) 37 | for(i in seq(filename)) { 38 | airquality <- read.csv(filename[i]) 39 | good <- complete.cases(airquality) 40 | airquality <- airquality[good, ] 41 | nobs[i] <- nrow(airquality) 42 | #accumulator <- accumulator + sum(airquality[pollutant], na.rm = TRUE) 43 | } 44 | result = data.frame(id, nobs) 45 | result 46 | } -------------------------------------------------------------------------------- /Programming Assignment 1 - Air Pollution/specdata/corr.R: -------------------------------------------------------------------------------- 1 | corr <- function(directory, threshold = 0) { 2 | ## 'directory' is a character vector of length 1 indicating 3 | ## the location of the CSV files 4 | 5 | ## 'threshold' is a numeric vector of length 1 indicating the 6 | ## number of completely observed observations (on all 7 | ## variables) required to compute the correlation between 8 | ## nitrate and sulfate; the default is 0 9 | 10 | ## Return a numeric vector of correlations 11 | 12 | id = 1:332 13 | filename <- vector(mode="character", length=length(id)) 14 | for(i in seq_along(id)) { 15 | x <- id[i] 16 | id_string <- toString(x) 17 | if (x >= 1 && x <= 9) { 18 | monitor <- paste("00", id_string, ".csv", sep="") 19 | } 20 | else if (x >= 10 && x <= 99) { 21 | id_string <- toString(x) 22 | monitor <- paste("0", id_string, ".csv", sep="") 23 | } 24 | else { 25 | id_string <- toString(x) 26 | monitor <- paste(id_string, ".csv", sep="") 27 | } 28 | filename[i] <- monitor 29 | } 30 | #print(filename) 31 | 32 | #empty vector 33 | result <-vector(mode="numeric", length=0) 34 | for(i in seq(filename)) { 35 | airquality <- read.csv(filename[i]) 36 | good <- complete.cases(airquality) 37 | airquality <- airquality[good, ] 38 | if (nrow(airquality) > threshold) { 39 | # We need [[]] around pollutant instead of [] since airquality["sulfate"] 40 | # is a data.frame but we need a vector here. Hence, [[]]. Please note that using either 41 | #[[]] or [] gives the same results as the test cases 42 | correlation <- cor(airquality[["sulfate"]], airquality[["nitrate"]]) 43 | result <- append(result, correlation) 44 | #print(correlation) 45 | } 46 | } 47 | result 48 | } 49 | -------------------------------------------------------------------------------- /Programming Assignment 1 - Air Pollution/specdata/pollutantmean.R: -------------------------------------------------------------------------------- 1 | pollutantmean <- function(directory, pollutant, id = 1:332) { 2 | ## 'directory' is a character vector of length 1 indicating 3 | ## the location of the CSV files 4 | 5 | ## 'pollutant' is a character vector of length 1 indicating 6 | ## the name of the pollutant for which we will calculate the 7 | ## mean; either "sulfate" or "nitrate". 8 | 9 | ## 'id' is an integer vector indicating the monitor ID numbers 10 | ## to be used 11 | 12 | ## Return the mean of the pollutant across all monitors list 13 | ## in the 'id' vector (ignoring NA values) 14 | 15 | filename <- vector(mode="character", length=length(id)) 16 | for(i in seq_along(id)) { 17 | x <- id[i] 18 | id_string <- toString(x) 19 | if (x >= 1 && x <= 9) { 20 | monitor <- paste("00", id_string, ".csv", sep="") 21 | } 22 | else if (x >= 10 && x <= 99) { 23 | id_string <- toString(x) 24 | monitor <- paste("0", id_string, ".csv", sep="") 25 | } 26 | else { 27 | id_string <- toString(x) 28 | monitor <- paste(id_string, ".csv", sep="") 29 | } 30 | filename[i] <- monitor 31 | #print(monitor) 32 | } 33 | 34 | accumulator <- 0 35 | total <- 0 36 | for(i in filename) { 37 | airquality <- read.csv(i) 38 | good <- complete.cases(airquality[pollutant]) 39 | #good <- complete.cases(airquality[[pollutant]]) 40 | airquality <- airquality[good, ] 41 | total <- total + nrow(airquality) 42 | #accumulator <- accumulator + sum(airquality[pollutant], na.rm = TRUE) 43 | # We need [[]] around pollutant instead of [] since airquality[pollutant] 44 | # is a data.frame but we need a vector here. Please note that using either 45 | #[[]] or [] gives the same results as the test cases but only [[]] successfully 46 | #passes the submit() script 47 | accumulator <- accumulator + sum(airquality[[pollutant]], na.rm = TRUE) 48 | } 49 | accumulator/total 50 | } 51 | -------------------------------------------------------------------------------- /Programming Assignment 1 - Air Pollution/specdata/submitscript1.R: -------------------------------------------------------------------------------- 1 | checkPkgs <- function() { 2 | pkg.inst <- installed.packages() 3 | pkgs <- c("RCurl", "digest") 4 | have.pkg <- pkgs %in% rownames(pkg.inst) 5 | 6 | if(any(!have.pkg)) { 7 | cat("Some packages need to be installed\n") 8 | r <- readline("Install necessary packages [y/n]? ") 9 | if(tolower(r) == "y") { 10 | need <- pkgs[!have.pkg] 11 | message("installing packages ", 12 | paste(need, collapse = ", ")) 13 | install.packages(need) 14 | } 15 | } 16 | } 17 | 18 | checkPkgs() 19 | 20 | CLASS <- "rprog-003" 21 | challenge.url <- paste("http://class.coursera.org", CLASS, 22 | "assignment/challenge", sep = "/") 23 | submit.url <- paste("http://class.coursera.org", CLASS, 24 | "assignment/submit", sep = "/") 25 | 26 | loginPrompt <- function() { 27 | email <- readline("Submission login (email): ") 28 | passwd <- readline("Submission password: ") 29 | r <- list(email = email, passwd = passwd) 30 | assign(".CourseraLogin", r, globalenv()) 31 | invisible(r) 32 | } 33 | 34 | submit <- function(manual = FALSE, resetLogin = FALSE) { 35 | library(RCurl) 36 | library(digest) 37 | if(!manual) { 38 | if(exists(".CourseraLogin") && !resetLogin) 39 | cred <- get(".CourseraLogin") 40 | else 41 | cred <- loginPrompt() 42 | if(!is.list(cred) || !(names(cred) %in% c("email", "passwd"))) 43 | stop("problem with login/password") 44 | email <- cred$email 45 | password <- cred$passwd 46 | } 47 | ## Prompt Submission Part 48 | sid <- partPrompt() 49 | 50 | ## Get output 51 | output <- getOutput(sid) 52 | 53 | if(!manual) { 54 | ## Get challenge 55 | ch <- getChallenge(email) 56 | 57 | ## Attempt submission with challenge 58 | ch.resp <- challengeResponse(password, ch$ch.key) 59 | results <- submitSolution(email, ch.resp, sid, output, ch$state) 60 | if(!length(results)) 61 | results <- "Incorrect!" 