Commit a21ac2b6acf9e6ec6402ee1bf724998936728727

Authored by Miguel Tuñón
1 parent ddea4061

Updated parsers

ISO27001effectiveness/DESCRIPTION
1 Package: ISO27001effectiveness 1 Package: ISO27001effectiveness
2 Type: Package 2 Type: Package
3 -Title: What the Package Does (Title Case) 3 +Title: Study about how ISO27001 certifications affect cyberattacks
4 Version: 0.1.0 4 Version: 0.1.0
5 Author: Who wrote it 5 Author: Who wrote it
6 Maintainer: The package maintainer <yourself@somewhere.net> 6 Maintainer: The package maintainer <yourself@somewhere.net>
7 -Description: More about what it does (maybe more than one line)  
8 - Use four spaces when indenting paragraphs within the Description. 7 +Description: Compare the cyberattacks reported in hackmaggedon website with data
  8 + obtained from the official ISO survey to 27001. Working around countries,
  9 + industrial sectors, etc.
9 License: What license is it under? 10 License: What license is it under?
10 Encoding: UTF-8 11 Encoding: UTF-8
11 LazyData: true 12 LazyData: true
12 RoxygenNote: 5.0.1 13 RoxygenNote: 5.0.1
13 Imports: xlsx, 14 Imports: xlsx,
14 - ggplot2 15 + ggplot2,
  16 + countrycode
ISO27001effectiveness/NAMESPACE
1 # Generated by roxygen2: do not edit by hand 1 # Generated by roxygen2: do not edit by hand
2 2
  3 +export(GetDefaultAttacksData)
  4 +export(GetISOSurveyCertsPerCountry)
  5 +export(GetISOSurveyCertsPerSector)
  6 +export(GetISOSurveySitesPerCountry)
  7 +export(ParseHMExcel)
  8 +export(ParseHMFolder)
  9 +export(ProccesISOSurveyByCountryRaw)
  10 +export(ProccesISOSurveyRaw)
  11 +export(ProcessHMRaw)
ISO27001effectiveness/R/Hackmageddon_Parser.R
@@ -49,16 +49,31 @@ ProcessHMRaw &lt;- function(dataset.raw, dateOffset){ @@ -49,16 +49,31 @@ ProcessHMRaw &lt;- function(dataset.raw, dateOffset){
49 #Standar names to the columns 49 #Standar names to the columns
50 dataset <- setNames(dataset.raw, c("Date", "Attack", "Target", "Country")) 50 dataset <- setNames(dataset.raw, c("Date", "Attack", "Target", "Country"))
51 51
52 - #Remove rows with Date NA 52 + #Data frame changes to standarize values and make easier the joins
53 dataset <- dataset[!is.na(dataset$Date),] 53 dataset <- dataset[!is.na(dataset$Date),]
54 dataset <- dataset[!is.na(dataset$Country),] 54 dataset <- dataset[!is.na(dataset$Country),]
55 - dataset <- dataset[!dataset$Country == ">1",]  
56 - dataset <- dataset[!dataset$Country == ">A",] 55 + dataset$Country <- toupper(dataset$Country)
  56 +
57 dataset <- dataset[!dataset$Country == "INT",] 57 dataset <- dataset[!dataset$Country == "INT",]
58 dataset <- dataset[!grepl(">",dataset$Country),] 58 dataset <- dataset[!grepl(">",dataset$Country),]
  59 + dataset <- dataset[dataset$Country != "N/A",]
59 dataset$Country <- gsub("\n"," ",dataset$Country) 60 dataset$Country <- gsub("\n"," ",dataset$Country)
60 dataset <- FilterMultiCountry(dataset) 61 dataset <- FilterMultiCountry(dataset)
61 - dataset <- dataset[!dataset$Country == "",] 62 + dataset <- dataset[dataset$Country != "",]
  63 +
  64 + dataset <- dataset[dataset$Country != "H",]
  65 + dataset <- dataset[dataset$Country != "W",]
