Branch to test graphs implementations

Miguel Tuñón
1 parent 7b836dff
Showing 5 changed files with 67 additions and 16 deletions
ISO27001effectiveness/R/Hackmageddon_Parser.R
ISO27001effectiveness/R/ISOSurvey_Parser.R
ISO27001effectiveness/R/ReportGraphs.R
ISO27001effectiveness/Report.Rmd
ISO27001effectiveness/Report.html
@@ -74,6 +74,10 @@ ProcessHMRaw &lt;- function(dataset.raw, dateOffset){
   dataset$Country <- gsub("UAE","AE",dataset$Country)
   dataset$Country <- gsub("CB","KH",dataset$Country)
+  CountryNames <- data.frame(countrycode::countrycode_data$country.name, countrycode::countrycode_data$iso2c, countrycode::countrycode_data$continent)
+  CountryNames <- setNames(CountryNames, c("Country_large","Country", "Continent"))
+  dataset <- merge(x = dataset, y = CountryNames, by = "Country", all.x = TRUE)
+  dataset <- dataset[!is.na(dataset$Continent),]
   #Format properly the date
   dataset$Date <- as.POSIXct(dataset$Date*86400, tz = "GMT", origin = dateOffset)
@@ -96,10 +96,12 @@ ProccesISOSurveyByCountryRaw &lt;- function(dataset.raw, years){
   #Translate country names to 2 letter code
-  CountryNames <- data.frame(countrycode::countrycode_data$country.name, countrycode::countrycode_data$iso2c)
-  CountryNames <- setNames(CountryNames, c("Country","country_short"))
+  CountryNames <- data.frame(countrycode::countrycode_data$country.name, countrycode::countrycode_data$iso2c, countrycode::countrycode_data$continent)
+  CountryNames <- setNames(CountryNames, c("Country","country_short", "Continent"))
   dataset <- merge(x = dataset, y = CountryNames, by = "Country", all.x = TRUE)
+  dataset <- dataset[!is.na(dataset$Continent),]
+
   dataset
 }
@@ -7,12 +7,15 @@
 #' @export
 GetReportGraphs <- function(Cert_PerCountry,Attacks) {
   #2012
-  graph1 <- ggplot2::qplot(main = "Countries with above average number of companies certified with ISO 27001 (2012)",
+  graph1 <- ggplot2::qplot(main = "Countries with above average number of companies certified with 27001 (2012)",
                   x = reorder(country_short,X2012),
                   y = X2012,
                   xlab = "Country",
                   ylab = "Number of certifications",
-                  data = Cert_PerCountry[Cert_PerCountry$X2012 > mean(Cert_PerCountry$X2012),])
+                  data = Cert_PerCountry[Cert_PerCountry$X2012 > mean(Cert_PerCountry$X2012),],
+                  geom = "col",
+                  fill = Continent)
+
   attacks2k12 <- Attacks[Attacks$Date < "2013-01-01" & Attacks$Date >= "2012-01-01",]
   frameAttacks2k12 <- as.data.frame(table(attacks2k12$Country))
   colnames(frameAttacks2k12) <- c("Country","Attacks")
@@ -21,7 +24,9 @@ GetReportGraphs &lt;- function(Cert_PerCountry,Attacks) {
                   y = Attacks,
                   xlab = "Country",
                   ylab = "Number of attacks",
-                  data = frameAttacks2k12[frameAttacks2k12$Attacks > mean(frameAttacks2k12$Attacks),])
+                  data = frameAttacks2k12[frameAttacks2k12$Attacks > mean(frameAttacks2k12$Attacks),],
+                  geom = "col",
+                  fill = Continent)
   Attacks2012ByMonth <- mutate(attacks2k12, month = format(attacks2k12$Date, "%m")) %>% group_by(month)
   Attack2012FreqByMonth <- as.data.frame(table(Attacks2012ByMonth$month))
@@ -35,12 +40,14 @@ GetReportGraphs &lt;- function(Cert_PerCountry,Attacks) {
                   xlab = "Month") + ggplot2::scale_x_continuous(breaks = 1:12)