62 | cat("Result: ", results, "\n") 63 | } 64 | else { 65 | outfile <- paste(sid, "output.txt", sep = "-") 66 | writeLines(as.character(output), outfile) 67 | cat(sprintf("Please upload the file '%s' to Coursera\n", 68 | outfile)) 69 | } 70 | invisible() 71 | } 72 | 73 | getOutput <- function(sid) { 74 | ## JUST FOR TESTING 75 | ### sid <- sub("-dev", "", sid, fixed = TRUE) 76 | if(sid == "pollutantmean-1") { 77 | source("pollutantmean.R") 78 | pollutantmean("specdata", "sulfate", 1:10) 79 | } 80 | else if(sid == "pollutantmean-2") { 81 | source("pollutantmean.R") 82 | pollutantmean("specdata", "nitrate", 70:72) 83 | } 84 | else if(sid == "pollutantmean-3") { 85 | source("pollutantmean.R") 86 | pollutantmean("specdata", "sulfate", 34) 87 | } 88 | else if(sid == "pollutantmean-4") { 89 | source("pollutantmean.R") 90 | pollutantmean("specdata", "nitrate") 91 | } 92 | else if(sid == "complete-1") { 93 | source("complete.R") 94 | cc <- complete("specdata", c(6, 10, 20, 34, 100, 200, 310)) 95 | paste(cc$nobs, collapse = "\n") 96 | } 97 | else if(sid == "complete-2") { 98 | source("complete.R") 99 | cc <- complete("specdata", 54) 100 | cc$nobs 101 | } 102 | else if(sid == "complete-3") { 103 | source("complete.R") 104 | set.seed(42) 105 | cc <- complete("specdata", 332:1) 106 | use <- sample(332, 10) 107 | paste(cc[use, "nobs"], collapse = "\n") 108 | } 109 | else if(sid == "corr-1") { 110 | source("corr.R") 111 | cr <- corr("specdata") 112 | cr <- sort(cr) 113 | set.seed(868) 114 | out <- round(cr[sample(length(cr), 5)], 4) 115 | paste(out, collapse = "\n") 116 | } 117 | else if(sid == "corr-2") { 118 | source("corr.R") 119 | cr <- corr("specdata", 129) 120 | cr <- sort(cr) 121 | n <- length(cr) 122 | set.seed(197) 123 | out <- c(n, round(cr[sample(n, 5)], 4)) 124 | paste(out, collapse = "\n") 125 | 126 | } 127 | else if(sid == "corr-3") { 128 | source("corr.R") 129 | cr <- corr("specdata", 2000) 130 | n <- length(cr) 131 | cr <- corr("specdata", 1000) 132 | cr <- sort(cr) 133 | paste(c(n, round(cr, 4)), collapse = "\n") 134 | } 135 | else { 136 | stop("invalid part number") 137 | } 138 | } 139 | 140 | partPrompt <- function() { 141 | sid <- c("pollutantmean-1", 142 | "pollutantmean-2", 143 | "pollutantmean-3", 144 | "pollutantmean-4", 145 | "complete-1", 146 | "complete-2", 147 | "complete-3", 148 | "corr-1", 149 | "corr-2", 150 | "corr-3" 151 | ) 152 | ## JUST FOR TESTING 153 | ## sid <- paste(sid, "dev", sep = "-") 154 | 155 | sidname <- c("'pollutantmean' part 1", 156 | "'pollutantmean' part 2", 157 | "'pollutantmean' part 3", 158 | "'pollutantmean' part 4", 159 | "'complete' part 1", 160 | "'complete' part 2", 161 | "'complete' part 3", 162 | "'corr' part 1", 163 | "'corr' part 2", 164 | "'corr' part 3" 165 | ) 166 | numparts <- length(sid) 167 | cat(paste(paste("[", seq_len(numparts), "]", sep = ""), sidname), 168 | sep = "\n") 169 | partnum <- readline(sprintf("Which part are you submitting [1-%d]? ", 170 | numparts)) 171 | partnum <- as.integer(partnum) 172 | if(is.na(partnum)) 173 | stop("please specify part number") 174 | if(partnum > numparts) 175 | stop("invalid part number") 176 | sid[partnum] 177 | } 178 | 179 | getChallenge <- function(email) { 180 | params <- list(email_address = email, response_encoding = "delim") 181 | result <- getForm(challenge.url, .params = params) 182 | s <- strsplit(result, "|", fixed = TRUE)[[1]] 183 | list(ch.key = s[5], state = s[7]) 184 | } 185 | 186 | challengeResponse <- function(password, ch.key) { 187 | x <- paste(ch.key, password, sep = "") 188 | digest(x, algo = "sha1", serialize = FALSE) 189 | } 190 | 191 | submitSolution <- function(email, ch.resp, sid, output, signature, src = "", 192 | http.version = NULL) { 193 | output <- as.character(base64(output)) 194 | src <- as.character(base64(src)) 195 | params <- list(assignment_part_sid = sid, 196 | email_address = email, 197 | submission = output, 198 | submission_aux = src, 199 | challenge_response = ch.resp, 200 | state = signature) 201 | params <- lapply(params, URLencode) 202 | result <- postForm(submit.url, .params = params) 203 | s <- strsplit(result, "\\r\\n")[[1]] 204 | tail(s, 1) 205 | } 206 | -------------------------------------------------------------------------------- /Programming Assignment 1 - Air Pollution/submitscript1.R: -------------------------------------------------------------------------------- 1 | checkPkgs <- function() { 2 | pkg.inst <- installed.packages() 3 | pkgs <- c("RCurl", "digest") 4 | have.pkg <- pkgs %in% rownames(pkg.inst) 5 | 6 | if(any(!have.pkg)) { 7 | cat("Some packages need to be installed\n") 8 | r <- readline("Install necessary packages [y/n]? ") 9 | if(tolower(r) == "y") { 10 | need <- pkgs[!have.pkg] 11 | message("installing packages ", 12 | paste(need, collapse = ", ")) 13 | install.packages(need) 14 | } 15 | } 16 | } 17 | 18 | checkPkgs() 19 | 20 | CLASS <- "rprog-003" 21 | challenge.url <- paste("http://class.coursera.org", CLASS, 22 | "assignment/challenge", sep = "/") 23 | submit.url <- paste("http://class.coursera.org", CLASS, 24 | "assignment/submit", sep = "/") 25 | 26 | loginPrompt <- function() { 27 | email <- readline("Submission login (email): ") 28 | passwd <- readline("Submission password: ") 29 | r <- list(email = email, passwd = passwd) 30 | assign(".CourseraLogin", r, globalenv()) 31 | invisible(r) 32 | } 33 | 34 | submit <- function(manual = FALSE, resetLogin = FALSE) { 35 | library(RCurl) 36 | library(digest) 37 | if(!manual) { 38 | if(exists(".CourseraLogin") && !resetLogin) 39 | cred <- get(".CourseraLogin") 40 | else 41 | cred <- loginPrompt() 42 | if(!is.list(cred) || !(names(cred) %in% c("email", "passwd"))) 43 | stop("problem with login/password") 44 | email <- cred$email 45 | password <- cred$passwd 46 | } 47 | ## Prompt Submission Part 48 | sid <- partPrompt() 49 | 50 | ## Get output 51 | output <- getOutput(sid) 52 | 53 | if(!manual) { 54 | ## Get challenge 55 | ch <- getChallenge(email) 56 | 57 | ## Attempt submission with challenge 58 | ch.resp <- challengeResponse(password, ch$ch.key) 59 | results <- submitSolution(email, ch.resp, sid, output, ch$state) 60 | if(!length(results)) 61 | results <- "Incorrect!" 