  66 + dataset <- dataset[dataset$Country != "14",]
  67 + dataset <- dataset[dataset$Country != "EU",]
  68 + dataset <- dataset[dataset$Country != "UN",]
  69 + dataset <- dataset[dataset$Country != "TI",]
  70 + dataset <- dataset[dataset$Country != ".TI",]
  71 + dataset$Country <- gsub("G8","GI",dataset$Country)
  72 + dataset$Country <- gsub("UK","GB",dataset$Country)
  73 + dataset$Country <- gsub("EN","GB",dataset$Country)
  74 + dataset$Country <- gsub("UAE","AE",dataset$Country)
  75 + dataset$Country <- gsub("CB","KH",dataset$Country)
  76 +
62 77
63 #Format properly the date 78 #Format properly the date
64 dataset$Date <- as.POSIXct(dataset$Date*86400, tz = "GMT", origin = dateOffset) 79 dataset$Date <- as.POSIXct(dataset$Date*86400, tz = "GMT", origin = dateOffset)
@@ -66,28 +81,43 @@ ProcessHMRaw &lt;- function(dataset.raw, dateOffset){ @@ -66,28 +81,43 @@ ProcessHMRaw &lt;- function(dataset.raw, dateOffset){
66 dataset 81 dataset
67 } 82 }
68 83
  84 +#' Look for rows with more than one country target and split into multiple
  85 +#'
  86 +#' @param dataset.pre data.frame to process
  87 +#'
  88 +#' @return data.frame
69 FilterMultiCountry <- function(dataset.pre) { 89 FilterMultiCountry <- function(dataset.pre) {
  90 +
  91 + #data.frame with multiple taget country rows
70 multi <- dataset.pre[grepl(" ",dataset.pre$Country),] 92 multi <- dataset.pre[grepl(" ",dataset.pre$Country),]
71 93
72 - dataset <- dataset.pre[!grepl(" ",dataset.pre$Country),] 94 + if (nrow(multi) == 0) { #Ignore if there are not multiple target rows
73 95
74 - for (i in 1:nrow(multi)) {  
75 - crow <- multi[i,] 96 + dataset.pre
  97 + } else {
76 98
77 - country_s <- strsplit(toString(crow$Country), " ") 99 + #data.frame with every rows except multi ones
  100 + dataset <- dataset.pre[!grepl(" ",dataset.pre$Country),]
78 101
79 - for (j in 1:length(country_s)) {  
80 - Date <- crow[1]  
81 - Attack <- crow[2]  
82 - Target <- crow[3]  
83 - Country <- country_s[[1]][j]  
84 - new.row <- data.frame(Date, Attack, Target, Country)  
85 - print(new.row)  
86 - dataset <- rbind(dataset, new.row) 102 + #Iterate over multi
  103 + for (i in 1:nrow(multi)) {
  104 + crow <- multi[i,] #current row
  105 +
  106 + country_s <- strsplit(toString(crow$Country), " ")[[1]] #each country target
  107 +
  108 + #Iterate over each country target
  109 + for (j in 1:length(country_s)) {
  110 + Date <- crow[1]
  111 + Attack <- crow[2]
  112 + Target <- crow[3]
  113 + Country <- country_s[j]
  114 + new.row <- data.frame(Date, Attack, Target, Country)
  115 + dataset <- rbind(dataset, new.row) #Append new row to output data.frame
  116 + }
87 } 117 }
88 - }  
89 118
90 - dataset 119 + dataset
  120 + }
91 } 121 }
92 122
93 #' Parse every excel file into a folder 123 #' Parse every excel file into a folder
ISO27001effectiveness/R/ISOSurvey_Parser.R
@@ -69,6 +69,7 @@ ProccesISOSurveyRaw &lt;- function(dataset.raw, years){ @@ -69,6 +69,7 @@ ProccesISOSurveyRaw &lt;- function(dataset.raw, years){
69 #' @param years List of years to return, c("X2006", "X2010", ...) 69 #' @param years List of years to return, c("X2006", "X2010", ...)