   #2013
-  graph4 <- ggplot2::qplot(main = "Countries with above average number of companies certified with ISO 27001 (2013)",
+  graph4 <- ggplot2::qplot(main = "Countries with above average number of companies certified with 27001 (2013)",
                   x = reorder(country_short,X2013),
                   y = X2013,
                   xlab = "Country",
                   ylab = "Number of certifications",
-                  data = Cert_PerCountry[Cert_PerCountry$X2013 > mean(Cert_PerCountry$X2013),])
+                  data = Cert_PerCountry[Cert_PerCountry$X2013 > mean(Cert_PerCountry$X2013),]
+                  , geom = "col",
+                  fill = Continent)
   attacks2k13 <- Attacks[Attacks$Date < "2014-01-01" & Attacks$Date >= "2013-01-01",]
   frameAttacks2k13 <- as.data.frame(table(attacks2k13$Country))
   colnames(frameAttacks2k13) <- c("Country","Attacks")
@@ -49,7 +56,9 @@ GetReportGraphs &lt;- function(Cert_PerCountry,Attacks) {
                   y = Attacks,
                   xlab = "Country",
                   ylab = "Number of attacks",
-                  data = frameAttacks2k13[frameAttacks2k13$Attacks > mean(frameAttacks2k13$Attacks),])
+                  data = frameAttacks2k13[frameAttacks2k13$Attacks > mean(frameAttacks2k13$Attacks),]
+                  , geom = "col",
+                  fill = Continent)
   Attacks2013ByMonth <- mutate(attacks2k13, month = format(attacks2k13$Date, "%m")) %>% group_by(month)
   Attack2013FreqByMonth <- as.data.frame(table(Attacks2013ByMonth$month))
@@ -63,12 +72,14 @@ GetReportGraphs &lt;- function(Cert_PerCountry,Attacks) {
                   xlab = "Month") + ggplot2::scale_x_continuous(breaks = 1:12)
   #2014
-  graph7 <- ggplot2::qplot(main = "Countries with above average number of companies certified with ISO 27001 (2014)",
+  graph7 <- ggplot2::qplot(main = "Countries with above average number of companies certified with 27001 (2014)",
                   x = reorder(country_short,X2014),
                   y = X2014,
                   xlab = "Country",
                   ylab = "Number of certifications",
-                  data = Cert_PerCountry[Cert_PerCountry$X2014 > mean(Cert_PerCountry$X2014),])
+                  data = Cert_PerCountry[Cert_PerCountry$X2014 > mean(Cert_PerCountry$X2014),]
+                  , geom = "col",
+                  fill = Continent)
   attacks2k14 <- Attacks[Attacks$Date < "2015-01-01" & Attacks$Date >= "2014-01-01",]
   frameAttacks2k14 <- as.data.frame(table(attacks2k14$Country))
   colnames(frameAttacks2k14) <- c("Country","Attacks")
@@ -77,7 +88,9 @@ GetReportGraphs &lt;- function(Cert_PerCountry,Attacks) {
                   y = Attacks,
                   xlab = "Country",
                   ylab = "Number of attacks",
-                  data = frameAttacks2k14[frameAttacks2k14$Attacks > mean(frameAttacks2k14$Attacks),])
+                  data = frameAttacks2k14[frameAttacks2k14$Attacks > mean(frameAttacks2k14$Attacks),]
+                  , geom = "col",
+                  fill = Continent)
   Attacks2014ByMonth <- mutate(attacks2k14, month = format(attacks2k14$Date, "%m")) %>% group_by(month)
   Attack2014FreqByMonth <- as.data.frame(table(Attacks2014ByMonth$month))
@@ -91,12 +104,14 @@ GetReportGraphs &lt;- function(Cert_PerCountry,Attacks) {
                   xlab = "Month") + ggplot2::scale_x_continuous(breaks = 1:12)
   #2015