62 | cat("Result: ", results, "\n") 63 | } 64 | else { 65 | outfile <- paste(sid, "output.txt", sep = "-") 66 | writeLines(as.character(output), outfile) 67 | cat(sprintf("Please upload the file '%s' to Coursera\n", 68 | outfile)) 69 | } 70 | invisible() 71 | } 72 | 73 | getOutput <- function(sid) { 74 | ## JUST FOR TESTING 75 | ### sid <- sub("-dev", "", sid, fixed = TRUE) 76 | if(sid == "pollutantmean-1") { 77 | source("pollutantmean.R") 78 | pollutantmean("specdata", "sulfate", 1:10) 79 | } 80 | else if(sid == "pollutantmean-2") { 81 | source("pollutantmean.R") 82 | pollutantmean("specdata", "nitrate", 70:72) 83 | } 84 | else if(sid == "pollutantmean-3") { 85 | source("pollutantmean.R") 86 | pollutantmean("specdata", "sulfate", 34) 87 | } 88 | else if(sid == "pollutantmean-4") { 89 | source("pollutantmean.R") 90 | pollutantmean("specdata", "nitrate") 91 | } 92 | else if(sid == "complete-1") { 93 | source("complete.R") 94 | cc <- complete("specdata", c(6, 10, 20, 34, 100, 200, 310)) 95 | paste(cc$nobs, collapse = "\n") 96 | } 97 | else if(sid == "complete-2") { 98 | source("complete.R") 99 | cc <- complete("specdata", 54) 100 | cc$nobs 101 | } 102 | else if(sid == "complete-3") { 103 | source("complete.R") 104 | set.seed(42) 105 | cc <- complete("specdata", 332:1) 106 | use <- sample(332, 10) 107 | paste(cc[use, "nobs"], collapse = "\n") 108 | } 109 | else if(sid == "corr-1") { 110 | source("corr.R") 111 | cr <- corr("specdata") 112 | cr <- sort(cr) 113 | set.seed(868) 114 | out <- round(cr[sample(length(cr), 5)], 4) 115 | paste(out, collapse = "\n") 116 | } 117 | else if(sid == "corr-2") { 118 | source("corr.R") 119 | cr <- corr("specdata", 129) 120 | cr <- sort(cr) 121 | n <- length(cr) 122 | set.seed(197) 123 | out <- c(n, round(cr[sample(n, 5)], 4)) 124 | paste(out, collapse = "\n") 125 | 126 | } 127 | else if(sid == "corr-3") { 128 | source("corr.R") 129 | cr <- corr("specdata", 2000) 130 | n <- length(cr) 131 | cr <- corr("specdata", 1000) 132 | cr <- sort(cr) 133 | paste(c(n, round(cr, 4)), collapse = "\n") 134 | } 135 | else { 136 | stop("invalid part number") 137 | } 138 | } 139 | 140 | partPrompt <- function() { 141 | sid <- c("pollutantmean-1", 142 | "pollutantmean-2", 143 | "pollutantmean-3", 144 | "pollutantmean-4", 145 | "complete-1", 146 | "complete-2", 147 | "complete-3", 148 | "corr-1", 149 | "corr-2", 150 | "corr-3" 151 | ) 152 | ## JUST FOR TESTING 153 | ## sid <- paste(sid, "dev", sep = "-") 154 | 155 | sidname <- c("'pollutantmean' part 1", 156 | "'pollutantmean' part 2", 157 | "'pollutantmean' part 3", 158 | "'pollutantmean' part 4", 159 | "'complete' part 1", 160 | "'complete' part 2", 161 | "'complete' part 3", 162 | "'corr' part 1", 163 | "'corr' part 2", 164 | "'corr' part 3" 165 | ) 166 | numparts <- length(sid) 167 | cat(paste(paste("[", seq_len(numparts), "]", sep = ""), sidname), 168 | sep = "\n") 169 | partnum <- readline(sprintf("Which part are you submitting [1-%d]? ", 170 | numparts)) 171 | partnum <- as.integer(partnum) 172 | if(is.na(partnum)) 173 | stop("please specify part number") 174 | if(partnum > numparts) 175 | stop("invalid part number") 176 | sid[partnum] 177 | } 178 | 179 | getChallenge <- function(email) { 180 | params <- list(email_address = email, response_encoding = "delim") 181 | result <- getForm(challenge.url, .params = params) 182 | s <- strsplit(result, "|", fixed = TRUE)[[1]] 183 | list(ch.key = s[5], state = s[7]) 184 | } 185 | 186 | challengeResponse <- function(password, ch.key) { 187 | x <- paste(ch.key, password, sep = "") 188 | digest(x, algo = "sha1", serialize = FALSE) 189 | } 190 | 191 | submitSolution <- function(email, ch.resp, sid, output, signature, src = "", 192 | http.version = NULL) { 193 | output <- as.character(base64(output)) 194 | src <- as.character(base64(src)) 195 | params <- list(assignment_part_sid = sid, 196 | email_address = email, 197 | submission = output, 198 | submission_aux = src, 199 | challenge_response = ch.resp, 200 | state = signature) 201 | params <- lapply(params, URLencode) 202 | result <- postForm(submit.url, .params = params) 203 | s <- strsplit(result, "\\r\\n")[[1]] 204 | tail(s, 1) 205 | } 206 | -------------------------------------------------------------------------------- /Programming Assignment 2 - Lexical Scoping/Here's how makeVector and cachemean work_files/1.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/muntasir2165/R-Programming-Assignments-1--2--and-3-/3dd6003062ddf6851a2baa06b04ed96e9eabfb60/Programming Assignment 2 - Lexical Scoping/Here's how makeVector and cachemean work_files/1.jpg -------------------------------------------------------------------------------- /Programming Assignment 2 - Lexical Scoping/Here's how makeVector and cachemean work_files/172.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/muntasir2165/R-Programming-Assignments-1--2--and-3-/3dd6003062ddf6851a2baa06b04ed96e9eabfb60/Programming Assignment 2 - Lexical Scoping/Here's how makeVector and cachemean work_files/172.jpg -------------------------------------------------------------------------------- /Programming Assignment 2 - Lexical Scoping/Here's how makeVector and cachemean work_files/204.min.js: -------------------------------------------------------------------------------- 1 | !function(e){var t=/.*\/204\.(min\.)?js(\?.*)?$/,n=4e3,o=function(t){var n=[];for(var o in t)n.push("string"!=typeof t[o]&&e.JSON?o+"="+encodeURIComponent(e.JSON.stringify(t[o])):o+"="+encodeURIComponent(t[o].toString()));return e.JSON||n.push("_noJSON_=true"),n.join("&")},i=function(t,n,o){var i=document.createElement("iframe"),r=(new Date).getTime().toString();document.body.appendChild(i),i.style.display="none",i.name=r,i.contentWindow.name=r;var s=document.createElement("div");s.style.display="none";var a=document.createElement("form");a.target=r,a.action=t,a.method="POST",s.appendChild(a);var c;for(var p in n)c=document.createElement("input"),c.type="hidden",c.name=p,c.value="string"!=typeof n[p]&&e.JSON?e.JSON.stringify(n[p]):n[p].toString(),a.appendChild(c);document.body.appendChild(s),i.onload=i.onreadystatechange=function(){this.readyState&&"complete"!=this.readyState||(i.onreadystatechange=i.onload=null,i.parentNode.removeChild(i),a.parentNode.removeChild(a),o&&"function"==typeof o&&o())},a.submit()},r=function(e,t,n,o){var r=document.createElement("script");r.type="text/javascript",r.async=!0,r.src=e+"?"+n,r.onload=r.onreadystatechange=function(){this.readyState&&"complete"!=this.readyState||(r.onreadystatechange=r.onload=null,r.parentNode.removeChild(r),o&&"function"==typeof o&&o())},r.onerror=function(){i(e,t,o)},document.getElementsByTagName("head")[0].appendChild(r)},s=function(e,t,s){var a=o(t);a.length=0;n--)c.remove(e[n],t)},h=function(e){e.options.session=e.session();var t=e.options.initialReferrerTracker,n={domain:e.options.domain,days:365};e.options.initialReferrer=c.setOnce(t,e.options.from,n)},u=function(){for(var n=e.document.scripts||document.getElementsByTagName("script"),o=n.length,i=e.document.referrer,r=e.location.host.split(".");r.length>2;)r.shift();this.options={user:null,version:null,session:null,client:"204",from:i,domain:"."+r.join("."),currentURL:e.location.href,tracker:"__204u",initialReferrerTracker:"__204r",beacon:"https://eventing.coursera.org/info"};for(var s=0;o>s;s++)if(t.test(n[s].src)){var a=/^.+\?(.*)$/.exec(n[s].src);if(a)for(var c=a[1].split("&"),p=0;p

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Not now, '+jade.escape(null==(jade_interp=timeLeft)?"":jade_interp)+" remaining.