70 #' 70 #'
71 #' @return data.frame 71 #' @return data.frame
  72 +#' @export
72 #' 73 #'
73 #' @examples 74 #' @examples
74 #' 75 #'
@@ -79,8 +80,24 @@ ProccesISOSurveyByCountryRaw &lt;- function(dataset.raw, years){ @@ -79,8 +80,24 @@ ProccesISOSurveyByCountryRaw &lt;- function(dataset.raw, years){
79 #Standard proccess 80 #Standard proccess
80 dataset <- ProccesISOSurveyRaw(dataset.raw, years) 81 dataset <- ProccesISOSurveyRaw(dataset.raw, years)
81 82
  83 + dataset$Country <- gsub("Bolivia","Bolivia, Plurinational State of",dataset$Country)
  84 + dataset$Country <- gsub("Cape Verde","Cabo Verde",dataset$Country)
  85 + dataset$Country <- gsub("Congo, Republic of","Congo, the Democratic Republic of the",dataset$Country)
  86 + dataset$Country <- gsub("Côte D'ivoire","Cote d'Ivoire",dataset$Country)
  87 + dataset$Country <- gsub("Gibraltar (UK)","Gibraltar",dataset$Country)
  88 + dataset$Country <- gsub("Hong Kong, China","Hong Kong",dataset$Country)
  89 + dataset$Country <- gsub("Macau, China","Macao",dataset$Country)
  90 + dataset$Country <- gsub("Palestine","Palestine, State of",dataset$Country)
  91 + dataset$Country <- gsub("San Marino, Republic of","San Marino",dataset$Country)
  92 + dataset$Country <- gsub("Taipei, Chinese","Taiwan, Province of China",dataset$Country)
  93 + dataset$Country <- gsub("The Former Yugoslav Republic of Macedonia","Macedonia, the former Yugoslav Republic of",dataset$Country)
  94 + dataset$Country <- gsub("United States of America","United States",dataset$Country)
  95 + dataset$Country <- gsub("Venezuela","Venezuela, Bolivarian Republic of",dataset$Country)
  96 +
  97 +
82 #Translate country names to 2 letter code 98 #Translate country names to 2 letter code
83 - CountryNames <- GetCountryAbrev() 99 + CountryNames <- data.frame(countrycode::countrycode_data$country.name, countrycode::countrycode_data$iso2c)
  100 + CountryNames <- setNames(CountryNames, c("Country","country_short"))
84 dataset <- merge(x = dataset, y = CountryNames, by = "Country", all.x = TRUE) 101 dataset <- merge(x = dataset, y = CountryNames, by = "Country", all.x = TRUE)
85 102
86 dataset 103 dataset
ISO27001effectiveness/R/Util.R deleted
1 -#-----------------------------Util functions--------------------------------------------------  
2 -  
3 -#' Return the 2 letter code of a country relation  
4 -#'  
5 -#' Relation of country names included in the ISO Survey input file with 2 letter code  
6 -#' included on the hackmaggedon input files  
7 -#'  
8 -#' @return data.frame  
9 -GetCountryAbrev <- function(){  
10 - Country <- c("Afghanistan", "Albania", "Algeria", "American Samoa", "Andorra", "Angola", "Anguilla", "Antarctica", "Antigua and Barbuda", "Argentina", "Armenia", "Aruba", "Australia", "Austria", "Azerbaijan", "Bahamas", "Bahrain", "Bangladesh", "Barbados", "Belarus", "Belgium", "Belize", "Benin", "Bermuda", "Bhutan", "Bolivia", "Bonaire", "Bosnia and Herzegovina", "Botswana", "Bouvet Island", "Brazil", "British Indian Ocean Territory", "Brunei Darussalam", "Bulgaria", "Burkina Faso", "Burundi", "Cambodia", "Cameroon", "Canada", "Cape Verde", "Cayman Islands", "Central African Republic", "Chad", "Chile", "China", "Christmas Island", "Cocos (Keeling) Islands", "Colombia", "Comoros", "Congo", "Congo, Republic of", "Cook Islands", "Costa