ttnc <- read.csv('https://www.dropbox.com/s/eomae5ql6pzao0g/Titanic.csv?raw=1') #all passengers = 1313 all_passengers <- length(ttnc[,1]) #------------------------------------ # BEFORE ICEBERG # Filter male and female passengers all_w <- ttnc[ttnc$Sex == "female",] all_m <- ttnc[ttnc$Sex == "male",] aW <- length(all_w[,1]) #462 aM <- length(all_m[,1]) #851 #------------------------------------ # Filter females by passenger class w_1stC <- all_w[all_w$PClass == "1st",] w_2ndC <- all_w[all_w$PClass == "2nd",] w_3rdC <- all_w[all_w$PClass == "3rd",] w1c <- length(w_1stC[,1]) #143 w2c <- length(w_2ndC[,1]) #107 w3c <- length(w_3rdC[,1]) #212 #------------------------------------- # Filter males by passenger class m_1stC <- all_m[all_m$PClass == "1st",] m_2ndC <- all_m[all_m$PClass == "2nd",] m_3rdC <- all_m[all_m$PClass == "3rd",] m1c <- length(m_1stC[,1]) #179 m2c <- length(m_2ndC[,1]) #172 m3c <- length(m_3rdC[,1]) #499 #------------------------------------- #------------------------------------- # AFTER ICEBERG # Filter male and female survivors all_ws <- all_w[all_w$Survived ==1,] all_ms <- all_m[all_m$Survived ==1,] lost_at_sea <- ttnc[ttnc$Survived ==0,] wS <- length(all_ws[,1]) #308 mS <- length(all_ms[,1]) #142 las <- length(lost_at_sea[,1]) #863 #----------------------------------- # Filter female survivors by class w_1cs <- w_1stC[w_1stC$Survived ==1,] w_2cs <- w_2ndC[w_2ndC$Survived ==1,] w_3cs <- w_3rdC[w_3rdC$Survived ==1,] w1cS <- length(w_1cs[,1]) #134 w2cS <- length(w_2cs[,1]) #94 w3cS <- length(w_3cs[,1]) #80 #------------------------------------ # Filter male survivors by class m_1cs <- m_1stC[m_1stC$Survived ==1,] m_2cs <- m_2ndC[m_2ndC$Survived ==1,] m_3cs <- m_3rdC[m_3rdC$Survived ==1,] m1cS <- length(m_1cs[,1]) #59 m2cS <- length(m_2cs[,1]) #25 m3cS <- length(m_3cs[,1]) #58 #------------------------------------- #------------------------------------- # CHARTS DATA HERE all <- c(aM,aW) women <- c(w1c,w2c,w3c) men <- c(m1c,m2c,m3c) survival_rate <- c(las,mS,wS) female_survivors <- c(w1cS,w2cS,w3cS) male_survivors <- c(m1cS,m2cS,m3cS) #----------------------------------- # LABELS f_classes <- c(paste(w1c,"\n1st Class"),paste(w2c,"\n2nd Class"),paste(w3c,"\n3rd Class")) m_classes <- c(paste(m1c,"\n1st Class"),paste(m2c,"\n2nd Class"),paste(m3c,"\n3rd Class")) genders <- c(paste(aM,"Males" ),paste(aW,"Females")) mortality <- c(paste(las,"Lost\nat Sea "),paste(mS,"Males \nsurvived "),paste(wS,"Females\nsurvived")) f_survive <- c(paste(w1cS,"\n1st Class"),paste(w2cS,"\n2nd Class"),paste(w3cS,"\n3rd Class")) m_survive <- c(paste(m1cS,"\n1st Class"),paste(m2cS,"\n2nd Class"),paste(m3cS,"\n3rd Class")) #----------------------------------- # CHARTS CREATION HERE png(file = "titanic passengers.png", height=3000, units="px", ) par(mfrow = c(6,1)) pie(all, main = "\nGender of Passengers\non Titanic", label = genders, cex.main = 2.5, cex =2, col = c("red","blue"), ) pie(survival_rate, label = mortality, main = "\nSurvival Rate", cex.main = 2.5, cex = 2, col = c("black","red","blue"), ) pie(women, main = "\nComplement of Females\nby Class", label = f_classes, cex.main = 2.5, cex = 2, col = c("purple","blue","green"), ) pie(female_survivors, main = "\nFemale Survivors by\nPassenger Class", label = f_survive, cex.main = 2.5, cex = 2, col = c("purple","blue","green"), ) pie(men, main = "\nComplement of Males\nby Class", label = m_classes, cex.main = 2.5, cex = 2, col = c("red","orange","yellow"), ) pie(male_survivors, main = "\nMale Survivors by\nPassenger Class", label = m_survive, cex.main = 2.5, cex = 2, col = c("red","orange","yellow"), ) #----------------------------------- #----------------------------------- cat("

TITANIC STATISTICS

") cat("")

Titanic Statistics