-  graph10 <- ggplot2::qplot(main = "Countries with above average number of companies certified with ISO 27001 (2015)",
+  graph10 <- ggplot2::qplot(main = "Countries with above average number of companies certified with 27001 (2015)",
                   x = reorder(country_short,X2015),
                   y = X2015,
                   xlab = "Country",
                   ylab = "Number of certifications",
-                  data = Cert_PerCountry[Cert_PerCountry$X2015 > mean(Cert_PerCountry$X2015),])
+                  data = Cert_PerCountry[Cert_PerCountry$X2015 > mean(Cert_PerCountry$X2015),]
+                  , geom = "col",
+                  fill = Continent)
   attacks2k15 <- Attacks[Attacks$Date < "2016-01-01" & Attacks$Date >= "2015-01-01",]
   frameAttacks2k15 <- as.data.frame(table(attacks2k15$Country))
   colnames(frameAttacks2k15) <- c("Country","Attacks")
@@ -105,7 +120,9 @@ GetReportGraphs &lt;- function(Cert_PerCountry,Attacks) {
                   y = Attacks,
                   xlab = "Country",
                   ylab = "Number of attacks",
-                  data = frameAttacks2k15[frameAttacks2k15$Attacks > mean(frameAttacks2k15$Attacks),])
+                  data = frameAttacks2k15[frameAttacks2k15$Attacks > mean(frameAttacks2k15$Attacks),]
+                  , geom = "col",
+                  fill = Continent)
   Attacks2015ByMonth <- mutate(attacks2k15, month = format(attacks2k15$Date, "%m")) %>% group_by(month)
   Attack2015FreqByMonth <- as.data.frame(table(Attacks2015ByMonth$month))
 ---
 title: "ISO 27001 Effectiveness"
-output: html_document
+output:
+  html_document: default
+  pdf_document: default
 ---
-```{r setup, include=FALSE}
+```{r setup, include=TRUE}
 knitr::opts_chunk$set(echo = TRUE)
 library(ISO27001effectiveness)
 library(xlsx)
@@ -120,6 +120,32 @@ $(document).ready(function () {
 </div>
+<pre class="r"><code>knitr::opts_chunk$set(echo = TRUE)
+library(ISO27001effectiveness)
+library(xlsx)</code></pre>
+<pre><code>## Loading required package: rJava</code></pre>
+<pre><code>## Loading required package: xlsxjars</code></pre>
+<pre class="r"><code>library(ggplot2)
+library(dplyr)</code></pre>
+<pre><code>## 
+## Attaching package: 'dplyr'</code></pre>
+<pre><code>## The following objects are masked from 'package:stats':
+## 
+##     filter, lag</code></pre>
+<pre><code>## The following objects are masked from 'package:base':
+## 
+##     intersect, setdiff, setequal, union</code></pre>
+<pre class="r"><code>library(countrycode)
+
+source(&quot;./Main.R&quot;)</code></pre>
+<pre><code>## Scale for 'x' is already present. Adding another scale for 'x', which
+## will replace the existing scale.</code></pre>
+<pre><code>## Scale for 'x' is already present. Adding another scale for 'x', which
+## will replace the existing scale.
+## Scale for 'x' is already present. Adding another scale for 'x', which
+## will replace the existing scale.
+## Scale for 'x' is already present. Adding another scale for 'x', which
+## will replace the existing scale.</code></pre>
 <div id="abstract" class="section level2">
 <h2>Abstract</h2>
 <p>La creciente preocupación de muchas empresas con infraestructura IT crítica frente a ciberataques ha llevado a algunas de ellas a tomar medidas de seguridad como la creación de departamentos de Seguridad de la Información, llevar a cabo auditorías de seguridad y obtener certificaciones de seguridad entre otras.</p>