Rica", "Croatia", "Cuba", "Curaçao", "Cyprus", "Czech Republic", "Côte D'ivoire", "Denmark", "Djibouti", "Dominica", "Dominican Republic", "Ecuador", "Egypt", "El Salvador", "Equatorial Guinea", "Eritrea", "Estonia", "Ethiopia", "Falkland Islands (Malvinas)", "Faroe Islands", "Fiji", "Finland", "France", "French Guiana", "French Polynesia", "French Southern Territories", "Gabon", "Gambia", "Georgia", "Germany", "Ghana", "Gibraltar (UK)", "Greece", "Greenland", "Grenada", "Guadeloupe", "Guam", "Guatemala", "Guernsey", "Guinea", "Guinea-Bissau", "Guyana", "Haiti", "Heard Island and McDonald Mcdonald Islands", "Holy See (Vatican City State)", "Honduras", "Hong Kong, China", "Hungary", "Iceland", "India", "Indonesia", "Iran, Islamic Republic of", "Iraq", "Ireland", "Isle of Man", "Israel", "Italy", "Jamaica", "Japan", "Jersey", "Jordan", "Kazakhstan", "Kenya", "Kiribati", "Korea, Democratic People's Republic of", "Korea, Republic of", "Kuwait", "Kyrgyzstan", "Lao People's Democratic Republic", "Latvia", "Lebanon", "Lesotho", "Liberia", "Libya", "Liechtenstein", "Lithuania", "Luxembourg", "Macau, China", "The Former Yugoslav Republic of Macedonia", "Madagascar", "Malawi", "Malaysia", "Maldives", "Mali", "Malta", "Marshall Islands", "Martinique", "Mauritania", "Mauritius", "Mayotte", "Mexico", "Micronesia, Federated States of", "Moldova, Republic of", "Monaco", "Mongolia", "Montenegro", "Montserrat", "Morocco", "Mozambique", "Myanmar", "Namibia", "Nauru", "Nepal", "Netherlands", "New Caledonia", "New Zealand", "Nicaragua", "Niger", "Nigeria", "Niue", "Norfolk Island", "Northern Mariana Islands", "Norway", "Oman", "Pakistan", "Palau", "Palestine", "Panama", "Papua New Guinea", "Paraguay", "Peru", "Philippines", "Pitcairn", "Poland", "Portugal", "Puerto Rico", "Qatar", "Romania", "Russian Federation", "Rwanda", "Reunion", "Saint Barthelemy", "Saint Helena", "Saint Kitts and Nevis", "Saint Lucia", "Saint Martin (French part)", "Saint Pierre and Miquelon", "Saint Vincent and the Grenadines", "Samoa", "San Marino, Republic of", "Sao Tome and Principe", "Saudi Arabia", "Senegal", "Serbia", "Seychelles", "Sierra Leone", "Singapore", "Sint Maarten (Dutch part)", "Slovakia", "Slovenia", "Solomon Islands", "Somalia", "South Africa", "South Georgia and the South Sandwich Islands", "South Sudan", "Spain", "Sri Lanka", "Sudan", "Suriname", "Svalbard and Jan Mayen", "Swaziland", "Sweden", "Switzerland", "Syrian Arab Republic", "Taiwan, Province of China", "Tajikistan", "Tanzania, United Republic of", "Thailand", "Timor-Leste", "Togo", "Tokelau", "Tonga", "Trinidad and Tobago", "Tunisia", "Turkey", "Turkmenistan", "Turks and Caicos Islands", "Tuvalu", "Uganda", "Ukraine", "United Arab Emirates", "United Kingdom", "United States of America", "United States Minor Outlying Islands", "Uruguay", "Uzbekistan", "Vanuatu", "Venezuela", "Viet Nam", "British Virgin Islands", "US Virgin Islands", "Wallis and Futuna", "Western Sahara", "Yemen", "Zambia", "Zimbabwe", "Aland Islands", "Taipei, Chinese")  