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-------------------------------------------------------------------------------- /Programming Assignment 2 - Lexical Scoping/Here's how makeVector and cachemean work_files/header.js: -------------------------------------------------------------------------------- 1 | define(["underscore","backbone","js/lib/readme","pages/spark/app","i18n!pages/spark/views/template/nls/header","pages/spark/views/template/header.html"],function(_,Backbone,Readme,Coursera,_t,template){"use strict";var header=Backbone.View.extend({name:"header",className:"coursera-header",attributes:{role:"menubar"},initialize:function(){this.on("view:appended",function(){try{var dashboardLink="data/dashboard",onDashboardAlready=-1!==window.location.pathname.indexOf(dashboardLink,window.location.pathname.length-dashboardLink.length);if(!onDashboardAlready){for(var readmeLinks=$("[data-readme=data-dashboard-announcement] a"),i=0;i=max)return this.emitter.trigger("aged"),!1;if(_private.open)return _private.stack.push(this),!1;else return _private.open=!0,!0}},ReadMe=function(el,options){var that=this;this.$el=$(el),this.emitter=LucidJS.emitter(this),this.customize(options),window.setTimeout(function(){that.open()},this.options["show.delay"]||0)};ReadMe.prototype.customize=function(settings){var that=this,height;if(this.options=_.extend({},DataAttributes.parse(this.$el,_private.defaults,"data-readme-"),settings),this.$el.addClass(this.options["class"]),"banner"==this.options.type)this.$el.css({visibility:"hidden"}).show(),height=this.$el.outerHeight(),this.$el.css({visibility:"visible"}).hide(),this.options["animate.open"]={"margin-top":0},this.options["animate.close"]={"margin-top":-height},this.options["animate.duration"]=250,this.on("opening",function(){that.$el.css({visibility:"visible","margin-top":-height}).show().prependTo($("body"))});else if("footer-sticky"==this.options.type)this.$el.css({visibility:"hidden"}).show(),height=this.$el.outerHeight(),this.$el.css({visibility:"visible"}).hide(),this.options["animate.open"]={bottom:0},this.options["animate.close"]={bottom:-height},this.options["animate.duration"]=250,this.on("opening",function(){that.$el.css({visibility:"visible",position:"absolute",left:0,right:0,bottom:-height}).show().appendTo($("body"))});return this},ReadMe.prototype.open=function(){var that=this;if(_private.canShow.call(this)){if(!this.options["show.until.closed"]&&this.options["show.count"])_private.increaseCount.call(this);if(this.emitter.trigger("opening"),_private.stack.push(this),this.$el.on(this.options["bind.close"]+".readme","["+this.options["attribute.close"]+"]",function(){if(that.options["show.until.closed"]&&that.options["show.count"])_private.increaseCount.call(that);that.close()}),this.$el.is("["+this.options["attribute.close"]+"]"))this.$el.on(this.options["bind.close"]+".readme",function(){if(that.options["show.until.closed"]&&that.options["show.count"])_private.increaseCount.call(that);that.close()});if(this.options["animate.open"])this.$el.css({"margin-top":-100}).prependTo($("body")).show(),this.$el.animate(this.options["animate.open"],{duration:this.options["animate.duration"],complete:function(){that.emitter.trigger("open")}});else this.$el.show(),this.emitter.trigger("open")}},ReadMe.prototype.close=function(){var that=this;if(this.trigger("closing"),_private.stack.shift(),this.options["animate.close"])this.$el.animate(this.options["animate.close"],{duration:this.options["animate.duration"],complete:function(){if(that.$el.off(".readme"),that.$el.hide().remove(),that.emitter.trigger("close"),_private.open=!1,_private.stack.length)_private.stack[0].open()}});else if(this.$el.off(".readme"),this.$el.hide().remove(),this.emitter.trigger("close"),_private.open=!1,_private.stack.length)_private.stack[0].open()};var external=function(el,options){return _private.getReadMe(el,options)||_private.makeReadMe(el,options)};return external};if("function"==typeof define&&define.amd)define(["jquery","underscore","js/lib/cookie","js/lib/lucid","js/lib/moment","js/lib/data.attributes"],function($,_,cookie,LucidJS,Moment,DataAttributes){return Module($,_,cookie,LucidJS,Moment,DataAttributes)});else if("undefined"!=typeof window&&"undefined"==typeof ender)wndw.ReadMe=Module(wndw.$,wndw._,wndw.Cookie,wndw.LucidJS,wndw.moment,wndw.DataAttributes)}(window); -------------------------------------------------------------------------------- /Programming Assignment 2 - Lexical Scoping/Here's how makeVector and cachemean work_files/sidebar(1).js: -------------------------------------------------------------------------------- 1 | define({es:!0,fr:!0,pt:!0,ru:!0,tr:!0,zh:!0,"zh-hk":"zh-tw","zh-mo":"zh-tw","zh-tw":!0}); -------------------------------------------------------------------------------- /Programming Assignment 2 - Lexical Scoping/Here's how makeVector and cachemean work_files/sidebar.html.js: -------------------------------------------------------------------------------- 1 | !function(wndw){var jadify=function(jade,_t){var yudify=function template(locals){var buf=[],jade_mixins={},jade_interp,locals_for_with=locals||{};return function(course,user,config,_t,navbar,Date,url){if(buf.push('")}("course"in locals_for_with?locals_for_with.course:"undefined"!=typeof course?course:void 0,"user"in locals_for_with?locals_for_with.user:"undefined"!=typeof user?user:void 0,"config"in locals_for_with?locals_for_with.config:"undefined"!=typeof config?config:void 0,"_t"in locals_for_with?locals_for_with._t:"undefined"!=typeof _t?_t:void 0,"navbar"in locals_for_with?locals_for_with.navbar:"undefined"!=typeof navbar?navbar:void 0,"Date"in locals_for_with?locals_for_with.Date:"undefined"!=typeof Date?Date:void 0,"url"in locals_for_with?locals_for_with.url:"undefined"!=typeof url?url:void 0),buf.join("")};return function(locals){if(locals&&locals._t)_t=locals._t.merge(_t);return yudify(locals)}};if("function"==typeof define&&define.amd)define(["js/lib/jade","i18n!pages/spark/views/template/nls/sidebar"],function(jade,_t){return jadify(jade,_t)});else wndw.jade.templates["pages.spark.views.template.sidebar"]=jadify(wndw.jade.helpers)}(window); -------------------------------------------------------------------------------- /Programming Assignment 2 - Lexical Scoping/Here's how makeVector and cachemean work_files/sidebar.js: -------------------------------------------------------------------------------- 1 | define(["jquery","underscore","backbone","pages/spark/app","i18n!pages/spark/views/template/nls/sidebar","pages/spark/views/template/sidebar.html","spark/app/signature/js/signature_track"],function($,_,Backbone,Coursera,_t,template,SigtrackFunctions){var sidebar=Backbone.View.extend({name:"sidebar",className:"coursera-sidebar",attributes:{role:"menubar"},initialize:function(){},render:function(){return this.$el.html(template({_t:_t,course:Coursera.course,user:Coursera.user,navbar:Coursera.navbar,config:Coursera.config,url:encodeURIComponent(decodeURIComponent(window.location.href))})),this.updateSidebar(),SigtrackFunctions.addLastChanceModalInteraction(this.$el),this},updateSidebar:function(){function markLink(query){if(foundActiveLink)return;var matches=[];if($navbar.find(query).each(function(){matches.push($(this).parent()),foundActiveLink=!0}),1==matches.length)if(foundActiveLink=!0,-1==window.location.href.indexOf("/search?q"))matches[0].addClass("active"),matches[0].find("a").append('(selected)')}this.$el.find(".course-navbar-container li").removeClass("active"),this.$el.find(".course-navbar-container li").remove(".course-navbar-selected-marker");var $navbar=this.$el.find(".course-navbar-container li"),foundActiveLink=!1;markLink('a[href="'+window.location.pathname+"/index"+window.location.search+'"]'),markLink('a[href="'+window.location.pathname+window.location.search+'"]'),markLink('a[href="'+window.location.href+'"]'),markLink('a[href="'+window.location.pathname+'"]'),markLink('a[href="'+window.location.href+'/index"]'),markLink('a[href="'+window.location.pathname+'/index"]'),markLink('a[href^="'+window.location.href.split("?")[0]+'"]')}});return sidebar}); -------------------------------------------------------------------------------- /Programming Assignment 2 - Lexical Scoping/Here's how makeVector and cachemean work_files/signatureTrackLastChanceModal.html.js: -------------------------------------------------------------------------------- 1 | !function(wndw){var jadify=function(jade,_t){_t="undefined"!=typeof _t?_t:function(key,interpolationHash){if("object"==typeof interpolationHash)return key.replace(/[#!]\{([^}]+?)\}/g,function(match,interpKey){return interpolationHash[interpKey]||interpKey});else return key};var yudify=function template(locals){var buf=[],jade_mixins={},jade_interp,locals_for_with=locals||{};return function(ribbon,specialization,certBaseImage,universityLogo,course,timeLeft){if(buf.push('

Closing Soon!

Don\'t miss out on your Verified Certificate!

