Kaggle – Data Set – Titanic – Analysis Using R

Kaggle – Data Set – Titanic – Analysis Using R – Practice

#Hypothesis_01 – Higher Class People count is > Middile > Low – verified
#Hypothesis_02 – More people Suvived in First Class > Middle Class > Lowe Class vice versa
#Hypothesis_03 – Title have significance Mrs married either traveling alone or with Spouce
#Hypothesis_04 – Young boys/girls eithe have spouce nor traveling with Sibblings or with Parents
#Hypothesis_05 – More Men perished in Lower Class
#Hypothesis_06 – Averge aged women >30 are married
#Hypothesis_07 – Duplicate Names – Same name but two different person

#Set the working directory
setwd(“C:/Users/asket/Documents/Exploratory Data Analysis/DataSet/DataSamples/titanic”)
#Get working directory
getwd()
#Read Test and Train Data
train_titanic<-read.csv(“train.csv”, header = TRUE)
test_titanic<-read.csv(“test.csv”, header = TRUE)
#view the data
View(train_titanic) #is having one variable more than test #12
View(test_titanic) #test doesnt have the survived column #11
#need to have the survived column in the test and bind them with train to make the
#super set of the data
#create a [1*1] data frame variable is Survived , all the rows of test
#all the columns of test data set
test.survived <-data.frame(Survived= rep(“NONE”,nrow(test_titanic)),test_titanic[,])
View(test.survived)
#combain the data using rbind
titanic.bind<-rbind(train_titanic,test.survived)
View(titanic.bind)
#glance of the data
str(titanic.bind)
#convert the Surviced and PC Class as FACTOR
titanic.bind$Survived<-as.factor(titanic.bind$Survived)
titanic.bind$Pclass<-as.factor(titanic.bind$Pclass)
#check the grouping of survived & PC Class
#if the no of people perished is 10 and live is 1 then not good
#pc class high clas > middle class > low class
#to check above please run table model
table(titanic.bind$Survived)
table(titanic.bind$Pclass)
#install library ggplot
library(ggplot2)
#Hypothesis , the people who stayed in Upper Deck (more) saved
#lets check this fact in the Train data set
train_titanic$Pclass<-as.factor(train_titanic$Pclass)
#train_titanic$Survived<-as.factor(train_titanic$Survived)
str(train_titanic$Pclass)
attach(train_titanic)
str(train_titanic)
#Hypothesis is tested
ggplot(train_titanic,aes(x=Pclass,fill = factor(Survived))) +
stat_count(width = 0.5) +
xlab (“Class”) + ylab (“Count”) + labs(fill = “Survived”)
#Examine the Name variable, it is mentioned as FACTOR, coz these names are Unique hence
#R recognized it as Factor created nrow levels
head(as.character(train_titanic$Name))
#Check the name uniqness
length(unique(as.character(titanic.bind$Name)))
#1307 Unique Names, need to find out the duplicate
dupe.names<-as.character(titanic.bind[which
(duplicated(as.character(titanic.bind$Name))),”Name”])
dupe.names
#Techically these are not duplicate rows different people of same Name
titanic.bind[which(titanic.bind$Name %in% dupe.names),]

#lets examing sib(sibling)sp(spouse) & par(parent)ch(child)
library(stringr)
#Who are Miss
passenger_Miss<-titanic.bind[which(str_detect(titanic.bind$Name,”Miss.”)),]
head(passenger_Miss,n=5)
#sibsp – siblings / spouses aboard the Titanic
#parch – parents / children aboard the Titanic
#Confirmed that Miss. is Non Married women as we have one 4 years old girl who is travelling
#with Sibbling and her parents who has Mss. in her Name

#Hypothesis
#the Title and Age has the relationship with each other

passenger_Miss<-titanic.bind[which(str_detect(titanic.bind$Name,”Mrs.”)),]
head(passenger_Miss,n=5)

#Looks like the Older Women who has Mrs. looks like married and they are traveling with
#their spouse or with their sibblings

#lets Examine SEX

passenger.male<-titanic.bind[which(titanic.bind$Sex == ‘male’),]
head(passenger.male,n=5)
#Master title looks like Young boy
#Most of the men in top5 are perished
#Most of them in Class-3

#Now lets try to plot Survived & PC_Class & Title of the passenger to see the relationship between

getTitleName <- function(name) {
name <- as.character(name)

if (length(grep(“Miss. “, name)) > 0)
{
return(“Miss.”)
}
else if (length(grep(“Master.”, name)) > 0)
{
return(“Master.”)
}
else if (length(grep(“Mrs”, name)) > 0)
{
return(“Mrs”)
}
else if (length(grep(“Mr.”, name)) > 0)
{
return(“Mr.”)
}
else {
return(“Other.”)
}