11 - country_short <- c("AF", "AL", "DZ", "AS", "AD", "AO", "AI", "AQ", "AG", "AR", "AM", "AW", "AU", "AT", "AZ", "BS", "BH", "BD", "BB", "BY", "BE", "BZ", "BJ", "BM", "BT", "BO", "BQ", "BA", "BW", "BV", "BR", "IO", "BN", "BG", "BF", "BI", "KH", "CM", "CA", "CV", "KY", "CF", "TD", "CL", "CN", "CX", "CC", "CO", "KM", "CG", "CD", "CK", "CR", "HR", "CU", "CW", "CY", "CZ", "CI", "DK", "DJ", "DM", "DO", "EC", "EG", "SV", "GQ", "ER", "EE", "ET", "FK", "FO", "FJ", "FI", "FR", "GF", "PF", "TF", "GA", "GM", "GE", "DE", "GH", "GI", "GR", "GL", "GD", "GP", "GU", "GT", "GG", "GN", "GW", "GY", "HT", "HM", "VA", "HN", "HK", "HU", "IS", "IN", "ID", "IR", "IQ", "IE", "IM", "IL", "IT", "JM", "JP", "JE", "JO", "KZ", "KE", "KI", "KP", "KR", "KW", "KG", "LA", "LV", "LB", "LS", "LR", "LY", "LI", "LT", "LU", "MO", "MK", "MG", "MW", "MY", "MV", "ML", "MT", "MH", "MQ", "MR", "MU", "YT", "MX", "FM", "MD", "MC", "MN", "ME", "MS", "MA", "MZ", "MM", "NA", "NR", "NP", "NL", "NC", "NZ", "NI", "NE", "NG", "NU", "NF", "MP", "NO", "OM", "PK", "PW", "PS", "PA", "PG", "PY", "PE", "PH", "PN", "PL", "PT", "PR", "QA", "RO", "RU", "RW", "RE", "BL", "SH", "KN", "LC", "MF", "PM", "VC", "WS", "SM", "ST", "SA", "SN", "RS", "SC", "SL", "SG", "SX", "SK", "SI", "SB", "SO", "ZA", "GS", "SS", "ES", "LK", "SD", "SR", "SJ", "SZ", "SE", "CH", "SY", "TW", "TJ", "TZ", "TH", "TL", "TG", "TK", "TO", "TT", "TN", "TR", "TM", "TC", "TV", "UG", "UA", "AE", "GB", "US", "UM", "UY", "UZ", "VU", "VE", "VN", "VG", "VI", "WF", "EH", "YE", "ZM", "ZW", "AX", "CN")  
12 -  
13 - dataset <- data.frame(Country, country_short)  
14 -  
15 - dataset  
16 -}  
ISO27001effectiveness/man/FilterMultiCountry.Rd 0 → 100644
  1 +% Generated by roxygen2: do not edit by hand
  2 +% Please edit documentation in R/Hackmageddon_Parser.R
  3 +\name{FilterMultiCountry}
  4 +\alias{FilterMultiCountry}
  5 +\title{Look for rows with more than one country target and split into multiple}
  6 +\usage{
  7 +FilterMultiCountry(dataset.pre)
  8 +}
  9 +\arguments{
  10 +\item{dataset.pre}{data.frame to process}
  11 +}
  12 +\value{
  13 +data.frame
  14 +}
  15 +\description{
  16 +Look for rows with more than one country target and split into multiple
  17 +}
  18 +
ISO27001effectiveness/man/GetCountryAbrev.Rd deleted
1 -% Generated by roxygen2: do not edit by hand  
2 -% Please edit documentation in R/Util.R  
3 -\name{GetCountryAbrev}  
4 -\alias{GetCountryAbrev}  
5 -\title{Return the 2 letter code of a country relation}  
6 -\usage{  
7 -GetCountryAbrev()  
8 -}  
9 -\value{  
10 -data.frame  
11 -}  
12 -\description{  
13 -Relation of country names included in the ISO Survey input file with 2 letter code  
14 -included on the hackmaggedon input files  
15 -}  
16 -  
ISO27001effectiveness/man/GetDefaultAttacksData.Rd 0 → 100644
  1 +% Generated by roxygen2: do not edit by hand
  2 +% Please edit documentation in R/Hackmageddon_Parser.R
  3 +\name{GetDefaultAttacksData}
  4 +\alias{GetDefaultAttacksData}
  5 +\title{Parse the default data from the package from hackmaggedon (2012-2016)}
  6 +\usage{
  7 +GetDefaultAttacksData()
  8 +}
  9 +\value{
  10 +data.frame
  11 +}
  12 +\description{
  13 +Parse the default data from the package from hackmaggedon (2012-2016)
  14 +}
  15 +\examples{
  16 +Attacks <- GetDefaultAttacksData()
  17 +}
  18 +
ISO27001effectiveness/man/GetISOSurveyCertsPerCountry.Rd 0 → 100644
  1 +% Generated by roxygen2: do not edit by hand
  2 +% Please edit documentation in R/ISOSurvey_Parser.R
  3 +\name{GetISOSurveyCertsPerCountry}
  4 +\alias{GetISOSurveyCertsPerCountry}