'),!specialization)buf.push('

Not now
');else buf.push("

Did you know that "+jade.escape(null==(jade_interp=course.get("name"))?"":jade_interp)+" is part of the "+jade.escape(null==(jade_interp=specialization.numCourse)?"":jade_interp)+"-course "+jade.escape(null==(jade_interp=specialization.name)?"":jade_interp)+' Specialization?

Specialization Title
'+jade.escape(null==(jade_interp=specialization.name)?"":jade_interp)+"

Join this course's Signature Track and you'll be on your way to earning a Specialization Certificate! You have "+jade.escape(null==(jade_interp=timeLeft)?"":jade_interp)+' left to join.

Not now

');buf.push("
")}("ribbon"in locals_for_with?locals_for_with.ribbon:"undefined"!=typeof ribbon?ribbon:void 0,"specialization"in locals_for_with?locals_for_with.specialization:"undefined"!=typeof specialization?specialization:void 0,"certBaseImage"in locals_for_with?locals_for_with.certBaseImage:"undefined"!=typeof certBaseImage?certBaseImage:void 0,"universityLogo"in locals_for_with?locals_for_with.universityLogo:"undefined"!=typeof universityLogo?universityLogo:void 0,"course"in locals_for_with?locals_for_with.course:"undefined"!=typeof course?course:void 0,"timeLeft"in locals_for_with?locals_for_with.timeLeft:"undefined"!=typeof timeLeft?timeLeft:void 0),buf.join("")};return function(locals){if(locals&&locals._t)_t=locals._t.merge(_t);return yudify(locals)}};if("function"==typeof define&&define.amd)define(["js/lib/jade"],function(jade,_t){return jadify(jade,_t)});else wndw.jade.templates["spark.app.signature.js.signatureTrackLastChanceModal"]=jadify(wndw.jade.helpers)}(window); -------------------------------------------------------------------------------- /Programming Assignment 2 - Lexical Scoping/Here's how makeVector and cachemean work_files/signature_track.js: -------------------------------------------------------------------------------- 1 | define(["jquery","pages/spark/app","js/lib/cookie","js/lib/modals","spark/app/signature/js/signatureTrackLastChanceModal.html","spark/app/signature/js/flexjoinLastChanceModal.html","js/lib/coursera.ab","js/lib/util"],function($,Coursera,Cookie,Modal,signatureTrackLastChanceModal,flexjoinLastChanceModal,AB,util){var functionList={addLastChanceModalInteraction:function($el){if(!Coursera.user.get("last_access_time"))return;var signup_url=Coursera.course.get("host")+"signature/course/"+Coursera.course.get("shortname")+"/"+Coursera.course.get("id"),specialization=Coursera.course.get("specialization");if(specialization)signup_url=Coursera.course.get("host")+"specialization/"+specialization.short_name+"/"+specialization.id;var sigtrackStatus=Coursera.course.get("signatureTrackStatus");if(1!==sigtrackStatus.signature_track_enabled)return;if(1===sigtrackStatus.signature_track_sign_up_now&&!Coursera.user.inSignatureTrack()&&!Coursera.user.isStaffOrSuperuser()){if(1!=Cookie.get("spark_signaturetrack_hide")){var join_label=null,join_st_button=null;if(!specialization){var join_label_id=AB.session.getExperiment("sigtrack_demonstrated_uses2").getChosenVariant();join_label={base:"Earn a Verified Certificate!","show-qualifications":"Show Your New Qualifications with a Verified Certificate","further-qualifications":"Deepen Your Qualifications with a Verified Certificate","list-resume":"Upgrade Your Resume with a Verified Certificate","list-cv":"Upgrade Your C.V. with a Verified Certificate","add-linkedin":"Add Verified Certificates to Your LinkedIn Profile","official-rec":"Earn Official Recognition from Top Universities","rec-achievement":"Get Recognition for Your Achievement with a Verified Certificate","link-identity":"Link Your Coursework to Your Identity","commitment-complete":"Motivate Yourself to Complete with a Verified Certificate","share-certificate":"Share Your Achievement With a Unique Certificate URL","share-records":"Show Your Success with Shareable Course Records","advance-career":"Advance Your Career with Verified Certificates","present-employer":"Gain Workplace Recognition, Earn Your Verified Certificate"}[join_label_id],join_st_button="Get Started"}else if(specialization)join_label='The "'+Coursera.course.get("specialization").name+'" Specialization',join_st_button="Learn More";$("body").prepend("
× "+join_label+" "+join_st_button+"
"),$(".course-signaturetrack-topbanner-close").click(function(){$(".course-signaturetrack-topbanner").hide(),Cookie.set("spark_signaturetrack_hide",1,{expires:new Date("2020"),path:"/"+Coursera.course.get("sessionName")})})}var makeLastChanceModal=function(arg){return $(signatureTrackLastChanceModal({ribbon:arg.ribbon,universityLogo:arg.universityLogo,certBaseImage:arg.certBaseImage,studentName:arg.studentName,course:arg.course,specialization:arg.course.get("specialization"),timeLeft:arg.timeLeft}))},makeFlexjoinModal=function(arg){return $(flexjoinLastChanceModal({ribbon:arg.ribbon,universityLogo:arg.universityLogo,certBaseImage:arg.certBaseImage,studentName:arg.studentName,course:arg.course,specialization:arg.course.get("specialization"),timeLeft:arg.timeLeft,closeDate:arg.closeDate}))};if((sigtrackStatus.signature_track_last_chance_dialog||sigtrackStatus.flexjoin_last_chance_dialog)&&!Coursera.user.get("last_chance_modal")&&!util.isMobileDevice()){var $modalDiv;if(sigtrackStatus.flexjoin_last_chance_dialog)$modalDiv=makeFlexjoinModal({ribbon:Coursera.course.get("assetUnversionedLink")+"/pages/signature/views/ribbon_stripes.png",timeLeft:sigtrackStatus.signature_track_duration_left,course:Coursera.course,studentName:Coursera.user.get("full_name"),certBaseImage:Coursera.course.get("assetUnversionedLink")+"/images/signature/template-cert-preview.png",universityLogo:Coursera.course.get("host")+"/maestro/api/course/"+Coursera.course.get("id")+"/university_logo",closeDate:sigtrackStatus.flexjoin_registration_close_date});else $modalDiv=makeLastChanceModal({ribbon:Coursera.course.get("assetUnversionedLink")+"/pages/signature/views/ribbon_stripes.png",timeLeft:sigtrackStatus.signature_track_duration_left,course:Coursera.course,studentName:Coursera.user.get("full_name"),certBaseImage:Coursera.course.get("assetUnversionedLink")+"/images/signature/template-cert-preview.png",universityLogo:Coursera.course.get("host")+"/maestro/api/course/"+Coursera.course.get("id")+"/university_logo"});var modal=new Modal($modalDiv,{"overlay.class":"coursera-signature-modal-overlay-darker","overlay.close":!1});modal.on("open",function(){if($(".course-signaturetrack-modal-learnmore").on("click",function(){window.open(signup_url+"?utm_source=spark&utm_medium=lastchance")}),Coursera.course.get("specialization"))$(".course-specialization-modal-learnmore").on("click",function(){window.open(signup_url+"?utm_source=spark&utm_medium=lastchance")})}),modal.on("close",function(){Coursera.api.get("signature/user/set_last_chance")}),modal.open()}}}};return functionList}); -------------------------------------------------------------------------------- /Programming Assignment 2 - Lexical Scoping/Here's how makeVector and cachemean work_files/spark.forum.hg.css: -------------------------------------------------------------------------------- 1 | /* bootstrap variables ------------------------------------------------------ */ 2 | /* human-grading variables -------------------------------------------------- */ 3 | /* bootstrap mixins --------------------------------------------------------- */ 4 | .clearfix { 5 | *zoom: 1; 6 | } 7 | .clearfix:before, 8 | .clearfix:after { 9 | display: table; 10 | content: ""; 11 | } 12 | .clearfix:after { 13 | clear: both; 14 | } 15 | .hide-text { 16 | overflow: hidden; 17 | text-indent: 100%; 18 | white-space: nowrap; 19 | } 20 | .input-block-level { 21 | display: block; 22 | width: 100%; 23 | min-height: 28px; 24 | /* Make inputs at least the height of their button counterpart */ 25 | 26 | /* Makes inputs behave like true block-level elements */ 27 | 28 | -webkit-box-sizing: border-box; 29 | -moz-box-sizing: border-box; 30 | -ms-box-sizing: border-box; 31 | box-sizing: border-box; 32 | } 33 | /* human-grading mixins ----------------------------------------------------- */ 34 | /* human-grading form group ------------------------------------------------- */ 35 | .hg-qna > .assessmentExposition, 36 | .hg-qna > .assessmentAnswer, 37 | .hg-qna > .assessmentEvaluation { 38 | min-height: 20px; 39 | padding: 19px 19px 0 19px; 40 | margin-bottom: 20px; 41 | background-color: white; 42 | -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.05); 43 | -moz-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.05); 44 | box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.05); 45 | border: 1px solid #ccc; 46 | border: 1px solid rgba(0, 0, 0, 0.1); 47 | } 48 | .hg-qna > .assessmentExposition { 49 | background-color: #efefef; 50 | padding-bottom: 19px; 51 | } 52 | .hg-qna > .assessmentExposition + .assessmentAnswer, 53 | .hg-qna > .assessmentExposition + .assessmentEvaluation { 54 | /* Negate the assessmentExposition box's margin-bottom */ 55 | 56 | margin-top: -20px; 57 | } 58 | .hg-qna > .assessmentAnswer > *, 59 | .hg-qna > .assessmentEvaluation > * { 60 | margin-bottom: 18px; 61 | } 62 | -------------------------------------------------------------------------------- /Programming Assignment 2 - Lexical Scoping/Here's how makeVector and cachemean work_files/student-page.html.js: -------------------------------------------------------------------------------- 1 | !function(wndw){var jadify=function(jade,_t){_t="undefined"!=typeof _t?_t:function(key,interpolationHash){if("object"==typeof interpolationHash)return key.replace(/[#!]\{([^}]+?)\}/g,function(match,interpKey){return interpolationHash[interpKey]||interpKey});else return key};var yudify=function template(locals){var buf=[],jade_mixins={},jade_interp;return buf.push('
'),buf.join("")};return function(locals){if(locals&&locals._t)_t=locals._t.merge(_t);return yudify(locals)}};if("function"==typeof define&&define.amd)define(["js/lib/jade"],function(jade,_t){return jadify(jade,_t)});else wndw.jade.templates["pages.spark.views.template.student-page"]=jadify(wndw.jade.helpers)}(window); -------------------------------------------------------------------------------- /Programming Assignment 2 - Lexical Scoping/Here's how makeVector and cachemean work_files/student-page.js: -------------------------------------------------------------------------------- 1 | define(["jquery","backbone","underscore","pages/spark/views/template/student-page.html","js/lib/api","js/core/coursera","js/lib/cookie"],function($,Backbone,_,template,API,Coursera,cookie){var page=Backbone.View.extend({name:"page",subregions:{header:"pages/spark/views/template/header",sidebar:"pages/spark/views/template/sidebar"},initialize:function(){this.bind("view:appended",this.scroll),this.bind("view:updated",this.scroll)},scroll:function(){$("html, body").scrollTop(0),$(window).trigger("scroll")},renderPrioritySupportButton:function(){function showSupportButton(network_name){$("[data-networkprioritysupportwidget]").text(network_name+" Priority Support"),$("[data-networkprioritysupportwidget]").show()}var cookieName="network-priority-support",cookieValue=cookie.get(cookieName);if(cookieValue){try{cookieValue=JSON.parse(cookieValue)}catch(e){return Coursera.multitracker.push(["CPP Priority Cookie Value",cookieValue]),void cookie.clear(cookieName)}if(cookieValue.network_name)showSupportButton(cookieValue.network_name);return}if(Math.random()>.25)return;var path="signature/user/get_premium_support_network",postData={data:{"user-id":Coursera.user.get("id"),"session-id":Coursera.course.get("id")},success:function(d){if(null!==d&&d.network_name)cookie.set(cookieName,JSON.stringify({network_name:d.network_name}),{expires:7,path:"/"+Coursera.course.get("sessionName")}),showSupportButton(d.network_name);else if(null!==d&&d.error)cookie.set(cookieName,JSON.stringify({error:d.error}),{expires:7,path:"/"+Coursera.course.get("sessionName")})},error:function(){}};Coursera.api.get(path,postData)},render:function(){var regions=this.region.regions,self=this,page=$(template());return self.$el.append(page),_.each(["header","sidebar","body"],function(type){if(!regions[type]){if("body"!=type)page.find(".coursera-"+type).hide();else page.find(".coursera-body").replaceWith($("#spark").show());return}page.find(".coursera-"+type).replaceWith(regions[type].view.el)}),this.renderPrioritySupportButton(),self}});return page}); -------------------------------------------------------------------------------- /Programming Assignment 2 - Lexical Scoping/Here's how makeVector and cachemean work_files/university_logo: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/muntasir2165/R-Programming-Assignments-1--2--and-3-/3dd6003062ddf6851a2baa06b04ed96e9eabfb60/Programming Assignment 2 - Lexical Scoping/Here's how makeVector and cachemean work_files/university_logo -------------------------------------------------------------------------------- /Programming Assignment 2 - Lexical Scoping/cachematrix.R: -------------------------------------------------------------------------------- 1 | ## The following functions calculate the inverse of a matrix and saves it 2 | ## to the cache such that the next time the user attempts to calculate the 3 | ## matrix inverse, the previously saved value is returned instead of 4 | ## repeating the calculation. 5 | 6 | ## This function creates a special "matrix" object, which is really a list 7 | ## containing a function to 8 | ## 1. set the value of the matrix 9 | ## 2. get the value of the matrix 10 | ## 3. set the value of the inverse 11 | ## 4. get the value of the inverse 12 | 13 | makeCacheMatrix <- function(x = matrix()) { 14 | ## create a matrix object x and some associated sub-functions/methods 15 | 16 | ## define the cache m 17 | m <- NULL 18 | set <- function(y) { 19 | x <<- y ## assign the input matrix y to the variable x in the 20 | ## parent environment 21 | m <<- NULL ## re-initialize m in the parent environment to null 22 | } 23 | get <- function() x ## return the matrix x 24 | setinverse <- function(inverse) m <<- inverse ## set the cache m equal 25 | ## to the inverse of the matrix x 26 | getinverse <- function() m ## return the cached inverse of x 27 | list(set = set, get = get, 28 | setinverse = setinverse, 29 | getinverse = getinverse) 30 | } 31 | 32 | 33 | ## The following function calculates the inverse of the special "matrix" created 34 | ## with the above function. However, it first checks to see if the inverse 35 | ## has already been caclulated. If so, it 'get's the inverse from the cache 36 | ## and skips the computation. Otherwise, it calculates the matrix inverse 37 | ## and sets the value of the inverse in the cache via the 'setinverse' function. 38 | 39 | cacheSolve <- function(x, ...) { 40 | ## Return a matrix that is the inverse of 'x' 41 | 42 | m <- x$getinverse() 43 | if(!is.null(m)) { 44 | message("getting cached data") 45 | return(m) 46 | } 47 | data <- x$get() 48 | m <- solve(data, ...) 49 | x$setinverse(m) 50 | m 51 | } 52 | -------------------------------------------------------------------------------- /Programming Assignment 3 - Hospital Quality/best.R: -------------------------------------------------------------------------------- 1 | best <- function(state, outcome) { 2 | ## Read outcome data 3 | ##outcome_name: "heart attack", "heart failure", "pneumonia" 4 | 5 | ## Check that state and outcome are valid 6 | ## Return hospital name in that state with lowest 30-day death 7 | ## rate 8 | #read in the desired data 9 | data <- read.csv("outcome-of-care-measures.csv", colClasses = "character") 10 | 11 | #check if the state and outcomes are valid 12 | states <- data[ , 7] 13 | outcomes <- c("heart attack", "heart failure", "pneumonia") 14 | if ((state %in% states) == FALSE) { 15 | stop(print("invalid state")) 16 | } 17 | else if ((outcome %in% outcomes) == FALSE) { 18 | stop(print("invalid outcome")) 19 | } 20 | 21 | #get the subset of the data with the desired state 22 | new_data <- subset(data, State == state) 23 | 24 | #get the desired outcome column from the data file 25 | if (outcome == "heart attack") { 26 | outcome_column <- 11 27 | } 28 | else if (outcome == "heart failure") { 29 | outcome_column <- 17 30 | } 31 | else { 32 | outcome_column <- 23 33 | } 34 | 35 | #get rid of the NA's in the desired outcome column 36 | required_columns <- as.numeric(new_data[,outcome_column]) 37 | bad <- is.na(required_columns) 38 | desired_data <- new_data[!bad, ] 39 | 40 | #find the hospitals in the rows with the minimum outcome value 41 | columns_considered <- as.numeric(desired_data[, outcome_column]) 42 | desired_rows <- which(columns_considered == min(columns_considered)) 43 | desired_hospitals <- desired_data[desired_rows, 2] 44 | 45 | #if there are multiple hospitals with the minimum outcome value, then 46 | #return the first hospital name from the alphabetically sorted hospital 47 | #names list 48 | if (length(desired_hospitals) > 1) { 49 | hospitals_sorted <- sort(desired_hospitals) 50 | hospitals_sorted[1] 51 | } 52 | else { 53 | desired_hospitals 54 | } 55 | } -------------------------------------------------------------------------------- /Programming Assignment 3 - Hospital Quality/rankall.R: -------------------------------------------------------------------------------- 1 | rankall <- function(outcome, num = "best") { 2 | ## Read outcome data 3 | 4 | ## Check that state and outcome are valid 5 | ## For each state, find the hospital of the given rank 6 | ## Return a data frame with the hospital names and the 7 | ## (abbreviated) state name 8 | 9 | #read in the desired data 10 | data <- read.csv("outcome-of-care-measures.csv", colClasses = "character") 11 | 12 | #create a list of states and initialize a character array to hold the 13 | #required hospital names 14 | state <- levels(factor(data[, 7])) 15 | hospital <- vector(mode="character") 16 | 17 | for (i in seq(state)) { 18 | hospital[i] <- rankhospital(state[i], outcome, num) 19 | } 20 | data.frame(hospital, state) 21 | } 22 | -------------------------------------------------------------------------------- /Programming Assignment 3 - Hospital Quality/rankhospital.R: -------------------------------------------------------------------------------- 1 | rankhospital <- function(state, outcome, num = "best") { 2 | ## Read outcome data 3 | 4 | ## Check that state and outcome are valid 5 | ## Return hospital name in that state with the given rank 6 | ## 30-day death rate 7 | 8 | #read in the desired data 9 | data <- read.csv("outcome-of-care-measures.csv", colClasses = "character") 10 | 11 | #check if the state and outcomes are valid 12 | states <- data[ , 7] 13 | outcomes <- c("heart attack", "heart failure", "pneumonia") 14 | if ((state %in% states) == FALSE) { 15 | stop(print("invalid state")) 16 | } 17 | else if ((outcome %in% outcomes) == FALSE) { 18 | stop(print("invalid outcome")) 19 | } 20 | 21 | #get the subset of the data with the desired state 22 | new_data <- subset(data, State == state) 23 | 24 | #get the desired outcome column from the data file 25 | if (outcome == "heart attack") { 26 | outcome_column <- 11 27 | } 28 | else if (outcome == "heart failure") { 29 | outcome_column <- 17 30 | } 31 | else { 32 | outcome_column <- 23 33 | } 34 | 35 | #if num is greater that the number of hospitals in the desired state, 36 | # return NA 37 | if (is.numeric(num) == TRUE) { 38 | if (length(data[,2]) < num) { 39 | return(NA) 40 | } 41 | } 42 | 43 | #get rid of the NA's in the desired outcome column 44 | new_data[, outcome_column] <- as.numeric(new_data[,outcome_column]) 45 | bad <- is.na(new_data[, outcome_column]) 46 | desired_data <- new_data[!bad, ] 47 | 48 | #arrange the modified dataframe in ascending order of the outcome values 49 | outcome_column_name <- names(desired_data)[outcome_column] 50 | hospital_column_name <- names(desired_data)[2] 51 | index <- with(desired_data, order(desired_data[outcome_column_name], desired_data[hospital_column_name])) 52 | ordered_desired_data <- desired_data[index, ] 53 | 54 | #if nume is either "best" or "worst", then interpret it to the 55 | #corresponding numerical value 56 | if (is.character(num) == TRUE) { 57 | if (num == "best") { 58 | num = 1 59 | } 60 | else if (num == "worst") { 61 | num = length(ordered_desired_data[, outcome_column]) 62 | } 63 | } 64 | #return the hospital name with the outcome ranking of num 65 | ordered_desired_data[num, 2] 66 | } 67 | -------------------------------------------------------------------------------- /Programming Assignment 3 - Hospital Quality/rprog-data-ProgAssignment3-data.zip: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/muntasir2165/R-Programming-Assignments-1--2--and-3-/3dd6003062ddf6851a2baa06b04ed96e9eabfb60/Programming Assignment 3 - Hospital Quality/rprog-data-ProgAssignment3-data.zip -------------------------------------------------------------------------------- /Programming Assignment 3 - Hospital Quality/rprog-data-ProgAssignment3-data/Hospital_Revised_Flatfiles.pdf: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/muntasir2165/R-Programming-Assignments-1--2--and-3-/3dd6003062ddf6851a2baa06b04ed96e9eabfb60/Programming Assignment 3 - Hospital Quality/rprog-data-ProgAssignment3-data/Hospital_Revised_Flatfiles.pdf -------------------------------------------------------------------------------- /Programming Assignment 3 - Hospital Quality/rprog-data-ProgAssignment3-data/best.R: -------------------------------------------------------------------------------- 1 | best <- function(state, outcome) { 2 | ## Read outcome data 3 | ##outcome_name: "heart attack", "heart failure", "pneumonia" 4 | 5 | ## Check that state and outcome are valid 6 | ## Return hospital name in that state with lowest 30-day death 7 | ## rate 8 | #read in the desired data 9 | data <- read.csv("outcome-of-care-measures.csv", colClasses = "character") 10 | 11 | #check if the state and outcomes are valid 12 | states <- data[ , 7] 13 | outcomes <- c("heart attack", "heart failure", "pneumonia") 14 | if ((state %in% states) == FALSE) { 15 | stop(print("invalid state")) 16 | } 17 | else if ((outcome %in% outcomes) == FALSE) { 18 | stop(print("invalid outcome")) 19 | } 20 | 21 | #get the subset of the data with the desired state 22 | new_data <- subset(data, State == state) 23 | 24 | #get the desired outcome column from the data file 25 | if (outcome == "heart attack") { 26 | outcome_column <- 11 27 | } 28 | else if (outcome == "heart failure") { 29 | outcome_column <- 17 30 | } 31 | else { 32 | outcome_column <- 23 33 | } 34 | 35 | #get rid of the NA's in the desired outcome column 36 | required_columns <- as.numeric(new_data[,outcome_column]) 37 | bad <- is.na(required_columns) 38 | desired_data <- new_data[!bad, ] 39 | 40 | #find the hospitals in the rows with the minimum outcome value 41 | columns_considered <- as.numeric(desired_data[, outcome_column]) 42 | desired_rows <- which(columns_considered == min(columns_considered)) 43 | desired_hospitals <- desired_data[desired_rows, 2] 44 | 45 | #if there are multiple hospitals with the minimum outcome value, then 46 | #return the first hospital name from the alphabetically sorted hospital 47 | #names list 48 | if (length(desired_hospitals) > 1) { 49 | hospitals_sorted <- sort(desired_hospitals) 50 | hospitals_sorted[1] 51 | } 52 | else { 53 | desired_hospitals 54 | } 55 | } -------------------------------------------------------------------------------- /Programming Assignment 3 - Hospital Quality/rprog-data-ProgAssignment3-data/rankall.R: -------------------------------------------------------------------------------- 1 | rankall <- function(outcome, num = "best") { 2 | ## Read outcome data 3 | 4 | ## Check that state and outcome are valid 5 | ## For each state, find the hospital of the given rank 6 | ## Return a data frame with the hospital names and the 7 | ## (abbreviated) state name 8 | 9 | #read in the desired data 10 | data <- read.csv("outcome-of-care-measures.csv", colClasses = "character") 11 | 12 | #create a list of states and initialize a character array to hold the 13 | #required hospital names 14 | state <- levels(factor(data[, 7])) 15 | hospital <- vector(mode="character") 16 | 17 | for (i in seq(state)) { 18 | hospital[i] <- rankhospital(state[i], outcome, num) 19 | } 20 | data.frame(hospital, state) 21 | } 22 | -------------------------------------------------------------------------------- /Programming Assignment 3 - Hospital Quality/rprog-data-ProgAssignment3-data/rankhospital.R: -------------------------------------------------------------------------------- 1 | rankhospital <- function(state, outcome, num = "best") { 2 | ## Read outcome data 3 | 4 | ## Check that state and outcome are valid 5 | ## Return hospital name in that state with the given rank 6 | ## 30-day death rate 7 | 8 | #read in the desired data 9 | data <- read.csv("outcome-of-care-measures.csv", colClasses = "character") 10 | 11 | #check if the state and outcomes are valid 12 | states <- data[ , 7] 13 | outcomes <- c("heart attack", "heart failure", "pneumonia") 14 | if ((state %in% states) == FALSE) { 15 | stop(print("invalid state")) 16 | } 17 | else if ((outcome %in% outcomes) == FALSE) { 18 | stop(print("invalid outcome")) 19 | } 20 | 21 | #get the subset of the data with the desired state 22 | new_data <- subset(data, State == state) 23 | 24 | #get the desired outcome column from the data file 25 | if (outcome == "heart attack") { 26 | outcome_column <- 11 27 | } 28 | else if (outcome == "heart failure") { 29 | outcome_column <- 17 30 | } 31 | else { 32 | outcome_column <- 23 33 | } 34 | 35 | #if num is greater that the number of hospitals in the desired state, 36 | # return NA 37 | if (is.numeric(num) == TRUE) { 38 | if (length(data[,2]) < num) { 39 | return(NA) 40 | } 41 | } 42 | 43 | #get rid of the NA's in the desired outcome column 44 | new_data[, outcome_column] <- as.numeric(new_data[,outcome_column]) 45 | bad <- is.na(new_data[, outcome_column]) 46 | desired_data <- new_data[!bad, ] 47 | 48 | #arrange the modified dataframe in ascending order of the outcome values 49 | outcome_column_name <- names(desired_data)[outcome_column] 50 | hospital_column_name <- names(desired_data)[2] 51 | index <- with(desired_data, order(desired_data[outcome_column_name], desired_data[hospital_column_name])) 52 | ordered_desired_data <- desired_data[index, ] 53 | 54 | #if nume is either "best" or "worst", then interpret it to the 55 | #corresponding numerical value 56 | if (is.character(num) == TRUE) { 57 | if (num == "best") { 58 | num = 1 59 | } 60 | else if (num == "worst") { 61 | num = length(ordered_desired_data[, outcome_column]) 62 | } 63 | } 64 | #return the hospital name with the outcome ranking of num 65 | ordered_desired_data[num, 2] 66 | } 67 | -------------------------------------------------------------------------------- /Programming Assignment 3 - Hospital Quality/rprog-doc-ProgAssignment3.pdf: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/muntasir2165/R-Programming-Assignments-1--2--and-3-/3dd6003062ddf6851a2baa06b04ed96e9eabfb60/Programming Assignment 3 - Hospital Quality/rprog-doc-ProgAssignment3.pdf -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | R Programming Assignments - 1, 2and 3 2 | ====================================== 3 | 4 | Programming assignments for the course "R Programming" 5 | 6 | **Programming Assignment 1 - Air Pollution** 7 | For this first programming assignment you will write three functions that are meant to 8 | interact with dataset that accompanies this assignment. The dataset is contained in a zip 9 | file specdata.zip that you can download from the Coursera web site. 10 | 11 | **Programming Assignment 2 - Lexical Scoping** 12 | This second programming assignment will require you to write an R function is able to 13 | cache potentially time-consuming computations. For example, taking the mean of a numeric 14 | vector is typically a fast operation. However, for a very long vector, it may take too 15 | long to compute the mean, especially if it has to be computed repeatedly (e.g. in a loop). 16 | If the contents of a vector are not changing, it may make sense to cache the value of the 17 | mean so that when we need it again, it can be looked up in the cache rather than 18 | recomputed. 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")}("ribbon"in locals_for_with?locals_for_with.ribbon:"undefined"!=typeof ribbon?ribbon:void 0,"specialization"in locals_for_with?locals_for_with.specialization:"undefined"!=typeof specialization?specialization:void 0,"certBaseImage"in locals_for_with?locals_for_with.certBaseImage:"undefined"!=typeof certBaseImage?certBaseImage:void 0,"universityLogo"in locals_for_with?locals_for_with.universityLogo:"undefined"!=typeof universityLogo?universityLogo:void 0,"course"in locals_for_with?locals_for_with.course:"undefined"!=typeof course?course:void 0,"timeLeft"in locals_for_with?locals_for_with.timeLeft:"undefined"!=typeof timeLeft?timeLeft:void 0),buf.join("")};return function(locals){if(locals&&locals._t)_t=locals._t.merge(_t);return yudify(locals)}};if("function"==typeof define&&define.amd)define(["js/lib/jade"],function(jade,_t){return jadify(jade,_t)});else wndw.jade.templates["spark.app.signature.js.signatureTrackLastChanceModal"]=jadify(wndw.jade.helpers)}(window); -------------------------------------------------------------------------------- /swirl Programming Assignment/Assignment Details Coursera_files/signature_track.js: -------------------------------------------------------------------------------- 1 | define(["jquery","pages/spark/app","js/lib/cookie","js/lib/modals","spark/app/signature/js/signatureTrackLastChanceModal.html","spark/app/signature/js/flexjoinLastChanceModal.html","js/lib/coursera.ab","js/lib/util"],function($,Coursera,Cookie,Modal,signatureTrackLastChanceModal,flexjoinLastChanceModal,AB,util){var functionList={addLastChanceModalInteraction:function($el){if(!Coursera.user.get("last_access_time"))return;var signup_url=Coursera.course.get("host")+"signature/course/"+Coursera.course.get("shortname")+"/"+Coursera.course.get("id"),specialization=Coursera.course.get("specialization");if(specialization)signup_url=Coursera.course.get("host")+"specialization/"+specialization.short_name+"/"+specialization.id;var sigtrackStatus=Coursera.course.get("signatureTrackStatus");if(1!==sigtrackStatus.signature_track_enabled)return;if(1===sigtrackStatus.signature_track_sign_up_now&&!Coursera.user.inSignatureTrack()&&!Coursera.user.isStaffOrSuperuser()){if(1!=Cookie.get("spark_signaturetrack_hide")){var join_label=null,join_st_button=null;if(!specialization){var join_label_id=AB.session.getExperiment("sigtrack_demonstrated_uses2").getChosenVariant();join_label={base:"Earn a Verified Certificate!","show-qualifications":"Show Your New Qualifications with a Verified Certificate","further-qualifications":"Deepen Your Qualifications with a Verified Certificate","list-resume":"Upgrade Your Resume with a Verified Certificate","list-cv":"Upgrade Your C.V. with a Verified Certificate","add-linkedin":"Add Verified Certificates to Your LinkedIn Profile","official-rec":"Earn Official Recognition from Top Universities","rec-achievement":"Get Recognition for Your Achievement with a Verified Certificate","link-identity":"Link Your Coursework to Your Identity","commitment-complete":"Motivate Yourself to Complete with a Verified Certificate","share-certificate":"Share Your Achievement With a Unique Certificate URL","share-records":"Show Your Success with Shareable Course Records","advance-career":"Advance Your Career with Verified Certificates","present-employer":"Gain Workplace Recognition, Earn Your Verified Certificate"}[join_label_id],join_st_button="Get Started"}else if(specialization)join_label='The "'+Coursera.course.get("specialization").name+'" Specialization',join_st_button="Learn More";$("body").prepend("
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