  5 +\title{Get data of certificates per year and country from IS27001}
  6 +\usage{
  7 +GetISOSurveyCertsPerCountry()
  8 +}
  9 +\value{
  10 +data.frame
  11 +}
  12 +\description{
  13 +Get data of certificates per year and country from IS27001
  14 +}
  15 +\examples{
  16 +Cert_PerCountry <- GetISOSurveyCertsPerCountry()
  17 +}
  18 +
ISO27001effectiveness/man/GetISOSurveyCertsPerSector.Rd 0 → 100644
  1 +% Generated by roxygen2: do not edit by hand
  2 +% Please edit documentation in R/ISOSurvey_Parser.R
  3 +\name{GetISOSurveyCertsPerSector}
  4 +\alias{GetISOSurveyCertsPerSector}
  5 +\title{Get data of certificates per year and sector from IS27001}
  6 +\usage{
  7 +GetISOSurveyCertsPerSector()
  8 +}
  9 +\value{
  10 +data.frame
  11 +}
  12 +\description{
  13 +Get data of certificates per year and sector from IS27001
  14 +}
  15 +\examples{
  16 +Cert_PerSector <- GetISOSurveyCertsPerSector()
  17 +}
  18 +
ISO27001effectiveness/man/GetISOSurveySitesPerCountry.Rd 0 → 100644
  1 +% Generated by roxygen2: do not edit by hand
  2 +% Please edit documentation in R/ISOSurvey_Parser.R
  3 +\name{GetISOSurveySitesPerCountry}
  4 +\alias{GetISOSurveySitesPerCountry}
  5 +\title{Get data of sites per year and country from IS27001}
  6 +\usage{
  7 +GetISOSurveySitesPerCountry()
  8 +}
  9 +\value{
  10 +data.frame
  11 +}
  12 +\description{
  13 +Get data of sites per year and country from IS27001
  14 +}
  15 +\examples{
  16 +Sites_PerCountry <- GetISOSurveySitesPerCountry()
  17 +}
  18 +
ISO27001effectiveness/man/LoadParserLibraries.Rd deleted
1 -% Generated by roxygen2: do not edit by hand  
2 -% Please edit documentation in R/Util.R  
3 -\name{LoadParserLibraries}  
4 -\alias{LoadParserLibraries}  
5 -\title{Install and load required libraries}  
6 -\usage{  
7 -LoadParserLibraries()  
8 -}  
9 -\description{  
10 -This function checks if every required library is installed to be loaded, if not they will be installed and then loaded.  
11 -Libraries installed:  
12 - xlsx to parse excel files like ISO survey source format  
13 -}  
14 -  
ISO27001effectiveness/man/ParseHMExcel.Rd 0 → 100644
  1 +% Generated by roxygen2: do not edit by hand
  2 +% Please edit documentation in R/Hackmageddon_Parser.R
  3 +\name{ParseHMExcel}
  4 +\alias{ParseHMExcel}
  5 +\title{Parse an excel raw data file from armaggedon}
  6 +\usage{
  7 +ParseHMExcel(file, cols)
  8 +}
  9 +\arguments{
  10 +\item{file}{path to the excel file}
  11 +
  12 +\item{cols}{list of columns index to read}
  13 +}
  14 +\value{
  15 +data.frame
  16 +}
  17 +\description{
  18 +Parse an excel raw data file from armaggedon
  19 +}
  20 +\examples{
  21 +data.raw <- ParseHMExcel("./data/hackmaggedon/file.xls", c(2, 3, 6, 5))
  22 +}
  23 +
ISO27001effectiveness/man/ParseHMFolder.Rd 0 → 100644
  1 +% Generated by roxygen2: do not edit by hand
  2 +% Please edit documentation in R/Hackmageddon_Parser.R
  3 +\name{ParseHMFolder}
  4 +\alias{ParseHMFolder}
  5 +\title{Parse every excel file into a folder}
  6 +\usage{
  7 +ParseHMFolder(folder, cols, dateOffset)
  8 +}
  9 +\arguments{
  10 +\item{folder}{path to the folder to iterate}
  11 +
  12 +\item{cols}{columns to parse into each file}
  13 +
  14 +\item{dateOffset}{origin to calc the dates into each file}
  15 +}
  16 +\value{
  17 +data.frame
  18 +}
  19 +\description{
  20 +Parse every excel file into a folder
  21 +}
  22 +\examples{
  23 +data.pro <- ProcessHMRaw("./data/hackmaggedon/", c(1, 5, 3) "1899-12-30")
  24 +}
  25 +
ISO27001effectiveness/man/ProccesISOSurveyByCountryRaw.Rd
@@ -2,7 +2,7 @@ @@ -2,7 +2,7 @@
2 % Please edit documentation in R/ISOSurvey_Parser.R 2 % Please edit documentation in R/ISOSurvey_Parser.R
3 \name{ProccesISOSurveyByCountryRaw} 3 \name{ProccesISOSurveyByCountryRaw}
4 \alias{ProccesISOSurveyByCountryRaw} 4 \alias{ProccesISOSurveyByCountryRaw}
5 -\title{Process raw data from ISO survey} 5 +\title{Join data from ISOSurvey with 2 letter code countries plus process raw.data}
6 \usage{ 6 \usage{
7 ProccesISOSurveyByCountryRaw(dataset.raw, years) 7 ProccesISOSurveyByCountryRaw(dataset.raw, years)
8 } 8 }
@@ -15,12 +15,11 @@ ProccesISOSurveyByCountryRaw(dataset.raw, years) @@ -15,12 +15,11 @@ ProccesISOSurveyByCountryRaw(dataset.raw, years)
15 data.frame 15 data.frame
16 } 16 }
17 \description{ 17 \description{
18 -Proccess the raw data from ISO survey to replace NAs, normalizate country names and filter years 18 +Join data from ISOSurvey with 2 letter code countries plus process raw.data
19 } 19 }
20 \examples{ 20 \examples{
21 21
22 Cert_PerCountry <- ProccesISOSurveyRaw(Cert_PerCountry, c("X2010", "X2011", "X2012", "X2013", "X2014", "X2015")) 22 Cert_PerCountry <- ProccesISOSurveyRaw(Cert_PerCountry, c("X2010", "X2011", "X2012", "X2013", "X2014", "X2015"))
23 Sites_PerCountry <- ProccesISOSurveyRaw(Sites_PerCountry, c("X2010", "X2011", "X2012", "X2013", "X2014", "X2015")) 23 Sites_PerCountry <- ProccesISOSurveyRaw(Sites_PerCountry, c("X2010", "X2011", "X2012", "X2013", "X2014", "X2015"))
24 -Cert_PerSector <- ProccesISOSurveyRaw(Cert_PerSector, c("X2010", "X2011", "X2012", "X2013", "X2014", "X2015"))  
25 } 24 }
26 25
ISO27001effectiveness/man/ProccesISOSurveyRaw.Rd 0 → 100644
  1 +% Generated by roxygen2: do not edit by hand
  2 +% Please edit documentation in R/ISOSurvey_Parser.R
  3 +\name{ProccesISOSurveyRaw}
  4 +\alias{ProccesISOSurveyRaw}
  5 +\title{PRocess raw data parsed from excel file ISOSurvey27001}
  6 +\usage{
  7 +ProccesISOSurveyRaw(dataset.raw, years)
  8 +}
  9 +\arguments{
  10 +\item{dataset.raw}{data.frame with raw data}
  11 +
  12 +\item{years}{list of years to include preceded with a X}
  13 +}
  14 +\value{
  15 +data.frame
  16 +}
  17 +\description{
  18 +PRocess raw data parsed from excel file ISOSurvey27001
  19 +}
  20 +\examples{
  21 +Cert_PerSector <- ProccesISOSurveyRaw(Cert_PerSector, c("X2010", "X2011", "X2012", "X2013", "X2014", "X2015"))
  22 +}
  23 +
ISO27001effectiveness/man/ProcessHMRaw.Rd 0 → 100644
  1 +% Generated by roxygen2: do not edit by hand
  2 +% Please edit documentation in R/Hackmageddon_Parser.R
  3 +\name{ProcessHMRaw}
  4 +\alias{ProcessHMRaw}
  5 +\title{Prepare raw data from hackmaggedon's excel to use it}
  6 +\usage{
  7 +ProcessHMRaw(dataset.raw, dateOffset)
  8 +}
  9 +\arguments{
  10 +\item{dataset.raw}{data.frame with raw data}
  11 +
  12 +\item{dateOffset}{origin to add the numeric date}
  13 +}
  14 +\value{
  15 +data.frame
  16 +}
  17 +\description{
  18 +Prepare raw data from hackmaggedon's excel to use it
  19 +}
  20 +\examples{
  21 +data.pro <- ProcessHMRaw(data.raw, "1899-12-30")
  22 +}
  23 +